Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 + 2460 word(s) 2460 2021-10-14 08:55:13 |
2 h Meta information modification 2460 2021-10-28 04:27:21 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Budini, M. Neuroplasticity. Encyclopedia. Available online: https://encyclopedia.pub/entry/15480 (accessed on 28 March 2024).
Budini M. Neuroplasticity. Encyclopedia. Available at: https://encyclopedia.pub/entry/15480. Accessed March 28, 2024.
Budini, Mauro. "Neuroplasticity" Encyclopedia, https://encyclopedia.pub/entry/15480 (accessed March 28, 2024).
Budini, M. (2021, October 27). Neuroplasticity. In Encyclopedia. https://encyclopedia.pub/entry/15480
Budini, Mauro. "Neuroplasticity." Encyclopedia. Web. 27 October, 2021.
Neuroplasticity
Edit

Neuroplasticity can be defined as the ability of the nervous system to modify its structure on the basis of different environmental changes and stimulation.

neuroplasticity critical period perceptual learning acoustic and visual biofeedback synaptic plasticity

1. Neuroplasticity: Definition and Mechanisms

Neural plasticity can be distinguished as structural and functional plasticity. The structural plasticity refers to modifications occurring in neurons’ axons and dendrites in addition to renovation of these cells and synapses (neurogenesis and synaptogenesis). On the other hand, the functional plasticity comprehends the biochemical mechanisms behind synaptic efficacy [1]. This is a continuous remodeling process which allows short-term, medium-term, and long-term reshaping of the synaptic net, contributing to modifying or renewing its functions [2]. Thus, the brain’s plasticity plays a pivotal role throughout the lifespan of the individual, from the critical period in early development—with the creation of new neural maps thanks to learning through sense stimulations—to adulthood and old age, when these circuits are stabilized. However, this neural reshaping may also be elicited by peripheral or central nervous system (CNS) lesions [3][4]. For example, after a peripheral nervous lesion or limb amputation, the corresponding cortical areas begin to receive signals from peripheral areas surrounding the damaged site. This has been documented in the primary motor cortex (M1) after a peripheral nerve lesion, causing the extension of nearby cortical areas in the M1 territory [5]. On the other hand, if a cortical lesion occurs, its function ends up being carried out by nearby cortical areas. Furthermore, animal experimentations showed how, after an M1 ischemic lesion, the use of specific training, such as constraint therapy applied to the limb involved, could enhance the reorganization of unharmed M1 portions [6]. Merzenich et al. demonstrated how the primary cortical sensory map in adult animals can go through a process of reorganization after various peripheral sensory perturbations. In particular, studies on monkeys showed how after the section of the median nerve, somatosensory representation of its innervation areas undergoes rapid reorganization. Moreover, the cortical areas near the ones of the median nerve expand at its expense, as seen for the cortical representations of the ulnar nerve [7][8]. In a study of Kaas et al. based on macaques that underwent upper limb deafferentation 12 years earlier, the stimulation of the animal’s face produced activation of the area representing the deafferented limb, showing how there had been a reorganization of these two neighboring cortical areas [9].

