A computational model for cerebral cortical dysfunction in autism spectrum disorders

Selective oxytocin receptor activation prevents prefrontal circuit dysfunction and social behavioral alterations in response to chronic prefrontal cortex activation in male rats

Introduction

Social behavioral changes are a hallmark of several neurodevelopmental and neuropsychiatric conditions, nevertheless the underlying neural substrates of such dysfunction remain poorly understood. Building evidence points to the prefrontal cortex (PFC) as one of the key brain regions that orchestrates social behavior. We used this concept with the aim to develop a translational rat model of social-circuit dysfunction, the chronic PFC activation model (CPA).

Methods

Chemogenetic designer receptor hM3Dq was used to induce chronic activation of the PFC over 10 days, and the behavioral and electrophysiological signatures of prolonged PFC hyperactivity were evaluated. To test the sensitivity of this model to pharmacological interventions on longer timescales, and validate its translational potential, the rats were treated with our novel highly selective oxytocin receptor (OXTR) agonist RO6958375, which is not activating the related vasopressin V1a receptor.

Results

CPA rats showed reduced sociability in the three-chamber sociability test, and a concomitant decrease in neuronal excitability and synaptic transmission within the PFC as measured by electrophysiological recordings in acute slice preparation. Sub-chronic treatment with a low dose of the novel OXTR agonist following CPA interferes with the emergence of PFC circuit dysfunction, abnormal social behavior and specific transcriptomic changes.

Discussion

These results demonstrate that sustained PFC hyperactivity modifies circuit characteristics and social behaviors in ways that can be modulated by selective OXTR activation and that this model may be used to understand the circuit recruitment of prosocial therapies in drug discovery.

Replicable Patterns of Memory Impairments in Children With Autism and Their Links to Hyperconnected Brain Circuits

BACKGROUND

Memory impairments have profound implications for social communication and educational outcomes in children with autism spectrum disorder (ASD). However, the precise nature of memory dysfunction in children with ASD and the underlying neural circuit mechanisms remain poorly understood. The default mode network (DMN) is a brain network that is associated with memory and cognitive function, and DMN dysfunction is among the most replicable and robust brain signatures of ASD.

METHODS

We used a comprehensive battery of standardized episodic memory assessments and functional circuit analyses in 25 8- to 12-year-old children with ASD and 29 matched typically developing control children.

RESULTS

Memory performance was reduced in children with ASD compared with control children. General and face memory emerged as distinct dimensions of memory difficulties in ASD. Importantly, findings of diminished episodic memory in children with ASD were replicated in 2 independent data sets. Analysis of intrinsic functional circuits associated with the DMN revealed that general and face memory deficits were associated with distinct, hyperconnected circuits: Aberrant hippocampal connectivity predicted diminished general memory while aberrant posterior cingulate cortex connectivity predicted diminished face memory. Notably, aberrant hippocampal-posterior cingulate cortex circuitry was a common feature of diminished general and face memory in ASD.

CONCLUSIONS

Our results represent a comprehensive appraisal of episodic memory function in children with ASD and identify extensive and replicable patterns of memory reductions in children with ASD that are linked to dysfunction of distinct DMN-related circuits. These findings highlight a role for DMN dysfunction in ASD that extends beyond face memory to general memory function.

Binocular rivalry in autistic and socially anxious adults

Background

Social anxiousness is a pervasive symptom in both social anxiety disorder and autism spectrum conditions. Binocular rivalry, which occurs when different images are presented to each eye, has been used to explore how visual and cognitive processing differs across various clinical diagnoses. Previous studies have separately explored whether individuals with autism or anxiety experience binocular rivalry in ways that are different from neurotypical individuals.

Methods

We applied rivalry paradigms that are similar to those used in previous studies of autism and general anxiety to individuals experiencing symptoms of social anxiousness at clinical or subclinical levels. We also incorporated rivalrous stimuli featuring neutral and emotional facial valances to explore potential overlap of social processing components in social anxiety and autism.

Results

We hypothesized that higher levels of social anxiousness would increase binocular rivalry switch rates and that higher levels of autistic traits would decrease switch rates. However, stimulus condition did not affect switch rates in either diagnostic group, and switch rate was not significantly predictive of dimensional measures of either autism or social anxiety.

Discussion

This may suggest a common mechanism for atypical visual cognition styles previously associated with social anxiety and autism. Alternatively, differences in switch rates may only emerge at higher trait levels than reported by the participants in our studies. Furthermore, these findings may be influenced by sex differences in our unique sample.

New insights into binocular rivalry from the reconstruction of evolving percepts using model network dynamics

When the two eyes are presented with highly distinct stimuli, the resulting visual percept generally switches every few seconds between the two monocular images in an irregular fashion, giving rise to a phenomenon known as binocular rivalry. While a host of theoretical studies have explored potential mechanisms for binocular rivalry in the context of evoked model dynamics in response to simple stimuli, here we investigate binocular rivalry directly through complex stimulus reconstructions based on the activity of a two-layer neuronal network model with competing downstream pools driven by disparate monocular stimuli composed of image pixels. To estimate the dynamic percept, we derive a linear input-output mapping rooted in the non-linear network dynamics and iteratively apply compressive sensing techniques for signal recovery. Utilizing a dominance metric, we are able to identify when percept alternations occur and use data collected during each dominance period to generate a sequence of percept reconstructions. We show that despite the approximate nature of the input-output mapping and the significant reduction in neurons downstream relative to stimulus pixels, the dominant monocular image is well-encoded in the network dynamics and improvements are garnered when realistic spatial receptive field structure is incorporated into the feedforward connectivity. Our model demonstrates gamma-distributed dominance durations and well obeys Levelt's four laws for how dominance durations change with stimulus strength, agreeing with key recurring experimental observations often used to benchmark rivalry models. In light of evidence that individuals with autism exhibit relatively slow percept switching in binocular rivalry, we corroborate the ubiquitous hypothesis that autism manifests from reduced inhibition in the brain by systematically probing our model alternation rate across choices of inhibition strength. We exhibit sufficient conditions for producing binocular rivalry in the context of natural scene stimuli, opening a clearer window into the dynamic brain computations that vary with the generated percept and a potential path toward further understanding neurological disorders.

