Sex differences during development in cortical temporal processing and event related potentials in wild-type and fragile X syndrome model mice.

BACKGROUND: Autism spectrum disorder (ASD) is currently diagnosed in approximately 1 in 44 children in the United States, based on a wide array of symptoms, including sensory dysfunction and abnormal language development. Boys are diagnosed ~ 3.8 times more frequently than girls. Auditory temporal processing is crucial for speech recognition and language development. Abnormal development of temporal processing may account for ASD language impairments. Sex differences in the development of temporal processing may underlie the differences in language outcomes in male and female children with ASD. To understand mechanisms of potential sex differences in temporal processing requires a preclinical model. However, there are no studies that have addressed sex differences in temporal processing across development in any animal model of ASD. METHODS: To fill this major gap, we compared the development of auditory temporal processing in male and female wildtype (WT) and Fmr1 knock-out (KO) mice, a model of Fragile X Syndrome (FXS), a leading genetic cause of ASD-associated behaviors. Using epidural screw electrodes, we recorded auditory event related potentials (ERP) and auditory temporal processing with a gap-in-noise auditory steady state response (ASSR) paradigm at young (postnatal (p)21 and p30) and adult (p60) ages from both auditory and frontal cortices of awake, freely moving mice. RESULTS: The results show that ERP amplitudes were enhanced in both sexes of Fmr1 KO mice across development compared to WT counterparts, with greater enhancement in adult female than adult male KO mice. Gap-ASSR deficits were seen in the frontal, but not auditory, cortex in early development (p21) in female KO mice. Unlike male KO mice, female KO mice show WT-like temporal processing at p30. There were no temporal processing deficits in the adult mice of both sexes. CONCLUSIONS: These results show a sex difference in the developmental trajectories of temporal processing and hypersensitive responses in Fmr1 KO mice. Male KO mice show slower maturation of temporal processing than females. Female KO mice show stronger hypersensitive responses than males later in development. The differences in maturation rates of temporal processing and hypersensitive responses during various critical periods of development may lead to sex differences in language function, arousal and anxiety in FXS.

The relationship between gamma-band neural oscillations and language skills in youth with Autism Spectrum Disorder and their first-degree relatives.

BACKGROUND: Most children with Autism Spectrum Disorder (ASD) have co-occurring language impairments and some of these autism-specific language difficulties are also present in their non-autistic first-degree relatives. One of the possible neural mechanisms associated with variability in language functioning is alterations in cortical gamma-band oscillations, hypothesized to be related to neural excitation and inhibition balance. METHODS: We used a high-density 128-channel electroencephalography (EEG) to register brain response to speech stimuli in a large sex-balanced sample of participants: 125 youth with ASD, 121 typically developing (TD) youth, and 40 unaffected siblings (US) of youth with ASD. Language skills were assessed with Clinical Evaluation of Language Fundamentals. RESULTS: First, during speech processing, we identified significantly elevated gamma power in ASD participants compared to TD controls. Second, across all youth, higher gamma power was associated with lower language skills. Finally, the US group demonstrated an intermediate profile in both language and gamma power, with nonverbal IQ mediating the relationship between gamma power and language skills. LIMITATIONS: We only focused on one of the possible neural contributors to variability in language functioning. Also, the US group consisted of a smaller number of participants in comparison to the ASD or TD groups. Finally, due to the timing issue in EEG system we have provided only non-phase-locked analysis. CONCLUSIONS: Autistic youth showed elevated gamma power, suggesting higher excitation in the brain in response to speech stimuli and elevated gamma power was related to lower language skills. The US group showed an intermediate pattern of gamma activity, suggesting that the broader autism phenotype extends to neural profiles.

A hybrid CNN-SVM model for enhanced autism diagnosis.

