Neuroplasticity in Development, Aging, and Neurodegeneration: History
View Latest Version
Please note this is an old version of this entry, which may differ significantly from the current revision.
Contributor:
Patrícia Marzola
,
Thayza Melzer
,
Eloisa Pavesi
,
Joana Gil-Mohapel
,
Patricia S. Brocardo

Neuroplasticity refers to the ability of the brain to reorganize and modify its neural connections in response to environmental stimuli, experience, learning, injury, and disease processes. It encompasses a range of mechanisms, including changes in synaptic strength and connectivity, the formation of new synapses, alterations in the structure and function of neurons, and the generation of new neurons.

  • aging
  • cognitive function
  • lifestyle interventions
  • neurodegeneration
  • neurodevelopment
  • neuroplasticity

1. Introduction

The concept of neuroplasticity was first introduced by William James in 1890, and a few decades later, Jerzy Konorski coined the term “neural plasticity” [1][2]. Neuroplasticity refers to changes in brain structure and function throughout the lifespan. Neuroplasticity enables the brain to change and adapt to intrinsic or extrinsic stimuli by reorganizing its structure, function, or connections, resulting in physiological and morphological modifications. This dynamic process allows us to adjust to different experiences and circumstances and plays a significant role in learning, memory, and recovery from brain injuries [3].
Due to the multifaceted nature of neuroplasticity, different types of plasticity can impact brain structure and function [4][5]. Structural neuroplasticity refers to changes in the physical structures of neurons and neural networks, including the number, shape, strength, and connectivity of synapses [6], thus enabling the brain to adapt to changing environments and experiences. Numerous studies have indicated that structural plasticity occurs during development and continues into adulthood [7][8][9]. On the other hand, functional neuroplasticity refers to changes in neural network properties that involve efficiency, strength, and synchrony changes of synapses. Functional plasticity occurs rapidly, affecting various cognitive and behavioral processes relating to attention, memory, and perception [5][10].
One well-studied example of structural neuroplasticity is adult neurogenesis, the process by which new neurons are generated in the adult brain. This process occurs primarily in the subventricular zone (SVZ) that lines the lateral ventricles and in the dentate gyrus of the hippocampus, a brain region essential for learning and memory [9][11][12][13]. Several studies have shown that increased physical activity, exposure to enriched environments, and certain drugs can enhance neurogenesis and improve learning and memory [8][14][15][16]. Another example of structural neuroplasticity is dendritic spine remodeling, the process by which dendritic spines change in size, shape, and number in response to experience. Animal studies have shown that dendritic spine remodeling also plays a crucial role in learning and memory [17][18].
Functional neuroplasticity is thought to underlie memory formation, skill acquisition, and recovery from injury. An example of functional neuroplasticity is long-term potentiation (LTP), the persistent strengthening of synapses in response to repeated stimulation. LTP is thought to be a key mechanism underlying learning and memory [19]. Conversely, long-term depression (LTD) is the persistent weakening of synapses and also plays a role in learning and memory [20][21]. Another example of functional neuroplasticity is cortical reorganization, the process by which the brain’s sensory maps can change in response to experience or injury. Learning new abilities results in changes to functional connectivity among brain areas involved with motor control, sensory processing, and attention. For example, blind individuals can have enhanced sensory processing in other modalities, such as touch and hearing, due to cortical reorganization [22].

2. Neuroplasticity

Neuroplasticity, also known as brain plasticity or neural plasticity, is the biological capacity of the brain to adapt physiologically or even alter its anatomical structure in response to stimuli or damage [23]. This ability is central to learning, memory, injury recovery, and adaptation to environmental changes [24].

2.1. Structural Neuroplasticity

Structural neuroplasticity refers to physical changes to neural circuits, including the growth of new dendritic spines, axonal sprouting, and even neurogenesis. In particular, neurogenesis refers to generating new functional neurons, a multifaceted and tightly regulated process involving the proliferation, differentiation, and integration of new neurons from neural precursor cells. Each stage is characterized by the activation and presence of distinct transcriptional factors and markers [12][25][26][27]. Structural neuroplasticity is essential to rewiring the brain and has implications for recovery after brain injury, neurodevelopment, and adaptations to sensory input alterations throughout life [28].

2.1.1. Developmental Neurogenesis and Synaptogenesis

The development of the central nervous system (CNS) begins in the early weeks following fertilization, shortly after formation of the three embryonic germ layers, ectoderm, mesoderm, and endoderm, a crucial phase during embryonic development. The CNS derives from the differentiation of multipotent cells present in the ectoderm through the formation of the neural plate in the dorsal region of the embryo. This neural plate will fold its crest in the craniocaudal and rostrocaudal directions, forming the neural tube at embryonic day 30 in the human [29]. The closure of the neural tube marks the beginning of rapid brain enlargement from two groups of cells: neural stem cells (NSCs), which are multipotent cells that can give rise to various types of neural cells, including neurons, astrocytes, and oligodendrocytes, and express markers such as Sox 2 and Nestin; and neural precursor cells (NPCs), which are immediate descendants of neural stem cells, are committed to a neuronal fate and express markers such as Pax6, Dlx2, and Tbr2 [27][29]. Between weeks 4 and 5 of human embryonic development begins a phase known as interkinetic nuclear migration of NSCs and NPCs, which results in the symmetric division along the ventricular edge. This early proliferation leads to an exponential increase in the pool of progenitor cells that contribute to the expansion of surface area and thickness of the ventricular zone [27][30][31]. Around gestational week 5 (human embryonic day 42), the NPCs located in the ventricular zone, referred to as radial glial cells, begin to switch from symmetric to asymmetric cell division, generating one daughter cell that remains in the ventricular zone as a radial glial cell and a postmitotic neuron, marking the beginning of neurogenesis itself [30]. The process of differentiation of NPCs into neurons involves the successive expression of specific transcription factors and proteins, including Neurogenin (Ngn) and Mash 1 (Ascl1), doublecortin (DCX), βIII-tubulin (Tuj1), and finally NeuN, a marker of mature neurons [31]. Of note, new neurons also need to migrate to their appropriate locations within the brain. This process involves the support of radial glial cells and Cajal–Retzius cells, which create pathways such as the reelin pathway to aid migrating neurons in reaching their final destination [32].
A final step in the neurogenic process involves establishing functional connections between the newly generated neurons to form neural circuits. This process relies on synaptic plasticity or synaptogenesis. Synaptogenesis begins approximately in human gestational week 27 and continues to occur after birth. During the postnatal period, synapses are produced rapidly; by age two, the number of synapses is estimated to be twice the number in the adult brain. Indeed, synaptogenesis is an incredibly dynamic process in the human cerebral cortex in infancy and childhood [24], with the postnatal period being marked by enhanced experience-dependent sensitivity to sensory information. In addition, synaptic strength and efficacy alterations occur during the development [24], allowing the developing brain to adapt to environmental stimuli. This “critical period” is not sustained into adulthood, though, thus restricting the ability to indiscriminately store new sensory information [33]. Indeed, the number of synapses falls over the subsequent years and into adolescence through a process referred to as synaptic pruning, through which necessary synapses are preserved and redundant ones are eliminated [34]. These findings support the idea of “windows of opportunity” that enable the construction and consolidation of experience-dependent structural and functional brain connections during the neurodevelopment period [35] and explain why children can readily acquire new languages (and other skills). At the same time, this ability requires much more effort and attention later in life [36].
Of note, in addition to being influenced by environmental stimuli, the various stages of developmental neurogenesis and synaptogenesis are tightly regulated by numerous intrinsic factors [29][31], including transcription factors, growth factors (such as brain-derived neurotrophic factor (BDNF) and insulin-like growth factor (IGF)), cell adhesion molecules (such as N-cadherin, which aids in cell migration and synaptic connection formation), and signaling molecules (such as Notch, Sonic Hedgehog (SHH), Wnt, and fibroblast growth factor (FGF)).

2.1.2. Adult Neurogenesis

Although the original evidence in support of adult neurogenesis dates back to the 1960s with the pioneering work of the American neuroscientist Joseph Altman [25], it was only in the mid-1990s that this phenomenon became generally accepted [37] following the seminal work by Eriksson et al. (1998), who demonstrated the incorporation of bromodeoxyuridine (BrdU; a nucleotide analog) into the DNA of newly generated neurons in the human hippocampal dentate gyrus [38]. Since then, numerous studies have confirmed that neural stem cells are indeed present in juvenile and adult brains [39] and that neurogenesis continues to occur in select regions of the adult mammalian brain [14][40], the most important and widely studied being the subgranular zone (SGZ) of the hippocampal dentate gyrus [25] and the subventricular zone (SVZ) of the lateral ventricles [41]. Newborn neurons have also been described in other brain regions, referred to as “noncanonical” neurogenic areas [12], including the hypothalamus [42][43], neocortex [44][45], amygdala [46], cerebellum [47][48], and striatum [39][49]. Of note, adult neurogenesis is thought to have functional significance. For example, adult hippocampal neurogenesis is involved in several emotional and cognitive functions, including spatial learning, memory, pattern separation, and mood regulation [11][50][51][52].
Similarly to developmental neurogenesis, adult neurogenesis is also modulated by several intrinsic and extrinsic factors, including trophic support [53][54], epigenetic factors [55], physical activity [16], stress [56], environmental enrichment [14], and pharmacological interventions, such as antidepressants [57][58][59]. On the other hand, a reduction or dysregulation of the neurogenic processes may contribute, at least in part, to alterations in cognition and emotional resilience seen with normal aging [60][61][62], as well as with various psychiatric and neurodegenerative conditions, including addiction [63], autism spectrum disorder [64][65], major depressive disorder [66], Huntington’s disease (HD) [67], and Alzheimer’s disease (AD) [68].

2.2. Functional Neuroplasticity

In contrast to structural neuroplasticity, functional neuroplasticity refers to changes in the functional organization of neural circuits. Synaptogenesis represents a structural aspect of plasticity but also has functional implications. The formation of new synapses or the strengthening of existing ones can enhance the communication and transmission of signals among neurons, leading to functional changes in neuronal circuits. These adaptations include two forms of synaptic plasticity, long-term potentiation (LTP) and long-term depression (LTD), through which the strength of synaptic connections between neurons can change in response to different patterns of neuronal activity, thus contributing to memory formation, skill acquisition, and habituation [69]. According to this hypothesis, learning or experiencing something new can strengthen synaptic connections. This, in turn, increases the efficiency of synaptic neurotransmission, ultimately aiding in memory consolidation and information recall [70][71].
The term LTP was first introduced in 1973 by Bliss and Lomo [72]. The authors demonstrated the long-lasting increase of synaptic strength in the dentate gyrus of the hippocampus following high-frequency stimulation. Later, in 1993, Bliss and Collingridge expanded on these findings and discussed the potential implications of LTP in the context of a cellular memory model [19]. LTP is one of the most well-studied mechanisms underlying neuroplasticity and is a specific cellular and synaptic process in which the strength of a synapse is increased, resulting in more efficient transmission of signals between the presynaptic and the postsynaptic neurons. Mechanistically, LTP involves changes that can last for an extended period (days, weeks, or even years) in the synaptic structure, such as an increase in the size and shape of postsynaptic dendritic spines as well as the increase in the area of postsynaptic density (PSD) and the number of neurotransmitter receptors of the postsynaptic membrane in response to the calcium-dependent activation of N-methyl-D-aspartate (NMDA) receptors [73]. LTP is often described using the principle of Hebbian plasticity, which states that synapses that are repeatedly active at the same time tend to strengthen their connections. This principle aligns with the idea that the brain adapts to experiences and reinforces the neural pathways associated with those experiences [74].
On the other hand, LTD is the process of decreasing synaptic strength, resulting in a less efficient transmission of signals in response to the depolarization of the postsynaptic neuron for an extended period. LTD helps maintain synaptic connections’ overall balance and efficiency, which is essential for synaptic homeostasis [21]. Both LTP and LTD are critical for the adaptative capabilities of the CNS and allow neural circuits to adjust their connections and synaptic strength in response to experiences, cognitive function, memory consolidation, and habituation [69][70].
In summary, functional and structural plasticity play an important role in brain function, and changes in neuroplasticity may be associated with diseases and disorders of the CNS. It is worth noting that neuroplasticity is most robust during development, but it persists throughout life. This fact has significant implications for understanding brain function, recovery from brain injury, and potentially treating neurological and psychiatric disorders.

3. Neurodevelopment and Neuroplasticity

The brain is arguably the most complex organ in the human body, and its development is a continuous process that starts early in gestation and continues throughout adulthood [75]. Neurodevelopment is a highly orchestrated process involving the proliferation, migration, differentiation, and maturation of neurons and the formation and refinement of synaptic connections between them [76]. Normal neurodevelopment is essential for the proper functioning of the nervous system, and any disruption in this process can lead to a wide range of neurodevelopmental and neurological disorders, such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and epilepsy [77]. The causes of these disorders are complex and multifactorial, involving genetic and environmental factors that can affect brain development and function [7]. Studies have shown that neuroplasticity involves many aspects of brain development, including forming and refining neural connections during early development and acquiring new skills and abilities throughout life [78][79]. In addition, neuroplasticity plays a crucial role in recovery from brain injury and stroke and in treating neurological and psychiatric disorders, such as depression and anxiety [80][81].
On the other hand, neuroplasticity disruptions can adversely affect neurodevelopment. Exposure to toxic substances during development, such as alcohol or drugs, can impair neuroplasticity and disrupt normal brain development [82][83]. Similarly, experiences with chronic stress or trauma can impair neuroplasticity and lead to permanent changes in brain structure and function [84]. Understanding the role of neuroplasticity in normal brain development is critical for identifying and addressing factors that can disrupt this process and lead to neurodevelopmental and neurological disorders. This section discusses the stages of normal neurodevelopment and the factors influencing this process.

3.1. Prenatal Stage (from Conception until Birth)

Neurodevelopment is a critical process that begins approximately two to three weeks after conception with the formation of the neural tube [85]. Neurulation involves the folding and fusion of the lateral ends of the neural plate and is a crucial stage in the formation of the brain and spinal cord. Abnormalities during neurulation can result in neural tube defects, such as spina bifida [86]. Following neurulation, neurogenesis and neuronal migration occur, which are also critical processes in neurodevelopment. Neurogenesis occurs primarily during the first trimester of pregnancy and in specific brain regions, such as the ventricular zone [26]. Neuronal migration occurs during the second trimester of pregnancy. It is essential for proper brain development, allowing neurons to form correct connections with other neurons and establish functional neural circuits [87].
During neurogenesis and neural migration, environmental factors such as stress, nutrition, alcohol exposure, and sensory input can influence the rate and direction of these processes. For example, exposure to stress hormones during gestation has been shown to alter the timing of neurogenesis and the migration of new neurons, leading to changes in brain structure and function [88].
Another significant event during embryonic development is the division of the neural tube into three primary brain vesicles, which give rise to the different structures of the brain [89]. Microglia migrate into the developing brain during the early stages of gestation, around 4–5 weeks after fertilization, and establish the pool of resident immune cells [90]. Gliogenesis, which produces region- and subtype-specific glia, begins at 22 weeks of gestation and continues throughout adulthood [91]. Glial cells also aid in the myelination of neurons at approximately 32 weeks of pregnancy, a process that continues after birth and into adulthood [92]. At 18 weeks of gestation, the excess of cells is eliminated through apoptosis, a form of programmed cell death, resulting in the refinement of cell populations and ensuring proper development and synaptic connectivity in the mature brain [93]. Synaptogenesis begins in utero at approximately 27 weeks of gestation but predominantly occurs after birth, coinciding with the growth of dendrites and axons and axonal myelination [35]. The pruning of excess synapses and dendritic processes continues after birth, a necessary process for proper neural network formation, with disruptions of this step being linked to various neurological disorders [94]. By the end of the prenatal period, major fiber pathways, such as the thalamocortical pathway, have been established [31]. These critical stages of brain development are essential for a healthy and functional brain. Conversely, disruptions in fetal brain development have been linked to an increased risk of psychiatric disorders, such as autism and schizophrenia [95]. The complexity of these processes highlights the importance of proper prenatal care, including good nutrition and avoiding harmful substances such as alcohol and drugs, which can adversely affect brain development [82][96].
The developmental origins of the health and disease hypothesis (DOHaD) propose that environmental exposure during early life (particularly during the prenatal period) can permanently influence the long-term development of disease. The initial studies addressing this relationship observed the association between gestational malnutrition and the phenotypes of the offspring, as well as the risk of developing metabolic diseases such as obesity, diabetes, and cardiovascular diseases later in life. In accordance with this, later studies have identified epigenetic modifications in fetal DNA as a response to environmental stimuli, which can permanently alter protein expression and phenotypes in the offspring. Of note, some of the environmental factors causing epigenetic modifications besides maternal nutrition include smoking, maternal stress, and infection [97][98].
During prenatal development, genetic information plays a crucial role in orchestrating events that determine the formation and refinement of neural connections. A complex sequence of guidance molecules instructs newly born cells on what type of neurons to become and where to go, while genetically determined intrinsic neural activity instructs the refinement of axonal projections, which are guided by molecular cues to their approximate target area [99]. While these events are critical for proper brain development, prenatal disruptions can negatively affect neuroplasticity. For example, prenatal exposure to teratogenic factors such as alcohol can interfere with glutamatergic and GABAergic neurotransmitter function, destabilizing previously tentative synapses [100][101]. This interference can lead to structurally different yet functionally viable circuits. Studies have also shown that neuroplastic changes during the prenatal period can have long-lasting effects on brain development and behavior. For example, maternal stress during pregnancy has been linked to altered brain development and increased risk for behavioral disorders such as ADHD and ASD in the offspring, negatively impacting cognitive and emotional outcomes later in life and increasing the risk for mental health conditions in adulthood [102].
Interestingly, through non-invasive techniques such as fetal magnetoencephalography (fMEG) that record neural responses to external stimuli like music, speech, and touch [103], it has been shown that exposure to music during the prenatal period can enhance the development of the auditory system and improve cognitive function later in life [104]. In addition, studies have shown that the fetus can recognize and respond to familiar voices, including the mother’s voice. This recognition can be attributed to the development of the auditory system, which is functional by the 16th week of gestation [105].