1.1. Biological Basis of Neuroplasticity: Microscopic Aspects

The biological processes that underlie neuroplasticity take place at both the microscopic and macroscopic levels. Microscopic mechanisms include neurogenesis, synaptic activity modifications, reactivation of latent synaptic networks, and modulation of neural circuits mediated by glia and an extracellular matrix. During the early stages of development, the proliferation and differentiation of neurons and their structures (e.g., dendrites and axons), as well as their connections through synapses, take place [10]. Afterward, because of sense stimulation and experience, these networks are molded through apoptosis and the modification or regression of synaptic connections [11][12]. These structural changes may also take place after a brain injury, showing renovation in particular dendrites [13]. There is also evidence concerning the role of neurotrophins (NTs) in neural plasticity, mediating the differentiation and survival of neurons in synaptic transmission and reshaping [14][15]. In addition to neurogenesis, synaptic plasticity plays an important role in the brain’s reorganization. It refers to the modulation of synaptic efficacy due to repetitive nerve impulses. Thus, this process is based on changing the stimulation from a presynaptic to postsynaptic cell, providing an increase or decrease in synaptic efficacy, named long-term potentiation (LTP) and long-term depression (LTD), respectively [16][3][17][18]. LTP originates from rapid presynaptic depolarization of the synapses, which activates NMDA-type glutamate receptors in the postsynaptic membrane, causing a rise in intracellular Ca++ levels. This induces the expression of AMPA-type glutamate receptors in the postsynaptic membrane, leading to an increase in synaptic strength. It also causes the release of brain-derived neuronal growth factor (BDNF) in neurons, which enhances LTP and enlarges the dendrites ([3][19] “AMPARs and synaptic plasticity: The last 25 years”). On the contrary, LTD comes from slow repetitive stimulation of the synapses, which causes a migration of AMPA receptors in the cytoplasm [17]. While LTP has a key role in learning and memorization, as seen in the hippocampus, both LTP and LTD seem to mediate the reorganization of neural networks in the sensory motor cortex [20]. In a review article, Sheperd et al. described how ARC gene expression is involved in the regulation of synaptic plasticity. In fact, it seems to control the neural output of excitatory neurons by facilitating LTD and by modulating the expression of AMPA glutamate receptors [21][22]. In a work by Pfeiffer, B. and Huber, K., it is explained how, in order to maintain LTP and LTD as functional synaptic changes in the cortical areas, it seems that local or dendritic specific protein synthesis is required [23]. Another kind of synaptic plasticity is represented by the conversion of silent synapses in active connections. The organization of cortical networks in functional areas is granted by the activity of inhibitor GABA interneurons, which stop the horizontal connections between different areas. Events such as sensory deprivation or learning may interrupt this kind of control, unleashing these latent connections and creating a sort of short-term plasticity [24][25]. A synapse’s activity can also be directly influenced by neuroglia. This wide network, through the production of neurotransmitters and extracellular mediators, has the potential to improve synaptic transmission [26][27]. Moreover, glial cells can also communicate with each other by using gap junctions and intracellular messengers [28] to coordinate the activity of neural networks. Control of the neuronal activity is also accomplished by the extracellular matrix [29].

1.2. Biological Basis of Neuroplasticity: Macroscopic Aspects

Several mechanisms lead to functional reshaping at a macroscopic level. Macroscopic changes include cross-modal plasticity, a modality-specific brain area that is deprived of its usual sensory input and becomes responsive to the stimulation of other modalities. For example, the occipital cortex in visually impaired patients may be activated by sound changes [30]. Furthermore, a vicariation modality is possible, as the takeover of the function by areas not originally involved in the damaged performance that are remote from the site of the primary damage, known as diaschisis [31]. Other macroscopic mechanisms of plasticity are functional redundancies, or intrinsic reorganization of eloquent areas with multiple cortical representations of the same function within the same region. On the other hand, a reorganization within a functional network is another crucial pathway, as other regions belonging to the same functional network may be recruited: the perilesional areas first, and if still insufficient to the functional purpose, remote structures [4]. If the unimodal association areas are damaged, there is a rapid over-recruiting of new areas to sustain the impaired process based on an activation–hyperactivation pattern. These compensatory strategies were first described on the dorsolateral prefrontal or intraparietal cortices [32]. These mechanisms can also have a macroscopic impact on the volume of gray matter, as analyses revealed a region of increased gray matter in Broca’s area in the left inferior frontal gyrus in musicians, and studies of the anatomical effects after environmental experience and training in humans demonstrated a cortical volumetric increase [33][34].

2. Neuroplasticity in the Auditory System

The initial idea of plasticity applied to the hearing system was that of a process starting once the inner ear starts functioning and then shaped by experience only during a critical period in early development. However, in the last few decades, several studies demonstrated how the auditory system remains capable of reorganizing itself in response to different auditory stimulations or sensory organ modifications. Thus, the auditory system has a plasticity potential which also continues in adulthood. This process may vary from short-term adaptation to long-term modification of neural circuits, as seen in the case of hearing loss. This may derive from the effect of different sensory inputs (bottom-up processes) or the influence of learning, attention, or doing specific tasks (top-down processes) [35][36][37].

