The comorbidity between Autism Spectrum Disorder (ASD) and epilepsy has been widely demonstrated, and many hypotheses regarding the common neurobiological bases of these disorders have been put forward. A variable, but significant, prevalence of abnormalities on electroencephalogram (EEG) has been documented in non-epileptic children with ASD; therefore, several scientific studies have tried to demonstrate the role of these abnormalities as a possible biomarker of altered neural connectivity in ASD individuals.
According to the criteria of the Diagnostic and Statistical Manual of Mental Disorders (5th Edition, Text Revision) [1], Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder (NDD) with a prevalence of about 1% in the global population [2], characterized by persistent deficits in social communication and social interaction across multiple contexts and by the presence of restricted, repetitive patterns of behavior, interests, or activities. ASD symptoms must arise during the early period of development and cause clinically significant impairment in social, occupational, or other important areas of adaptive functioning. Furthermore, to make a diagnosis of ASD, these symptoms must not be explained by intellectual disability (ID), even if these two NDDs frequently co-occur: according to recent data from the Centers for Disease Control and Prevention, 37.9% of children with ASD also meet the criteria for ID [3]. In addition, ASD can frequently be associated with other NDDs (i.e., Attention-Deficit/Hyperactivity Disorder, language disorders, developmental coordination disorder, learning disorders) [4], or with a wide variety of neurological/somatic comorbidities (i.e., epilepsy, sleep problems, gastrointestinal disorders) [5]. In recent years, many genetic and environmental factors implicated in the pathogenesis of ASD have been identified [6][7], even if approximately 85% of individuals with ASD are still defined as idiopathic [8]. In this conceptual framework, an increasing number of scientific studies report a growing interest in characterizing neurobiological mechanisms possibly underlying ASD, including the alteration of neuronal proteins and brain circuits [9][10], in order to define useful biomarkers for early diagnosis and more effective treatment. For this purpose, many studies have recently focused on the use of neuroimaging techniques in infancy: firstly, to define canonical versus atypical developmental trajectories of the human brain, and secondly, to search for potential and valuable biomarkers of NDDs, as mentioned above [11]. Neurophysiological techniques can provide additional functional insights into ASD neurobiology. Amongst these methods, electroencephalogram (EEG) appears particularly attractive. It is a noninvasive tool, first introduced by Hans Berger in 1924 for human use, which allows for recording the electrical activity of the human brain derived from the summation of the excitatory and inhibitory postsynaptic potentials of neurons [12]. Datasets obtained with EEG can be assessed using visual examination and interpretation (qualitative EEG) or elaborated to obtain quantitative metrics (quantitative EEG). Both analysis techniques can be used in children with ASD, yet qualitative EEG is more directly linked to the possible occurrence of seizures [13][14].
As a matter of fact, the comorbidity of ASD with epilepsy has been extensively demonstrated over the last few years. The prevalence of epilepsy in people with ASD ranges from 1.8% to 60% [15][16], depending on several factors heterogeneously distributed within various study populations, such as:
In the last decade, the co-occurrence of ASD and epilepsy has also pioneered the demonstration of the common neurobiological bases that these disorders seem to share.
It has been widely demonstrated that an imbalance between excitatory and inhibitory neurotransmission can be found in people with epilepsy, involving glutamate (Glu, excitatory circuits) and gamma-aminobutyric acid (GABA, inhibitory circuits) as the main neurotransmitters implicated in the epileptogenesis through many different mechanisms of alteration [29][30][31][32][33][34][35][36][37], but recently, some studies also focused on other neurotransmitters (i.e., acetylcholine) and glial cells, in an attempt to better explain the neurobiological basis of epilepsy [34].
Interestingly, there is some convincing evidence that most of the aforementioned alterations can be also found in the brain tissues of ASD patients [31][38][39][40][41][42].
Moreover, most of the neurobiological bases shared by ASD (and, more broadly, neurodevelopmental disorders) and epilepsy likely originate from common genetic causes, which can explain the altered expression of a large variety of proteins involved in neurotransmission. For example, variants of the gene GABARD (encoding for the delta subunit of GABA-A receptors) would predispose to both ASD and generalized epilepsy [43]. Other genes involved in the early stages of brain development and migration of neuronal progenitors have been associated with both ASD and epilepsy (i.e., the CYFIP1 gene, the CHD5 gene, CASPR2 and other genes coding for neurexins) [44][45][46][47].