3.2. Infancy and Childhood

After birth, the human brain undergoes refinement and reorganization, particularly during sensitive and critical periods known as “windows of brain plasticity,” which are most pronounced in early childhood but continue into adolescence and adulthood [35]. During this stage, the brain undergoes an extraordinary growth spurt, with neurons forming connections at an astonishing rate. As the brain triples in size during the first two years of life, it builds an immense network of neural circuits that enables the processing of sensory information and the development of higher-order cognitive functions [106]. Studies have shown that early experiences and environmental factors are essential in shaping the developing brain. For example, language development begins early in life. It involves a complex interplay of genetic and environmental factors [107] and is strongly influenced by early exposure to language and sounds [108][109].
Another critical aspect of neurodevelopment in childhood (as well as adolescence; see below) is the development of executive skills such as attention, working memory, and self-control. These skills are important for academic achievement, social functioning, and well-being [110]. The development of executive functioning skills is influenced by several factors, including genetics, environmental factors, and experiences [111]. Brain neuroplasticity during infancy is also essential for developing social and emotional skills. Infants develop the ability to recognize and respond to emotional cues and to form secure bonds with caregivers. These skills, critical for social and emotional development, are shaped by early experiences and essential for later well-being [112]. The growth and development of the brain during this period lays the foundation for later cognitive, social, and emotional abilities. Therefore, providing infants and children with a nurturing and stimulating environment that promotes and supports optimal brain development is essential.
Windows of opportunity are necessary for developing new skills; however, they leave the brain vulnerable to the harmful effects of the environment. In the same way that environmental stimuli lead to necessary and expected neuronal remodeling while learning a new skill that will be important throughout life, adverse situations can potentially result in maladaptive changes. The World Health Organization (WHO) has coined the term early stress to refer to adverse situations that occur during childhood, from birth to 18 years of age. Early stress can include coping with conditions such as living in extreme poverty, violence, abuse (physical, sexual, or psychological), neglect, and grief, among other examples. According to the WHO, around one billion children and adolescents are exposed to some type of early stress every year [113][114]. When a child experiences a form of early stress, the hypothalamic–pituitary–adrenal (HPA) axis is activated, resulting in the release of cortisol, which in turn activates the sympathetic nervous system, thus triggering the fight-or-flight response as a defense mechanism [115].
However, when the stress response is chronic and exacerbated, it leads to adverse effects, including deregulating the HPA axis. Indeed, the sustained release of high levels of cortisol into the blood plasma can result in the disruption of the feedback loop that regulates the HPA axis, causing resistance to cortisol and ultimately resulting in the damage of various brain regions, including the hippocampus [116][117]. Indeed, when in excess, cortisol (or corticosterone in rodents) causes damage to dendritic arborization, the morphology of dendritic spines, and the synaptic integrity of hippocampal neurons. Male C57BL/6N mice that were subjected to an environmental stress protocol (insufficient sawdust in the housing box) between postnatal days 2 and 9 showed decreased arborization and lower density of dendritic spines in pyramidal neurons in the CA3 region of the hippocampus [118]. Furthermore, exposure to early stress induces decreased neurogenesis in the dentate gyrus of the hippocampus in C57 adult mice [119].
Notably, the impact of hyperactivation of the HPA axis on brain morphology and behavior (including the development of self-destructive behaviors, less tolerance to adverse everyday situations, greater vulnerability to substance abuse, and difficulties in interpersonal relationships) is well documented in the literature [120][121]. Indeed, reductions in adult neurogenesis, dendritic arborization, and glucocorticoid receptor density changes have been observed in the hippocampus of adults who experienced early stress [121][122]. Furthermore, exposure to early stress has also been associated with decreased gray matter and increased psychiatric disorders, including anxiety and depression [123]. Furthermore, studies have demonstrated the relationship between the experience of early stress in childhood and the development of alcohol dependence later in life [124]. A survey of 3592 adults on their drinking habits and history of early stress showed that the average age at which alcohol intake began was lower in people with traumatic experiences. While most participants said they drink to socialize and feel good, around 10% said they use alcohol to “deal with problems and stress” [125]. In addition, Pilowsky and collaborators (2009) demonstrated an association between traumatic events occurring in childhood and adolescence with a greater frequency of heavy episodic drinking and an early onset of alcohol consumption, with data highlighting that experiencing two or more traumatic events early in life increased the propensity for alcohol dependence in adulthood. The chronicity and severity of these episodes were also associated with the risk of relapse in female patients who were undergoing treatment for cocaine addiction [126][127].

3.3. Adolescence

As children grow into adolescence, their brains mature, accompanied by significant cognitive, social, and emotional development. Indeed, neuroimaging studies have shown that the adolescent brain undergoes considerable changes in the prefrontal cortex, which is responsible for higher-order cognitive functions, such as decision making, impulse control, attention, and working memory [128]. The prefrontal cortex is also involved in social and emotional processing, and its development during adolescence is crucial for acquiring social and emotional skills, including navigating complex social relationships, empathizing with others, and regulating emotions. Indeed, the prefrontal cortex undergoes significant changes in its structural and functional connectivity during adolescence, and these changes have been related to improvements in social cognition and emotion regulation [129][130]. Moreover, recent studies have highlighted the role of the social brain network, which includes regions such as the medial prefrontal cortex, the temporoparietal junction, and the amygdala, in social and emotional processing during adolescence [131][132]. These brain regions are involved in social cognition, empathy, and emotional regulation, and their development during adolescence is crucial for social and emotional competence.
Understanding the neurobiological changes during adolescence is crucial for promoting healthy brain development and preventing mental health conditions during this critical period of life. One of the most significant changes during adolescence is synaptic pruning, which involves the elimination of unnecessary synapses and neural connections. This process makes the brain more efficient by reducing neural noise and enhancing information processing [133]. Synaptic pruning occurs mainly in the prefrontal cortex but also affects other brain regions, such as the hippocampus and amygdala [34].

3.4. Adulthood

In adulthood, the rate of neurodevelopment slows down significantly. However, the brain retains the capacity to form new neurons and connections and adapt to new experiences throughout life. One mechanism through which the brain can continue to adapt is adult neurogenesis, which is thought to play an important role in learning and memory, as well as in mood regulation and the stress response [11][50][51][52].
In addition to the hippocampus and the SVZ, additional brain regions have also emerged as sites where adult neurogenesis can take place [12]. Indeed, animal studies have delineated neurogenic loci encompassing the hypothalamus [134], striatum [135][136][137], substantia nigra (SN) [138], cerebral cortex [139], and amygdala [140]. Evidence indicates that the genesis of neurons in these newly identified neurogenic areas is attributable to the migration of NSPCs, typically originating from the SVZ [137][140][141][142][143][144]. Concurrently, some studies have challenged this notion and proposed the existence of endogenous pools of NSPCs within these regions, capable of local replication and integration into neuronal circuits [134][135][145][146].
The hypothalamus, one of the major regulatory centers in the brain, controls various homeostatic processes, and hypothalamic neural stem cells (htNSCs) have been shown to interfere with these processes. Indeed, the hypothalamic neurogenesis is thought to influence metabolism and fat storage, as evidenced by multiple studies on the impacts of a high-fat diet (HFD) in mice [43][147][148]. Furthermore, neurogenesis within the hypothalamus is also thought to contribute to behavioral and sexual functions, as elucidated in studies by Bernstein et al. (1993) [149], Fowler et al. (2002) [150], and Cheng et al. (2004) [151]. Additionally, emerging research suggests that neurogenesis in the hypothalamus undergoes alterations during aging [152], prompting investigations into the potential implications of age-related changes in hypothalamic neurogenesis on overall physiological homeostasis and cognitive functions [153].
Of note, deficits in adult hippocampal neurogenesis (as well as other forms of structural and functional plasticity) have been implicated not only in normal aging [60], but also in various psychiatric [66] and neurodegenerative [67][68] conditions. Conversely, classic antidepressants such as monoamine oxidase inhibitors (MAOIs), tricyclic antidepressants, and selective serotonin reuptake inhibitors (SSRIs) have been shown to possess pro-neurogenic properties, and these are thought to mediate, at least in part, their antidepressant effects [57][58][154][155]. More recently, ketamine, an anesthetic with antidepressant properties, was also shown to increase adult hippocampal neurogenesis in rodents [156]. Other studies have explored the potential of environmental enrichment (such as exposing animals to a stimulating environment with toys and social interactions) [8][14][157] and physical exercise [157][158][159] in promoting adult hippocampal neurogenesis. These findings highlight the exciting potential of pharmacologic and non-pharmacologic interventions in promoting adult hippocampal neurogenesis and potentially improving human brain health and cognitive function.

3.5. Prenatal Factors That Impact Neurodevelopment and Neuroplasticity

Several prenatal factors can significantly impact neurodevelopment, and multiple lines of research have identified maternal nutrition, exposure to toxins (e.g., alcohol and illicit drugs), and infection as crucial determinants. Insufficient nutrition during pregnancy can lead to low birth weight and impaired cognitive development [160]. Moreover, maternal nutrition has been associated in preclinical and clinical research with altered neuropsychiatric outcomes in the offspring [161][162]. Of note, insulin has been identified as a critical modulator of neuronal network development during the early phases of life [163]. Studies have shown an association between impaired insulin signaling in the hippocampus of adolescent and adult offspring of obese mice with impairments in hippocampal gene expression, neurogenesis, and synaptic plasticity [164][165][166][167]. Furthermore, a recent study in rodents also suggested that an appropriate maternal diet, especially fiber-rich, could regulate and reverse these neurocognitive alterations [167]. One possible mechanism underlying the effects of a maternal high-fat diet on these neurodevelopment outcomes is related to altered Notch 1 signaling activation, which in turn is thought to inhibit the proliferation and differentiation of neural progenitors [168]. In addition, maternal excess salt intake has also been associated with changes in brain development and neural plasticity in rodents, particularly concerning synaptic transmission and neuroplasticity in the hippocampus [169].
Exposure to toxins, including alcohol, illicit drugs, and heavy metals such as lead, significantly impacts the developing brain, potentially resulting in brain damage and developmental delays [170]. These toxic substances can enter the body through various sources, including environmental pollution, contaminated food and water, and maternal substance use. Alcohol exposure during pregnancy has been linked to fetal alcohol spectrum disorders (FASDs), a range of neurodevelopmental and behavioral problems that can result in lifelong disabilities and neurocognitive abnormalities [82][171].
Consumption of cannabis (marijuana) during the prenatal period has also been shown to affect neurodevelopmental processes. Indeed, in utero exposure to Δ9-tetrahydrocannabinol was associated with behavioral alterations in adolescent rats, including impairment in aversive limbic memory, decreased instrumental learning, and increased alcohol consumption [172]. Similarly, exposure to illicit drugs, including stimulants (such as cocaine and methamphetamine) and opioids (such as heroin), can cause a range of adverse effects, including congenital disabilities, low birth weight, and developmental delays [173]. Exposure to heavy metals can also cause irreversible damage to the developing brain, leading to a range of cognitive, behavioral, and developmental problems [174]. Maternal infections during pregnancy can also have severe consequences for fetal development. For example, rubella infection during pregnancy can lead to congenital malformations, including hearing loss and intellectual disabilities [175]. Although the association between COVID-19 and congenital anomalies in babies conceived and born during the pandemic is still unclear due to the lack of knowledge on fetal and perinatal complications following COVID-19 infection, some studies have shown an increase in the rate of CNS congenital anomalies during the pandemic [176][177][178]. The long-term neuroplastic changes caused by COVID-19 infections are still unclear and require further investigation.

3.6. Postnatal Factors That Impact Neurodevelopment and Neuroplasticity

After birth, several postnatal factors can significantly influence neurodevelopment and neuroplasticity. Nutrition, social interaction, and environmental factors can all affect brain development during the postnatal period. Nutritional status is a critical determinant of brain growth and development, particularly during the first 1000 days of life [179]. In rodents, a high-fat diet during the postnatal period can negatively impact cognition and synaptic plasticity and promote neuroinflammation and microglial activation [180]. For example, ingestion of sweeteners, such as aspartame and sucralose, can induce changes in behavior and neuroplasticity, including decreases in hippocampal neurogenesis and BDNF levels in rats in a sex-dependent manner [181]. In humans, breastfeeding has been associated with improved metabolic and neurocognitive health outcomes in infants [182], effects that are thought to be mediated, at least in part, by the unique properties and lipid composition of maternal milk [183]. In addition, several studies have shown that inadequate nutrition during infancy and early childhood can lead to long-term cognitive deficits, reduced academic achievement, and behavioral problems [184][185]. In contrast, adequate nutrition during this period can promote optimal brain development, including improved cognitive and behavioral outcomes [186][187].
As explained above (see Section 3.2), the early years of life are a period of significant neuroplasticity, and experiences during this time can shape the structure and function of the brain [188]. Social interaction and early childhood experiences, such as language exposure, are critical for optimal brain development. Studies have shown that children who experience high-quality early care and education, including language-rich environments, have better cognitive, social–emotional, and academic outcomes than those who do not [189][190]. Conversely, lack of stimulation, social deprivation, and neglect can have long-lasting adverse effects on brain development, including reduced cortical thickness and gray matter volume [191] and increased risk of cognitive deficits and developmental delays [192].
Life experience and environmental enrichment positively modulate behavior and neuroplasticity during critical periods and throughout life [33][193]. Environmental enrichment during childhood, adolescence, and adulthood has been shown to promote neurogenesis and affect the pattern of monosynaptic inputs in animal models [14][157][194]. Additionally, environmental enrichment has been shown to improve spatial learning performance and neuroplasticity while increasing hippocampal volume and BDNF levels in various animal models [157][195]. In humans, evaluating the impact of environmental enrichment on brain neuroplasticity and function is much more complex due to the number of potential confounding variables. However, a recent randomized control trial has assessed the effects of environment and neurodevelopment and concluded that interventions that can reduce poverty could promote changes in children’s brain function and the development of higher-order cognitive skills. This study found that infant neuroplasticity was positively correlated with economic status, which in turn is known to impact numerous socio-economic factors that can influence a child’s well-being, including household income and expenses, type and amount of work of the mother, parenting behavior, and overall family wellbeing and stress [196]. Social interactions can also be considered a form of environmental enrichment known to modulate neuroplasticity. In particular, maternal contact has been shown to impact neurodevelopment and to have long-lasting effects on behavior. Appropriate maternal care during the first postnatal week can promote life-long stress resilience in rodents [197].
In conclusion, neuroplasticity is a critical determinant of brain growth and development not only prenatally but also during the postnatal period. Several prenatal factors, such as maternal nutrition, exposure to toxins, and infection, can potentially result in or contribute to the offspring’s cognitive, behavioral, and developmental problems. On the other hand, an appropriate maternal diet, especially one rich in fiber, can help prevent neurocognitive alterations caused by a maternal high-fat diet. The early years of postnatal life are also particularly significant for brain development, as experiences during this time can shape the structure and function of the brain. Adequate nutrition, language-rich environments, high-quality early care, education, and rewarding social interactions and stimulation are critical for optimal brain development during this period. Environmental enrichment during childhood and adolescence can increase neuroplasticity and improve cognitive outcomes. In contrast, exposure to toxins, social deprivation, neglect, and harmful environmental factors can have a long-lasting negative impact on brain development, potentially leading to long-term cognitive deficits and behavioral and psychological disturbances.

3.7. Sex Hormones and Neuroplasticity

Sex hormones are now known to have widespread actions in both the male and female brains, through mechanisms thought to involve both genomic and nongenomic receptors. Indeed, many neural and behavioral functions are affected by sex hormones such as estrogens, including mood, cognitive function, blood pressure regulation, motor coordination, pain, and opioid sensitivity [198]. Moreover, sex-specific differences have been reported with regards to hippocampal-dependent cognition and neurogenesis, suggesting that sex hormones are involved in these processes. Indeed, estrogens have been shown to modulate certain forms of spatial and contextual memory, as well as different forms of neuroplasticity including neurogenesis, primarily in the adult female hippocampus [199][200].
Peripheral sex steroid hormones, including estrogens, progesterone, testosterone, and other androgens, are able to cross the blood–brain barrier and reach the brain. Furthermore, hippocampal neurons are capable of synthesizing sex steroids de novo from cholesterol, since neural cells express all the enzymes required for the synthesis of estradiol and testosterone, the end products of sex steroidogenesis [201][202][203][204][205][206]. Regarding 17β-estradiol (E2) in particular, its synthesis in hippocampal neurons is homeostatically controlled by Ca2+ transients and is regulated by the release of gonadotropin-releasing hormone (GnRH) [207]. Indeed, release of GnRH from GnRH-positive neurons in the hippocampus is thought to regulate the local synthesis of sex steroids in a sex-dependent manner and thus contribute to the sexual differentiation of hippocampal neurons during the perinatal period [207][208]. Of note, a GnRH-induced increase in estradiol synthesis appears to provide a link between the hypothalamus and the hippocampus, and this may underlie, at least in part, estrous cyclicity of spine density in the female hippocampus [203][207]. Furthermore, sex hormones can initiate gene transcription and activate signaling cascades by utilizing genomic and non-genomic [198][209] mechanisms that play a key role in coordinating various physiological and pathological neuroplasticity-related events, such as formation or remodeling of dendritic spines, neurogenesis, synaptogenesis, and myelination modulation [210]. For example, the study by Lu et al. in 2019, employing a forebrain-neuron-specific aromatase knock-out mouse model, provided compelling genetic evidence of the involvement of neuron-derived E2 in modulating AKT-ERK and CREB-BDNF signaling cascades. This study established that neuron-derived E2 is essential for normal expression of LTP and other forms of synaptic plasticity, as well as cognitive function in both male and female brains [211]. However, it has also been proposed that whereas E2 appears to be essential to maintaining synaptic transmission and synaptic connectivity in the female hippocampus, dihydrotestosterone appears to be crucial for synaptic transmission and synaptic connectivity in the male hippocampus [204][207][208]. As the expression of sex hormones varies throughout the lifespan, its effects on neuroplasticity during distinct periods of development, adulthood, and aging must also be considered. Along these lines, strategies aimed at restoring and/or maintaining normal hormone levels in the brain throughout the lifespan such as physical exercise are thought to be beneficial in promoting brain health in general and neuroplasticity in particular [212].