2.1. Mechanisms of Auditory Plasticity

An example of auditory system plasticity is stimulus-specific adaptation (SAA), a process leading to a lower neuron response to repeated acoustic stimulation [38]. This has been demonstrated by presenting a series of identical stimuli interspersed with individual different ones, during which neurons showed adaptation to first stimuli while they continued responding to the second ones. Such findings suggest how SSA could be a sort of adaptation of the auditory cortex to acoustic stimuli in order to focus only on relevant ones [36]. Hearing system plasticity may also happen as a consequence of hearing loss so that it reorganizes itself after the injury. The first studies about this kind of plasticity were performed on animals and adult humans after cochlear injury, analyzing changes in a neuron’s frequency sound selectivity and the remodeling of the corresponding area in cortical tonotopical map [36][39]. In fact, damage to hair cells in the cochlea or exposure to high-intensity sounds can result in the inability to discriminate precise sound frequencies. It has been noted that, after an injury, the portions of the auditory cortex surrounding the area which represented the damaged part of the cochlea expands at its expense [37][40]. The result is that a higher number of neurons focus on frequencies that are still heard. However, even if this plasticity may seem useful because it avoids losing frequency discrimination, it disrupts the neural coding in the auditory cortex. In fact, the reorganization of the auditory system, which has the aim to continue hearing certain frequencies after an injury, does not help to recover from hearing loss [30][36]. On the contrary, it seems to be a maladaptive process, as it has been associated with tinnitus [36]. This may result from the fact that, after an injury, some neurons in the auditory cortex start responding to different frequencies, which could lead to inappropriate coding of certain frequency stimuli [35][41][42]. Patients suffering from these kinds of injuries can benefit from the use of cochlear implants. In particular, it has been noted how hearing recovery largely depends on the auditory system plasticity induced by these hearing aids [43]. The role of these implants is to make the patient hear certain sound frequencies again after a cochlear injury so that the neurons which used to respond to those frequencies can be stimulated again. After implantation in deaf adults due to cochlear injuries, sound frequency discrimination and thus speech understanding are gradually restored [44][45]. These implants’ effects on the auditory cortex can be observed through magnetoencephalography (MEG). Pantev et al. reported increased evoked brain activity in the auditory cortexes of two deaf adults with implants, which related to the increase of neural activity in these areas due to the restored auditory stimuli [46]. It is important to consider that the beneficial effect of hearing aids depends on when they are implanted after the cochlear injury. We discussed above how, after an injury, auditory fields which were stimulated from that part of the damaged cochlea start responding to the frequencies of nearby neurons. This could lead to interference between these stimuli and those provided by hearing aids [35]. Moreover, the deprivation of this stimulation can also induce cross-modal plasticity of other sensory modalities at the expense of these auditory cortex areas [47]. The result is that these patients will not benefit from hearing aid stimulation, or at least these forms of plasticity can lead to a maladaptation if hearing aids are implanted late [48][49]. For this reason, in order to obtain the best result from hearing aids, it is important to consider early implantation after an injury [35][37].
Plasticity in the hearing system may also derive from the repetition of a specific pattern of tasks, consisting of focusing and discriminating specific auditory stimuli. This kind of training is known as perceptual learning. Most studies on this form of plasticity were based on training regarding sound frequency discrimination. During the training in animals, as the frequency identification improves, there is a progressive increase in the representation of those frequencies in the auditory cortex [50][51]. In humans, an example of perceptual learning is the one resulting from musical training, which influences the cortical processing of sound stimuli both in the auditory cortex and in the brainstem [52][53].