Increased Reliability of Visually-Evoked Activity in Area V1 of the MECP2-Duplication Mouse Model of Autism

Atypical sensory processing is now thought to be a core feature of the autism spectrum. Influential theories have proposed that both increased and decreased neural response reliability within sensory systems could underlie altered sensory processing in autism. Here, we report evidence for abnormally increased reliability of visual-evoked responses in layer 2/3 neurons of adult male and female primary visual cortex in the MECP2-duplication syndrome animal model of autism. Increased response reliability was due in part to decreased response amplitude, decreased fluctuations in endogenous activity, and an abnormal decoupling of visual-evoked activity from endogenous activity. Similar to what was observed neuronally, the optokinetic reflex occurred more reliably at low contrasts in mutant mice compared with controls. Retinal responses did not explain our observations. These data suggest that the circuit mechanisms for combining sensory-evoked and endogenous signal and noise processes may be altered in this form of syndromic autism.SIGNIFICANCE STATEMENT Atypical sensory processing is now thought to be a core feature of the autism spectrum. Influential theories have proposed that both increased and decreased neural response reliability within sensory systems could underlie altered sensory processing in autism. Here, we report evidence for abnormally increased reliability of visual-evoked responses in primary visual cortex of the animal model for MECP2-duplication syndrome, a high-penetrance single-gene cause of autism. Visual-evoked activity was abnormally decoupled from endogenous activity in mutant mice, suggesting in line with the influential "hypo-priors" theory of autism that sensory priors embedded in endogenous activity may have less influence on perception in autism.

On the relationship between GABA+ and glutamate across the brain

Equilibrium between excitation and inhibition (E/I balance) is key to healthy brain function. Conversely, disruption of normal E/I balance has been implicated in a range of central neurological pathologies. Magnetic resonance spectroscopy (MRS) provides a non-invasive means of quantifying in vivo concentrations of excitatory and inhibitory neurotransmitters, which could be used as diagnostic biomarkers. Using the ratio of excitatory and inhibitory neurotransmitters as an index of E/I balance is common practice in MRS work, but recent studies have shown inconsistent evidence for the validity of this proxy. This is underscored by the fact that different measures are often used in calculating E/I balance such as glutamate and Glx (glutamate and glutamine). Here we used a large MRS dataset obtained at ultra-high field (7 T) measured from 193 healthy young adults and focused on two brain regions - prefrontal and occipital cortex - to resolve this inconsistency. We find evidence that there is an inter-individual common ratio between GABA+ (γ-aminobutyric acid and macromolecules) and Glx in the occipital, but not prefrontal cortex. We further replicate the prefrontal result in a legacy dataset (n = 78) measured at high-field (3 T) strength. By contrast, with ultra-high field MRS data, we find extreme evidence that there is a common ratio between GABA+ and glutamate in both prefrontal and occipital cortices, which cannot be explained by participant demographics, signal quality, fractional tissue volume, or other metabolite concentrations. These results are consistent with previous electrophysiological and theoretical work supporting E/I balance. Our findings indicate that MRS-detected GABA+ and glutamate (but not Glx), are a reliable measure of E/I balance .

Visual illusion susceptibility in autism: A neural model

While atypical sensory perception is reported among individuals with autism spectrum disorder (ASD), the underlying neural mechanisms of autism that give rise to disruptions in sensory perception remain unclear. We developed a neural model with key physiological, functional and neuroanatomical parameters to investigate mechanisms underlying the range of representations of visual illusions related to orientation perception in typically developed subjects compared to individuals with ASD. Our results showed that two theorized autistic traits, excitation/inhibition imbalance and weakening of top‐down modulation, could be potential candidates for reduced susceptibility to some visual illusions. Parametric correlation between cortical suppression, balance of excitation/inhibition, feedback from higher visual areas on one hand and susceptibility to a class of visual illusions related to orientation perception on the other hand provide the opportunity to investigate the contribution and complex interactions of distinct sensory processing mechanisms in ASD. The novel approach used in this study can be used to link behavioural, functional and neuropathological studies; estimate and predict perceptual and cognitive heterogeneity in ASD; and form a basis for the development of novel diagnostics and therapeutics.

Visual consciousness dynamics in adults with and without autism

Sensory differences between autism and neuro-typical populations are well-documented and have often been explained by either weak-central-coherence or excitation/inhibition-imbalance cortical theories. We tested these theories with perceptual multi-stability paradigms in which dissimilar images presented to each eye generate dynamic cyclopean percepts based on ongoing cortical grouping and suppression processes. We studied perceptual multi-stability with Interocular Grouping (IOG), which requires the simultaneous integration and suppression of image fragments from both eyes, and Conventional Binocular Rivalry (CBR), which only requires global suppression of either eye, in 17 autistic adults and 18 neurotypical participants. We used a Hidden-Markov-Model as tool to analyze the multistable dynamics of these processes. Overall, the dynamics of multi-stable perception were slower (i.e. there were longer durations and fewer transitions among perceptual states) in the autistic group compared to the neurotypical group for both IOG and CBR. The weighted Markovian transition distributions revealed key differences between both groups and paradigms. The results indicate overall lower levels of suppression and decreased levels of grouping in autistic than neurotypical participants, consistent with elements of excitation/inhibition imbalance and weak-central-coherence theories.

Alteration of Effective Connectivity in the Default Mode Network of Autism After an Intervention

Neuroimaging has revealed numerous atypical functional connectivity of default mode network (DMN) dedicated to social communications (SC) in autism spectrum disorder (ASD), yet their nature and directionality remain unclear. Here, preschoolers with autism received physical intervention from a 12-week mini-basketball training program (12W-MBTP). Therefore, the directionality and nature of regional interactions within the DMN after the intervention are evaluated while assessing the impact of an intervention on SC. Based on the results of independent component analysis (ICA), we applied spectral dynamic causal modeling (DCM) for participants aged 3–6 years (experimental group, N = 17, control group, N = 14) to characterize the longitudinal changes following intervention in intrinsic and extrinsic effective connectivity (EC) between core regions of the DMN. Then, we analyzed the correlation between the changes in EC and SRS-2 scores to establish symptom-based validation. We found that after the 12W-MBTP intervention, the SRS-2 score of preschoolers with ASD in the experimental group was decreased. Concurrently, the inhibitory directional connections were observed between the core regions of the DMN, including increased self-inhibition in the medial prefrontal cortex (mPFC), and the changes of EC in mPFC were significantly correlated with change in the social responsiveness scale-2 (SRS-2) score. These new findings shed light on DMN as a potential intervention target, as the inhibitory information transmission between its core regions may play a positive role in improving SC behavior in preschoolers with ASD, which may be a reliable neuroimaging biomarker for future studies.