4. Aging, Neurodegeneration, and Neuroplasticity

4.1. Physiological Aging

Aging is a natural process affecting various physiological systems, including the immune, cardiovascular, musculoskeletal, and nervous systems [213]. According to the United Nations, the proportion of people over 60 is projected to reach 25% by 2050 [214][215], reflecting a global trend towards population aging. As the population ages worldwide, the incidence of age-related diseases and the associated healthcare costs also increase.
The World Health Organization (WHO) defines healthy aging as the process of optimizing opportunities for physical, mental, and social well-being to enable older individuals to maintain their functional abilities that allow them to participate actively in society [216]. This definition encompasses not only the absence of disease but also emphasizes the importance of maintaining functional capacity and engagement in activities that contribute to a fulfilling life. For older adults, healthy aging involves healthy lifestyle habits and behaviors, including healthy nutrition, regular physical activity, and avoiding smoking, excessive drinking, and illicit drugs.
Aging increases the risk of developing chronic diseases such as cardiovascular disease, diabetes, and cancer. For example, type 2 diabetes is more prevalent in older adults, with approximately one in four adults over the age of 65 being affected by this metabolic disorder [217]. Cancer incidence also increases with age, with approximately 60% of all cancer cases occurring in adults over the age of 65 [218]. Moreover, ischemic heart disease, stroke, and chronic obstructive pulmonary disease (COPD) are common causes of mortality in the elderly population [219]. Additionally, aging is characterized by a decline in immune function linked to the accumulation of senescent cells, which secrete pro-inflammatory cytokines and contribute to chronic inflammation, ultimately resulting in tissue damage [220]. Indeed, aging is associated with cellular senescence, a state of irreversible growth arrest, which can be induced by various stressors, such as oxidative stress, resulting in the damage of cellular proteins, lipids, and DNA [221], as well as telomere shortening [222].
One of the critical differences between physiological and pathological brain aging relates to cognitive reserve and the maintenance of cognition in physiological aging versus the presence of notable cognitive decline in pathological aging. Indeed, the intrinsic capacity of the nervous system to regenerate and compensate for neuronal loss (i.e., the “brain reserve”) may counteract neurodegeneration and its consequences [223]. Within this scenario, environmental (e.g., lifestyle) and genetic factors influence the degree of resiliency to aging, thus influencing how much the intrinsic “brain reserve” can help prevent age-related neuronal damage and loss. Cognitive reserve depends on how efficiently the system can tap into the brain reserve [224]. In animal studies, several intrinsic and extrinsic factors, including sex, body weight, physical activity, sleep duration, and anxiety and stress, can all affect the cognitive reserve and the onset of cognitive impairments with aging [225].
On the other hand, regulation of neuroinflammation and oxidative stress, as well as maintenance of calcium homeostasis, can promote cellular resilience and neuronal circuit adaptation and ultimately increase cognitive reserve [226][227][228]. Nevertheless, the aging brain does experience significant structural and functional changes, particularly affecting the hippocampus and cerebral cortex [60][229]. Depending on the cognitive reserve of the brain, alterations in neurons and their connectivity may decrease cognitive function [60] and increase the risk of developing age-related neurological disorders such as AD and Parkinson’s disease (PD) [230][231][232][233].
In addition to affecting neuronal structure and function, aging has also been associated with astrocytic dysfunction and subsequent synaptic disturbances. Indeed, in old animals, deficiencies in astrocytic glutamate uptake have been related to synaptic plasticity impairments and age-related cognitive decline. Furthermore, astrocytes’ role in maintaining antioxidant defenses may also be compromised by aging, which can further contribute to neurodegeneration [234].
In addition, microglia (immune cells of the brain) and oligodendrocytes (myelinating cells of the CNS) are also affected by aging. Indeed, an age-related reduction in both white matter volume, myelinization, and microglia activation has been observed in the aged brain, with an impairment in microglia activation being associated with decreased neuroprotection and a compromised process of synapse elimination [234]. Neuroinflammation is a well-established contributor to age-related cognitive impairments and hippocampal neurogenesis deficits. The production of inflammatory mediators, including cytokines, interleukins, and neurotrophins, as well as the activation of glia and other immune cells, can have a direct impact on synaptic plasticity and neurogenesis and with that exacerbate the processes associated not only with normal aging but also with neurodegenerative disorders [235][236].
One of the most notable changes associated with aging is mitochondrial dysfunction. With age, mitochondria become less efficient at producing adenosine triphosphate (ATP) and more prone to producing toxic reactive oxygen species (ROS) [213], which in turn can cause neuronal dysfunction and, ultimately, cell death. Dysregulation of mitochondrial function contributes to the pathogenesis of age-related diseases, including neurodegenerative disorders. Indeed, mitochondrial dysfunction has been implicated in AD and PD [237]. The accumulation of mitochondrial DNA mutations has been observed in aged mice, and this has been linked to increased oxidative damage [238]. Intracellular Ca2+ dysregulation has also been implicated in age-related cognitive decline [239][240]. Indeed, an increase in intracellular Ca2+ levels in dorsal hippocampus CA1 pyramidal neurons has been shown to contribute to memory impairment in aged animals [241]. Furthermore, reduced NMDA receptor activation and LTP can impair Ca2+-dependent synaptic plasticity in old animals [242].
Interventions targeting the various physiological systems affected by aging may increase the lifespan and improve the quality of life of older individuals. For example, physical exercise has been shown to improve cardiovascular function, increase neuroplasticity, and promote the production of anti-inflammatory cytokines, all of which can help mitigate the adverse effects of aging on the body and the brain [243][244]. Furthermore, promoting healthy lifestyle habits such as maintaining a nutritious diet, engaging in regular physical exercise, and avoiding smoking and excessive alcohol consumption can also help minimize the impact of aging on individuals and society [60][159]. Indeed, maintaining functional capacity and improving well-being can enhance the quality of life for older individuals and drastically reduce healthcare costs.

4.2. Neurodegeneration

Neurodegeneration is characterized by the progressive loss of neuronal structure and function, leading to irreversible neuronal damage and cell death [245]. Neurodegeneration underlies the development of several neurodegenerative diseases, including AD, PD, as well as HD, and amyotrophic lateral sclerosis (ALS) [246][247][248]. Neurodegenerative diseases affect millions worldwide, with AD and PD being the most common neurodegenerative disorders. In the United States, as many as 6.2 million people may have AD, as reported by the Alzheimer’s Disease Association in 2022 [249]. Similarly, nearly a million Americans are living with PD, according to the Parkinson’s Foundation [250]. The incidence of these disorders is expected to triple by 2050, highlighting the need for effective prevention and treatment strategies [251].
Multiple factors are known to contribute to the neurodegenerative processes that culminate in neuronal damage and, ultimately, cell death [235][252]. For example, protein misfolding, aggregation, and deposition have long been recognized as neuropathological hallmarks common to many neurodegenerative disorders, including AD, PD, HD, and ALS [247][253][254][255]. Moreover, mitochondrial dysfunction (which can result from genetic mutations, exposure to environmental toxins, as well as physiological aging) [256], ROS generation and accumulation, and a consequent increase in oxidative stress [247][257][258] have all been shown to play a role in the pathogenesis of several neurodegenerative disorders, including AD, PD, and HD. In addition, neuroinflammation has also been implicated in the development of neurodegenerative diseases [259][260][261]. Other factors contributing to aging and neurodegeneration (and consequent neuroplasticity impairment) include genetic and environmental factors [233].

4.2.1. Protein Aggregation in Neurodegeneration

Neurodegenerative diseases are characterized by the accumulation and aggregation of disease-specific proteins such as beta-amyloid and tau in AD, alpha-synuclein in PD, and mutant huntingtin in HD [262]. These proteins misfold and form toxic oligomers and fibrils that interfere with normal cellular functions, eventually leading to cell death. This process is known as protein aggregation. The formation of abnormal protein aggregates is believed to arise from disturbances in the proteostasis network. This tightly regulated system ensures proper protein folding, trafficking, and degradation under normal conditions [263]. Disruptions to the proteostasis network can result from genetic mutations, aging, environmental stimuli, or a combination of several factors. Such disruptions can trigger the accumulation of misfolded proteins, formation of protein aggregates, increased neuroinflammation and oxidative stress, and activation of apoptotic pathways, ultimately culminating in neuronal death.
The endoplasmic reticulum (ER) is a critical component of the proteostasis network and is involved in the folding and processing of proteins [264]. Disruptions to ER function can accumulate misfolded proteins and trigger ER stress, activating the unfolded protein response (UPR) [265]. The UPR signaling pathway activates adaptive pathways to improve protein folding and promote quality control mechanisms and degradative pathways [266]. Recent studies have shown that the UPR plays a role in the pathogenesis of neurodegenerative diseases. For example, in AD, the UPR is activated in response to the accumulation of beta-amyloid [267], while in PD, it is activated in response to the accumulation of alpha-synuclein [268]. However, if the UPR fails to restore proteostasis or if the accumulation of misfolded proteins exceeds the capacity of the cellular machinery to degrade them, the UPR can also activate apoptotic pathways, thus resulting in neuronal death [263].

4.2.2. Mitochondrial Dysfunction and Oxidative Stress in Neurodegeneration

Oxidative stress and mutations in mitochondrial DNA contribute to aging and neurodegenerative diseases [269]. Several studies have shown that mitochondrial DNA mutations accumulate in the aging brain and are associated with cognitive decline [258][270][271]. Moreover, increased levels of ROS have been shown to induce mitochondrial DNA mutations and damage the mitochondrial respiratory chain, leading to mitochondrial dysfunction and neuronal death [272][273][274]. Furthermore, recent studies have shown that the crosstalk between oxidative stress and other pathological mechanisms, such as protein misfolding and inflammation, can further exacerbate mitochondrial damage and neuronal death [275].
An increasing number of disease-specific proteins have been found to interact with mitochondria. For example, mutant huntingtin has been shown to disrupt mitochondrial function and dynamics in HD [276]. Moreover, dysfunctional mitochondria may precipitate AD since beta-amyloid disrupts mitochondrial function and impairs energy production in brain cells [277][278]. PD is also associated with mitochondrial dysfunction, including impaired mitochondrial dynamics and oxidative stress [279], and oxidative stress has been linked to alpha-synuclein accumulation in dopaminergic neurons, a hallmark of the disease [280]. Together, these studies suggest that mitochondrial dysfunction is involved in the pathogenesis of multiple neurodegenerative disorders.

4.2.3. Neuroinflammation in Neurodegeneration

Neuroinflammation is a complex process mediated by microglia and astrocytes and is thought to play a role in several neurodegenerative diseases [281]. Microglia can assume phagocytic phenotypes and release inflammatory cytokines in response to various stimuli, including protein aggregates and pathogens [282]. For example, protein aggregates, such as beta-amyloid in AD and alpha-synuclein in PD, can activate microglia and induce chronic neuroinflammation, leading to neuronal dysfunction and death [283][284]. Moreover, oligomeric aggregates of beta-amyloid, tau, and alpha-synuclein can initiate both glial and neuronal inflammation by activating several inflammatory pathways [283][285][286]. In agreement, a recent study has shown that induced peripheral inflammation can potentiate the adverse effects of alpha-synuclein oligomers by exacerbating neuroinflammation and cognitive deficits in a synucleinopathy mouse model [287].
In response to injury or inflammation, activated astrocytes (i.e., astrogliosis) can also contribute to neuroinflammation by releasing cytokines and chemokines, further activating microglia and perpetuating neuroinflammation [288]. In agreement, a recent study showed that activated microglia can promote the activation of neurotoxic reactive astrocytes (A1 type), resulting in both neuron and oligodendrocyte death. Of note, reactive A1 astrocytes have been reported in various neurodegenerative diseases, including AD, PD, HD, ALS, and multiple sclerosis [284]. In animal models of AD, reactive astrocytes were associated with atrophy of glial fibrillary acidic protein (GFAP)-positive cells and the presence of amyloid deposits in brain regions such as the hippocampus [289].

4.2.4. Genetic and Environmental Factors in Neurodegeneration

Genetic and environmental factors can also contribute to neuroinflammation and neurodegeneration [290]. For example, mutations in the triggering receptor expressed on the myeloid cells 2 (TREM2) gene, expressed by microglia, have been linked to an increased risk of AD and other neurodegenerative diseases [291]. Moreover, genome-wide association studies have identified new genetic risk factors for AD and PD [292].
In addition, environmental factors such as exposure to toxins, infection, and traumatic brain injury (TBI) have also been shown to increase the risk of various neurodegenerative diseases [293][294][295]. For example, exposure to pesticides, heavy metals, and solvents has been linked to increased incidence of AD and PD [293]. Viral infections, such as herpes simplex virus type 1 and human herpes virus 6, have also been associated with the development of AD [294]. Furthermore, TBI has been linked to the development of chronic traumatic encephalopathy, a neurodegenerative disease commonly found in athletes and military veterans [295].

4.3. Correlation between Aging, Neurodegeneration, and Neuroplasticity

Several lines of evidence have supported a strong correlation between aging, neurodegeneration, and neuroplasticity. With age, both neurogenesis (i.e., the generation of new neurons) and synaptic plasticity (i.e., the ability of neurons to form new connections) decline [296]. These changes are thought to contribute to the development and progression of neurodegenerative processes by impairing the ability of the brain to compensate for the effects of physiological aging and/or incurred damage while maintaining normal function. On the other hand, engaging in activities that promote neuroplasticity, such as learning new skills or engaging in regular physical exercise, has been shown to help maintain cognitive function and slow cognitive decline in older adults [159][297]. These findings suggest that interventions designed to enhance neuroplasticity may slow or potentially reverse the effects of neurodegeneration in older adults.
The hippocampus and hippocampal neuroplasticity are particularly affected by the aging process. Age-related changes in the hippocampus, such as increased oxidative stress, neuroinflammation, altered gene expression, hormone imbalance, reduced neurogenesis, and impaired synaptic plasticity, have all been associated with cognitive decline [60]. Indeed, several studies have shown that aging is associated with decreased synaptic plasticity, including LTP and LTD, which are thought to underlie learning and memory. For example, hippocampal LTP was reduced in older adults, and this decrease was associated with poorer memory performance [298]. Of note, the decline in hippocampal LTP observed in aging rats was also shown to be associated with a decrease in the expression of estrogen receptors in the hippocampus [299]. Furthermore, aged animals were shown to have decreased synaptic plasticity in the projections from the entorhinal cortex to the dentate gyrus [300] and reduced neuronal excitability of CA1 pyramidal neurons [301]. Conversely, improving cyclic AMP response element-binding protein (CREB) signalizing enhanced cognitive performance in aged animals [302].
In addition, aging has also been associated with a decline in structural plasticity throughout the brain, including the hippocampus. Indeed, aging is associated with reduced dendritic arborization and length, spine density [303][304][305], as well as decreased synaptogenesis (i.e., formation of new synapses) [296]. Furthermore, adult neurogenesis also dramatically declines with age, with the proportion of neuronal stem cells that survive to become mature neurons being significantly reduced in the aged brain [306][307]. Of note, such decreases have been shown to impact learning strategies in aged mice [307]. In humans, neuroimaging studies have shown that aging is associated with a decrease in gray matter volume and cortical thickness, which may reflect a reduction in synaptic density [308].
In summary, the decline in neuroplasticity accompanying aging has important implications for cognitive function and the risk of developing neurodegenerative diseases. Understanding the mechanisms underlying the age-related decline in neuroplasticity is crucial for developing strategies to promote healthy aging and reduce the risk of age-related neurological disorders. To this end, non-invasive strategies aimed at improving neuroplasticity, including physical exercise, cognitive stimulation, social engagement, and dietary interventions, hold promise in halting the course of neurodegeneration in the aging brain [159][212][309][310].

4.4. Non-Pharmacologic and Non-Invasive Strategies to Promote Neuroplasticity during Aging

As described above, molecular and structural changes within the brain with aging can contribute to a decline in brain function and neurodegeneration [311]. However, the cognitive reserve (i.e., the ability of the brain to cope with damage and deterioration) can significantly reduce the risk of dementia and other age-related neurodegenerative conditions. Various non-invasive and non-pharmacological approaches have been shown to increase the cognitive reserve and potentially counteract the deleterious effects of aging by protecting the brain against age-associated neurodegenerative processes [312]. These strategies, including physical exercise, environmental enrichment and social stimulation, a healthy diet, and caloric restriction, as well as sleep hygiene, have been shown to enhance brain plasticity and improve cognitive function in aging individuals [313] while also counteracting several age-induced alterations in brain signaling, structure, and function [60]. The following sections outline some of the non-invasive and non-pharmacological strategies proposed to increase neuroplasticity in the aging brain.

4.4.1. Physical Exercise

Physical exercise is a well-established, non-invasive strategy for promoting neuroplasticity during aging [314][315]. Exercise is known to increase the production of growth factors, such as BDNF, which promote the survival and growth of neurons and synapses and play a key role in neuroplasticity [316]. In addition, exercise has also been shown to increase the expression of synapsin-I, a presynaptic protein related to motor performance [317].
Various studies have now shown the beneficial effects of exercise in maintaining cognitive function in aging [159][315][318][319]. Indeed, physical exercise increased hippocampal volume, improved spatial memory in older adults [318], and promoted cognitive function in individuals with mild cognitive impairment and dementia [319][320][321]. A systematic review and meta-analysis of 17 randomized controlled trials found that exercise interventions improved cognitive function, including memory, attention, processing speed, and executive function, in older adults [322]. A separate meta-analysis of 29 randomized controlled trials also found that exercise interventions were associated with significant improvements in cognitive function in healthy older adults [323]. A recent study using transcranial magnetic stimulation (TMS) found that older adults who engaged in regular physical exercise had more remarkable cortical plasticity than those who did not exercise regularly [324]. This suggests that exercise directly impacts the ability of the brain to adapt and change in response to environmental stimuli during aging. In addition, a study using magnetic resonance imaging (MRI) found that older adults who engaged in regular physical activity had greater gray matter volume in the prefrontal cortex, a brain region important for higher-order cognitive functions and decision making [325].
Together, these studies suggest that exercise can be a powerful tool for promoting neuroplasticity and cognitive health during aging. By increasing trophic support through the production of BDNF and promoting changes in brain structure and function, exercise may help protect the brain against age-related cognitive decline and improve the quality of life in later years.

4.4.2. Cognitive Stimulation and Socialization

Several lines of evidence have suggested that cognitive stimulation can effectively promote neuroplasticity and brain health during aging. Cognitive stimulation encompasses activities that challenge the brain, such as reading, writing, playing cognitive games, or learning new skills. These activities promote the formation of new neuronal connections and can help maintain cognitive function during aging [326]. A systematic review and meta-analysis found that engaging in mentally stimulating activities was associated with a lower risk of cognitive decline and dementia [327]. Older adults engaged in mentally stimulating activities had greater gray matter volume in brain regions important for memory and cognitive function [328], and an active cognitive lifestyle is associated with a more favorable cognitive trajectory in older persons [329]. Leisure activities such as reading, playing board games, playing musical instruments, and dancing were associated with a reduced risk of dementia in individuals older than 75 [330]. Learning new skills is one way to engage in mentally stimulating activities. In fact, learning a new skill, such as juggling, was associated with changes in brain structure and function, including increased gray matter volume in the visual and motor areas of the brain [78][79].
Socially interacting with others, such as friends and family, and engaging in social activities can also promote cognitive and emotional stimulation. Older adults who engaged in social activities, such as volunteering or participating in community events, had a lower risk of cognitive decline than those who did not engage in such activities [331]. On the other hand, a study found that social isolation was associated with a higher risk of dementia in older adults. This study followed over 2000 older adults for up to 7 years and found that those who were socially isolated had a 60% higher risk of developing dementia than those with social support [332]. Of note, socialization has been shown to promote the formation of new neuronal connections and enhance cognitive function. Indeed, socializing with others was associated with increased gray matter volume in brain regions important for memory and social cognition [333].
Furthermore, several studies showed that genetic and lifestyle factors play a role in determining the individual risk of dementia and cognitive impairment. The ε4 allele of the apolipoprotein E (APOE ε4) gene is the strongest known genetic risk factor for dementia and cognitive impairment. The association between APOE ε4 and faster cognitive decline was reduced in participants who were regularly engaged in productive activities [334].