2.2. Biological Basis of Auditory Plasticity

Auditory plasticity develops at microscopic levels through different processes, including molecular and cellular mechanisms involved in cortex reorganization. Brain-derived neurotrophic factor (BDNF) plays a role in adult organization of the auditory cortex [54]. BDNF contributes to the maturation of GABAergic interneurons including parvalbumin (PV) interneurons, which contribute to regulating the onset and ending of critical periods and thus the plasticity potential [55]. In fact, a reduction of inhibitory transmission has the potential to re-open the plasticity window of the critical period [56]. This can be achieved through the loss of acoustic input at a juvenile age [57] or in adulthood [58]. Glutamate has also been found to have a role in auditory plasticity, as a block of NMDA receptors performed using ketamine reduces the amplitude and augments the latency of Mismatch Negativity (MMN). MMN is an evoked potential which occurs in response to an unexpected auditory stimulus, placed in a series of repetitive tones which differ from the latter. MMN is considered to be a measure of auditory plasticity, as it can be generated by the nervous system only if a memory trace of the repetitive tones has already been formed. In fact, the stimulus-specific adaptation (SSA) of auditory cortex neurons to these patterns seems to be necessary for MMN [59]. Microglia are also able to mediate cortical plasticity. These nonneural cells are activated after brain damage and act by removing neurons’ debris after their death, but they are also active in non-injured brains through monitoring synaptic functions and playing a role in their maturation or elimination through fagocitation of axonal terminals and dendritic spines. In a study conducted on mice, Paolicelli et al. showed these roles of microglia on the synapses. In particular, the study was based on mice lacking Cx3cr1, a receptor for fractaline, a chemochine which guides microglia migration. These receptors are usually expressed on neurons through which they recall the microglia. During their development, mice brains lacking these receptors showed lowered synaptic pruning, which resulted in immature synapses [60][61]. Microglia activity may be induced by traumatic noise exposure [62]. Neurotransmitters have the potential to influence synaptic plasticity. Cholinergic projections to the auditory cortex can play a role in plasticity by inhibiting PV interneurons during the development ages in the critical period [63] and also in adulthood [64]. In an experiment on cats, McKenna et al. showed how, in the presence of ACh during a presentation of a series of different tones with different sound frequency stimuli, there was a facilitated response in the auditory cortex toward frequencies which differed from the neurons’ “best frequency” [65]. Kilgard et al. demonstrated how a simultaneous electrical stimulation of an adult rat’s basal forebrain (thus with consequent cholinergic cortical projections) and presentation of auditory stimuli with a precise frequency produced an expansion of the auditory cortex tuned on that frequency [66].