Autism is a representative disorder of pervasive developmental disorder. It exerts influence upon an individual's behavior and performance, potentially co-occurring with other mental illnesses. Consequently, an effective diagnostic approach proves to be invaluable in both therapeutic interventions and the timely provision of medical support. Currently, most scholars' research primarily relies on neuroimaging techniques for auxiliary diagnosis and does not take into account the distinctive features of autism's social impediments. In order to address this deficiency, this paper introduces a novel convolutional neural network-support vector machine model that integrates resting state functional magnetic resonance imaging data with the social responsiveness scale metrics for the diagnostic assessment of autism. We selected 821 subjects containing the social responsiveness scale measure from the publicly available Autism Brain Imaging Data Exchange dataset, including 379 subjects with autism spectrum disorder and 442 typical controls. After preprocessing of fMRI data, we compute the static and dynamic functional connectivity for each subject. Subsequently, convolutional neural networks and attention mechanisms are utilized to extracts their respective features. The extracted features, combined with the social responsiveness scale features, are then employed as novel inputs for the support vector machine to categorize autistic patients and typical controls. The proposed model identifies salient features within the static and dynamic functional connectivity, offering a possible biological foundation for clinical diagnosis. By incorporating the behavioral assessments, the model achieves a remarkable classification accuracy of 94.30%, providing a more reliable support for auxiliary diagnosis.

Atypical neural encoding of faces in individuals with autism spectrum disorder.

Individuals with autism spectrum disorder (ASD) experience pervasive difficulties in processing social information from faces. However, the behavioral and neural mechanisms underlying social trait judgments of faces in ASD remain largely unclear. Here, we comprehensively addressed this question by employing functional neuroimaging and parametrically generated faces that vary in facial trustworthiness and dominance. Behaviorally, participants with ASD exhibited reduced specificity but increased inter-rater variability in social trait judgments. Neurally, participants with ASD showed hypo-activation across broad face-processing areas. Multivariate analysis based on trial-by-trial face responses could discriminate participant groups in the majority of the face-processing areas. Encoding social traits in ASD engaged vastly different face-processing areas compared to controls, and encoding different social traits engaged different brain areas. Interestingly, the idiosyncratic brain areas encoding social traits in ASD were still flexible and context-dependent, similar to neurotypicals. Additionally, participants with ASD also showed an altered encoding of facial saliency features in the eyes and mouth. Together, our results provide a comprehensive understanding of the neural mechanisms underlying social trait judgments in ASD.

Atypical functional connectivity between the amygdala and visual, salience regions in infants with genetic liability for autism.

The amygdala undergoes a period of overgrowth in the first year of life, resulting in enlarged volume by 12 months in infants later diagnosed with ASD. The overgrowth of the amygdala may have functional consequences during infancy. We investigated whether amygdala connectivity differs in 12-month-olds at high likelihood (HL) for ASD (defined by having an older sibling with autism), compared to those at low likelihood (LL). We examined seed-based connectivity of left and right amygdalae, hypothesizing that the HL and LL groups would differ in amygdala connectivity, especially with the visual cortex, based on our prior reports demonstrating that components of visual circuitry develop atypically and are linked to genetic liability for autism. We found that HL infants exhibited weaker connectivity between the right amygdala and the left visual cortex, as well as between the left amygdala and the right anterior cingulate, with evidence that these patterns occur in distinct subgroups of the HL sample. Amygdala connectivity strength with the visual cortex was related to motor and communication abilities among HL infants. Findings indicate that aberrant functional connectivity between the amygdala and visual regions is apparent in infants with genetic liability for ASD and may have implications for early differences in adaptive behaviors.

Neuroanatomy of autism: what is the role of the cerebellum?