Clinical Trial Registration: This study registered with the Chinese Clinical Trial Registry (ChiCTR1900024973) on August 05, 2019.

Dorsal raphe nucleus to anterior cingulate cortex 5-HTergic neural circuit modulates consolation and sociability

Consolation is a common response to the distress of others in humans and some social animals, but the neural mechanisms underlying this behavior are not well characterized. By using socially monogamous mandarin voles, we found that optogenetic or chemogenetic inhibition of 5-HTergic neurons in the dorsal raphe nucleus (DR) or optogenetic inhibition of serotonin (5-HT) terminals in the anterior cingulate cortex (ACC) significantly decreased allogrooming time in the consolation test and reduced sociability in the three-chamber test. The release of 5-HT within the ACC and the activity of DR neurons were significantly increased during allogrooming, sniffing, and social approaching. Finally, we found that the activation of 5-HT1A receptors in the ACC was sufficient to reverse consolation and sociability deficits induced by the chemogenetic inhibition of 5-HTergic neurons in the DR. Our study provided the first direct evidence that DR-ACC 5-HTergic neural circuit is implicated in consolation-like behaviors and sociability.

No balance between glutamate+glutamine and GABA+ in visual or motor cortices of the human brain: A magnetic resonance spectroscopy study

Theoretical work, supported by electrophysiological evidence, asserts that a balance between excitation and inhibition (E/I) is critical for healthy brain function. In magnetic resonance spectroscopy (MRS) studies, the ratio of excitatory (glutamate) and inhibitory (γ-aminobutyric acid, GABA) neurotransmitters is often used as a proxy for this E/I balance. Recent MRS work found a positive correlation between GABA+ and Glx (glutamate+glutamine) in medial parietal cortex, providing validation for this proxy and supporting the link between the E/I balance observed in electrophysiology and that detected with MRS. Here we assess the same relationship, between GABA+ and Glx, in visual and motor cortices of male and female human participants. We find moderate to strong evidence that there is no positive correlation between these neurotransmitters in either location. We show this holds true when controlling for a range of other factors (i.e., demographics, signal quality, tissue composition, other neurochemicals) and regardless of the state of neural activity (i.e., resting/active). These results show that there is no brain-wide balance between excitatory and inhibitory neurotransmitters and indicates a dissociation between the E/I balance observed in electrophysiological work and the ratio of MRS-detected neurotransmitters.

Comparison of methods for spectral alignment and signal modelling of GABA-edited MR spectroscopy data

Many methods exist for aligning and quantifying magnetic resonance spectroscopy (MRS) data to measure in vivo γ-aminobutyric acid (GABA). Research comparing the performance of these methods is scarce partly due to the lack of ground-truth measurements. The concentration of GABA is approximately two times higher in grey matter than in white matter. Here we use the proportion of grey matter within the MRS voxel as a proxy for ground-truth GABA concentration to compare the performance of four spectral alignment methods (i.e., retrospective frequency and phase drift correction) and six GABA signal modelling methods. We analyse a diverse dataset of 432 MEGA-PRESS scans targeting multiple brain regions and find that alignment to the creatine (Cr) signal produces GABA+ estimates that account for approximately twice as much of the variance in grey matter as the next best performing alignment method. Further, Cr alignment was the most robust, producing the fewest outliers. By contrast, all signal modelling methods, except for the single-Lorentzian model, performed similarly well. Our results suggest that variability in performance is primarily caused by differences in the zero-order phase estimated by each alignment method, rather than frequency, resulting from first-order phase offsets within subspectra. These results provide support for Cr alignment as the optimal method of processing MEGA-PRESS to quantify GABA. However, more broadly, they demonstrate a method of benchmarking quantification of in vivo metabolite concentration from other MRS sequences.

Advances in the computational understanding of mental illness

Computational psychiatry is a rapidly growing field attempting to translate advances in computational neuroscience and machine learning into improved outcomes for patients suffering from mental illness. It encompasses both data-driven and theory-driven efforts. Here, recent advances in theory-driven work are reviewed. We argue that the brain is a computational organ. As such, an understanding of the illnesses arising from it will require a computational framework. The review divides work up into three theoretical approaches that have deep mathematical connections: dynamical systems, Bayesian inference and reinforcement learning. We discuss both general and specific challenges for the field, and suggest ways forward.

Regional balance between glutamate+glutamine and GABA+ in the resting human brain

Models of healthy brain function and psychiatric conditions assume that excitatory and inhibitory activity are balanced in the human brain at multiple spatial and temporal scales. In human neuroimaging, concentrations of the major excitatory (glutamate) and inhibitory (γ-aminobutyric acid, GABA) neurotransmitters are measured in vivo using magnetic resonance spectroscopy (MRS). However, despite the central importance of E/I balance to theories of brain function, a relationship between regional glutamate and GABA levels in the human brain has not been shown. We addressed this question in a large corpus of edited MRS data collected at 19 different sites (n = 220). Consistent with the notion of E/I balance, we found that levels of glutamate+glutamine (Glx) and GABA+ were highly correlated (R = 0.52, p = 2.86 x 10⁻¹⁴). This relationship held when controlling for site, scanner vendor, and demographics. Controlling for neurochemicals associated with neuronal density and metabolism (i.e. N-acetylaspartate and creatine) significantly reduced the correlation between GABA+ and Glx, suggesting that the levels of GABA+ and Glx may be critically linked to regional metabolism. These results are consistent with the notion that excitation and inhibition are balanced in the human brain.