References

  1. Fernandez-Espejo, E.; Rodriguez-Espinosa, N. Psychostimulant Drugs and Neuroplasticity. Pharmaceuticals 2011, 4, 976–991.
  2. Deperrois, N.; Graupner, M. Short-term depression and long-term plasticity together tune sensitive range of synaptic plasticity. PLoS Comput. Biol. 2020, 16, e1008265.
  3. Duffau, H. Brain Plasticity and Reorganization Before, During, and After Glioma Resection. In Glioblastoma; Elsevier: Amsterdam, The Netherlands, 2016; pp. 225–236.
  4. Duffau, H. Brain plasticity: From pathophysiological mechanisms to therapeutic applications. J. Clin. Neurosci. 2006, 13, 885–897.
  5. Sanes, J.N.; Donoghue, J.P. Plasticity and Primary Motor Cortex. Annu. Rev. Neurosci. 2000, 23, 393–415.
  6. Nudo, R.J.; Wise, B.M.; SiFuentes, F.; Milliken, G.W. Neural Substrates for the Effects of Rehabilitative Training on Motor Recovery After Ischemic Infarct. Science 1996, 272, 1791–1794.
  7. Merzenich, M.; Kaas, J.; Wall, J.; Nelson, R.; Sur, M.; Felleman, D. Topographic reorganization of somatosensory cortical areas 3b and 1 in adult monkeys following restricted deafferentation. Neuroscience 1983, 8, 33–55.
  8. Merzenich, M.; Kaas, J.; Wall, J.; Sur, M.; Nelson, R.; Felleman, D. Progression of change following median nerve section in the cortical representation of the hand in areas 3b and 1 in adult owl and squirrel monkeys. Neuroscience 1983, 10, 639–665.
  9. Kaas, J.H. Plasticity of Sensory and Motor Maps in Adult Mammals. Annu. Rev. Neurosci. 1991, 14, 137–167.
  10. Holmes, G.L.; McCabe, B. Brain development and generation of brain pathologies. Int. Rev. Neurobiol. 2001, 45, 17–41.
  11. Cruikshank, S.J.; Weinberger, N.M. Evidence for the Hebbian hypothesis in experience-dependent physiological plasticity of neocortex: A critical review. Brain Res. Rev. 1996, 22, 191–228.
  12. Trachtenberg, J.T.; Chen, B.E.; Knott, G.W.; Feng, G.; Sanes, J.R.; Welker, E.; Svoboda, K. Long-term in vivo imaging of experience-dependent synaptic plasticity in adult cortex. Nat. Cell Biol. 2002, 420, 788–794.
  13. Maletic-Savatic, M. Rapid Dendritic Morphogenesis in CA1 Hippocampal Dendrites Induced by Synaptic Activity. Science 1999, 283, 1923–1927.
  14. Poo, M.-M. Neurotrophins as synaptic modulators. Nat. Rev. Neurosci. 2001, 2, 24–32.
  15. McAllister, A.K.; Katz, L.C.; Lo, D.C. Neurotrophins and synaptic plasticity. Annu. Rev. Neurosci. 1999, 22, 295–318.
  16. Johnston, M.V. Plasticity in the developing brain: Implications for rehabilitation. Dev. Disabil. Res. Rev. 2009, 15, 94–101.
  17. Hartmann, M.; Heumann, R.; Lessmann, V. Synaptic secretion of BDNF after high-frequency stimulation of glutamatergic synapses. EMBO J. 2001, 20, 5887–5897.
  18. Malenka, R.C.; Bear, M.F. LTP and LTD. Neuron 2004, 44, 5–21.
  19. Huganir, R.L.; Nicoll, R.A. AMPARs and Synaptic Plasticity: The Last 25 Years. Neuron 2013, 80, 704–717.
  20. Feldman, D.E.; Nicoll, R.A.; Malenka, R.C. Synaptic plasticity at thalamocortical synapses in developing rat somatosensory cor-tex: LTP, LTD, and silent synapses. J. Neurobiol. 1999, 41, 92–101.
  21. Shepherd, J.; Bear, M.F. New views of Arc, a master regulator of synaptic plasticity. Nat. Neurosci. 2011, 14, 279–284.
  22. Jakkamsetti, V.; Tsai, N.-P.; Gross, C.; Molinaro, G.; Collins, K.A.; Nicoletti, F.; Wang, K.H.; Osten, P.; Bassell, G.J.; Gibson, J.R.; et al. Experience-Induced Arc/Arg3.1 Primes CA1 Pyramidal Neurons for Metabotropic Glutamate Receptor-Dependent Long-Term Synaptic Depression. Neuron 2013, 80, 72–79.