According to the scientific literature, the presence of epileptiform—and sometimes also non-epileptiform—abnormalities on the first EEG performed seems to be predictive of an increased risk of subsequent and earlier onset epilepsy. This is self-explicating in conditions [48][49][50] characterized by a predisposition to epilepsy per se co-occurring with ASD symptoms, such as the Tuberous Sclerosis Complex (TSC). In TSC, EEG abnormalities occurring early during the disease course predict the development of epilepsy.
Conversely, it is difficult to demonstrate that early EEG abnormalities predict unprovoked seizures in children with idiopathic ASD. Indeed, EEG could be interpreted as a biomarker of epileptogenesis, considering epileptiform EEG discharges may predate epilepsy in children with febrile seizures [51][52] and are associated with further seizures in children with a first clinical episode [53]. Theoretically, EEG could also be related to the neurodevelopmental outcome, even though there is still an important lack of evidence in this field and further studies to confirm its role as a predictive biomarker in neurodevelopmental disorders are needed.
Within the literature relating to the relationship between autism and EEG abnormalities, one of the most important issues that needs to be highlighted is the presence of a certain heterogeneity regarding the diagnostic criteria used to identify patients with autism: this is due to the fact that ASD diagnostic criteria have changed over time, influencing significantly the percentage of EEG abnormalities found in the various study cohorts. The rate of EEG abnormalities correlates, indeed, with the severity of ASD [18][54][55]: the greater the number of patients with severe ASD, the higher the rate of EEG abnormalities will tend to be. To understand what the problem is, it is necessary to remember that DSM-IV [56], DSM-IV-TR [57] and ICD-10 [58] referred to autism as a member of the Pervasive Developmental Disorders group, which included different nosographic entities characterized by different severity. In DSM-5 [59], this academic subdivision was abandoned, and these disorders, which actually represent the spectrum of the fundamental core symptoms of autism, were grouped under the single name of Autism Spectrum Disorder.
Even referring only to the last ten years, some scientific studies referred for patient selection to DSM-IV [55][60], others to DSM-IV-TR [61], others to ICD-10 [62] and still others to DSM-5 [54][63][64][65][66][67]: the same studies can also variously refer to patients with Autistic Disorder, or to individuals with Childhood Autism. These two names refer to the same disease, which can also be referred to as Kanner’s Autism: this definition refers to the most severe type of autism, which, not surprisingly, is associated with a greater prevalence of epilepsy [18] and EEG abnormalities.; in conclusion, in scientific studies investigating a possible correlation between EEG abnormalities and ASD phenotype, it is possible to find cohorts including patients with a profound heterogeneity of disease severity, as shown in Figure 1. For example, it was possible to find in the same cohort both low-functioning and high-functioning ASD patients (that, in the past, would have fallen under two different diagnoses—Autistic Disorder and Asperger Disorder, respectively) in proportion to each other, often not even made explicit by the authors.
Figure 1.
The criteria used to diagnose ASD influence the EEG abnormality rates
[54][55][60][61][62][63][64][65][66][67]
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Similarly, the rate of epileptic patients within the study cohorts also influences the rates of EEG abnormalities, although the relationship is more complex than one might expect. Always referring to the same ten articles [54][55][60][61][62][63][64][65][66][67], by relating the rate of EEG abnormalities only with the rate of epilepsy, we could be mistakenly led to think, paradoxically, that a higher rate of epilepsy is associated with a lower rate of EEG abnormalities, as it is shown in Figure 2. This is due to the fact that the rate of EEG abnormalities, as well as the rate of epilepsy itself, are also influenced by other variables heterogeneously distributed in the populations under study, such as the severity of the autistic phenotype, the functional profile and the presence of other neuropsychiatric comorbidities: this makes it complex to understand the role of epilepsy in the interpretation of the results.
Figure 2.
Relationship between EEG abnormality rates and only the rate of epilepsy as a variable taken independently of the rest
[54][55][60][61][62][63][64][65][66][67]
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The link that unites the severity of the autism phenotype and EEG abnormalities has its roots in the pathophysiological consequences of epileptic discharges. Jarero-Basulto et al., 2018 [68] carried out a literature review that analyzes the close relationship between epilepsy and neuroplasticity. In samples affected by Temporal Lobe Epilepsy (TLE), obtained from animal models and human post-mortem brains or post-operative specimens [69], several authors found the presence of anomalous neuronal circuits in the hippocampal region. It seems that epileptic discharges, not necessarily long-lasting (as in the case of Status Epilepticus) but recurring over time, are capable of determining neuronal death and axonal sprouting in the affected area. The latter, according to some authors, is a reaction to neuronal death [70] but, according to others, the discharges themselves, without the involvement of neuronal death, can trigger it [71]. Neuronal loss and/or the formation of new synapses will lead to the development of aberrant neuronal circuits, characterized by an excitation/inhibition imbalance. This alteration could be due to various mechanisms:
This excitation/inhibition imbalance, on the one hand, would, in turn, facilitate the appearance of new epileptic discharges, and, on the other hand, would predispose individuals to the development of other psychiatric comorbidities, including ASD [75][76][77], Major Depressive Disorder, anxiety and psychosis [78].