Temporal Dynamics of GABA and Glx in the Visual Cortex

Magnetic resonance spectroscopy (MRS) can be used in vivo to quantify neurometabolite concentration and provide evidence for the involvement of different neurotransmitter systems (e.g., inhibitory and excitatory) in sensory and cognitive processes. The relatively low signal-to-noise ratio of MRS measurements has shaped the types of questions that it has been used to address. In particular, temporal resolution is often sacrificed in MRS studies to achieve a signal sufficient to produce a reliable estimate of neurometabolite concentration. Here we apply novel analyses with large datasets from human participants (both sexes) to reveal the dynamics of GABA⁺ and Glx in visual cortex while participants are at rest (with eyes closed) and compare this with changes in posterior cingulate cortex from a previously collected dataset (under different conditions). We find that the dynamic concentration of GABA⁺ and Glx in visual cortex drifts in opposite directions; that is, GABA⁺ decreases while Glx increases over time. Further, we find that in visual, but not posterior cingulate cortex, the concentration of GABA⁺ predicts that of Glx 120 s later, such that a change in GABA⁺ is correlated with a subsequent opposite change in Glx. Together, these results expose novel temporal trends and interdependencies of primary neurotransmitters in visual cortex. More broadly, we demonstrate the feasibility of using MRS to investigate in vivo dynamic changes of neurometabolites.

A Conserved Tyrosine Residue in Slitrk3 Carboxyl-Terminus Is Critical for GABAergic Synapse Development

Single-passing transmembrane protein, Slitrk3 (Slit and Trk-like family member 3, ST3), is a synaptic cell adhesion molecule highly expressed at inhibitory synapses. Recent studies have shown that ST3, through its extracellular domain, selectively regulates inhibitory synapse development via the trans-synaptic interaction with presynaptic cell adhesion molecule, receptor protein tyrosine phosphatase δ (PTPδ) and the cis-interaction with postsynaptic cell adhesion molecule, Neuroligin 2 (NL2). However, little is known about the physiological function of ST3 intracellular, carboxyl (C)-terminal region. Here we report that in heterologous cells, ST3 C-terminus is not required for ST3 homo-dimerization and trafficking to the cell surface. In contrast, in hippocampal neurons, ST3 C-terminus, more specifically, the conserved tyrosine Y969 (in mice), is critical for GABAergic synapse development. Indeed, overexpression of ST3 Y969A mutant markedly reduced the gephyrin puncta density and GABAergic transmission in hippocampal neurons. In addition, single-cell genetic deletion of ST3 strongly impaired GABAergic transmission. Importantly, wild-type (WT) ST3, but not the ST3 Y969A mutant, could fully rescue GABAergic transmission deficits in neurons lacking endogenous ST3, confirming a critical role of Y969 in the regulation of inhibitory synapses. Taken together, our data identify a single critical residue in ST3 C-terminus that is important for GABAergic synapse development and function.

Dynamical modeling of multi-scale variability in neuronal competition

Variability is observed at multiple-scales in the brain and ubiquitous in perception. However, the nature of perceptual variability is an open question. We focus on variability during perceptual rivalry, a form of neuronal competition. Rivalry provides a window into neural processing since activity in many brain areas is correlated to the alternating perception rather than a constant ambiguous stimulus. It exhibits robust properties at multiple scales including conscious awareness and neuron dynamics. The prevalent theory for spiking variability is called the balanced state; whereas, the source of perceptual variability is unknown. Here we show that a single biophysical circuit model, satisfying certain mutual inhibition architectures, can explain spiking and perceptual variability during rivalry. These models adhere to a broad set of strict experimental constraints at multiple scales. As we show, the models predict how spiking and perceptual variability changes with stimulus conditions.

Biophysical Psychiatry-How Computational Neuroscience Can Help to Understand the Complex Mechanisms of Mental Disorders

The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a "biophysical psychiatry," an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field toward novel treatment options.

Motor cortex excitability and inhibitory imbalance in autism spectrum disorder assessed with transcranial magnetic stimulation: a systematic review

Cortical excitation/inhibition (E/I) imbalances contribute to various clinical symptoms observed in autism spectrum disorder (ASD). However, the detailed pathophysiologic underpinning of E/I imbalance remains uncertain. Transcranial magnetic stimulation (TMS) motor-evoked potentials (MEP) are a non-invasive tool for examining cortical inhibition in ASD. Here, we conducted a systematic review on TMS neurophysiology in motor cortex (M1) such as MEPs and short-interval intracortical inhibition (SICI) between individuals with ASD and controls. Out of 538 initial records, we identified six articles. Five studies measured MEP, where four studies measured SICI. There were no differences in MEP amplitudes between the two groups, whereas SICI was likely to be reduced in individuals with ASD compared with controls. Notably, SICI largely reflects GABA(A) receptor-mediated function. Conversely, other magnetic resonance spectroscopy and postmortem methodologies assess GABA levels. The present review demonstrated that there may be neurophysiological deficits in GABA receptor-mediated function in ASD. In conclusion, reduced GABAergic function in the neural circuits could underlie the E/I imbalance in ASD, which may be related to the pathophysiology of clinical symptoms of ASD. Therefore, a novel treatment that targets the neural circuits related to GABA(A) receptor-mediated function in regions involved in the pathophysiology of ASD may be promising.

Altered resting-state dynamics in autism spectrum disorder: Causal to the social impairment?

Autism spectrum disorder (ASD) is characterized by profound impairments in social abilities and by restricted interests and repetitive behaviors. Much work in the past decade has been dedicated to understanding the brain-bases of ASD, and in the context of resting-state functional connectivity fMRI in high-functioning adolescents and adults, the field has established a set of reliable findings: decreased cortico-cortical interactions among brain regions thought to be engaged in social processing, along with a simultaneous increase in thalamo-cortical and striato-cortical interactions. However, few studies have attempted to manipulate these altered patterns, leading to the question of whether such patterns are actually causally involved in producing the corresponding behavioral impairments. We discuss a few such recent attempts in the domains of fMRI neurofeedback and overt social interaction during scanning, and we conclude that the evidence of causal involvement is somewhat mixed. We highlight the potential role of the thalamus and striatum in ASD and emphasize the need for studies that directly compare scanning during multiple cognitive states in addition to the resting-state.