Autism (or autism spectrum disorder) was initially defined as a psychiatric disorder, with the likely cause maternal behavior (the very destructive "refrigerator mother" theory). It took several decades for research into brain mechanisms to become established. Both neuropathological and imaging studies found differences in the cerebellum in autism spectrum disorder, the most widely documented being a decreased density of Purkinje cells in the cerebellar cortex. The popular interpretation of these results is that cerebellar neuropathology is a critical cause of autism spectrum disorder. We challenge that view by arguing that if fewer Purkinje cells are critical for autism spectrum disorder, then any condition that causes the loss of Purkinje cells should also cause autism spectrum disorder. We will review data on damage to the cerebellum from cerebellar lesions, tumors, and several syndromes (Joubert syndrome, Fragile X, and tuberous sclerosis). Collectively, these studies raise the question of whether the cerebellum really has a role in autism spectrum disorder. Autism spectrum disorder is now recognized as a genetically caused developmental disorder. A better understanding of the genes that underlie the differences in brain development that result in autism spectrum disorder is likely to show that these genes affect the development of the cerebellum in parallel with the development of the structures that do underlie autism spectrum disorder.

Infants' reorienting efficiency depends on parental autistic traits and predicts future socio-communicative behaviors.

Attentional reorienting is dysfunctional not only in children with autism spectrum disorder (ASD), but also in infants who will develop ASD, thus constituting a potential causal factor of future social interaction and communication abilities. Following the research domain criteria framework, we hypothesized that the presence of subclinical autistic traits in parents should lead to atypical infants' attentional reorienting, which in turn should impact on their future socio-communication behavior in toddlerhood. During an attentional cueing task, we measured the saccadic latencies in a large sample (total enrolled n = 89; final sample n = 71) of 8-month-old infants from the general population as a proxy for their stimulus-driven attention. Infants were grouped in a high parental traits (HPT; n = 23) or in a low parental traits (LPT; n = 48) group, according to the degree of autistic traits self-reported by their parents. Infants (n = 33) were then longitudinally followed to test their socio-communicative behaviors at 21 months. Results show a sluggish reorienting system, which was a longitudinal predictor of future socio-communicative skills at 21 months. Our combined transgenerational and longitudinal findings suggest that the early functionality of the stimulus-driven attentional network-redirecting attention from one event to another-could be directly connected to future social and communication development.

More than meets the eye: A conserved sensorimotor reflex helps unravel the circuit mechanisms of ASD.

Animal models are instrumental to understanding the mechanisms underlying autism spectrum disorder, yet translating human behavioral phenotypes remains challenging. Wang et al. leverage a conserved sensorimotor reflex to elucidate synaptic deficits in Scn2a haploinsufficiency and pilot novel rescue strategies.

Reduced lateralization of multiple functional brain networks in autistic males.

BACKGROUND: Autism spectrum disorder has been linked to a variety of organizational and developmental deviations in the brain. One such organizational difference involves hemispheric lateralization, which may be localized to language-relevant regions of the brain or distributed more broadly. METHODS: In the present study, we estimated brain hemispheric lateralization in autism based on each participant's unique functional neuroanatomy rather than relying on group-averaged data. Additionally, we explored potential relationships between the lateralization of the language network and behavioral phenotypes including verbal ability, language delay, and autism symptom severity. We hypothesized that differences in hemispheric asymmetries in autism would be limited to the language network, with the alternative hypothesis of pervasive differences in lateralization. We tested this and other hypotheses by employing a cross-sectional dataset of 118 individuals (48 autistic, 70 neurotypical). Using resting-state fMRI, we generated individual network parcellations and estimated network asymmetries using a surface area-based approach. A series of multiple regressions were then used to compare network asymmetries for eight significantly lateralized networks between groups. RESULTS: We found significant group differences in lateralization for the left-lateralized Language (d = -0.89), right-lateralized Salience/Ventral Attention-A (d = 0.55), and right-lateralized Control-B (d = 0.51) networks, with the direction of these group differences indicating less asymmetry in autistic males. These differences were robust across different datasets from the same participants. Furthermore, we found that language delay stratified language lateralization, with the greatest group differences in language lateralization occurring between autistic males with language delay and neurotypical individuals. CONCLUSIONS: These findings evidence a complex pattern of functional lateralization differences in autism, extending beyond the Language network to the Salience/Ventral Attention-A and Control-B networks, yet not encompassing all networks, indicating a selective divergence rather than a pervasive one. Moreover, we observed an association between Language network lateralization and language delay in autistic males.