One of the most suggested neurobiological mechanisms of ASD pathophysiology consisted of an imbalance between excitation and inhibition signaling, of which the nature is still a subject of debate. The first hypothesis, formulated by Rubenstein and Merzenich in 2003 [75], supports the prevalence of the excitatory component, but other authors subsequently observed the prevalence of the inhibitory component [76], at least in some particular types of autism, such as the one linked to Rett Syndrome.
From this point of view, a very interesting role is played by Parvalbumin (PV), which is a Ca2+-binding protein belonging to the EF-hand superfamily: it is mainly located in the cytoplasm, but extracellular isoforms also exist [79]. Parvalbumin can be found in many different cells, including type-II muscle fibers, kidney cells, some cells belonging to the endocrine system, myocardiocytes, cells of the inner ear and some neurons of the Peripheral Nervous System (PNS) and Central Nervous System (CNS). The latter includes Parvalbumin-expressing (PV+) GABAergic interneurons, which represent the largest class of inhibitory GABAergic neurons in the CNS: they are fast-spiking cells that, in the cerebral cortex, provide feedforward and feedback synaptic inhibition onto a diverse set of cell types, including pyramidal cells, other inhibitory interneurons and themselves [80]. More precisely, some of these Parvalbumin-expressing (PV+) GABAergic interneurons, represented by PV+ Chandelier Cells and PV+ Basket Cells, appear to have the function of synchronizing the activity of various cortical pyramidal cells [81] through their rhythmic inhibition.
Abnormalities affecting Parvalbumin-expressing (PV+) GABAergic interneurons cause an excitation/inhibition imbalance, which correlates with the autistic phenotype [82][83]. In particular, two diametrically opposite effects can occur [83]: the loss of PV+ GABAergic interneurons determine an imbalance in favor of excitation, while the reduction in PV expression levels, in the absence of an effective reduction in the number of interneurons, is responsible for an imbalance in favor of inhibition. Therefore, these abnormalities could explain both hypotheses relating to the excitation/inhibition imbalance [75][76] and the debate today is still open. For example, Hashemi et al., 2016 [84] found a significant reduction in the number of PV+ GABAergic interneurons in some cortical areas of ASD patients, while Filice et al., 2016 [83] argued that the reduction in PV expression levels, in the absence of an effective reduction in the number of PV+ GABAergic interneurons could represent an element common to some forms of ASD.
Interestingly, in animal models (rats), it has been observed that, by inducing epileptic seizures with 4-aminopyridine administration, it is possible to reduce the expression of PV [74]. These data seem to strengthen the hypothesis of a pathophysiological link between EEG abnormalities and atypical neurodevelopment in ASD subjects.
Given the notable prevalence of epilepsy and EEG abnormalities in the ASD population, it is important to investigate the possible role that EEG abnormalities could play in the pathophysiology of autism. Indeed, several studies have addressed the possible relationship between EEG and the autism phenotype.
EEG abnormalities can be divided into ictal abnormalities, when their occurrence is associated with seizures, and interictal abnormalities. The latter can in turn be distinguished into epileptiform and non-epileptiform. In order to identify a possible association between ASD and EEG abnormalities, it should be clarified which type of abnormalities are found in the various studies so that they can be classified in the exact same way, so as to reduce the subjectivity of interpretation. Similarly, it would be very important to specify the location of the EEG anomalies, as different locations can be associated with different phenotypic aspects. In spite of this, the authors of several articles available in the literature provided rather inconsistent classifications [54][55][61][62][64][67] or did not specify which particular anomalous graphoelements they found [60][63][65][66].