Clinical effectiveness of repetitive transcranial magnetic stimulation treatment in children and adolescents with neurodevelopmental disorders: A systematic review

Neurodevelopmental disorders, including autism spectrum disorder, are common in children and adolescents, but treatment strategies remain limited. Although repetitive transcranial magnetic stimulation has been studied for neurodevelopmental disorders, there is no clear consensus on its therapeutic effects. This systematic review examined literature on repetitive transcranial magnetic stimulation for children and adolescents with neurodevelopmental disorders published up to 2018 using the PubMed database. The search identified 264 articles and 14 articles met eligibility criteria. Twelve of these studies used conventional repetitive transcranial magnetic stimulation and two studies used theta burst stimulation. No severe adverse effects were reported in these studies. In patients with autism spectrum disorder, low-frequency repetitive transcranial magnetic stimulation and intermittent theta burst stimulation applied to the dorsolateral prefrontal cortex may have therapeutic effects on social functioning and repetitive behaviors. In patients with attention deficit/hyperactivity disorder, low-frequency repetitive transcranial magnetic stimulation applied to the left dorsolateral prefrontal cortex and high-frequency repetitive transcranial magnetic stimulation applied to the right dorsolateral prefrontal cortex may target inattention, hyperactivity, and impulsivity. In patients with tic disorders, low-frequency repetitive transcranial magnetic stimulation applied to the bilateral supplementary motor area improved tic symptom severity. This systematic review suggests that repetitive transcranial magnetic stimulation may be a promising intervention for children and adolescents with neurodevelopmental disorders. The results warrant further large randomized controlled trials of repetitive transcranial magnetic stimulation in children with neurodevelopmental disorders.

Functional MRI connectivity of children with autism and low verbal and cognitive performance

Background

Functional neuroimaging research in autism spectrum disorder has reported patterns of decreased long-range, within-network, and interhemispheric connectivity. Research has also reported increased corticostriatal connectivity and between-network connectivity for default and attentional networks. Past studies have excluded individuals with autism and low verbal and cognitive performance (LVCP), so connectivity in individuals more significantly affected with autism has not yet been studied. This represents a critical gap in our understanding of brain function across the autism spectrum.

Methods

Using behavioral support procedures adapted from Nordahl, et al. (J Neurodev Disord 8:20–20, 2016), we completed non-sedated structural and functional MRI scans of 56 children ages 7–17, including LVCP children (n = 17, mean IQ = 54), children with autism and higher performance (HVCP, n = 20, mean IQ = 106), and neurotypical children (NT, n = 19, mean IQ = 111). Preparation included detailed intake questionnaires, video modeling, behavioral and anxiety reduction techniques, active noise-canceling headphones, and in-scan presentation of the Inscapes movie paradigm from Vanderwal et al. (Neuroimage 122:222–32, 2015). A high temporal resolution multiband echoplanar fMRI protocol analyzed motion-free time series data, extracted from concatenated volumes to mitigate the influence of motion artifact. All participants had > 200 volumes of motion-free fMRI scanning. Analyses were corrected for multiple comparisons.

Results

LVCP showed decreased within-network connectivity in default, salience, auditory, and frontoparietal networks (LVCP < HVCP) and decreased interhemispheric connectivity (LVCP < HVCP=NT). Between-network connectivity was higher for LVCP than NT between default and dorsal attention and frontoparietal networks. Lower IQ was associated with decreased connectivity within the default network and increased connectivity between default and dorsal attention networks.

Conclusions

This study demonstrates that with moderate levels of support, including readily available techniques, information about brain similarities and differences in LVCP individuals can be further studied. This initial study suggested decreased network segmentation and integration in LVCP individuals. Further imaging studies of LVCP individuals with larger samples will add to understanding of origins and effects of autism on brain function and behavior.

Electronic supplementary material

The online version of this article (10.1186/s13229-018-0248-y) contains supplementary material, which is available to authorized users.

Imbalance of Functional Connectivity and Temporal Entropy in Resting-State Networks in Autism Spectrum Disorder: A Machine Learning Approach

Background: Two approaches to understanding the etiology of neurodevelopmental disorders such as Autism Spectrum Disorder (ASD) involve network level functional connectivity (FC) and the dynamics of neuronal signaling. The former approach has revealed both increased and decreased FC in individuals with ASD. The latter approach has found high frequency EEG oscillations and higher levels of epilepsy in children with ASD. Together, these findings have led to the hypothesis that atypical excitatory-inhibitory neural signaling may lead to imbalanced association pathways. However, simultaneously reconciling local temporal dynamics with network scale spatial connectivity remains a difficult task and thus empirical support for this hypothesis is lacking. Methods: We seek to fill this gap by combining two powerful resting-state functional MRI (rs-fMRI) methods-functional connectivity (FC) and wavelet-based regularity analysis. Wavelet-based regularity analysis is an entropy measure of the local rs-fMRI time series signal. We examined the relationship between the RSN entropy and integrity in individuals with ASD and controls from the Autism Brain Imaging Data Exchange (ABIDE) cohort using a putative set of 264 functional brain regions-of-interest (ROI). Results: We observed that an imbalance in intra- and inter-network FC across 11 RSNs in ASD individuals (p = 0.002) corresponds to a weakened relationship with RSN temporal entropy (p = 0.02). Further, we observed that an estimated RSN entropy model significantly distinguished ASD from controls (p = 0.01) and was associated with level of ASD symptom severity (p = 0.003). Conclusions: Imbalanced brain connectivity and dynamics at the network level coincides with their decoupling in ASD. The association with ASD symptom severity presents entropy as a potential biomarker.

Evaluation of Differences in Temporal Synchrony Between Brain Regions in Individuals With Autism and Typical Development

IMPORTANCE

Despite reports of widespread but heterogeneous atypicality of functional connectivity in individuals with autism, little is known regarding the temporal dynamics of functional brain connections and how they relate to autistic traits.

OBJECTIVE

To investigate differences in temporal synchrony between brain regions in individuals with autism and those with typical development.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study, conducted at the University of Utah, included 90 adolescent and adult male participants. A larger sample from the multisite Autism Brain Imaging Data Exchange (ABIDE) was also used as a replication sample. The study includes data acquired between December 2016 and April 2018. Aggregate data included in the replication sample were released to the public in August 2012 (ABIDE I) and June 2016 (ABIDE II). Data analysis were conducted between January 2018 and April 2018.

EXPOSURES

Male individuals diagnosed as having autism (n = 52) and typically developing male individuals (n = 38).

MAIN OUTCOMES AND MEASURES

Long duration (30 minutes/individual) of multiband, multiecho functional magnetic resonance imaging was acquired to estimate functional connectivity between brain regions. Sustained connectivity, a measure of functional connectivity duration, as well as lagged temporal dynamics related to functional connectivity, were compared between groups for 361 gray matter regions of interest and a 17-network parcellation. Lagged findings were replicated in the larger ABIDE sample (n = 1402). Sustained connectivity findings were also associated with behavioral and cognitive variables.