4.4.3. Diet and Caloric Restriction

Diet plays a significant role in promoting neuroplasticity, especially during the aging process. The brain is a complex organ that requires numerous nutrients, including vitamins, minerals, antioxidants, and essential fatty acids [335]. Several studies have found that a healthy diet rich in fruits, vegetables, whole grains, and lean protein provides the nutrients necessary for optimal brain function [336][337].
In particular, the role of omega-3 fatty acids in promoting neuroplasticity is well documented. These fatty acids are essential for brain health and are found in high concentrations in fatty fish such as salmon, sardines, and mackerel [338]. For example, a randomized controlled trial involving older adults with mild cognitive impairment found that supplementation with omega-3 fatty acids for 12 weeks significantly improved cognitive function compared to the placebo group [339]. In a different study, supplementation with omega-3 fatty acids was also shown to improve cognitive function in healthy older adults [340]. Furthermore, Dullemeijer et al. (2007) found that higher plasma levels of n-3 polyunsaturated fatty acids were associated with a reduced decline in sensorimotor speed and complex cognitive processing in older adults [341]. In addition to omega-3 fatty acids, macro and micronutrients present in balanced diets, such as B vitamins and flavonoids, can prevent or mitigate age-related degenerative processes [342].
Conversely, diets high in saturated and trans fats have been linked to cognitive decline and dementia. A systematic review and meta-analysis of prospective studies found that a higher intake of saturated fats was associated with a higher risk of cognitive impairment and dementia [343]. Similarly, a study by Morris et al. found that a diet high in saturated fat was associated with a greater risk of developing AD [344]. In agreement, Solfrizzi et al. (2006) found that a diet high in trans fats was associated with cognitive decline in older adults [345]. Of note, trans fats have been shown to have adverse effects on brain function, as they can impair synaptic plasticity, alter membrane composition, and increase neuroinflammation [343]. These findings suggest that diets high in saturated and trans fats may negatively impact brain health and should be avoided.
Caloric restriction is another dietary strategy that promotes neuroplasticity and improves cognitive function. Caloric restriction involves reducing calorie intake by a certain percentage while maintaining adequate nutrition [346]. Animal studies have demonstrated that caloric restriction can enhance neuroplasticity by increasing the production of neurotrophic factors, such as BDNF [347][348]. Recent human studies have also suggested that caloric restriction may benefit brain function. A randomized controlled trial of overweight adults found that a 25% reduction in calorie intake for two years resulted in significant improvements in verbal memory and executive function compared to the control group [349].

4.4.4. Sleep Hygiene and Quality of Sleep

Sleep is critical in maintaining brain health and cognitive function, particularly in older adults. Numerous studies have demonstrated the importance of sleep in promoting neuroplasticity, particularly during learning and memory consolidation [350][351]. Sleep is also essential for clearing out toxic waste products and allowing the brain to regenerate [352].
Sleep deprivation has been associated with cognitive decline, particularly in older adults. Indeed, chronic sleep deprivation has been linked to a faster rate of cognitive decline in this population [353], while poor sleep quality was associated with a greater risk of developing dementia [354]. Recently, a study by Lucey and colleagues (2021) found that disrupted sleep was associated with increased levels of AD-related proteins in the cerebrospinal fluid [355].
Given this, and to promote optimal brain function, it is recommended that older adults sleep 7–8 h per night [356]. Also, maintaining good sleep hygiene practices, such as avoiding caffeine and electronic devices before bedtime and creating a relaxing sleep environment, can help improve the quality and quantity of sleep. Several lines of evidence have also highlighted the importance of regular exercise, healthy eating, and managing stress for promoting good sleep and overall brain health [357][358].