In ASD patients, EEG abnormalities have been found in all four brain lobes, which are involved in carrying out different functions [85][86][87][88][89].The impairment of both the temporal and frontal lobe may drive the core symptoms of ASD such as the alteration in social functions and ability to process emotions and facial expressions, nonverbal communicative behaviors and relational skills and executive functions [90][91]. However, the underlying pathophysiology may derive from an aberrant connectivity between different brain regions rather than a straight morphological alteration of brain structures [92]. The comorbidity between ASD and epilepsy may also be influenced by aberrant connectivity between different brain regions. People with Frontal Lobe Epilepsy (FLE) and Temporal Lobe Epilepsy (TLE) may also exhibit specific neurodevelopmental features partially overlapping with the ASD spectrum (e.g., behavioral disorders, attention liability, alteration of executive functions, intellectual disability, language impairment or memory impairment) independently from seizure occurrence. In particular, people with FLE may be particularly prone to deficient executive functions and memory impairment, suggesting the involvement of an underlying neuronal circuitry of the frontal lobe. FLE patients may present anomalies that mainly concern visuospatial organization, planning ability, response inhibition, impulse control, working memory, verbal search, mental flexibility and programming of complex motor sequences. All of this can also lead to the development of difficulties in mathematical calculation and reading [93]. Regarding language, some authors [94] maintain that FLE patients present an initial temporary impairment of linguistic understanding associated with persistent impairment of linguistic production, while others [95][96][97] believe that impaired verbal search and impaired verbal fluency are also associated. Regarding memory impairment, some authors [98] maintain that long-term epileptic activity constitutes a risk factor for this anomaly. Regarding intellectual disability, some authors [97][99][100][101] maintain that FLE is associated with a reduction in IQ, while others [102] believe that IQ is not compromised. What is most interesting is the fact that these anomalies, when present, tend to undergo remission following anti-epileptic treatment [95]: this suggests that they are closely linked to epilepsy. It has been observed that in the ASD population, epilepsy correlates with behavioral disorder severity [103], as well as, significantly, with the phenomenon of autistic regression [17].
As mentioned for behavioral problems, cognitive impairment, in all its facets, can also be found in ASD patients [59][104][105][106][107][108][109][110][111][112][113][114][115][116][117][118][119][120][121]. In ASD patients, ID is significantly associated with epilepsy [122][123], and the prevalence of the latter is higher in ASD patients with ID compared with ASD patients without ID [26]. In addition, the presence of epilepsy is a significant factor in ID severity [15][17][124][125][126][127][128]. In ASD patients, epileptic discharges often affect the frontal lobe [129], causing a potential frontal lobe dysfunction which, as previously mentioned, could explain some traits of the autistic phenotype [130][131].
Given what has been said so far, it is reasonable to assume that epileptic discharges can interfere with brain maturation during childhood, shaping a child’s phenotype even up to the onset of pathological conditions. A reduction in PV+ GABAergic interneurons [84] has been found in the pre-frontal cortex of ASD subjects, which, as thwe researchers aalready mentioned, can be triggered by epileptic discharges repeated over time [74]. This aspect, in addition to predisposing a patient to an excitation/inhibition imbalance [84], typical of ASD, is also associated with a greater incidence of anxiety-like behaviors [132] in animal models, which are part of the typical comorbidities of ASD patients [78].
Leaving epilepsy aside, it is important not to neglect SEAs, which are present in both epileptic and non-epileptic ASD patients; among the latter, they show a prevalence varying from 8% to 60.7% [17][62][109][126][133][134][135][136][137][138][139][140][141][142][143][144][145]. This variability is probably due to sampling and methodological heterogeneity in collecting and interpreting EEG tracings [23]. Although these abnormalities can also be found in healthy individuals [146][147][148], they are significantly more frequent in ASD patients, who exhibit them in all four cerebral lobes. According to some authors [141], the most frequent site is represented by the temporal lobe, but another study [149] reports that the first position is occupied by the frontal lobe with a rate of 78%.