RESULTS

In 52 males with autism (mean [SD] age, 27.73 [8.66] years) and 38 control males with typical development (mean [SD] age, 27.09 [7.49] years), increases in both sustained and functional connectivity at several lags were found in individuals with autism compared with the control group. Group differences in functional connectivity were replicated in the larger ABIDE data set at a 6-second lag. Measures of symptom severity in individuals with autism were positively associated with sustained connectivity values. In the control group, sustained connectivity was negatively associated with cognitive processing. A replication sample (n = 1402) composed of 579 individuals with autism (80 female and 499 male; mean [SD] age, 15.08 [6.89] years) and 823 in the control group (211 female and 612 male; mean [SD] age, 15.06 [6.79] years) from the ABIDE data set was also analyzed.

CONCLUSIONS AND RELEVANCE

Whereas the magnitude of functional connectivity in autism is variable across brain regions, participant samples, and development, prolonged temporal synchrony of functional connections is reproducibly observed in autism, suggesting a potential mechanism for core symptoms.

Biomarkers for detection, prognosis and therapeutic assessment of neurological disorders

Neurological disorders have aroused a significant concern among the health scientists globally, as diseases such as Parkinson's, Alzheimer's and dementia lead to disability and people have to live with them throughout the life. Recent evidence suggests that a number of environmental chemicals such as pesticides (paraquat) and metals (lead and aluminum) are also the cause of these diseases and other neurological disorders. Biomarkers can help in detecting the disorder at the preclinical stage, progression of the disease and key metabolomic alterations permitting identification of potential targets for intervention. A number of biomarkers have been proposed for some neurological disorders based on laboratory and clinical studies. In silico approaches have also been used by some investigators. Yet the ideal biomarker, which can help in early detection and follow-up on treatment and identifying the susceptible populations, is not available. An attempt has therefore been made to review the recent advancements of in silico approaches for discovery of biomarkers and their validation. In silico techniques implemented with multi-omics approaches have potential to provide a fast and accurate approach to identify novel biomarkers.

Autistic Traits Are Not a Strong Predictor of Binocular Rivalry Dynamics

It has been suggested that differences in binocular rivalry switching rates and mixed percept durations in ASD could serve as a biomarker of excitation/inhibition imbalances in the autistic brain. If so, one would expect these differences to extend to neurotypical groups with high vs. low levels of autistic tendency. Previous studies did not detect any correlations between binocular rivalry dynamics and Autism Spectrum Quotient (AQ) scores in neurotypical control groups; however it is unclear whether this was due to the characteristics of the rivalry stimuli that were used. We further investigated this possibility in a sample of neurotypical young adults. The binocular rivalry stimuli were simple gratings, complex objects, or scrambled objects, which were presented dichoptically, either at fixation or in the periphery. A Bayesian correlation analysis showed that individuals with higher AQ scores tended to have lower perceptual switching rates for the centrally presented, simple grating rival stimuli. However, there was no evidence of a relationship between AQ and switching rates, reversal rates or mixed percept durations for any of the other binocular rivalry conditions. Overall, our findings suggest that in the non-clinical population, autistic personality traits are not a strong predictor of binocular rivalry dynamics.

Vision in children with autism spectrum disorder: a critical review

Autism spectrum disorder (ASD) is a common neurodevelopmental condition with approximately 1-2 per cent prevalence in the population. The condition has lifelong effects for the individual and family, and early intervention and management helps maximise quality of life and outcomes. Many studies of vision in ASD have attempted to link the behavioural and sensory deficits in ASD with underlying visual processing. From this work, it is clear that individuals with ASD 'see' and process the world differently, but there remain gaps in our understanding. This review will summarise our current knowledge of key aspects of visual functions and the optometric profile of ASD. This includes findings regarding visual acuity and contrast sensitivity, refractive error, eye movements, binocular vision, near visual functions and retinal structure in ASD. From this, a pattern of knowledge emerges for children with ASD: we should expect normal visual acuity; there will likely be atypical eye movements and susceptibility for subtle visuo-motor deficits, there is an increased prevalence of strabismus; an increased likelihood of astigmatism and possibly other refractive errors; attention, crowding and task complexity will likely be problematic; and retinal structure and function may be compromised. Bringing this together, these findings highlight that further work is necessary, not only to understand how higher-level functions link to behaviours, but also to ensure there is a sound understanding of the building-blocks of vision to fully grasp the profile of visual processing as a whole in ASD. This review will give a translational viewpoint for clinicians, and underline the benefits of comprehensive vision care in ASD.

Enriched expression of genes associated with autism spectrum disorders in human inhibitory neurons

Autism spectrum disorder (ASD) is highly heritable but genetically heterogeneous. The affected neural circuits and cell types remain unclear and may vary at different developmental stages. By analyzing multiple sets of human single cell transcriptome profiles, we found that ASD candidates showed relatively enriched gene expression in neurons, especially in inhibitory neurons. ASD candidates were also more likely to be the hubs of the co-expression gene module that is highly expressed in inhibitory neurons, a feature not detected for excitatory neurons. In addition, we found that upregulated genes in multiple ASD cortex samples were enriched with genes highly expressed in inhibitory neurons, suggesting a potential increase of inhibitory neurons and an imbalance in the ratio between excitatory and inhibitory neurons in ASD brains. Furthermore, the downstream targets of several ASD candidates, such as CHD8, EHMT1 and SATB2, also displayed enriched expression in inhibitory neurons. Taken together, our analyses of single cell transcriptomic data suggest that inhibitory neurons may be a major neuron subtype affected by the disruption of ASD gene networks, providing single cell functional evidence to support the excitatory/inhibitory (E/I) imbalance hypothesis.

A model of individualized canonical microcircuits supporting cognitive operations

Major cognitive functions such as language, memory, and decision-making are thought to rely on distributed networks of a large number of basic elements, called canonical microcircuits. In this theoretical study we propose a novel canonical microcircuit model and find that it supports two basic computational operations: a gating mechanism and working memory. By means of bifurcation analysis we systematically investigate the dynamical behavior of the canonical microcircuit with respect to parameters that govern the local network balance, that is, the relationship between excitation and inhibition, and key intrinsic feedback architectures of canonical microcircuits. We relate the local behavior of the canonical microcircuit to cognitive processing and demonstrate how a network of interacting canonical microcircuits enables the establishment of spatiotemporal sequences in the context of syntax parsing during sentence comprehension. This study provides a framework for using individualized canonical microcircuits for the construction of biologically realistic networks supporting cognitive operations.