This entry is adapted from the peer-reviewed paper 10.3390/brainsci13121610

References

  1. James, W. Habits. In The Principles of Psychology; Henry Holt and Company: New York, NY, USA, 1890; pp. 104–127.
  2. Konorski, J. Conditioned Reflexes and Neuron Organization, Facsimile Reprint of the 1948; Cambridge University Press: Cambridge, UK, 1968.
  3. Voss, P.; Thomas, M.E.; Cisneros-Franco, J.M.; de Villers-Sidani, É. Dynamic Brains and the Changing Rules of Neuroplasticity: Implications for Learning and Recovery. Front. Psychol. 2017, 8, 1657.
  4. Draganski, B.; May, A. Training-Induced Structural Changes in the Adult Human Brain. Behav. Brain Res. 2008, 192, 137–142.
  5. Frizzell, T.O.; Phull, E.; Khan, M.; Song, X.; Grajauskas, L.A.; Gawryluk, J.; D’Arcy, R.C.N. Imaging Functional Neuroplasticity in Human White Matter Tracts. Brain Struct. Funct. 2022, 227, 381–392.
  6. Leuner, B.; Gould, E. Structural Plasticity and Hippocampal Function. Annu. Rev. Psychol. 2010, 61, 111–140.
  7. Chen, X.; Zhou, X.; Yang, L.; Miao, X.; Lu, D.-H.; Yang, X.-Y.; Zhou, Z.-B.; Kang, W.-B.; Chen, K.-Y.; Zhou, L.-H.; et al. Neonatal Exposure to Low-Dose (1.2%) Sevoflurane Increases Rats’ Hippocampal Neurogenesis and Synaptic Plasticity in Later Life. Neurotox. Res. 2018, 34, 188–197.
  8. Garthe, A.; Roeder, I.; Kempermann, G. Mice in an Enriched Environment Learn More Flexibly Because of Adult Hippocampal Neurogenesis. Hippocampus 2016, 26, 261–271.
  9. Kempermann, G.; Song, H.; Gage, F.H. Neurogenesis in the Adult Hippocampus. Cold Spring Harb. Perspect. Biol. 2015, 7, a018812.
  10. Takeuchi, N.; Izumi, S.-I. Rehabilitation with Poststroke Motor Recovery: A Review with a Focus on Neural Plasticity. Stroke Res. Treat. 2013, 2013, 128641.
  11. Aimone, J.B.; Li, Y.; Lee, S.W.; Clemenson, G.D.; Deng, W.; Gage, F.H. Regulation and Function of Adult Neurogenesis: From Genes to Cognition. Physiol. Rev. 2014, 94, 991–1026.
  12. Jurkowski, M.P.; Bettio, L.; Woo, E.K.; Patten, A.; Yau, S.-Y.; Gil-Mohapel, J. Beyond the Hippocampus and the SVZ: Adult Neurogenesis Throughout the Brain. Front. Cell. Neurosci. 2020, 14, 576444.
  13. Zhao, C.; Deng, W.; Gage, F.H. Mechanisms and Functional Implications of Adult Neurogenesis. Cell 2008, 132, 645–660.
  14. Kempermann, G.; Kuhn, H.G.; Gage, F.H. More Hippocampal Neurons in Adult Mice Living in an Enriched Environment. Nature 1997, 386, 493–495.
  15. Lazarov, O.; Mattson, M.P.; Peterson, D.A.; Pimplikar, S.W.; van Praag, H. When Neurogenesis Encounters Aging and Disease. Trends Neurosci. 2010, 33, 569–579.
  16. van Praag, H.; Kempermann, G.; Gage, F.H. Running Increases Cell Proliferation and Neurogenesis in the Adult Mouse Dentate Gyrus. Nat. Neurosci. 1999, 2, 266–270.
  17. Lai, C.S.W.; Franke, T.F.; Gan, W.-B. Opposite Effects of Fear Conditioning and Extinction on Dendritic Spine Remodelling. Nature 2012, 483, 87–91.
  18. Yang, G.; Pan, F.; Gan, W.-B. Stably Maintained Dendritic Spines Are Associated with Lifelong Memories. Nature 2009, 462, 920–924.
  19. Bliss, T.V.P.; Collingridge, G.L. A Synaptic Model of Memory: Long-Term Potentiation in the Hippocampus. Nature 1993, 361, 31–39.
  20. Bear, M.F.; Malenka, R.C. Synaptic Plasticity: LTP and LTD. Curr. Opin. Neurobiol. 1994, 4, 389–399.
  21. Pinar, C.; Fontaine, C.J.; Triviño-Paredes, J.; Lottenberg, C.P.; Gil-Mohapel, J.; Christie, B.R. Revisiting the Flip Side: Long-Term Depression of Synaptic Efficacy in the Hippocampus. Neurosci. Biobehav. Rev. 2017, 80, 394–413.
  22. Pascual-Leone, A.; Hamilton, R. Chapter 27 The Metamodal Organization of the Brain. Prog. Brain Res. 2001, 134, 427–445.
  23. Kourosh-Arami, M.; Hosseini, N.; Komaki, A. Brain Is Modulated by Neuronal Plasticity during Postnatal Development. J. Physiol. Sci. 2021, 71, 34.
  24. Johnston, M.V.; Ishida, A.; Ishida, W.N.; Matsushita, H.B.; Nishimura, A.; Tsuji, M. Plasticity and Injury in the Developing Brain. Brain Dev. 2009, 31, 1–10.
  25. Altman, J.; Das, G.D. Autoradiographic and Histological Evidence of Postnatal Hippocampal Neurogenesis in Rats. J. Comp. Neurol. 1965, 124, 319–335.
  26. Ming, G.; Song, H. Adult Neurogenesis in the Mammalian Brain: Significant Answers and Significant Questions. Neuron 2011, 70, 687–702.
  27. Budday, S.; Steinmann, P.; Kuhl, E. Physical Biology of Human Brain Development. Front. Cell. Neurosci. 2015, 9, 257.
  28. Gage, F.H. Structural Plasticity of the Adult Brain. Dialogues Clin. Neurosci. 2004, 6, 135–141.
  29. Bhatt, S.; Diaz, R.; Trainor, P.A. Signals and Switches in Mammalian Neural Crest Cell Differentiation. Cold Spring Harb. Perspect. Biol. 2013, 5, a008326.
  30. Kosodo, Y.; Röper, K.; Haubensak, W.; Marzesco, A.-M.; Corbeil, D.; Huttner, W.B. Asymmetric Distribution of the Apical Plasma Membrane during Neurogenic Divisions of Mammalian Neuroepithelial Cells. EMBO J. 2004, 23, 2314–2324.
  31. Stiles, J.; Jernigan, T.L. The Basics of Brain Development. Neuropsychol. Rev. 2010, 20, 327–348.
  32. Gil-Sanz, C.; Franco, S.J.; Martinez-Garay, I.; Espinosa, A.; Harkins-Perry, S.; Müller, U. Cajal-Retzius Cells Instruct Neuronal Migration by Coincidence Signaling between Secreted and Contact-Dependent Guidance Cues. Neuron 2013, 79, 461–477.
  33. Patton, M.H.; Blundon, J.A.; Zakharenko, S.S. Rejuvenation of Plasticity in the Brain: Opening the Critical Period. Curr. Opin. Neurobiol. 2019, 54, 83–89.
  34. Huttenlocher, P.R.; Dabholkar, A.S. Regional Differences in Synaptogenesis in Human Cerebral Cortex. J. Comp. Neurol. 1997, 387, 167–178.
  35. Ismail, F.Y.; Fatemi, A.; Johnston, M.V. Cerebral Plasticity: Windows of Opportunity in the Developing Brain. Eur. J. Paediatr. Neurol. 2017, 21, 23–48.
  36. Faust, T.E.; Gunner, G.; Schafer, D.P. Mechanisms Governing Activity-Dependent Synaptic Pruning in the Developing Mammalian CNS. Nat. Rev. Neurosci. 2021, 22, 657–673.
  37. Fares, J.; Bou Diab, Z.; Nabha, S.; Fares, Y. Neurogenesis in the Adult Hippocampus: History, Regulation, and Prospective Roles. Int. J. Neurosci. 2019, 129, 598–611.
  38. Eriksson, P.S.; Perfilieva, E.; Björk-Eriksson, T.; Alborn, A.-M.; Nordborg, C.; Peterson, D.A.; Gage, F.H. Neurogenesis in the Adult Human Hippocampus. Nat. Med. 1998, 4, 1313–1317.
  39. Merkle, F.T.; Tramontin, A.D.; García-Verdugo, J.M.; Alvarez-Buylla, A. Radial Glia Give Rise to Adult Neural Stem Cells in the Subventricular Zone. Proc. Natl. Acad. Sci. USA 2004, 101, 17528–17532.
  40. Kuhn, H.; Dickinson-Anson, H.; Gage, F. Neurogenesis in the Dentate Gyrus of the Adult Rat: Age-Related Decrease of Neuronal Progenitor Proliferation. J. Neurosci. 1996, 16, 2027–2033.
  41. Lois, C.; Alvarez-Buylla, A. Long-Distance Neuronal Migration in the Adult Mammalian Brain. Science 1994, 264, 1145–1148.
  42. Maggi, R.; Zasso, J.; Conti, L. Neurodevelopmental Origin and Adult Neurogenesis of the Neuroendocrine Hypothalamus. Front. Cell. Neurosci. 2015, 8, 440.
  43. Kokoeva, M.V.; Yin, H.; Flier, J.S. Neurogenesis in the Hypothalamus of Adult Mice: Potential Role in Energy Balance. Science 2005, 310, 679–683.
  44. Villalba, A.; Götz, M.; Borrell, V. The Regulation of Cortical Neurogenesis. Curr. Top. Dev. Biol. 2021, 142, 1–66.
  45. Gould, E.; Reeves, A.J.; Graziano, M.S.A.; Gross, C.G. Neurogenesis in the Neocortex of Adult Primates. Science 1999, 286, 548–552.
  46. Roeder, S.S.; Burkardt, P.; Rost, F.; Rode, J.; Brusch, L.; Coras, R.; Englund, E.; Håkansson, K.; Possnert, G.; Salehpour, M.; et al. Evidence for Postnatal Neurogenesis in the Human Amygdala. Commun. Biol. 2022, 5, 366.
  47. Ponti, G.; Peretto, P.; Bonfanti, L. Genesis of Neuronal and Glial Progenitors in the Cerebellar Cortex of Peripuberal and Adult Rabbits. PLoS ONE 2008, 3, e2366.
  48. Andreotti, J.P.; Prazeres, P.H.D.M.; Magno, L.A.V.; Romano-Silva, M.A.; Mintz, A.; Birbrair, A. Neurogenesis in the Postnatal Cerebellum after Injury. Int. J. Dev. Neurosci. 2018, 67, 33–36.
  49. Ernst, A.; Alkass, K.; Bernard, S.; Salehpour, M.; Perl, S.; Tisdale, J.; Possnert, G.; Druid, H.; Frisén, J. Neurogenesis in the Striatum of the Adult Human Brain. Cell 2014, 156, 1072–1083.
  50. Bruel-Jungerman, E.; Rampon, C.; Laroche, S. Adult Hippocampal Neurogenesis, Synaptic Plasticity and Memory: Facts and Hypotheses. Rev. Neurosci. 2007, 18, 93–114.
  51. Koehl, M.; Abrous, D.N. A New Chapter in the Field of Memory: Adult Hippocampal Neurogenesis. Eur. J. Neurosci. 2011, 33, 1101–1114.
  52. Samuels, B.A.; Hen, R. Neurogenesis and Affective Disorders. Eur. J. Neurosci. 2011, 33, 1152–1159.
  53. Åberg, M.A.I.; Åberg, N.D.; Hedbäcker, H.; Oscarsson, J.; Eriksson, P.S. Peripheral Infusion of IGF-I Selectively Induces Neurogenesis in the Adult Rat Hippocampus. J. Neurosci. 2000, 20, 2896–2903.
  54. Zigova, T.; Pencea, V.; Wiegand, S.J.; Luskin, M.B. Intraventricular Administration of BDNF Increases the Number of Newly Generated Neurons in the Adult Olfactory Bulb. Mol. Cell. Neurosci. 1998, 11, 234–245.
  55. Yao, B.; Christian, K.M.; He, C.; Jin, P.; Ming, G.; Song, H. Epigenetic Mechanisms in Neurogenesis. Nat. Rev. Neurosci. 2016, 17, 537–549.
  56. Du Preez, A.; Onorato, D.; Eiben, I.; Musaelyan, K.; Egeland, M.; Zunszain, P.A.; Fernandes, C.; Thuret, S.; Pariante, C.M. Chronic Stress Followed by Social Isolation Promotes Depressive-like Behaviour, Alters Microglial and Astrocyte Biology and Reduces Hippocampal Neurogenesis in Male Mice. Brain. Behav. Immun. 2021, 91, 24–47.
  57. Malberg, J.E.; Eisch, A.J.; Nestler, E.J.; Duman, R.S. Chronic Antidepressant Treatment Increases Neurogenesis in Adult Rat Hippocampus. J. Neurosci. 2000, 20, 9104–9110.
  58. Manev, H.; Uz, T.; Smalheiser, N.R.; Manev, R. Antidepressants Alter Cell Proliferation in the Adult Brain in Vivo and in Neural Cultures in Vitro. Eur. J. Pharmacol. 2001, 411, 67–70.
  59. Micheli, L.; Ceccarelli, M.; D’Andrea, G.; Tirone, F. Depression and Adult Neurogenesis: Positive Effects of the Antidepressant Fluoxetine and of Physical Exercise. Brain Res. Bull. 2018, 143, 181–193.
  60. Bettio, L.E.B.; Rajendran, L.; Gil-Mohapel, J. The Effects of Aging in the Hippocampus and Cognitive Decline. Neurosci. Biobehav. Rev. 2017, 79, 66–86.
  61. Boldrini, M.; Fulmore, C.A.; Tartt, A.N.; Simeon, L.R.; Pavlova, I.; Poposka, V.; Rosoklija, G.B.; Stankov, A.; Arango, V.; Dwork, A.J.; et al. Human Hippocampal Neurogenesis Persists throughout Aging. Cell Stem Cell 2018, 22, 589–599.e5.
  62. Isaev, N.K.; Stelmashook, E.V.; Genrikhs, E.E. Neurogenesis and Brain Aging. Rev. Neurosci. 2019, 30, 573–580.
  63. Gipson, C.D.; Kupchik, Y.M.; Kalivas, P.W. Rapid, Transient Synaptic Plasticity in Addiction. Neuropharmacology 2014, 76, 276–286.
  64. Bicker, F.; Nardi, L.; Maier, J.; Vasic, V.; Schmeisser, M.J. Criss-crossing Autism Spectrum Disorder and Adult Neurogenesis. J. Neurochem. 2021, 159, 452–478.
  65. Hansel, C. Deregulation of Synaptic Plasticity in Autism. Neurosci. Lett. 2019, 688, 58–61.
  66. Fries, G.R.; Saldana, V.A.; Finnstein, J.; Rein, T. Molecular Pathways of Major Depressive Disorder Converge on the Synapse. Mol. Psychiatry 2023, 28, 284–297.
  67. Murphy, K.P.S.J.; Carter, R.J.; Lione, L.A.; Mangiarini, L.; Mahal, A.; Bates, G.P.; Dunnett, S.B.; Morton, A.J. Abnormal Synaptic Plasticity and Impaired Spatial Cognition in Mice Transgenic for Exon 1 of the Human Huntington’s Disease Mutation. J. Neurosci. 2000, 20, 5115–5123.
  68. Babcock, K.R.; Page, J.S.; Fallon, J.R.; Webb, A.E. Adult Hippocampal Neurogenesis in Aging and Alzheimer’s Disease. Stem Cell Rep. 2021, 16, 681–693.
  69. Magee, J.C.; Grienberger, C. Synaptic Plasticity Forms and Functions. Annu. Rev. Neurosci. 2020, 43, 95–117.
  70. Baltaci, S.B.; Mogulkoc, R.; Baltaci, A.K. Molecular Mechanisms of Early and Late LTP. Neurochem. Res. 2019, 44, 281–296.
  71. Mainberger, F.; Langer, S.; Mall, V.; Jung, N.H. Impaired Synaptic Plasticity in RASopathies: A Mini-Review. J. Neural Transm. 2016, 123, 1133–1138.
  72. Bliss, T.V.P.; Lømo, T. Long-Lasting Potentiation of Synaptic Transmission in the Dentate Area of the Anaesthetized Rabbit Following Stimulation of the Perforant Path. J. Physiol. 1973, 232, 331–356.
  73. Gall, C.M.; Le, A.A.; Lynch, G. Sex Differences in Synaptic Plasticity Underlying Learning. J. Neurosci. Res. 2023, 101, 764–782.
  74. Lynch, M.A. Long-Term Potentiation and Memory. Physiol. Rev. 2004, 84, 87–136.
  75. Johnson, M.H. Functional Brain Development in Humans. Nat. Rev. Neurosci. 2001, 2, 475–483.
  76. Stiles, J. The Fundamentals of Brain Development: Integrating Nature and Nurture; Harvard University Press: Cambridge, MA, USA, 2008.
  77. Pascual-Leone, A.; Amedi, A.; Fregni, F.; Merabet, L.B. THE PLASTIC HUMAN BRAIN CORTEX. Annu. Rev. Neurosci. 2005, 28, 377–401.
  78. Draganski, B.; Gaser, C.; Busch, V.; Schuierer, G.; Bogdahn, U.; May, A. Changes in Grey Matter Induced by Training. Nature 2004, 427, 311–312.
  79. Boyke, J.; Driemeyer, J.; Gaser, C.; Büchel, C.; May, A. Training-Induced Brain Structure Changes in the Elderly. J. Neurosci. 2008, 28, 7031–7035.
  80. Castrén, E.; Hen, R. Neuronal Plasticity and Antidepressant Actions. Trends Neurosci. 2013, 36, 259–267.
  81. Kleim, J.A.; Barbay, S.; Cooper, N.R.; Hogg, T.M.; Reidel, C.N.; Remple, M.S.; Nudo, R.J. Motor Learning-Dependent Synaptogenesis Is Localized to Functionally Reorganized Motor Cortex. Neurobiol. Learn. Mem. 2002, 77, 63–77.
  82. Gil-Mohapel, J.; Boehme, F.; Kainer, L.; Christie, B.R. Hippocampal Cell Loss and Neurogenesis after Fetal Alcohol Exposure: Insights from Different Rodent Models. Brain Res. Rev. 2010, 64, 283–303.
  83. Miller, M.W. Effects of Prenatal Exposure to Alcohol on Postnatal Brain Development. Nat. Rev. Neurosci. 2018, 19, 639–651.
  84. McEwen, B.S.; Bowles, N.P.; Gray, J.D.; Hill, M.N.; Hunter, R.G.; Karatsoreos, I.N.; Nasca, C. Mechanisms of Stress in the Brain. Nat. Neurosci. 2015, 18, 1353–1363.
  85. Catala, M. Embryonic Development of the Central Nervous System. In Encyclopedia of Neuroscience; Springer: Berlin/Heidelberg, Germany, 2021; pp. 196–202.
  86. Copp, A.J.; Greene, N.D.E. Neural Tube Defects-Disorders of Neurulation and Related Embryonic Processes. Wiley Interdiscip. Rev. Dev. Biol. 2013, 2, 213–227.
  87. Rakic, P. Specification of Cerebral Cortical Areas. Science 1988, 241, 170–176.
  88. Lemaire, V.; Koehl, M.; Le Moal, M.; Abrous, D.N. Prenatal Stress Produces Learning Deficits Associated with an Inhibition of Neurogenesis in the Hippocampus. Proc. Natl. Acad. Sci. USA 2000, 97, 11032–11037.
  89. Martinez, S.; Alvarado-Mallart, R.M. Developmental Aspects of the Segmented Brain Hypothesis. Brain Res. Bull. 2002, 57, 301–305.
  90. Perry, V.H.; Hume, D.A.; Gordon, S. Immunohistochemical Localization of Macrophages and Microglia in the Adult and Developing Mouse Brain. Neuroscience 1985, 15, 313–326.
  91. Miller, F.D.; Gauthier-Fisher, A. Home at Last: Neural Stem Cell Niches Defined. Cell Stem Cell 2009, 4, 507–510.
  92. Paus, T. Growth of White Matter in the Adolescent Brain: Myelin or Axon? Brain Cogn. 2010, 72, 26–35.
  93. Kuan, C.-Y.; Roth, K.A.; Flavell, R.A.; Rakic, P. Mechanisms of Programmed Cell Death in the Developing Brain. Trends Neurosci. 2000, 23, 291–297.
  94. Bourgeois, J. Synaptogenesis, Heterochrony and Epigenesis in the Mammalian Neocortex. Acta Paediatr. 1997, 86, 27–33.
  95. Scott, J.G.; McNaughton, A.J.; Polis, I.; Stein, D.J. Childhood Trauma and COMT Genotype Interact to Increase Hippocampal Activation in Adulthood. Mol. Psychiatry 2006, 11, 1066–1067.
  96. Hultman, C.M.; Sparen, P.; Takei, N.; Murray, R.M.; Cnattingius, S.; Geddes, J. Prenatal and Perinatal Risk Factors for Schizophrenia, Affective Psychosis, and Reactive Psychosis of Early Onset: Case-Control Study Prenatal and Perinatal Risk Factors for Early Onset Schizophrenia, Affective Psychosis, and Reactive Psychosis. BMJ 1999, 318, 421–426.
  97. Lacagnina, S. The Developmental Origins of Health and Disease (DOHaD). Am. J. Lifestyle Med. 2020, 14, 47–50.
  98. Wadhwa, P.; Buss, C.; Entringer, S.; Swanson, J. Developmental Origins of Health and Disease: Brief History of the Approach and Current Focus on Epigenetic Mechanisms. Semin. Reprod. Med. 2009, 27, 358–368.
  99. de Juan Romero, C.; Borrell, V. Genetic Maps and Patterns of Cerebral Cortex Folding. Curr. Opin. Cell Biol. 2017, 49, 31–37.
  100. Toso, L.; Poggi, S.H.; Roberson, R.; Woodard, J.; Park, J.; Abebe, D.; Spong, C.Y. Prevention of Alcohol-Induced Learning Deficits in Fetal Alcohol Syndrome Mediated through NMDA and GABA Receptors. Am. J. Obstet. Gynecol. 2006, 194, 681–686.
  101. Olney, J.W.; Wozniak, D.F.; Jevtovic-Todorovic, V.; Farber, N.B.; Bittigau, P.; Ikonomidou, C. Glutamate and GABA Receptor Dysfunction in the Fetal Alcohol Syndrome. Neurotox. Res. 2002, 4, 315–325.
  102. Buss, C.; Entringer, S.; Wadhwa, P.D. Fetal Programming of Brain Development: Intrauterine Stress and Susceptibility to Psychopathology. Sci. Signal. 2012, 5, pt7.