Autism spectrum disorder diagnosis with EEG signals using time series maps of brain functional connectivity and a combined CNN-LSTM model.

BACKGROUND AND OBJECTIVE: People with autism spectrum disorder (ASD) often have cognitive impairments. Effective connectivity between different areas of the brain is essential for normal cognition. Electroencephalography (EEG) has been widely used in the detection of neurological diseases. Previous studies on detecting ASD with EEG data have focused on frequency-related features. Most of these studies have augmented data by splitting the dataset into time slices or sliding windows. However, such approaches to data augmentation may cause the testing data to be contaminated by the training data. To solve this problem, this study developed a novel method for detecting ASD with EEG data. METHODS: This study quantified the functional connectivity of the subject's brain from EEG signals and defined the individual to be the unit of analysis. Publicly available EEG data were gathered from 97 and 92 subjects with ASD and typical development (TD), respectively, while they were at rest or performing a task. Time-series maps of brain functional connectivity were constructed, and the data were augmented using a deep convolutional generative adversarial network. In addition, a combined network for ASD detection, based on convolutional neural network (CNN) and long short-term memory (LSTM), was designed and implemented. RESULTS: Based on functional connectivity, the network achieved classification accuracies of 81.08% and 74.55% on resting state and task state data, respectively. In addition, we found that the functional connectivity of ASD differed from TD primarily in the short-distance functional connectivity of the parietal and occipital lobes and in the distant connections from the right temporoparietal junction region to the left posterior temporal lobe. CONCLUSIONS: This paper provides a new perspective for better utilizing EEG to understand ASD. The method proposed in our study is expected to be a reliable tool to assist in the diagnosis of ASD.

Salience network connectivity is altered in 6-week-old infants at heightened likelihood for developing autism.

Converging evidence implicates disrupted brain connectivity in autism spectrum disorder (ASD); however, the mechanisms linking altered connectivity early in development to the emergence of ASD symptomatology remain poorly understood. Here we examined whether atypicalities in the Salience Network - an early-emerging neural network involved in orienting attention to the most salient aspects of one's internal and external environment - may predict the development of ASD symptoms such as reduced social attention and atypical sensory processing. Six-week-old infants at high likelihood of developing ASD based on family history exhibited stronger Salience Network connectivity with sensorimotor regions; infants at typical likelihood of developing ASD demonstrated stronger Salience Network connectivity with prefrontal regions involved in social attention. Infants with higher connectivity with sensorimotor regions had lower connectivity with prefrontal regions, suggesting a direct tradeoff between attention to basic sensory versus socially-relevant information. Early alterations in Salience Network connectivity predicted subsequent ASD symptomatology, providing a plausible mechanistic account for the unfolding of atypical developmental trajectories associated with vulnerability to ASD.

BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping.

Converging evidence increasingly suggests that psychiatric disorders, such as major depressive disorder (MDD) and autism spectrum disorder (ASD), are not unitary diseases, but rather heterogeneous syndromes that involve diverse, co-occurring symptoms and divergent responses to treatment. This clinical heterogeneity has hindered the progress of precision diagnosis and treatment effectiveness in psychiatric disorders. In this study, we propose BPI-GNN, a new interpretable graph neural network (GNN) framework for analyzing functional magnetic resonance images (fMRI), by leveraging the famed prototype learning. In addition, we introduce a novel generation process of prototype subgraph to discover essential edges of distinct prototypes and employ total correlation (TC) to ensure the independence of distinct prototype subgraph patterns. BPI-GNN can effectively discriminate psychiatric patients and healthy controls (HC), and identify biological meaningful subtypes of psychiatric disorders. We evaluate the performance of BPI-GNN against 11 popular brain network classification methods on three psychiatric datasets and observe that our BPI-GNN always achieves the highest diagnosis accuracy. More importantly, we examine differences in clinical symptom profiles and gene expression profiles among identified subtypes and observe that our identified brain-based subtypes have the clinical relevance. It also discovers the subtype biomarkers that align with current neuro-scientific knowledge.