Differences in change blindness to real-life scenes in adults with autism spectrum conditions

People often fail to detect large changes to visual scenes following a brief interruption, an effect known as ‘change blindness’. People with autism spectrum conditions (ASC) have superior attention to detail and better discrimination of targets, and often notice small details that are missed by others. Together these predict people with autism should show enhanced perception of changes in simple change detection paradigms, including reduced change blindness. However, change blindness studies to date have reported mixed results in ASC, which have sometimes included no differences to controls or even enhanced change blindness. Attenuated change blindness has only been reported to date in ASC in children and adolescents, with no study reporting reduced change blindness in adults with ASC. The present study used a change blindness flicker task to investigate the detection of changes in images of everyday life in adults with ASC (n = 22) and controls (n = 22) using a simple change detection task design and full range of original scenes as stimuli. Results showed the adults with ASC had reduced change blindness compared to adult controls for changes to items of marginal interest in scenes, with no group difference for changes to items of central interest. There were no group differences in overall response latencies to correctly detect changes nor in the overall number of missed detections in the experiment. However, the ASC group showed greater missed changes for marginal interest changes of location, showing some evidence of greater change blindness as well. These findings show both reduced change blindness to marginal interest changes in ASC, based on response latencies, as well as greater change blindness to changes of location of marginal interest items, based on detection rates. The findings of reduced change blindness are consistent with clinical reports that people with ASC often notice small changes to less salient items within their environment, and are in-line with theories of enhanced local processing and greater attention to detail in ASC. The findings of lower detection rates for one of the marginal interest conditions may be related to problems in shifting attention or an overly focused attention spotlight.

Sensory perception in autism

Autism is a complex neurodevelopmental condition, and little is known about its neurobiology. Much of autism research has focused on the social, communication and cognitive difficulties associated with the condition. However, the recent revision of the diagnostic criteria for autism has brought another key domain of autistic experience into focus: sensory processing. Here, we review the properties of sensory processing in autism and discuss recent computational and neurobiological insights arising from attention to these behaviours. We argue that sensory traits have important implications for the development of animal and computational models of the condition. Finally, we consider how difficulties in sensory processing may relate to the other domains of behaviour that characterize autism.

The Default Mode Network in Autism

Autism spectrum disorder (ASD) is characterized by deficits in social communication and interaction. Since its discovery as a major functional brain system, the default mode network (DMN) has been implicated in a number of psychiatric disorders, including ASD. Here we review converging multimodal evidence for DMN dysfunction in the context of specific components of social cognitive dysfunction in ASD: 'self-referential processing' - the ability to process social information relative to oneself and 'theory of mind' or 'mentalizing' - the ability to infer the mental states such as beliefs, intentions, and emotions of others. We show that altered functional and structural organization of the DMN, and its atypical developmental trajectory, are prominent neurobiological features of ASD. We integrate findings on atypical cytoarchitectonic organization and imbalance in excitatory-inhibitory circuits, which alter local and global brain signaling, to scrutinize putative mechanisms underlying DMN dysfunction in ASD. Our synthesis of the extant literature suggests that aberrancies in key nodes of the DMN and their dynamic functional interactions contribute to atypical integration of information about the self in relation to 'other', as well as impairments in the ability to flexibly attend to socially relevant stimuli. We conclude by highlighting open questions for future research.

Vision as a Beachhead

When neural circuits develop abnormally due to different genetic deficits and/or environmental insults, neural computations and the behaviors that rely on them are altered. Computational theories that relate neural circuits with specific quantifiable behavioral and physiological phenomena, therefore, serve as extremely useful tools for elucidating the neuropathological mechanisms that underlie different disorders. The visual system is particularly well suited for characterizing differences in neural computations; computational theories of vision are well established, and empirical protocols for measuring the parameters of those theories are well developed. In this article, we examine how psychophysical and neuroimaging measurements from human subjects are being used to test hypotheses about abnormal neural computations in autism, with an emphasis on hypotheses regarding potential excitation/inhibition imbalances. We discuss the complexity of relating specific computational abnormalities to particular underlying mechanisms given the diversity of neural circuits that can generate the same computation, and we discuss areas of research in which computational theories need to be further developed to provide useful frameworks for interpreting existing results. A final emphasis is placed on the need to extend existing ideas into developmental frameworks that take into account the dramatic developmental changes in neurophysiology (e.g., changes in excitation/inhibition balance) that take place during the first years of life, when autism initially emerges.

Aberrant Oscillatory Synchrony Is Biased Toward Specific Frequencies and Processing Domains in the Autistic Brain

BACKGROUND

Prevailing theories suggest that autism spectrum disorder (ASD) results from impaired brain communication, causing aberrant synchrony among neuronal populations. However, it remains debated whether synchrony abnormalities are among local or long-range circuits, are circuit specific or are generalized, reflect hypersynchrony or reflect hyposynchrony, and are frequency band-specific or are distributed across the frequency spectrum.

METHODS

To help clarify these unresolved questions, we recorded spontaneous magnetoencephalography data and used a data-driven, whole-brain analysis of frequency-specific interregional synchrony in higher-functioning adolescents and adults, with 17 ASD and 18 control subjects matched on age, IQ, and sex, and equal for motion.

RESULTS

Individuals with ASD showed local hypersynchrony in the theta band (4-7 Hz) in the lateral occipitotemporal cortex. Long-range hyposynchrony was seen in the alpha band (10-13 Hz), which was most prominent in neural circuitry underpinning social processing. The magnitude of this alpha band hyposynchrony was correlated with social symptom severity.

CONCLUSIONS

These results suggest that although ASD is associated with both decreased long-range synchrony and increased posterior local synchrony, with each effect limited to a specific frequency band, impairments in social functioning may be most related to decreased alpha band synchronization between critical nodes of the social processing network.