  103. Winkler, I.; Tervaniemi, M.; Schröger, E. Pre-Attentive Auditory Processing in the Human Brainstem and Cortex. Neurosci. Biobehav. Rev. 2021, 122, 332–351.
  104. Partanen, E.; Kujala, T.; Tervaniemi, M.; Huotilainen, M. Prenatal Music Exposure Induces Long-Term Neural Effects. PLoS ONE 2013, 8, e78946.
  105. Golub, M.D.; Sadtler, P.T.; Oby, E.R.; Quick, K.M.; Ryu, S.I.; Tyler-Kabara, E.C.; Batista, A.P.; Chase, S.M.; Yu, B.M. Learning by Neural Reassociation. Nat. Neurosci. 2018, 21, 607–616.
  106. Giedd, J.N. Structural Magnetic Resonance Imaging of the Adolescent Brain. Ann. N. Y. Acad. Sci. 2004, 1021, 77–85.
  107. Bishop, D.V.M.; Snowling, M.J. Developmental Dyslexia and Specific Language Impairment: Same or Different? Psychol. Bull. 2004, 130, 858–886.
  108. Kuhl, P.K. Brain Mechanisms in Early Language Acquisition. Neuron 2010, 67, 713–727.
  109. Werker, J.F.; Hensch, T.K. Critical Periods in Speech Perception: New Directions. Annu. Rev. Psychol. 2015, 66, 173–196.
  110. Diamond, A. Executive Functions. Annu. Rev. Psychol. 2013, 64, 135–168.
  111. Hackman, D.A.; Farah, M.J. Socioeconomic Status and the Developing Brain. Trends Cogn. Sci. 2009, 13, 65–73.
  112. Bowlby, J. Attachment and Loss: Retrospect and Prospect. Am. J. Orthopsychiatry 1982, 52, 664–678.
  113. World Health Organization. Global Status Report on Violence Prevention 2014; World Health Organization: Geneva, Switzerland, 2014.
  114. World Health Organization. Global Status Report on Preventing Violence against Children; World Health Organization: Geneva, Switzerland, 2020.
  115. Russell, G.; Lightman, S. The Human Stress Response. Nat. Rev. Endocrinol. 2019, 15, 525–534.
  116. McEwen, B.S. Neurobiological and Systemic Effects of Chronic Stress. Chronic Stress 2017, 1, 2470547017692328.
  117. Oomen, C.A.; Mayer, J.L.; De Kloet, E.R.; Joëls, M.; Lucassen, P.J. Brief Treatment with the Glucocorticoid Receptor Antagonist Mifepristone Normalizes the Reduction in Neurogenesis after Chronic Stress. Eur. J. Neurosci. 2007, 26, 3395–3401.
  118. Liu, R.; Yang, X.D.; Liao, X.M.; Xie, X.M.; Su, Y.A.; Li, J.T.; Wang, X.D.; Si, T.M. Early Postnatal Stress Suppresses the Developmental Trajectory of Hippocampal Pyramidal Neurons: The Role of CRHR1. Brain Struct. Funct. 2016, 221, 4525–4536.
  119. Fabricius, K.; Wörtwein, G.; Pakkenberg, B. The Impact of Maternal Separation on Adult Mouse Behaviour and on the Total Neuron Number in the Mouse Hippocampus. Brain Struct. Funct. 2008, 212, 403–416.
  120. Chocyk, A.; Majcher-Maoelanka, I.; Dudys, D.; Przyborowska, A.; Wêdzony, K. Impact of Early-Life Stress on the Medial Prefrontal Cortex Functions-a Search for the Pathomechanisms of Anxiety and Mood Disorders. Pharmacol. Rep. 2013, 65, 1462–1470.
  121. Herzberg, M.P.; Gunnar, M.R. Early Life Stress and Brain Function: Activity and Connectivity Associated with Processing Emotion and Reward. Neuroimage 2020, 209, 116493.
  122. McEwen, B.S.; Gianaros, P.J. Central Role of the Brain in Stress and Adaptation: Links to Socioeconomic Status, Health, and Disease. Ann. N. Y. Acad. Sci. 2010, 1186, 190–222.
  123. Hair, N.L.; Hanson, J.L.; Wolfe, B.L.; Pollak, S.D. Association of Child Poverty, Brain Development, and Academic Achievement. JAMA Pediatr. 2015, 169, 822–829.
  124. Enoch, M.-A. The Role of Early Life Stress as a Predictor for Alcohol and Drug Dependence. Psychopharmacology 2011, 214, 17–31.
  125. Rothman, E.F.; Edwards, E.M.; Heeren, T.; Hingson, R.W. Adverse Childhood Experiences Predict Earlier Age of Drinking Onset: Results from a Representative US Sample of Current or Former Drinkers. Pediatrics 2008, 122, 298–304.
  126. Pilowsky, D.J.; Keyes, K.M.; Hasin, D.S. Adverse Childhood Events and Lifetime Alcohol Dependence. Am. J. Public Health 2009, 99, 258–263.
  127. Hyman, S.M.; Paliwal, P.; Chaplin, T.M.; Mazure, C.M.; Rounsaville, B.J.; Sinha, R. Severity of Childhood Trauma Is Predictive of Cocaine Relapse Outcomes in Women but Not Men. Drug Alcohol Depend. 2008, 92, 208–216.
  128. Blakemore, S.-J.; Choudhury, S. Development of the Adolescent Brain: Implications for Executive Function and Social Cognition. J. Child Psychol. Psychiatry 2006, 47, 296–312.
  129. Fareri, D.S.; Gabard-Durnam, L.J.; Goff, B.; Tottenham, N. Developmental Trajectories of Amygdala-Prefrontal Morphology and Functioning in Adolescents: A Longitudinal Study. Neuroimage 2015, 118, 239–247.
  130. Gee, D.G.; Humphreys, K.L.; Flannery, J.; Goff, B.; Telzer, E.H.; Shapiro, M.; Hare, T.A.; Bookheimer, S.Y.; Tottenham, N. A Developmental Shift from Positive to Negative Connectivity in Human Amygdala–Prefrontal Circuitry. J. Neurosci. 2013, 33, 4584–4593.
  131. Blakemore, S.-J. Development of the Social Brain in Adolescence. J. R. Soc. Med. 2012, 105, 111–116.
  132. Tottenham, N.; Galván, A. Stress and the Adolescent Brain. Neurosci. Biobehav. Rev. 2016, 70, 217–227.
  133. Sowell, E.R.; Peterson, B.S.; Thompson, P.M.; Welcome, S.E.; Henkenius, A.L.; Toga, A.W. Mapping Cortical Change across the Human Life Span. Nat. Neurosci. 2003, 6, 309–315.
  134. Evans, J.; Sumners, C.; Moore, J.; Huentelman, M.J.; Deng, J.; Gelband, C.H.; Shaw, G. Characterization of Mitotic Neurons Derived From Adult Rat Hypothalamus and Brain Stem. J. Neurophysiol. 2002, 87, 1076–1085.
  135. Parent, A.; Côté, P.Y.; Lavoie, B. Chemical Anatomy of Primate Basal Ganglia. Prog. Neurobiol. 1995, 46, 131–197.
  136. Suzuki, S.O.; Goldman, J.E. Multiple Cell Populations in the Early Postnatal Subventricular Zone Take Distinct Migratory Pathways: A Dynamic Study of Glial and Neuronal Progenitor Migration. J. Neurosci. 2003, 23, 4240–4250.
  137. Shapiro, L.A.; Ng, K.; Zhou, Q.-Y.; Ribak, C.E. Subventricular Zone-Derived, Newly Generated Neurons Populate Several Olfactory and Limbic Forebrain Regions. Epilepsy Behav. 2009, 14, 74–80.
  138. Zhao, M.; Momma, S.; Delfani, K.; Carlén, M.; Cassidy, R.M.; Johansson, C.B.; Brismar, H.; Shupliakov, O.; Frisén, J.; Janson, A.M. Evidence for Neurogenesis in the Adult Mammalian Substantia Nigra. Proc. Natl. Acad. Sci. USA 2003, 100, 7925–7930.
  139. Magavi, S.S.; Leavitt, B.R.; Macklis, J.D. Induction of Neurogenesis in the Neocortex of Adult Mice. Nature 2000, 405, 951–955.
  140. Bernier, P.J.; Bédard, A.; Vinet, J.; Lévesque, M.; Parent, A. Newly Generated Neurons in the Amygdala and Adjoining Cortex of Adult Primates. Proc. Natl. Acad. Sci. USA 2002, 99, 11464–11469.
  141. Cao, Q.-L.; Howard, R.M.; Dennison, J.B.; Whittemore, S.R. Differentiation of Engrafted Neuronal-Restricted Precursor Cells Is Inhibited in the Traumatically Injured Spinal Cord. Exp. Neurol. 2002, 177, 349–359.
  142. Dayer, A.G.; Cleaver, K.M.; Abouantoun, T.; Cameron, H.A. New GABAergic Interneurons in the Adult Neocortex and Striatum Are Generated from Different Precursors. J. Cell Biol. 2005, 168, 415–427.
  143. Inta, D.; Alfonso, J.; von Engelhardt, J.; Kreuzberg, M.M.; Meyer, A.H.; van Hooft, J.A.; Monyer, H. Neurogenesis and Widespread Forebrain Migration of Distinct GABAergic Neurons from the Postnatal Subventricular Zone. Proc. Natl. Acad. Sci. USA 2008, 105, 20994–20999.
  144. Florio, M.; Huttner, W.B. Neural Progenitors, Neurogenesis and the Evolution of the Neocortex. Development 2014, 141, 2182–2194.
  145. Zecevic, N.; Rakic, P. Development of Layer I Neurons in the Primate Cerebral Cortex. J. Neurosci. 2001, 21, 5607–5619.
  146. Jhaveri, D.J.; Tedoldi, A.; Hunt, S.; Sullivan, R.; Watts, N.R.; Power, J.M.; Bartlett, P.F.; Sah, P. Evidence for Newly Generated Interneurons in the Basolateral Amygdala of Adult Mice. Mol. Psychiatry 2018, 23, 521–532.
  147. Lee, D.A.; Bedont, J.L.; Pak, T.; Wang, H.; Song, J.; Miranda-Angulo, A.; Takiar, V.; Charubhumi, V.; Balordi, F.; Takebayashi, H.; et al. Tanycytes of the Hypothalamic Median Eminence Form a Diet-Responsive Neurogenic Niche. Nat. Neurosci. 2012, 15, 700–702.
  148. Li, J.; Tang, Y.; Cai, D. IKKβ/NF-ΚB Disrupts Adult Hypothalamic Neural Stem Cells to Mediate a Neurodegenerative Mechanism of Dietary Obesity and Pre-Diabetes. Nat. Cell Biol. 2012, 14, 999–1012.
  149. Bernstein, P.L.; Zuo, M.; Cheng, M.-F. Social Condition Affects the Courtship Behavior of Male Ring Doves with Posterior Medial Hypothalamic Lesions. Behav. Neural Biol. 1993, 59, 120–125.
  150. Fowler, C.D.; Liu, Y.; Ouimet, C.; Wang, Z. The Effects of Social Environment on Adult Neurogenesis in the Female Prairie Vole. J. Neurobiol. 2002, 51, 115–128.
  151. Cheng, M.-F.; Peng, J.-P.; Chen, G.; Gardner, J.P.; Bonder, E.M. Functional Restoration of Acoustic Units and Adult-Generated Neurons after Hypothalamic Lesion. J. Neurobiol. 2004, 60, 197–213.
  152. Zhang, Y.; Kim, M.S.; Jia, B.; Yan, J.; Zuniga-Hertz, J.P.; Han, C.; Cai, D. Hypothalamic Stem Cells Control Ageing Speed Partly through Exosomal MiRNAs. Nature 2017, 548, 52–57.
  153. Plakkot, B.; Di Agostino, A.; Subramanian, M. Implications of Hypothalamic Neural Stem Cells on Aging and Obesity-Associated Cardiovascular Diseases. Cells 2023, 12, 769.
  154. Duman, R.S.; Nakagawa, S.; Malberg, J.E. Regulation of Adult Neurogenesis by Antidepressant Treatment. Neuropsychopharmacology 2001, 25, 836–844.
  155. Santarelli, L.; Saxe, M.; Gross, C.; Surget, A.; Battaglia, F.; Dulawa, S.; Weisstaub, N.; Lee, J.; Duman, R.; Arancio, O.; et al. Requirement of Hippocampal Neurogenesis for the Behavioral Effects of Antidepressants. Science 2003, 301, 805–809.
  156. Castello, N.A.; Nguyen, M.H.; Tran, J.D.; Cheng, D.; Green, K.N.; LaFerla, F.M. Ketamine-Induced Neurogenesis in Prefrontal Cortex Contributes to Antidepressant-like Effects. Proc. Natl. Acad. Sci. USA 2020, 117, 28794–28804.
  157. Gil-Mohapel, J.; Simpson, J.M.; Christie, B.R. Modulation of Adult Neurogenesis by Physical Exercise and Environmental Enrichment: Insights for the Treatment of Neurological Disorders. In Adult Neurogenesis and CNS Diseases; Transworld Research Network: Kerala, India, 2010; pp. 125–150.
  158. van Praag, H.; Christie, B.R.; Sejnowski, T.J.; Gage, F.H. Running Enhances Neurogenesis, Learning, and Long-Term Potentiation in Mice. Proc. Natl. Acad. Sci. USA 1999, 96, 13427–13431.
  159. Yau, S.; Gil-Mohapel, J.; Christie, B.R.; So, K. Physical Exercise-Induced Adult Neurogenesis: A Good Strategy to Prevent Cognitive Decline in Neurodegenerative Diseases? Biomed Res. Int. 2014, 2014, 403120.
  160. Christian, P.; Stewart, C.P.; Omumbo, J.A. Impact of Maternal and Child Nutrition on Health. Annu. Rev. Nutr. 2019, 39, 213–231.
  161. Edlow, A.G. Maternal Obesity and Neurodevelopmental and Psychiatric Disorders in Offspring. Prenat. Diagn. 2017, 37, 95–110.
  162. Rivera, H.M.; Christiansen, K.J.; Sullivan, E.L. The Role of Maternal Obesity in the Risk of Neuropsychiatric Disorders. Front. Neurosci. 2015, 9, 194.
  163. Dearden, L.; Ozanne, S.E. Early Life Origins of Metabolic Disease: Developmental Programming of Hypothalamic Pathways Controlling Energy Homeostasis. Front. Neuroendocrinol. 2015, 39, 3–16.
  164. Bae-Gartz, I.; Janoschek, R.; Breuer, S.; Schmitz, L.; Hoffmann, T.; Ferrari, N.; Branik, L.; Oberthuer, A.; Kloppe, C.-S.; Appel, S.; et al. Maternal Obesity Alters Neurotrophin-Associated MAPK Signaling in the Hypothalamus of Male Mouse Offspring. Front. Neurosci. 2019, 13, 962.
  165. Schmitz, L.; Kuglin, R.; Bae-Gartz, I.; Janoschek, R.; Appel, S.; Mesaros, A.; Jakovcevski, I.; Vohlen, C.; Handwerk, M.; Ensenauer, R.; et al. Hippocampal Insulin Resistance Links Maternal Obesity with Impaired Neuronal Plasticity in Adult Offspring. Psychoneuroendocrinology 2018, 89, 46–52.
  166. Van Dam, J.M.; Garrett, A.J.; Schneider, L.A.; Hodyl, N.A.; Goldsworthy, M.R.; Coat, S.; Rowan, J.A.; Hague, W.M.; Pitcher, J.B. Reduced Cortical Excitability, Neuroplasticity, and Salivary Cortisol in 11–13-Year-Old Children Born to Women with Gestational Diabetes Mellitus. EBioMedicine 2018, 31, 143–149.
  167. Yu, L.; Zhong, X.; He, Y.; Shi, Y. Butyrate, but Not Propionate, Reverses Maternal Diet-Induced Neurocognitive Deficits in Offspring. Pharmacol. Res. 2020, 160, 105082.
  168. Mendes-da-Silva, C.; Lemes, S.F.; Baliani, T.d.S.; Versutti, M.D.; Torsoni, M.A. Increased Expression of Hes5 Protein in Notch Signaling Pathway in the Hippocampus of Mice Offspring of Dams Fed a High-fat Diet during Pregnancy and Suckling. Int. J. Dev. Neurosci. 2015, 40, 35–42.
  169. Ge, Q.; Hu, X.; Ma, N.; Sun, M.; Zhang, L.; Cai, Z.; Tan, R.; Lu, H. Maternal High-salt Diet during Pregnancy Impairs Synaptic Plasticity and Memory in Offspring. FASEB J. 2021, 35, e21244.
  170. Wasserman, G.A.; Liu, X.; Parvez, F.; Ahsan, H.; Factor-Litvak, P.; van Geen, A.; Slavkovich, V.; Lolacono, N.J.; Cheng, Z.; Hussain, I.; et al. Water Arsenic Exposure and Children’s Intellectual Function in Araihazar, Bangladesh. Environ. Health Perspect. 2004, 112, 1329–1333.
  171. May, P.A.; Chambers, C.D.; Kalberg, W.O.; Zellner, J.; Feldman, H.; Buckley, D.; Kopald, D.; Hasken, J.M.; Xu, R.; Honerkamp-Smith, G.; et al. Prevalence of Fetal Alcohol Spectrum Disorders in 4 US Communities. JAMA 2018, 319, 474.
  172. Brancato, A.; Castelli, V.; Lavanco, G.; Marino, R.A.M.; Cannizzaro, C. In Utero Δ9-Tetrahydrocannabinol Exposure Confers Vulnerability towards Cognitive Impairments and Alcohol Drinking in the Adolescent Offspring: Is There a Role for Neuropeptide Y? J. Psychopharmacol. 2020, 34, 663–679.
  173. Volkow, N.D.; Jones, E.B. Have We Entered a New Era of Prenatal Cocaine Exposure? Neuropharmacology 2019, 151, 117–124.
  174. Grandjean, P.; Landrigan, P.J. Neurobehavioural Effects of Developmental Toxicity. Lancet Neurol. 2014, 13, 330–338.
  175. Dolk, H.; Lopes dos Santos, M.; Soares, P. Congenital Rubella Syndrome in the Era of Global Elimination of Measles and Rubella. Lancet 2017, 5, e287–e288.
  176. Mullins, E.; Evans, D.; Viner, R.M.; O’Brien, P. The Impact of the COVID-19 Pandemic on Perinatal Mental Health. J. Perinat. Med. 2021, 49, 327–329.
  177. Kancherla, V.; Razzaghi, H.; Okoniewski, K.C.; Wong, K.K.; Salihu, H.M.; Kirby, R.S.; Anjohrin, S.B. Increased Proportion of Reported Congenital Anomalies during the COVID-19 Pandemic. Birth Defects Res. 2021, 113, 1079–1087.
  178. Heidarzadeh, M.; Taheri, M.; Mazaheripour, Z.; Abbasi-Khameneh, F. The Incidence of Congenital Anomalies in Newborns before and during the Covid-19 Pandemic. Ital. J. Pediatr. 2022, 48, 174.
  179. Black, M.M.; Walker, S.P.; Fernald, L.C.H.; Andersen, C.T.; DiGirolamo, A.M.; Lu, C.; McCoy, D.C.; Fink, G.; Shawar, Y.R.; Shiffman, J.; et al. Early Childhood Development Coming of Age: Science through the Life Course. Lancet 2017, 389, 77–90.
  180. Vinuesa, A.; Bentivegna, M.; Calfa, G.; Filipello, F.; Pomilio, C.; Bonaventura, M.M.; Lux-Lantos, V.; Matzkin, M.E.; Gregosa, A.; Presa, J.; et al. Early Exposure to a High-Fat Diet Impacts on Hippocampal Plasticity: Implication of Microglia-Derived Exosome-like Extracellular Vesicles. Mol. Neurobiol. 2019, 56, 5075–5094.
  181. Arcego, D.M.; Olivo, L.B.; Moraes, R.O.; Garcia, E.d.S.; Silveira, A.C.; Krolow, R.; Couto-Pereira, N.d.S.; Lampert, C.; Toniazzo, A.P.; Nicola, F.d.C.; et al. Neurometabolic Effects of Sweetened Solution Intake during Adolescence Related to Depressive-like Phenotype in Rats. Nutrition 2020, 75–76, 110770.
  182. Lee, H.; Park, H.; Ha, E.; Hong, Y.-C.; Ha, M.; Park, H.; Kim, B.-N.; Lee, B.; Lee, S.-J.; Lee, K.Y.; et al. Effect of Breastfeeding Duration on Cognitive Development in Infants: 3-Year Follow-up Study. J. Korean Med. Sci. 2016, 31, 579.
  183. Abbink, M.R.; Schipper, L.; Naninck, E.F.G.; de Vos, C.M.H.; Meier, R.; van der Beek, E.M.; Lucassen, P.J.; Korosi, A. The Effects of Early Life Stress, Postnatal Diet Modulation, and Long-Term Western-Style Diet on Later-Life Metabolic and Cognitive Outcomes. Nutrients 2020, 12, 570.
  184. Ruel, M.T.; Alderman, H. Nutrition-Sensitive Interventions and Programmes: How Can They Help to Accelerate Progress in Improving Maternal and Child Nutrition? Lancet 2013, 382, 536–551.
  185. Victora, C.G.; Adair, L.; Fall, C.; Hallal, P.C.; Martorell, R.; Richter, L.; Sachdev, H.S. Maternal and Child Undernutrition: Consequences for Adult Health and Human Capital. Lancet 2008, 371, 340–357.
  186. Prado, E.L.; Abbeddou, S.; Adu-Afarwuah, S.; Arimond, M.; Ashorn, P.; Ashorn, U.; Brown, K.H.; Hess, S.Y.; Lartey, A.; Maleta, K.; et al. Linear Growth and Child Development in Burkina Faso, Ghana, and Malawi. Pediatrics 2016, 138, e20154698.
  187. Granat-McGregor, S.M.; Powell, C.A.; Walker, S.P. Nutritional Supplementation, Cognitive and Scholastic Outcomes of Kenyan Children. J. Nutr. 2007, 137, 2694–2699.
  188. Shonkoff, J.P.; Garner, A.S.; Siegel, B.S.; Dobbins, M.I.; Earls, M.F.; Garner, A.S.; McGuinn, L.; Pascoe, J.; Wood, D.L. The Lifelong Effects of Early Childhood Adversity and Toxic Stress. Pediatrics 2012, 129, e232–e246.
  189. Campbell, F.; Conti, G.; Heckman, J.J.; Moon, S.H.; Pinto, R.; Pungello, E.; Pan, Y. Early Childhood Investments Substantially Boost Adult Health. Science 2014, 343, 1478–1485.