Dynamic graph transformer network via dual-view connectivity for autism spectrum disorder identification.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that requires objective and accurate identification methods for effective early intervention. Previous population-based methods via functional connectivity (FC) analysis ignore the differences between positive and negative FCs, which provide the potential information complementarity. And they also require additional information to construct a pre-defined graph. Meanwhile, two challenging demand attentions are the imbalance of performance caused by the class distribution and the inherent heterogeneity of multi-site data. In this paper, we propose a novel dynamic graph Transformer network based on dual-view connectivity for ASD Identification. It is based on the Autoencoders, which regard the input feature as individual feature and without any inductive bias. First, a dual-view feature extractor is designed to extract individual and complementary information from positive and negative connectivity. Then Graph Transformer network is innovated with a hot plugging K-Nearest Neighbor (KNN) algorithm module which constructs a dynamic population graph without any additional information. Additionally, we introduce the PolyLoss function and the Vrex method to address the class imbalance and improve the model's generalizability. The evaluation experiment on 1102 subjects from the ABIDE I dataset demonstrates our method can achieve superior performance over several state-of-the-art methods and satisfying generalizability for ASD identification.

Parenting behaviors in mice: Olfactory mechanisms and features in models of autism spectrum disorders.

Rodents, along with numerous other mammals, heavily depend on olfactory cues to navigate their social interactions. Processing of olfactory sensory inputs is mediated by conserved brain circuits that ultimately trigger social behaviors, such as social interactions and parental care. Although innate, parenting is influenced by internal states, social experience, genetics, and the environment, and any significant disruption of these factors can impact the social circuits. Here, we review the molecular mechanisms and social circuits from the olfactory epithelium to central processing that initiate parental behaviors and their dysregulations that may contribute to the social impairments in mouse models of autism spectrum disorders (ASD). We discuss recent advances of the crucial role of olfaction in parental care, its consequences for social interactions, and the reciprocal influence on social interaction impairments in mouse models of ASD.

Exploring the neurological features of individuals with germline PTEN variants: A multicenter study.

OBJECTIVE: PTEN, a known tumor suppressor gene, is a mediator of neurodevelopment. Individuals with germline pathogenic variants in the PTEN gene, molecularly defined as PTEN hamartoma tumor syndrome (PHTS), experience a variety of neurological and neuropsychiatric challenges during childhood, including autism spectrum disorder (ASD). However, the frequency and nature of seizures and the utilization of allied health services have not been described. METHODS: Young patients with PHTS and sibling controls were recruited across five centers in the United States and followed every 6-12 months for a mean of 2.1 years. In addition to the history obtained from caregivers, neurodevelopmental evaluations and structured dysmorphology examinations were conducted, and brain MRI findings, received therapies, and epilepsy characteristics were reported. RESULTS: One hundred and seven patients with PHTS (median age 8.7 years; range 3-21 years) and 38 controls were enrolled. ASD and epilepsy were frequent among patients with PHTS (51% and 15%, respectively), with generalized epilepsy strongly associated with ASD. Patients with epilepsy often required two antiseizure medications. Neuroimaging revealed prominent perivascular spaces and decreased peritrigonal myelination in individuals with PHTS-ASD. Allied therapy use was frequent and involved physical, occupational, speech, and social skills therapies, with 89% of all patients with PHTS, regardless of ASD diagnosis, utilizing at least one service. INTERPRETATION: This prospective, longitudinal study highlights the wide neurological spectrum seen in young individuals with PHTS. ASD is common in PHTS, comorbid with epilepsy, and allied health services are used universally. Our findings inform care discussions with families about neurological outcomes in PHTS.