Regarding non-epileptiform SEAs, some authors [150] assert that they are associated with a less severe phenotype compared with epileptiform SEAs: ASD patients with epileptiform SEAs perform worse on executive functioning assessments and exhibit higher scores in inhibition self-control compared with the ones reporting non-epileptiform SEAs. Two studies relate non-epileptiform SEAs to the ASD phenotype: Akhter et al., 2021 [61] reports that they can be found in ASD patients both with ID and without ID and Santarone et al., 2023 [63] argue that there is a significant association between abnormal background activity during sleep and developmental delay. Other authors, however, do not relate non-epileptiform SEAs to the ASD phenotype [54][55][60][62][64][65][66][67]. This follows a widespread trend in the scientific literature, which focuses above all on the role of epileptiform abnormalities, attributing less importance to non-epileptiform ones. The number of studies that focus on the latter, in fact, is small compared with the impressive number of articles focusing on the former, and they report contrasting opinions between them [17][63][109][135][137][140][145][150][151][152]. An aspect worth discussing is that some authors maintain that epileptiform discharges, especially if early, with or without seizures, could have a negative impact on brain development, with consequent alteration of cognitive functions and behavior [153] and also social skills, relational abilities and inhibition control [150]. Hirosawa et al. believe, however, that epileptiform SEAs could have an ambivalent role in the pathophysiology of ASD. In their first study [154], they observed that a high number of epileptiform SEAs is associated with lower intelligence in non-ASD subjects and higher intelligence in ASD subjects. In their second study [155], they found better social skills in an ASD patient population with a high number of epileptiform SEAs: this association is supported by Hartley-McAndrew and Weinstock, 2010 [156] and contested by Milovanovic et al., 2019 [62]. In their third study [157], Hirosawa et al., 2021 formulated the hypothesis of the ambivalent nature of epileptiform SEAs: they claim that epileptiform SEAs could have the ability to “normalize” the neuroatypical development of ASD patients, lowering ASD severity; however, when the effect extends beyond brain tolerance, epileptiform SEAs could actually worsen autistic phenotype. Nonetheless, it is always necessary to keep in mind that the results they obtained are limited by the fact that all healthy controls selected for the study never presented SEAs.
In conclusion, given the potential pathophysiological role that EEG abnormalities, especially in the temporal and frontal lobes, could play in ASD, further study of cerebral electrophysiology in ASD patients is needed. In fact, EEG abnormalities, in addition to constituting a potential tool for early diagnosis—given their interesting relationship with a child’s development during the first year of life [17][145]—could also provide useful prognostic information [157]. Nonetheless, it is important to remember that ASD is a multifactorial disorder and its origin is not fully known, to the extent that idiopathic autism still represents 80–90% of all diagnoses [8][158][159][160][161]. The hypothesis of the etiopathogenetic link between epileptic seizures and autism can be advanced, at the moment, only for some patients, taking as a model syndromic forms of ASD in which epilepsy and autism often co-occur, such as, for example, Rett Syndrome [162], Angelman Syndrome [163] and Fragile X Syndrome [164].
The use of activation procedures, such as hyperventilation (HV) [165], intermittent photic stimulation (IPS) [166] and sleep deprivation [167][168], allows us to increase the probability of finding EEG abnormalities and, consequently, permits us to increase, albeit in a limited number of patients, especially young ones, the overall number of different types of identifiable EEG abnormalities [169]. Although HV and IPS are recommended as standard in routine and sleep EEG [170], among ten studies available in the literature relating to the relationship between autism and EEG abnormalities [54][55][60][61][62][63][64][65][66][67], only three of them mention their application [62][64][66], while only two studies mention sleep deprivation [54][66]: in one of these [66] sleep deprivation was not applied to all patients in the cohort, but the actual number was not made explicit. In the remaining six articles [55][60][61][63][65][67], therefore, the rate of EEG abnormalities is probably underestimated, as a portion was not detected with the use of activation procedures: this inevitably affects the comparability of the results obtained.
Similar considerations can be made for the duration of EEG recordings: the longer the recording, the greater the probability of finding EEG abnormalities. In routine EEG, it is true that the majority of abnormalities can be found during the first 20 min of recording, but it has been observed that it is possible to increase the yield by 11% by extending the duration to 40 min. Sometimes it is not possible to routinely carry out very long recordings due to costs, but from a research point of view, this aspect has a non-negligible weight, as the results obtained from recordings of different durations are not comparable in a standardized manner to each other. In the same ten studies aforementioned [54][55][60][61][62][63][64][65][66][67], a very notable heterogeneity in duration can be observed, both between different cohorts and within the same cohort and in two cases, the duration is not even made explicit [55][60]. Furthermore, in studies in which the duration of recording is provided as a range, the actual number of patients who underwent recordings of different durations is not specified.