  190. Yoshikawa, H.; Weiland, C.; Brooks-Gunn, J.; Burchinal, M.R.; Espinosa, L.M.; Gormley, W.T.; Ludwig, J.; Magnuson, K.A.; Phillips, D.; Zaslow, M.J. Investing in Our Future: The Evidence Base on Preschool Education; Society for Research in Child Development, Foundation for Child Development: Washington, DC, USA, 2013.
  191. Sheridan, M.A.; Fox, N.A.; Zeanah, C.H.; McLaughlin, K.A.; Nelson, C.A. Variation in Neural Development as a Result of Exposure to Institutionalization Early in Childhood. Proc. Natl. Acad. Sci. USA 2012, 109, 12927–12932.
  192. Nelson, C.A.; Thomas, K.M.; de Haan, M. Neural Bases of Cognitive Development. In Handbook of Child Psychology; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2007; pp. 1–56.
  193. Kempermann, G. Environmental Enrichment, New Neurons and the Neurobiology of Individuality. Nat. Rev. Neurosci. 2019, 20, 235–245.
  194. Bergami, M.; Masserdotti, G.; Temprana, S.G.; Motori, E.; Eriksson, T.M.; Göbel, J.; Yang, S.M.; Conzelmann, K.-K.; Schinder, A.F.; Götz, M.; et al. A Critical Period for Experience-Dependent Remodeling of Adult-Born Neuron Connectivity. Neuron 2015, 85, 710–717.
  195. Barichello, T.; Fagundes, G.D.; Generoso, J.S.; Dagostin, C.S.; Simões, L.R.; Vilela, M.C.; Comim, C.M.; Petronilho, F.; Quevedo, J.; Teixeira, A.L. Environmental Enrichment Restores Cognitive Deficits Induced by Experimental Childhood Meningitis. Rev. Bras. Psiquiatr. 2014, 36, 322–329.
  196. Troller-Renfree, S.V.; Costanzo, M.A.; Duncan, G.J.; Magnuson, K.; Gennetian, L.A.; Yoshikawa, H.; Halpern-Meekin, S.; Fox, N.A.; Noble, K.G. The Impact of a Poverty Reduction Intervention on Infant Brain Activity. Proc. Natl. Acad. Sci. USA 2022, 119, e2115649119.
  197. Vogel Ciernia, A.; Laufer, B.I.; Dunaway, K.W.; Mordaunt, C.E.; Coulson, R.L.; Totah, T.S.; Stolzenberg, D.S.; Frahm, J.C.; Singh-Taylor, A.; Baram, T.Z.; et al. Experience-Dependent Neuroplasticity of the Developing Hypothalamus: Integrative Epigenomic Approaches. Epigenetics 2018, 13, 318–330.
  198. Marrocco, J.; McEwen, B.S. Sex in the Brain: Hormones and Sex Differences. Dialogues Clin. Neurosci. 2016, 18, 373–383.
  199. Duarte-Guterman, P.; Yagi, S.; Chow, C.; Galea, L.A.M. Hippocampal Learning, Memory, and Neurogenesis: Effects of Sex and Estrogens across the Lifespan in Adults. Horm. Behav. 2015, 74, 37–52.
  200. Triviño-Paredes, J.; Patten, A.R.; Gil-Mohapel, J.; Christie, B.R. The Effects of Hormones and Physical Exercise on Hippocampal Structural Plasticity. Front. Neuroendocrinol. 2016, 41, 23–43.
  201. Hojo, Y.; Murakami, G.; Mukai, H.; Higo, S.; Hatanaka, Y.; Ogiue-Ikeda, M.; Ishii, H.; Kimoto, T.; Kawato, S. Estrogen Synthesis in the Brain—Role in Synaptic Plasticity and Memory. Mol. Cell. Endocrinol. 2008, 290, 31–43.
  202. Hojo, Y.; Hattori, T.; Enami, T.; Furukawa, A.; Suzuki, K.; Ishii, H.; Mukai, H.; Morrison, J.H.; Janssen, W.G.M.; Kominami, S.; et al. Adult Male Rat Hippocampus Synthesizes Estradiol from Pregnenolone by Cytochromes P45017α and P450 Aromatase Localized in Neurons. Proc. Natl. Acad. Sci. USA 2004, 101, 865–870.
  203. Kato, A.; Hojo, Y.; Higo, S.; Komatsuzaki, Y.; Murakami, G.; Yoshino, H.; Uebayashi, M.; Kawato, S. Female Hippocampal Estrogens Have a Significant Correlation with Cyclic Fluctuation of Hippocampal Spines. Front. Neural Circuits 2013, 7, 149.
  204. Okamoto, M.; Hojo, Y.; Inoue, K.; Matsui, T.; Kawato, S.; McEwen, B.S.; Soya, H. Mild Exercise Increases Dihydrotestosterone in Hippocampus Providing Evidence for Androgenic Mediation of Neurogenesis. Proc. Natl. Acad. Sci. USA 2012, 109, 13100–13105.
  205. Prange-Kiel, J.; Wehrenberg, U.; Jarry, H.; Rune, G.M. Para/Autocrine Regulation of Estrogen Receptors in Hippocampal Neurons. Hippocampus 2003, 13, 226–234.
  206. Camacho-Arroyo, I.; Piña-Medina, A.G.; Bello-Alvarez, C.; Zamora-Sánchez, C.J. Sex Hormones and Proteins Involved in Brain Plasticity. Vitam. Horm. 2020, 114, 145–165.
  207. Fester, L.; Rune, G.M. Sex Neurosteroids: Hormones Made by the Brain for the Brain. Neurosci. Lett. 2021, 753, 135849.
  208. Brunne, B.; Rune, G.M. Sex Neurosteroidogenesis and Hippocampal Network Maintenance. Curr. Opin. Endocr. Metab. Res. 2022, 23, 100316.
  209. McEwen, B.S.; Akama, K.T.; Spencer-Segal, J.L.; Milner, T.A.; Waters, E.M. Estrogen Effects on the Brain: Actions beyond the Hypothalamus via Novel Mechanisms. Behav. Neurosci. 2012, 126, 4–16.
  210. Brann, D.W.; Lu, Y.; Wang, J.; Zhang, Q.; Thakkar, R.; Sareddy, G.R.; Pratap, U.P.; Tekmal, R.R.; Vadlamudi, R.K. Brain-Derived Estrogen and Neural Function. Neurosci. Biobehav. Rev. 2022, 132, 793–817.
  211. Lu, Y.; Sareddy, G.R.; Wang, J.; Wang, R.; Li, Y.; Dong, Y.; Zhang, Q.; Liu, J.; O’Connor, J.C.; Xu, J.; et al. Neuron-Derived Estrogen Regulates Synaptic Plasticity and Memory. J. Neurosci. 2019, 39, 2792–2809.
  212. Bettio, L.E.B.; Thacker, J.S.; Rodgers, S.P.; Brocardo, P.S.; Christie, B.R.; Gil-Mohapel, J. Interplay between Hormones and Exercise on Hippocampal Plasticity across the Lifespan. Biochim. Biophys. Acta-Mol. Basis Dis. 2020, 1866, 165821.
  213. López-Otín, C.; Blasco, M.A.; Partridge, L.; Serrano, M.; Kroemer, G. The Hallmarks of Aging. Cell 2013, 153, 1194–1217.
  214. United Nations. World Population Ageing 2019; United Nations: New York, NY, USA, 2020.
  215. United Nations. World Population Ageing 2019: Highlights; United Nations: New York, NY, USA, 2019.
  216. World Health Organization. World Report on Ageing and Health; World Health Organization: Geneva, Switzerland, 2015.
  217. Centers for Disease Control and Prevention. Diabetes and Aging; Centers for Disease Control and Prevention: Atlanta, GA, USA, 2021.
  218. American Cancer Society. Cancer Facts and Figures 2021; American Cancer Society: Atlanta, GA, USA, 2021.
  219. Beard, J.R.; Officer, A.; de Carvalho, I.A.; Sadana, R.; Pot, A.M.; Michel, J.-P.; Lloyd-Sherlock, P.; Epping-Jordan, J.E.; Peeters, G.M.E.E.; Mahanani, W.R.; et al. The World Report on Ageing and Health: A Policy Framework for Healthy Ageing. Lancet 2016, 387, 2145–2154.
  220. Childs, B.G.; Durik, M.; Baker, D.J.; van Deursen, J.M. Cellular Senescence in Aging and Age-Related Disease: From Mechanisms to Therapy. Nat. Med. 2015, 21, 1424–1435.
  221. Navarro, A.; Boveris, A. The Mitochondrial Energy Transduction System and the Aging Process. Am. J. Physiol. Physiol. 2007, 292, C670–C686.
  222. Muñoz-Espín, D.; Serrano, M. Cellular Senescence: From Physiology to Pathology. Nat. Rev. Mol. Cell Biol. 2014, 15, 482–496.
  223. Stern, Y. Cognitive Reserve✩. Neuropsychologia 2009, 47, 2015–2028.
  224. Stern, Y.; Arenaza-Urquijo, E.M.; Bartrés-Faz, D.; Belleville, S.; Cantilon, M.; Chetelat, G.; Ewers, M.; Franzmeier, N.; Kempermann, G.; Kremen, W.S.; et al. Whitepaper: Defining and Investigating Cognitive Reserve, Brain Reserve, and Brain Maintenance. Alzheimers Dement. 2020, 16, 1305–1311.
  225. McQuail, J.A.; Dunn, A.R.; Stern, Y.; Barnes, C.A.; Kempermann, G.; Rapp, P.R.; Kaczorowski, C.C.; Foster, T.C. Cognitive Reserve in Model Systems for Mechanistic Discovery: The Importance of Longitudinal Studies. Front. Aging Neurosci. 2021, 12, 607685.
  226. Ionescu-Tucker, A.; Cotman, C.W. Emerging Roles of Oxidative Stress in Brain Aging and Alzheimer’s Disease. Neurobiol. Aging 2021, 107, 86–95.
  227. Baracaldo-Santamaría, D.; Avendaño-Lopez, S.S.; Ariza-Salamanca, D.F.; Rodriguez-Giraldo, M.; Calderon-Ospina, C.A.; González-Reyes, R.E.; Nava-Mesa, M.O. Role of Calcium Modulation in the Pathophysiology and Treatment of Alzheimer’s Disease. Int. J. Mol. Sci. 2023, 24, 9067.
  228. Lesuis, S.L.; Hoeijmakers, L.; Korosi, A.; de Rooij, S.R.; Swaab, D.F.; Kessels, H.W.; Lucassen, P.J.; Krugers, H.J. Vulnerability and Resilience to Alzheimer’s Disease: Early Life Conditions Modulate Neuropathology and Determine Cognitive Reserve. Alzheimers. Res. Ther. 2018, 10, 95.
  229. Jellinger, K.A.; Attems, J. Neuropathological Approaches to Cerebral Aging and Neuroplasticity. Dialogues Clin. Neurosci. 2013, 15, 29–43.
  230. Hy, L.X.; Keller, D.M. Prevalence of AD among Whites. Neurology 2000, 55, 198–204.
  231. Niu, H.; Álvarez-Álvarez, I.; Guillén-Grima, F.; Aguinaga-Ontoso, I. Prevalence and Incidence of Alzheimer’s Disease in Europe: A Meta-Analysis. Neurologia 2017, 32, 523–532.
  232. Knopman, D.S.; Amieva, H.; Petersen, R.C.; Chételat, G.; Holtzman, D.M.; Hyman, B.T.; Nixon, R.A.; Jones, D.T. Alzheimer Disease. Nat. Rev. Dis. Prim. 2021, 7, 33.
  233. Guo, J.; Huang, X.; Dou, L.; Yan, M.; Shen, T.; Tang, W.; Li, J. Aging and Aging-Related Diseases: From Molecular Mechanisms to Interventions and Treatments. Signal Transduct. Target. Ther. 2022, 7, 391.
  234. Verkhratsky, A.; Lazareva, N.; Semyanov, A. Glial Decline and Loss of Homeostatic Support Rather than Inflammation Defines Cognitive Aging. Neural Regen. Res. 2022, 17, 565.
  235. Barrientos, R.M.; Kitt, M.M.; Watkins, L.R.; Maier, S.F. Neuroinflammation in the Normal Aging Hippocampus. Neuroscience 2015, 309, 84–99.
  236. Wang, X.; Michaelis, E.K. Selective Neuronal Vulnerability to Oxidative Stress in the Brain. Front. Aging Neurosci. 2010, 2, 12.
  237. Grimm, A.; Eckert, A. Brain Aging and Neurodegeneration: From a Mitochondrial Point of View. J. Neurochem. 2017, 143, 418–431.
  238. Johnson, F.B.; Sinclair, D.A.; Guarente, L. Molecular Biology of Aging. Cell 1999, 96, 291–302.
  239. Khachaturian, Z.S. The Role of Calcium Regulation in Brain Aging: Reexamination of a Hypothesis. Aging Clin. Exp. Res. 1989, 1, 17–34.
  240. Foster, T.C. Calcium Homeostasis and Modulation of Synaptic Plasticity in the Aged Brain. Aging Cell 2007, 6, 319–325.
  241. Gant, J.C.; Chen, K.-C.; Kadish, I.; Blalock, E.M.; Thibault, O.; Porter, N.M.; Landfield, P.W. Reversal of Aging-Related Neuronal Ca2+ Dysregulation and Cognitive Impairment by Delivery of a Transgene Encoding FK506-Binding Protein 12.6/1b to the Hippocampus. J. Neurosci. 2015, 35, 10878–10887.
  242. Kumar, A.; Foster, T.C. Alteration in NMDA Receptor Mediated Glutamatergic Neurotransmission in the Hippocampus During Senescence. Neurochem. Res. 2019, 44, 38–48.
  243. Santos-Parker, J.R.; LaRocca, T.J.; Seals, D.R. Aerobic Exercise and Other Healthy Lifestyle Factors That Influence Vascular Aging. Adv. Physiol. Educ. 2014, 38, 296–307.
  244. Simpson, R.J.; Kunz, H.; Agha, N.; Graff, R. Exercise and the Regulation of Immune Functions. Prog. Mol. Biol. Transl. Sci. 2015, 135, 355–380.
  245. Fjell, A.M.; Walhovd, K.B. Structural Brain Changes in Aging: Courses, Causes and Cognitive Consequences. Rev. Neurosci. 2010, 21, 187–222.
  246. Beyer, K.; Domingo-Sàbat, M.; Ariza, A.; Guillazo-Blanch, G. Molecular Anatomy of the Nigrostriatal Pathway in the Rat: A Review. Neuroscience 2012, 227, 70–83.
  247. Gil, J.M.; Rego, A.C. Mechanisms of Neurodegeneration in Huntington’s Disease. Eur. J. Neurosci. 2008, 27, 2803–2820.
  248. Li, Y.; Liu, W.; Oo, T.F.; Wang, L.; Tang, Y.; Jackson-Lewis, V.; Zhou, C.; Geghman, K.; Bogdanov, M.; Przedborski, S.; et al. Mutant LRRK2R1441G BAC Transgenic Mice Recapitulate Cardinal Features of Parkinson’s Disease. Nat. Neurosci. 2009, 12, 826–828.
  249. Alzheimer’s Association. 2022 Alzheimer’s Disease Facts and Figures, More Than Normal Aging: Understanding Mild Cognitive Impairment; Alzheimer’s Association: Chicago, IL, USA, 2022.
  250. Parkinson’s Foundation. Statistics on Parkinson’s; Parkinson’s Foundation: New York, NY, USA, 2021.
  251. World Health Organization. Dementia; World Health Organization: Geneva, Switzerland, 2019.
  252. Bhat, A.H.; Dar, K.B.; Anees, S.; Zargar, M.A.; Masood, A.; Sofi, M.A.; Ganie, S.A. Oxidative Stress, Mitochondrial Dysfunction and Neurodegenerative Diseases; a Mechanistic Insight. Biomed. Pharmacother. 2015, 74, 101–110.
  253. Sweeney, P.; Park, H.; Baumann, M.; Dunlop, J.; Frydman, J.; Kopito, R.; McCampbell, A.; Leblanc, G.; Venkateswaran, A.; Nurmi, A.; et al. Protein misfolding in neurodegenerative diseases: Implications and strategies. Transl Neurodegener. 2017, 6, 1–13.
  254. DiFiglia, M.; Sapp, E.; Chase, K.O.; Davies, S.W.; Bates, G.P.; Vonsattel, J.P.; Aronin, N. Aggregation of Huntingtin in Neuronal Intranuclear Inclusions and Dystrophic Neurites in Brain. Science 1997, 277, 1990–1993.
  255. Moreno-Gonzalez, I.; Edwards III, G.; Salvadores, N. Shining a Light on Protein Misfolding and Aggregation in Neurological Diseases. Protein Sci. 2018, 27, 1820–1831.
  256. Sun, N.; Youle, R.J.; Finkel, T. The Mitochondrial Basis of Aging. Mol. Cell 2016, 61, 654–666.
  257. Hroudová, J.; Singh, N.; Fišar, Z. Mitochondrial Dysfunctions in Neurodegenerative Diseases: Relevance to Alzheimer’s Disease. Biomed Res. Int. 2014, 2014, 175062.
  258. Li, M.; Fu, X.; Xie, W.; Guo, W.; Li, B.; Cui, R.; Yang, W. Effect of Early Life Stress on the Epigenetic Profiles in Depression. Front. Cell Dev. Biol. 2020, 8, 867.
  259. Niranjan, R. The Role of Inflammatory and Oxidative Stress Mechanisms in the Pathogenesis of Parkinson’s Disease: Focus on Astrocytes. Mol. Neurobiol. 2014, 49, 28–38.
  260. das Neves, S.P.; Sousa, J.C.; Sousa, N.; Cerqueira, J.J.; Marques, F. Altered astrocytic function in experimental neuroinflammation and multiple sclerosis. Glia 2021, 69, 1341–1368.
  261. Xie, Z.; Morgan, T.E.; Rozovsky, I.; Finch, C.E.; Longo, D.L. The Inflammation-Coagulation Connection in Brain Aging and Alzheimer’s Disease. Neurosci. Biobehav. Rev. 2013, 37, 1572–1587.
  262. Prusiner, S.B. A Unifying Role for Prions in Neurodegenerative Diseases. Science 2012, 336, 1511–1513.
  263. Powers, E.T.; Balch, W.E. Diversity in the Origins of Proteostasis Networks—A Driver for Protein Function in Evolution. Nat. Rev. Mol. Cell Biol. 2013, 14, 237–248.
  264. Hoozemans, J.J.M.; van Haastert, E.S.; Nijholt, D.A.T.; Rozemuller, A.J.M.; Eikelenboom, P.; Scheper, W. The Unfolded Protein Response Is Activated in Pretangle Neurons in Alzheimer’s Disease Hippocampus. Am. J. Pathol. 2009, 174, 1241–1251.
  265. Hetz, C.; Saxena, S. ER Stress and the Unfolded Protein Response in Neurodegeneration. Nat. Rev. Neurol. 2017, 13, 477–491.
  266. Smith, H.L.; Mallucci, G.R. The Unfolded Protein Response: Mechanisms and Therapy of Neurodegeneration. Brain 2016, 139, 2113–2121.
  267. Hoozemans, J.J.M.; Veerhuis, R.; Van Haastert, E.S.; Rozemuller, J.M.; Baas, F.; Eikelenboom, P.; Scheper, W. The Unfolded Protein Response Is Activated in Alzheimer’s Disease. Acta Neuropathol. 2005, 110, 165–172.
  268. Bellucci, A.; Navarria, L.; Zaltieri, M.; Falarti, E.; Bodei, S.; Sigala, S.; Battistin, L.; Spillantini, M.; Missale, C.; Spano, P. Induction of the Unfolded Protein Response by α-Synuclein in Experimental Models of Parkinson’s Disease. J. Neurochem. 2011, 116, 588–605.
  269. Briston, T.; Hicks, A.R. Mitochondrial Dysfunction and Neurodegenerative Proteinopathies: Mechanisms and Prospects for Therapeutic Intervention. Biochem. Soc. Trans. 2018, 46, 829–842.
  270. Kraytsberg, Y.; Kudryavtseva, E.; McKee, A.C.; Geula, C.; Kowall, N.W.; Khrapko, K. Mitochondrial DNA Deletions Are Abundant and Cause Functional Impairment in Aged Human Substantia Nigra Neurons. Nat. Genet. 2006, 38, 518–520.
  271. Rhein, V.; Baysang, G.; Rao, S.; Meier, F.; Bonert, A.; Müller-Spahn, F.; Eckert, A. Amyloid-Beta Leads to Impaired Cellular Respiration, Energy Production and Mitochondrial Electron Chain Complex Activities in Human Neuroblastoma Cells. Cell. Mol. Neurobiol. 2009, 29, 1063–1071.
  272. Du, J.; Wang, Y.; Hunter, R.; Wei, Y.; Blumenthal, R.; Falke, C.; Khairova, R.; Zhou, R.; Yuan, P.; Machado-Vieira, R.; et al. Dynamic Regulation of Mitochondrial Function by Glucocorticoids. Proc. Natl. Acad. Sci. USA 2009, 106, 3543–3548.
  273. Schon, E.A.; Przedborski, S. Mitochondria: The Next (Neurode)Generation. Neuron 2011, 70, 1033–1053.
  274. Nunomura, A.; Moreira, P.I.; Castellani, R.J.; Lee, H.; Zhu, X.; Smith, M.A.; Perry, G. Oxidative Damage to RNA in Aging and Neurodegenerative Disorders. Neurotox. Res. 2012, 22, 231–248.
  275. Mishra, S.R.; Mahapatra, K.K.; Behera, B.P.; Patra, S.; Bhol, C.S.; Panigrahi, D.P.; Praharaj, P.P.; Singh, A.; Patil, S.; Dhiman, R.; et al. Mitochondrial dysfunction as a driver of NLRP3 inflammasome activation and its modulation through mitophagy for potential therapeutics. Int. J. Biochem Cell Biol. 2021, 136, 106013.
  276. Choo, Y.S. Mutant Huntingtin Directly Increases Susceptibility of Mitochondria to the Calcium-Induced Permeability Transition and Cytochrome c Release. Hum. Mol. Genet. 2004, 13, 1407–1420.
  277. Gallart-Palau, X.; Lee, B.S.; Adav, S.S.; Qian, J.; Serra, A.; Park, J.E.; Lai, M.K.; Chen, C.P.; Kalaria, R.N.; Sze, S.K. Gender differences in white matter pathology and mitochondrial dysfunction in Alzheimer’s disease with cerebrovascular disease. Mol. Brain. 2016, 17, 27.