Altered intra- and inter-network brain functional connectivity associated with prolonged screen time in pre-school children with autism spectrum disorder.

Prolonged screen time (ST) has adverse effects on autistic characteristics and language development. However, the mechanisms underlying the effects of prolonged ST on the neurodevelopment of children with autism spectrum disorder (ASD) remain unclear. Neuroimaging technology may help to further explain the role of prolonged ST in individuals with ASD. This study included 164 cases, all cases were divided into low-dose ST exposure (LDE group 108 cases) and high-dose ST exposure (HDE group 56 cases) based on the average ST of all subjects. Spatial independent component analysis (ICA) was used to identify resting state networks (RSNs) and investigate intra- and inter-network alterations in ASD children with prolonged ST. We found that the total Childhood Autism Rating Scale (CARS) scores in the HDE group were significantly higher than those in the LDE group (36.2 ± 3.1 vs. 34.6 ± 3.9, p = 0.008). In addition, the developmental quotient (DQ) of hearing and language in the HDE group were significantly lower than those in the LDE group (31.5 ± 13.1 vs. 42.5 ± 18.5, p < 0.001). A total of 13 independent components (ICs) were identified. Between-group comparison revealed that the HDE group exhibited decreased functional connectivity (FC) in the left precuneus (PCUN) of the default mode network (DMN), the right middle temporal gyrus (MTG) of the executive control network (ECN), and the right median cingulate and paracingulate gyri (MCG) of the attention network (ATN), compared with the LDE group. Additionally, there was an increase in FC in the right orbital part of the middle frontal gyrus (ORBmid) of the salience network (SAN), compared with the LDE group. The inter-network analysis revealed increased FC between the visual network (VN) and basal ganglia (BG) and decreased FC between the sensorimotor network (SMN) and DMN, SMN and ATN, SMN and auditory network (AUN), and DMN and SAN in the HDE group, compared with the LDE group. There was a significant negative correlation between altered FC values in MTG and total CARS scores in subjects (r = - 0.18, p = 0.018).  Conclusion: ASD children with prolonged ST often exhibit lower DQ of language development and more severe autistic characteristics. The alteration of intra- and inter-network FC may be a key neuroimaging feature of the effect of prolonged ST on neurodevelopment in ASD children.  Clinical trial registration: ChiCTR2100051141. What is Known: • Prolonged ST has adverse effects on autistic characteristics and language development. • Neuroimaging technology may help to further explain the role of prolonged ST in ASD. What is New: • This is the first study to explore the impact of ST on intra- and inter-network FC in children with ASD. • ASD children with prolonged ST have atypical changes in intra- and inter-brain network FC.

Volumetric alterations in the basal ganglia in autism Spectrum disorder: A systematic review.

INTRODUCTION: Recent research indicates that some brain structures show alterations in conditions such as Autism Spectrum Disorder (ASD). Among them, are the basal ganglia that are involved in motor, cognitive and behavioral neural circuits. OBJECTIVE: Review the literature that describes possible volumetric alterations in the basal ganglia of individuals with ASD and the impacts that these changes have on the severity of the condition. METHODOLOGY: This systematic review was registered in the design and reported according to the PRISMA Items and registered in PROSPERO (CRD42023394787). The study analyzed data from published clinical, case-contemplate, and cohort trials. The following databases were consulted: PubMed, Embase, Scopus, and Cochrane Central Register of Controlled Trials, using the Medical Subject Titles (MeSH) "Autism Spectrum Disorder" and "Basal Ganglia". The last search was carried out on February 28, 2023. RESULTS: Thirty-five eligible articles were collected, analyzed, and grouped according to the levels of alterations. CONCLUSION: The present study showed important volumetric alterations in the basal ganglia in ASD. However, the examined studies have methodological weaknesses that do not allow generalization and correlation with ASD manifestations.