Finally, another important aspect is represented by the resting state condition (wakefulness and/or sleep) in which the EEG recordings were carried out: once again, a significant heterogeneity can be observed in the manuscripts [54][55][60][61][62][63][64][65][66][67], both between different cohorts and within the same cohort, as previously stated. In this case, however, the recordings were not carried out in the same resting state, invalidating the standardization of the comparison, and also for some patients, a sleep recording was not obtained, which is extremely relevant because it decreases the probability of identifying EEG abnormalities [137][141][145][171]. Furthermore, providing an overnight EEG recording would allow us to analyze complete sleep cycles, including REM sleep, and could provide additional stronger information on the characterization of EEG abnormalities and their possible correlation with the ASD phenotype. Unfortunately, an overnight study on a child with ASD tends to be quite challenging, limited by the poor cooperation of patients. Nevertheless, as summarized by Petruzzelli et al., 2021 [172], in the last two decades, some scientific studies tried to examine objective macro- and microstructural sleep parameters by performing polysomnography or sleep EEG overnight. The study by Petruzzelli et al., 2021 provided a quantitative analysis of sleep microstructure patterns and showed alteration in sleep spindles, cycling alternating patterns, band powers and the Mu rhythm in ASD patients. However, the significance of these findings should be approached with caution due to the limited number of studies in this field and the clinical diversity of the study cohorts. On the other hand, regarding macrostructural sleep parameters, significant findings in ASD patients showed that ASD children take longer to fall asleep, get less sleep and experience more awakenings after falling asleep compared with typically developing children, which corresponds to a higher prevalence of nighttime insomnia symptoms [172].
The EEG tracings of ASD patients recorded during sleep are, indeed, full of abnormalities, which, in some cases, show a certain association with the autism phenotype. Six of the aforementioned articles [54][55][61][62][63][64] expose the abnormalities found during sleep, which include both epileptiform and non-epileptiform ones. Among the former, thwe researchers find spikes, polyspikes, polyspike waves, slow waves, slow spike waves, sharp waves and spike–wave complexes; among the latter, the researcherswe find background rhythmic theta/delta slowing, generalized intermittent slow waves, excessive beta activity, asymmetry, dysrhythmia/slowing down of the ground rhythm, paradoxical delta activity, irregular background activity, asynchrony and abnormal fast activity. Only Milovanovic et al., 2019 [62] and Kammoun et al., 2022 [54] also report the presence of disorganization of the sleep architecture, although this aspect is widely reported in numerous studies in the literature [173][174][175][176][177]. Kammoun et al., 2022 [54], in particular, report the presence of asynchrony of sleep spindles and poorly organized EEG and also suggest that sleep disorganization shows a certain association with language regression and behavioral problems. This association with the phenotype has been the subject of several studies in the literature that have resulted in contradictory conclusions [109][178][173][179].
Despite recent progress, there is still no certainty about the relationship between ASD and sleep disorders. For this reason, it is important to carry out studies on sleep EEG recordings in ASD patients and continue to investigate the signs and symptoms of sleep disorders because they are often identified before the diagnosis of ASD and could, according to some, constitute core symptoms of ASD [180].
Within the literature relating to the relationship between autism and EEG abnormalities, ten studies [54][55][60][61][62][63][64][65][66][67] cover overall the entire age range between 1.4 years and 12 years, with a prevailing interest in the middle childhood (6–11 y) and young teen (12–14 y) groups [181]. On the contrary, only two of them focus only on patients aged 5 years or less [63][65]. This reflects a fairly common trend in the literature, which is not in favor of the research work of an EEG biomarker for early diagnosis. Today, ASD is widely considered a Connectopathy [92], controversially characterized by hypo- or hyper-connectivity [182], depending on different studies [183]. This controversy was subsequently resolved by demonstrating the co-occurrence of the two phenomena in different areas of the brain [184] and by hypothesizing the coexistence between long-range hypoconnectivity and local hyperconnectivity [185]. It has been observed that these abnormalities of functional connectivity correlate with growth, as hyperconnectivity tends to prevail in childhood, while hypoconnectivity makes its appearance in adolescents/adults, alone [186], or in combination with hyperconnectivity [187]. Connectivity is studied with the use of either resting state functional MRI or diffusion tensor imaging [188], but it is plausible that these age-related differences in brain connectivity could be responsible for different electrophysiological brain behaviors in preschool children and adolescents. In addition, among ASD subjects, epilepsy has a higher peak incidence in adolescence [24]; therefore, it is inevitable that the pool of epileptiform EEG abnormalities will tend to be larger among older individuals. For these reasons, in order to be able to identify a specific EEG biomarker for the early diagnosis of ASD, it is appropriate to conduct studies that focus their attention more selectively on the preschool population.