  23. Pfeiffer, B.E.; Huber, K.M. Current Advances in Local Protein Synthesis and Synaptic Plasticity. J. Neurosci. 2006, 26, 7147–7150.
  24. Jacobs, K.M.; Donoghue, J.P. Reshaping the cortical motor map by unmasking latent intracortical connections. Science 1991, 251, 944–947.
  25. Blitz, D.M.; Foster, K.A.; Regehr, W.G. Short-term synaptic plasticity: A comparison of two synapses. Nat. Rev. Neurosci. 2004, 5, 630–640.
  26. Fields, R.D.; Stevens-Graham, B. New Insights into Neuron-Glia Communication. Science 2002, 298, 556–562.
  27. Citri, A.; Malenka, R.C. Synaptic Plasticity: Multiple Forms, Functions, and Mechanisms. Neuropsychopharmacology 2007, 33, 18–41.
  28. Rouach, N.; Glowinski, J.; Giaume, C. Activity-Dependent Neuronal Control of Gap-Junctional Communication in Astrocytes. J. Cell Biol. 2000, 149, 1513–1526.
  29. Dityatev, A.; Schachner, M. Extracellular matrix molecules and synaptic plasticity. Nat. Rev. Neurosci. 2003, 4, 456–468.
  30. Kujala, T.; Alho, K.; Näätänen, R. Cross-modal reorganization of human cortical functions. Trends Neurosci. 2000, 23, 115–120.
  31. Feeney, D.M.; Baron, J.C. Diaschisis. Stroke 1986, 17, 817–830.
  32. Rossini, P.M.; Forno, G.D. Integrated technology for evaluation of brain function and neural plasticity. Phys. Med. Rehabil. Clin. 2004, 15, 263–306.
  33. Luders, E.; Gaser, C.; Jancke, L.; Schlaug, G. A voxel-based approach to gray matter asymmetries. NeuroImage 2004, 22, 656–664.
  34. Anderson, B.J. Plasticity of gray matter volume: The cellular and synaptic plasticity that underlies volumetric change. Dev. Psychobiol. 2011, 53, 456–465.
  35. Kappel, V.; Moreno, A.C.D.P.; Buss, C.H. Plasticity of the auditory system: Theoretical considerations. Braz. J. Otorhinolaryngol. 2011, 77, 670–674.
  36. Irvine, D.R. Plasticity in the auditory system. Hear. Res. 2018, 362, 61–73.
  37. Dahmen, J.C.; King, A.J. Learning to hear: Plasticity of auditory cortical processing. Curr. Opin. Neurobiol. 2007, 17, 456–464.
  38. Nelken, I. Stimulus-specific adaptation and deviance detection in the auditory system: Experiments and models. Biol. Cybern. 2014, 108, 655–663.
  39. Kilgard, M.P. Cortical Map Reorganization without Cholinergic Modulation. Neuron 2005, 48, 529–530.
  40. Eggermont, J.J. Acquired hearing loss and brain plasticity. Hear. Res. 2017, 343, 176–190.
  41. Shore, S.E.; Roberts, L.E.; Langguth, B. Maladaptive plasticity in tinnitus–triggers, mechanisms and treatment. Nat. Rev. Neurol. 2016, 12, 150–160.
  42. Wu, C.; Stefanescu, R.A.; Martel, D.; Shore, S.E. Tinnitus: Maladaptive auditory–somatosensory plasticity. Hear. Res. 2016, 334, 20–29.
  43. Moore, D.R.; Shannon, R.V. Beyond cochlear implants: Awakening the deafened brain. Nat. Neurosci. 2009, 12, 686–691.
  44. Munro, K.J.; Lutman, M.E. The effect of speech presentation level on measurement of auditory acclimatization to amplified speech. J. Acoust. Soc. Am. 2003, 114, 484–495.
  45. Fu, Q.-J.; Galvin, J.J. Perceptual Learning and Auditory Training in Cochlear Implant Recipients. Trends Amplif. 2007, 11, 193–205.
  46. Pantev, C.; Dinnesen, A.; Ross, B.; Wollbrink, A.; Knief, A. Dynamics of Auditory Plasticity after Cochlear Implantation: A Longitudinal Study. Cereb. Cortex 2005, 16, 31–36.
  47. Hunt, D.; Yamoah, E.; Krubitzer, L. Multisensory plasticity in congenitally deaf mice: How are cortical areas functionally specified? Neuroscience 2006, 139, 1507–1524.
  48. Doucet, M.E.; Bergeron, F.; Lassonde, M.; Ferron, P.; Lepore, F. Cross-modal reorganization and speech perception in cochlear implant users. Brain 2006, 129, 3376–3383.