  278. Hansson Petersen, C.A.; Alikhani, N.; Behbahani, H.; Wiehager, B.; Pavlov, P.F.; Alafuzoff, I.; Leinonen, V.; Ito, A.; Winblad, B.; Glaser, E.; et al. The Amyloid β-Peptide Is Imported into Mitochondria via the TOM Import Machinery and Localized to Mitochondrial Cristae. Proc. Natl. Acad. Sci. USA 2008, 105, 13145–13150.
  279. Schapira, A.H.V. Mitochondrial Dysfunction in Parkinson’s Disease. Cell Death Differ. 2007, 14, 1261–1266.
  280. Surmeier, D.J.; Obeso, J.A.; Halliday, G.M. Parkinson’s Disease Is Not Simply a Prion Disorder. J. Neurosci. 2017, 37, 9799–9807.
  281. McGeer, P.L.; McGeer, E.G. Inflammation and Neurodegeneration in Parkinson’s Disease. Parkinsonism Relat. Disord. 2004, 10, S3–S7.
  282. Mandrekar-Colucci, S.; Karlo, J.C.; Landreth, G.E. Mechanisms Underlying the Rapid Peroxisome Proliferator-Activated Receptor-γ-Mediated Amyloid Clearance and Reversal of Cognitive Deficits in a Murine Model of Alzheimer’s Disease. J. Neurosci. 2012, 32, 10117–10128.
  283. Heneka, M.T.; Carson, M.J.; El Khoury, J.; Landreth, G.E.; Brosseron, F.; Feinstein, D.L.; Jacobs, A.H.; Wyss-Coray, T.; Vitorica, J.; Ransohoff, R.M.; et al. Neuroinflammation in Alzheimer’s Disease. Lancet Neurol. 2015, 14, 388–405.
  284. Liddelow, S.A.; Guttenplan, K.A.; Clarke, L.E.; Bennett, F.C.; Bohlen, C.J.; Schirmer, L.; Bennett, M.L.; Münch, A.E.; Chung, W.-S.; Peterson, T.C.; et al. Neurotoxic Reactive Astrocytes Are Induced by Activated Microglia. Nature 2017, 541, 481–487.
  285. Ising, C.; Heneka, M.T. Functional and Structural Damage of Neurons by Innate Immune Mechanisms during Neurodegeneration. Cell Death Dis. 2018, 9, 120.
  286. Lučiūnaitė, A.; McManus, R.M.; Jankunec, M.; Rácz, I.; Dansokho, C.; Dalgėdienė, I.; Schwartz, S.; Brosseron, F.; Heneka, M.T. Soluble Aβ Oligomers and Protofibrils Induce NLRP3 Inflammasome Activation in Microglia. J. Neurochem. 2020, 155, 650–661.
  287. La Vitola, P.; Balducci, C.; Baroni, M.; Artioli, L.; Santamaria, G.; Castiglioni, M.; Cerovic, M.; Colombo, L.; Caldinelli, L.; Pollegioni, L.; et al. Peripheral Inflammation Exacerbates A-synuclein Toxicity and Neuropathology in Parkinson’s Models. Neuropathol. Appl. Neurobiol. 2021, 47, 43–60.
  288. Colombo, E.; Farina, C. Astrocytes: Key Regulators of Neuroinflammation. Trends Immunol. 2016, 37, 608–620.
  289. Rodríguez-Arellano, J.J.; Parpura, V.; Zorec, R.; Verkhratsky, A. Astrocytes in Physiological Aging and Alzheimer’s Disease. Neuroscience 2016, 323, 170–182.
  290. Coppedè, F.; Mancuso, M.; Siciliano, G.; Migliore, L.; Murri, L. Genes and the environment in neurodegeneration. Biosci. Rep. 2006, 26, 341–367.
  291. Ulrich, J.D.; Holtzman, D.M. TREM2 Function in Alzheimer’s Disease and Neurodegeneration. ACS Chem. Neurosci. 2016, 7, 420–427.
  292. Gialluisi, A.; Reccia, M.G.; Modugno, N.; Nutile, T.; Lombardi, A.; Di Giovannantonio, L.G.; Pietracupa, S.; Ruggiero, D.; Scala, S.; Gambardella, S.; et al. Identification of Sixteen Novel Candidate Genes for Late Onset Parkinson’s Disease. Mol. Neurodegener. 2021, 16, 35.
  293. Costa, L.G. Neurotoxicity of Pesticides: A Brief Review. Front. Biosci. 2008, 13, 1240.
  294. Itzhaki, R.F.; Lathe, R.; Balin, B.J.; Ball, M.J.; Bearer, E.L.; Braak, H.; Bullido, M.J.; Carter, C.; Clerici, M.; Cosby, S.L.; et al. Microbes and Alzheimer’s Disease. J. Alzheimers Dis. 2016, 51, 979–984.
  295. McKee, A.C.; Stein, T.D.; Nowinski, C.J.; Stern, R.A.; Daneshvar, D.H.; Alvarez, V.E.; Lee, H.-S.; Hall, G.; Wojtowicz, S.M.; Baugh, C.M.; et al. The Spectrum of Disease in Chronic Traumatic Encephalopathy. Brain 2013, 136, 43–64.
  296. Morrison, J.H.; Baxter, M.G. The Ageing Cortical Synapse: Hallmarks and Implications for Cognitive Decline. Nat. Rev. Neurosci. 2012, 13, 240–250.
  297. Lövdén, M.; Bäckman, L.; Lindenberger, U.; Schaefer, S.; Schmiedek, F. A Theoretical Framework for the Study of Adult Cognitive Plasticity. Psychol. Bull. 2010, 136, 659–676.
  298. Burke, S.N.; Barnes, C.A.; Seneczko, K. Decreased Hippocampal LTP in Aged Rats Associated with Deficits in Explicit Memory Retrieval. Hippocampus 2010, 20, 817–827.
  299. Spencer, J.L.; Waters, E.M.; Milner, T.A.; Lee, F.S.; McEwen, B.S. BDNF Variant Val66Met Interacts with Estrous Cycle in the Control of Hippocampal Function. Proc. Natl. Acad. Sci. USA 2010, 107, 4395–4400.
  300. Amani, M.; Lauterborn, J.C.; Le, A.A.; Cox, B.M.; Wang, W.; Quintanilla, J.; Cox, C.D.; Gall, C.M.; Lynch, G. Rapid Aging in the Perforant Path Projections to the Rodent Dentate Gyrus. J. Neurosci. 2021, 41, 2301–2312.
  301. Buss, E.W.; Corbett, N.J.; Roberts, J.G.; Ybarra, N.; Musial, T.F.; Simkin, D.; Molina-Campos, E.; Oh, K.-J.; Nielsen, L.L.; Ayala, G.D.; et al. Cognitive Aging Is Associated with Redistribution of Synaptic Weights in the Hippocampus. Proc. Natl. Acad. Sci. USA 2021, 118, e1921481118.
  302. Yu, X.-W.; Oh, M.M.; Disterhoft, J.F. CREB, Cellular Excitability, and Cognition: Implications for Aging. Behav. Brain Res. 2017, 322, 206–211.
  303. Gharsemian-Shirvan, M.; Khodagholi, F.; Shaerzadeh, F. Age-Related Changes in Dendritic Arborization, Spine Morphology, and Synaptic Density: An Ultrastructural Study on CA1 Pyramidal Neurons of Rat Hippocampus. Synapse 2020, 74, e22101.
  304. Lilja, A.M.; Röjdner, J.; Mustafiz, T.; Thomé, C.M.; Storelli, E.; Gonzalez, D.; Unger-Lithner, C.; Greig, N.H.; Nordberg, A.; Marutle, A. Age-Dependent Neuroplasticity Mechanisms in Alzheimer Tg2576 Mice Following Modulation of Brain Amyloid-β Levels. PLoS ONE 2013, 8, e58752.
  305. Torres, L.L.; Quaglio, N.B.; de Souza, G.T.; Garcia, R.C.T. Synaptic Plasticity, Dementia and Alzheimer Disease. In Synaptic Plasticity in Neurodegenerative Diseases; Academic Press: Cambridge, MA, USA, 2020; pp. 67–90.
  306. Demars, M.; Hu, Y.-S.; Gadadhar, A.; Lazarov, O. Impaired Neurogenesis Is an Early Event in the Etiology of Familial Alzheimer’s Disease in Transgenic Mice. J. Neurosci. Res. 2010, 88, 2103–2117.
  307. Gil-Mohapel, J.; Brocardo, P.S.; Choquette, W.; Gothard, R.; Simpson, J.M.; Christie, B.R. Hippocampal Neurogenesis Levels Predict WATERMAZE Search Strategies in the Aging Brain. PLoS ONE 2013, 8, e75125.
  308. Fjell, A.M.; Walhovd, K.B.; Fennema-Notestine, C.; McEvoy, L.K.; Hagler, D.J.; Holland, D.; Brewer, J.B.; Dale, A.M. One-Year Brain Atrophy Evident in Healthy Aging. J. Neurosci. 2009, 29, 15223–15231.
  309. Hötting, K.; Röder, B. Beneficial Effects of Physical Exercise on Neuroplasticity and Cognition. Neurosci. Biobehav. Rev. 2013, 37, 2243–2257.
  310. Franzén, E.; Johansson, H.; Freidle, M.; Ekman, U.; Wallén, M.B.; Schalling, E.; Lebedev, A.; Lövdén, M.; Holmin, S.; Svenningsson, P.; et al. The EXPANd Trial: Effects of Exercise and Exploring Neuroplastic Changes in People with Parkinson’s Disease: A Study Protocol for a Double-Blinded Randomized Controlled Trial. BMC Neurol. 2019, 19, 280.
  311. Garzón, B.; Lövdén, M.; de Boer, L.; Axelsson, J.; Riklund, K.; Bäckman, L.; Nyberg, L.; Guitart-Masip, M. Role of Dopamine and Gray Matter Density in Aging Effects and Individual Differences of Functional Connectomes. Brain Struct. Funct. 2021, 226, 743–758.
  312. Katz, M.J.; Fratiglioni, L.; Wang, H.X.; Frisoni, G.B.; Bäckman, L. Maintaining Cognitive Health in Aging: The Role of Cognitive Reserve. Alzheimers. Res. Ther. 2021, 13, 1–11.
  313. Gavelin, H.M.; Dong, C.; Minkov, R.; Bahar-Fuchs, A.; Ellis, K.A.; Lautenschlager, N.T.; Mellow, M.L.; Wade, A.T.; Smith, A.E.; Finke, C.; et al. Combined physical and cognitive training for older adults with and without cognitive impairment: A systematic review and network meta-analysis of randomized controlled trials. Ageing Res Rev. 2021, 66, 101232.
  314. Duzel, E.; van Praag, H.; Sendtner, M. Can Physical Exercise in Old Age Improve Memory and Hippocampal Function? Brain 2016, 139, 662–673.
  315. Erickson, K.I.; Kramer, A.F. Aerobic Exercise Effects on Cognitive and Neural Plasticity in Older Adults. Br. J. Sports Med. 2008, 43, 22–24.
  316. Vaynman, S.; Ying, Z.; Gomez-Pinilla, F. Hippocampal BDNF Mediates the Efficacy of Exercise on Synaptic Plasticity and Cognition. Eur. J. Neurosci. 2004, 20, 2580–2590.
  317. Gutierrez, R.M.; Hidalgo-Lanussa, O.; Lattig, M.C.; Velez-Pardo, C. Exercise Intervention in Transgenic Alzheimer’s Rats Improves Hippocampal GABAergic Transmission and Cognition. Behav. Brain Res. 2018, 346, 136–143.
  318. Erickson, K.I.; Voss, M.W.; Prakash, R.S.; Basak, C.; Szabo, A.; Chaddock, L.; Kim, J.S.; Heo, S.; Alves, H.; White, S.M.; et al. Exercise Training Increases Size of Hippocampus and Improves Memory. Proc. Natl. Acad. Sci. USA 2011, 108, 3017–3022.
  319. van de Rest, O.; Berendsen, A.A.M.; Haveman-Nies, A.; de Groot, L.C.P.G.M. Dietary Patterns, Cognitive Decline, and Dementia: A Systematic Review. Adv. Nutr. 2015, 6, 154–168.
  320. Heyn, P.; Abreu, B.C.; Ottenbacher, K.J. The Effects of Exercise Training on Elderly Persons with Cognitive Impairment and Dementia: A Meta-Analysis. Arch. Phys. Med. Rehabil. 2004, 85, 1694–1704.
  321. Lautenschlager, N.T.; Cox, K.L.; Flicker, L.; Foster, J.K.; van Bockxmeer, F.M.; Xiao, J.; Greenop, K.R.; Almeida, O.P. Effect of Physical Activity on Cognitive Function in Older Adults at Risk for Alzheimer Disease. JAMA 2008, 300, 1027.
  322. Smith, P.J.; Blumenthal, J.A.; Hoffman, B.M.; Cooper, H.; Strauman, T.A.; Welsh-Bohmer, K.; Browndyke, J.N.; Sherwood, A. Aerobic Exercise and Neurocognitive Performance: A Meta-Analytic Review of Randomized Controlled Trials. Psychosom. Med. 2010, 72, 239–252.
  323. Northey, J.M.; Cherbuin, N.; Pumpa, K.L.; Smee, D.J.; Rattray, B. Exercise Interventions for Cognitive Function in Adults Older than 50: A Systematic Review with Meta-Analysis. Br. J. Sports Med. 2018, 52, 154–160.
  324. McGregor, K.M.; Crosson, B.; Mammino, K.; Omar, J.; García, P.S.; Nocera, J.R. Influences of 12-Week Physical Activity Interventions on TMS Measures of Cortical Network Inhibition and Upper Extremity Motor Performance in Older Adults—A Feasibility Study. Front. Aging Neurosci. 2018, 9, 422.
  325. Colcombe, S.J.; Erickson, K.I.; Scalf, P.E.; Kim, J.S.; Prakash, R.; McAuley, E.; Elavsky, S.; Marquez, D.X.; Hu, L.; Kramer, A.F. Aerobic Exercise Training Increases Brain Volume in Aging Humans. J. Gerontol. Ser. A Biol. Sci. Med. Sci. 2006, 61, 1166–1170.
  326. Maillot, P.; Perrot, A.; Hartley, A. Effects of Interactive Physical-Activity Video-Game Training on Physical and Cognitive Function in Older Adults. Psychol. Aging 2012, 27, 589–600.
  327. Yates, L.A.; Ziser, S.; Spector, A.; Orrell, M. Cognitive Leisure Activities and Future Risk of Cognitive Impairment and Dementia: Systematic Review and Meta-Analysis. Int. Psychogeriatr. 2016, 28, 1791–1806.
  328. Park, D.C.; Bischof, G.N. The Aging Mind: Neuroplasticity in Response to Cognitive Training. Dialogues Clin. Neurosci. 2013, 15, 109–119.
  329. Marioni, R.E.; Valenzuela, M.J.; van den Hout, A.; Brayne, C.; Matthews, F.E. Active Cognitive Lifestyle Is Associated with Positive Cognitive Health Transitions and Compression of Morbidity from Age Sixty-Five. PLoS ONE 2012, 7, e50940.
  330. Verghese, J.; Lipton, R.B.; Katz, M.J.; Hall, C.B.; Derby, C.A.; Kuslansky, G.; Ambrose, A.F.; Sliwinski, M.; Buschke, H. Leisure Activities and the Risk of Dementia in the Elderly. N. Engl. J. Med. 2003, 348, 2508–2516.
  331. Fabrigoule, C.; Letenneur, L.; Dartigues, J.F.; Zarrouk, M.; Commenges, D.; Barberger-Gateau, P. Social and Leisure Activities and Risk of Dementia: A Prospective Longitudinal Study. J. Am. Geriatr. Soc. 1995, 43, 485–490.
  332. Holwerda, T.J.; Deeg, D.J.H.; Beekman, A.T.F.; van Tilburg, T.G.; Stek, M.L.; Jonker, C.; Schoevers, R.A. Feelings of Loneliness, but Not Social Isolation, Predict Dementia Onset: Results from the Amsterdam Study of the Elderly (AMSTEL). J. Neurol. Neurosurg. Psychiatry 2014, 85, 135–142.
  333. Spreng, R.N.; Turner, G.R. Structural Covariance of the Default Network in Healthy and Pathological Aging. J. Neurosci. 2013, 33, 15226–15234.
  334. Zhang, Y.; Fu, S.; Ding, D.; Lutz, M.W.; Zeng, Y.; Yao, Y. Leisure Activities, APOE Ε4, and Cognitive Decline: A Longitudinal Cohort Study. Front. Aging Neurosci. 2021, 13, 736201.
  335. Gomez-Pinilla, F. The Combined Effects of Exercise and Foods in Preventing Neurological and Cognitive Disorders. Prev. Med. (Baltim.) 2011, 52, S75–S80.
  336. Morris, M.C.; Tangney, C.C.; Wang, Y.; Sacks, F.M.; Bennett, D.A.; Aggarwal, N.T. MIND Diet Associated with Reduced Incidence of Alzheimer’s Disease. Alzheimers Dement. 2015, 11, 1007–1014.
  337. Tangney, C.C.; Kwasny, M.J.; Li, H.; Wilson, R.S.; Evans, D.A.; Morris, M.C. Adherence to a Mediterranean-Type Dietary Pattern and Cognitive Decline in a Community Population. Am. J. Clin. Nutr. 2011, 93, 601–607.
  338. Innis, S.M. Dietary Omega 3 Fatty Acids and the Developing Brain. Brain Res. 2008, 1237, 35–43.
  339. Konagai, C.; Yanagimoto, K.; Hayamizu, K.; Han, L.; Tsuji, T.; Koga, Y. Effects of Krill Oil Containing N-3 Polyunsaturated Fatty Acids in Phospholipid Form on Human Brain Function: A Randomized Controlled Trial in Healthy Elderly Volunteers. Clin. Interv. Aging 2013, 8, 1247–1257.
  340. Witte, A.V.; Kerti, L.; Hermannstädter, H.M.; Fiebach, J.B.; Schreiber, S.J.; Schuchardt, J.P.; Hahn, A.; Flöel, A. Long-Chain Omega-3 Fatty Acids Improve Brain Function and Structure in Older Adults. Cereb. Cortex 2014, 24, 3059–3068.
  341. Dullemeijer, C.; Durga, J.; Brouwer, I.A.; van de Rest, O.; Kok, F.J.; Brummer, R.-J.M.; van Boxtel, M.P.; Verhoef, P. N−3 Fatty Acid Proportions in Plasma and Cognitive Performance in Older Adults. Am. J. Clin. Nutr. 2007, 86, 1479–1485.
  342. Melzer, T.M.; Manosso, L.M.; Yau, S.; Gil-Mohapel, J.; Brocardo, P.S. In Pursuit of Healthy Aging: Effects of Nutrition on Brain Function. Int. J. Mol. Sci. 2021, 22, 5026.
  343. Wu, L.; Sun, D.; Qu, X.; Zhang, R.; Wang, Y. Dietary Fat Intake and Risk of Cognitive Impairment or Dementia: A Systematic Review and Meta-Analysis. Ann. Med. 2018, 50, 698–712.
  344. Morris, M.C.; Evans, D.A.; Bienias, J.L.; Tangney, C.C.; Bennett, D.A.; Aggarwal, N.; Schneider, J.; Wilson, R.S. Dietary Fats and the Risk of Incident Alzheimer Disease. Arch. Neurol. 2003, 60, 194.
  345. Solfrizzi, V.; Colacicco, A.M.; D’Introno, A.; Capurso, C.; Torres, F.; Rizzo, C.; Capurso, A.; Panza, F. Dietary Intake of Unsaturated Fatty Acids and Age-Related Cognitive Decline: A 8.5-Year Follow-up of the Italian Longitudinal Study on Aging. Neurobiol. Aging 2006, 27, 1694–1704.
  346. Mattson, M.P.; Longo, V.D.; Harvie, M. Impact of Intermittent Fasting on Health and Disease Processes. Ageing Res. Rev. 2017, 39, 46–58.
  347. Lee, J.; Duan, W.; Long, J.M.; Ingram, D.K.; Mattson, M.P. Dietary Restriction Increases the Number of Newly Generated Neural Cells, and Induces BDNF Expression, in the Dentate Gyrus of Rats. J. Mol. Neurosci. 2000, 15, 99–108.
  348. Stranahan, A.M.; Lee, K.; Martin, B.; Maudsley, S.; Golden, E.; Cutler, R.G.; Mattson, M.P. Voluntary Exercise and Caloric Restriction Enhance Hippocampal Dendritic Spine Density and BDNF Levels in Diabetic Mice. Hippocampus 2009, 19, 951–961.
  349. Witte, A.V.; Fobker, M.; Gellner, R.; Knecht, S.; Flöel, A. Caloric Restriction Improves Memory in Elderly Humans. Proc. Natl. Acad. Sci. USA 2009, 106, 1255–1260.
  350. Marshall, L.; Helgadóttir, H.; Mölle, M.; Born, J. Boosting Slow Oscillations during Sleep Potentiates Memory. Nature 2006, 444, 610–613.
  351. Stickgold, R. Sleep-Dependent Memory Consolidation. Nature 2005, 437, 1272–1278.
  352. Xie, L.; Kang, H.; Xu, Q.; Chen, M.J.; Liao, Y.; Thiyagarajan, M.; O’Donnell, J.; Christensen, D.J.; Nicholson, C.; Iliff, J.J.; et al. Sleep Drives Metabolite Clearance from the Adult Brain. Science 2013, 342, 373–377.
  353. Cross, N.E.; Carrier, J.; Postuma, R.B.; Gosselin, N.; Kakinami, L.; Thompson, C.; Chouchou, F.; Dang-Vu, T.T. Association between insomnia disorder and cognitive function in middle-aged and older adults: A cross-sectional analysis of the Canadian Longitudinal Study on Aging. Sleep 2019, 42, zsz114.
  354. Lim, A.S.P.; Kowgier, M.; Yu, L.; Buchman, A.S.; Bennett, D.A. Sleep Fragmentation and the Risk of Incident Alzheimer’s Disease and Cognitive Decline in Older Persons. Sleep 2013, 36, 1027–1032.
  355. Lucey, B.P.; Wisch, J.; Boerwinkle, A.H.; Landsness, E.C.; Toedebusch, C.D.; McLeland, J.S.; Butt, O.H.; Hassenstab, J.; Morris, J.C.; Ances, B.M.; et al. Sleep and Longitudinal Cognitive Performance in Preclinical and Early Symptomatic Alzheimer’s Disease. Brain 2021, 144, 2852–2862.
  356. National Sleep Foundation. National Sleep Foundation Recommends New Sleep Times; National Sleep Foundation: Washington, DC, USA, 2022.
  357. Luyster, F.S.; Strollo, P.J.; Zee, P.C.; Walsh, J.K. Sleep: A Health Imperative. Sleep 2012, 35, 727–734.
  358. Saper, C.B.; Chou, T.C.; Scammell, T.E. The Sleep Switch: Hypothalamic Control of Sleep and Wakefulness. Trends Neurosci. 2001, 24, 726–731.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
This entry is offline, you can click here to edit this entry!
Video Production Service
Feedback