Impaired cerebellar plasticity hypersensitizes sensory reflexes in SCN2A-associated ASD.

Children diagnosed with autism spectrum disorder (ASD) commonly present with sensory hypersensitivity or abnormally strong reactions to sensory stimuli. Such hypersensitivity can be overwhelming, causing high levels of distress that contribute markedly to the negative aspects of the disorder. Here, we identify a mechanism that underlies hypersensitivity in a sensorimotor reflex found to be altered in humans and in mice with loss of function in the ASD risk-factor gene SCN2A. The cerebellum-dependent vestibulo-ocular reflex (VOR), which helps maintain one's gaze during movement, was hypersensitized due to deficits in cerebellar synaptic plasticity. Heterozygous loss of SCN2A-encoded NaV1.2 sodium channels in granule cells impaired high-frequency transmission to Purkinje cells and long-term potentiation, a form of synaptic plasticity important for modulating VOR gain. VOR plasticity could be rescued in mice via a CRISPR-activator approach that increases Scn2a expression, demonstrating that evaluation of a simple reflex can be used to assess and quantify successful therapeutic intervention.

Sex shapes gut-microbiota-brain communication and disease.

Research into the microbiota-gut-brain axis (MGBA) has entered a golden age, raising the hope that therapeutics acting on it may offer breakthroughs in the treatment of many illnesses. However, most of this work overlooks a fundamental, yet understudied, biological variable: sex. Sex differences exist at every level of the MGBA. Sex steroids shape the structure of the gut microbiota, and these microbes in turn regulate levels of bioactive sex steroids. These hormones and microbes act on gut sensory enteroendocrine cells, which modulate downstream activity in the enteric nervous system, vagus nerve, and brain. We examine recent advances in this field, and discuss the scientific and moral imperative to include females in biomedical research, using autism spectrum disorder (ASD) as an example.

Phosphodiesterase inhibitor, ibudilast alleviates core behavioral and biochemical deficits in the prenatal valproic acid exposure model of autism spectrum disorder.

BACKGROUND: Autism spectrum disorder (ASD) is categorized as a neurodevelopmental disorder, presenting with a variety of aetiological and phenotypical features. Ibudilast is known to produce beneficial effects in several neurological disorders including neuropathic pain, multiple sclerosis, etc. by displaying its neuroprotective and anti-inflammatory properties. Here, in our study, the pharmacological outcome of ibudilast administration was investigated in the prenatal valproic acid (VPA)-model of ASD in Wistar rats. METHODS: Autistic-like symptoms were induced in Wistar male pups of dams administered with Valproic acid (VPA) on embryonic day 12.5. VPA-exposed male pups were administered with two doses of ibudilast (5 and10 mg/kg) and all the groups were evaluated for behavioral parameters like social interaction, spatial memory/learning, anxiety, locomotor activity, and nociceptive threshold. Further, the possible neuroprotective effect of ibudilast was evaluated by assessing oxidative stress, neuroinflammation (IL-1ß, TNF-α, IL-6, IL-10) in the hippocampus, % area of Glial fibrillary acidic protein (GFAP)-positive cells and neuronal damage in the cerebellum. KEY FINDINGS: Treatment with ibudilast significantly attenuated prenatal VPA exposure associated social interaction and spatial learning/memory deficits, anxiety, hyperactivity, and increased nociceptive threshold, and it decreased oxidative stress markers, pro-inflammatory markers (IL-1ß, TNF-α, IL-6), and % area of GFAP-positive cells and restored neuronal damage. CONCLUSIONS: Ibudilast treatment has restored crucial ASD-related behavioural abnormalities, potentially through neuroprotection. Therefore, benefits of ibudilast administration in animal models of ASD suggest that ibudilast may have therapeutic potential in the treatment of ASD.