  49. Lee, H.-J.; Giraud, A.-L.; Kang, E.; Oh, S.-H.; Kang, H.; Kim, C.-S.; Lee, D.S. Cortical Activity at Rest Predicts Cochlear Implantation Outcome. Cereb. Cortex 2006, 17, 909–917.
  50. Recanzone, G.H.; Schreiner, C.; Merzenich, M.M. Plasticity in the frequency representation of primary auditory cortex following discrimination training in adult owl monkeys. J. Neurosci. 1993, 13, 87–103.
  51. Polley, D.B.; Steinberg, E.E.; Merzenich, M.M. Perceptual Learning Directs Auditory Cortical Map Reorganization through Top-Down Influences. J. Neurosci. 2006, 26, 4970–4982.
  52. Herholz, S.C.; Zatorre, R.J. Musical Training as a Framework for Brain Plasticity: Behavior, Function, and Structure. Neuron 2012, 76, 486–502.
  53. Carcagno, S.; Plack, C. Subcortical Plasticity Following Perceptual Learning in a Pitch Discrimination Task. J. Assoc. Res. Otolaryngol. 2010, 12, 89–100.
  54. Anomal, R.; De Villers-Sidani, E.; Merzenich, M.M.; Panizzutti, R. Manipulation of BDNF Signaling Modifies the Experience-Dependent Plasticity Induced by Pure Tone Exposure during the Critical Period in the Primary Auditory Cortex. PLoS ONE 2013, 8, e64208.
  55. Hensch, T.K. Critical period plasticity in local cortical circuits. Nat. Rev. Neurosci. 2005, 6, 877–888.
  56. Morishita, H.; Hensch, T.K. Critical period revisited: Impact on vision. Curr. Opin. Neurobiol. 2008, 18, 101–107.
  57. Kotak, V.C.; Fujisawa, S.; Lee, F.A.; Karthikeyan, O.; Aoki, C.; Sanes, D.H. Hearing Loss Raises Excitability in the Auditory Cortex. J. Neurosci. 2005, 25, 3908–3918.
  58. Balaram, P.; Hackett, T.; Polley, D. Synergistic Transcriptional Changes in AMPA and GABAA Receptor Genes Support Compensatory Plasticity Following Unilateral Hearing Loss. Neuroscience 2019, 407, 108–119.
  59. Harms, L.; Parras, G.G.; Michie, P.T.; Malmierca, M.S. The Role of Glutamate Neurotransmission in Mismatch Negativity (MMN), A Measure of Auditory Synaptic Plasticity and Change-detection. Neuroscience 2021, 456, 106–113.
  60. Paolicelli, R.C.; Bolasco, G.; Pagani, F.; Maggi, L.; Scianni, M.; Panzanelli, P.; Giustetto, M.; Ferreira, T.A.; Guiducci, E.; Dumas, L.; et al. Synaptic Pruning by Microglia Is Necessary for Normal Brain Development. Science 2011, 333, 1456–1458.
  61. Säljö, A.; Bao, F.; Hamberger, A.; Haglid, K.G.; Hansson, H.-A. Exposure to short-lasting impulse noise causes microglial and astroglial cell activation in the adult rat brain. Pathophysiology 2001, 8, 105–111.
  62. Takesian, A.E.; Kotak, V.C.; Sanes, D.H. Developmental hearing loss disrupts synaptic inhibition: Implications for auditory processing. Future Neurol. 2009, 4, 331–349.
  63. Letzkus, J.; Wolff, S.B.E.; Meyer, E.; Tovote, P.; Courtin, J.; Herry, C.; Lüthi, A. A disinhibitory microcircuit for associative fear learning in the auditory cortex. Nat. Cell Biol. 2011, 480, 331–335.
  64. Schafer, D.P.; Lehrman, E.K.; Kautzman, A.G.; Koyama, R.; Mardinly, A.; Yamasaki, R.; Ransohoff, R.M.; Greenberg, M.E.; Barres, B.A.; Stevens, B. Microglia Sculpt Postnatal Neural Circuits in an Activity and Complement-Dependent Manner. Neuron 2012, 74, 691–705.
  65. McKenna, T.M.; Ashe, J.H.; Weinberger, N.M. Cholinergic modulation of frequency receptive fields in auditory cortex: I. Frequency-specific effects of muscarinic agonists. Synapse 1989, 4, 30–43.
  66. Kilgard, M.P. Cortical Map Reorganization Enabled by Nucleus Basalis Activity. Science 1998, 279, 1714–1718.
More
Information
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
View Times: 589
Revisions: 2 times (View History)
Update Date: 28 Oct 2021
1000/1000