Binocular rivalry in children on the autism spectrum

When different images are presented to the eyes, the brain is faced with ambiguity, causing perceptual bistability: visual perception continuously alternates between the monocular images, a phenomenon called binocular rivalry. Many models of rivalry suggest that its temporal dynamics depend on mutual inhibition among neurons representing competing images. These models predict that rivalry should be different in autism, which has been proposed to present an atypical ratio of excitation and inhibition [the E/I imbalance hypothesis; Rubenstein & Merzenich, 2003]. In line with this prediction, some recent studies have provided evidence for atypical binocular rivalry dynamics in autistic adults. In this study, we examined if these findings generalize to autistic children. We developed a child‐friendly binocular rivalry paradigm, which included two types of stimuli, low‐ and high‐complexity, and compared rivalry dynamics in groups of autistic and age‐ and intellectual ability‐matched typical children. Unexpectedly, the two groups of children presented the same number of perceptual transitions and the same mean phase durations (times perceiving one of the two stimuli). Yet autistic children reported mixed percepts for a shorter proportion of time (a difference which was in the opposite direction to previous adult studies), while elevated autistic symptomatology was associated with shorter mixed perception periods. Rivalry in the two groups was affected similarly by stimulus type, and consistent with previous findings. Our results suggest that rivalry dynamics are differentially affected in adults and developing autistic children and could be accounted for by hierarchical models of binocular rivalry, including both inhibition and top‐down influences. Autism Res2017. ©2017 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research Autism Res 2017, 10: 1096–1106. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Differential sensory fMRI signatures in autism and schizophrenia: Analysis of amplitude and trial-to-trial variability

Autism and schizophrenia share multiple phenotypic and genotypic markers, and there is ongoing debate regarding the relationship of these two disorders. To examine whether cortical dynamics are similar across these disorders, we directly compared fMRI responses to visual, somatosensory and auditory stimuli in adults with autism (N=15), with schizophrenia (N=15), and matched controls (N=15). All participants completed a one-back letter detection task presented at fixation (to control attention) while task-irrelevant sensory stimulation was delivered to the different modalities. We focused specifically on the response amplitudes and the variability in sensory fMRI responses of the two groups, given the evidence of greater trial-to-trial variability in adults with autism. Both autism and schizophrenia individuals showed weaker signal-to-noise ratios (SNR) in sensory-evoked responses compared to controls (d>0.42), but for different reasons. For the autism group, the fMRI response amplitudes were indistinguishable from controls but were more variable trial-to-trial (d=0.47). For the schizophrenia group, response amplitudes were smaller compared to autism (d=0.44) and control groups (d=0.74), but were not significantly more variable (d<0.29). These differential group profiles suggest (1) that greater trial-to-trial variability in cortical responses may be specific to autism and is not a defining characteristic of schizophrenia, and (2) that blunted response amplitudes may be characteristic of schizophrenia. The relationship between the amplitude and the variability of cortical activity might serve as a specific signature differentiating these neurodevelopmental disorders. Identifying the neural basis of these responses and their relationship to the underlying genetic bases may substantially enlighten the understanding of both disorders.

Genetic variants in Alzheimer disease - molecular and brain network approaches

Genetic studies in late-onset Alzheimer disease (LOAD) are aimed at identifying core disease mechanisms and providing potential biomarkers and drug candidates to improve clinical care of AD. However, owing to the complexity of LOAD, including pathological heterogeneity and disease polygenicity, extraction of actionable guidance from LOAD genetics has been challenging. Past attempts to summarize the effects of LOAD-associated genetic variants have used pathway analysis and collections of small-scale experiments to hypothesize functional convergence across several variants. In this Review, we discuss how the study of molecular, cellular and brain networks provides additional information on the effects of LOAD-associated genetic variants. We then discuss emerging combinations of these omic data sets into multiscale models, which provide a more comprehensive representation of the effects of LOAD-associated genetic variants at multiple biophysical scales. Furthermore, we highlight the clinical potential of mechanistically coupling genetic variants and disease phenotypes with multiscale brain models.

Restoration of Mecp2 expression in GABAergic neurons is sufficient to rescue multiple disease features in a mouse model of Rett syndrome

The postnatal neurodevelopmental disorder Rett syndrome, caused by mutations in MECP2, produces a diverse array of symptoms, including loss of language, motor, and social skills and the development of hand stereotypies, anxiety, tremor, ataxia, respiratory dysrhythmias, and seizures. Surprisingly, despite the diversity of these features, we have found that deleting Mecp2 only from GABAergic inhibitory neurons in mice replicates most of this phenotype. Here we show that genetically restoring Mecp2 expression only in GABAergic neurons of male Mecp2 null mice enhanced inhibitory signaling, extended lifespan, and rescued ataxia, apraxia, and social abnormalities but did not rescue tremor or anxiety. Female Mecp2^+/- mice showed a less dramatic but still substantial rescue. These findings highlight the critical regulatory role of GABAergic neurons in certain behaviors and suggest that modulating the excitatory/inhibitory balance through GABAergic neurons could prove a viable therapeutic option in Rett syndrome.

DOI:http://dx.doi.org/10.7554/eLife.14198.001

Rett syndrome is a childhood brain disorder that mainly affects girls and causes symptoms including anxiety, tremors, uncoordinated movements and breathing difficulties. Rett syndrome is caused by mutations in a gene called MECP2, which is found on the X chromosome. Males with MECP2 mutations are rare but have more severe symptoms and die young. Many researchers who study Rett syndrome use mice as a model of the disorder. In particular, male mice with the mouse equivalent of the human MECP2 gene switched off in every cell in the body (also known as Mecp2-null mice) show many of the features of Rett syndrome and die at a young age.

The MECP2 gene is important for healthy brain activity. The brain contains two major types of neurons: excitatory neurons, which encourage other neurons to be active; and inhibitory neurons, which stop or dampen the activity of other neurons. In 2010, researchers reported that mice lacking Mecp2 in only their inhibitory neurons develop most of the same problems as those mice with no Mecp2 at all. This discovery led Ure et al. – including a researcher involved in the 2010 study – to ask if activating Mecp2 in the same neurons in otherwise Mecp2-null mice was enough to prevent some of their Rett syndrome-like symptoms.

The experiments showed that male mice that only have Mecp2 activated in their inhibitory neurons lived several months longer than male Mecp2-null mice. These male “rescue mice” also moved normally and had a normal body weight, though they still experienced anxiety, tremors and breathing difficulties. Female mice represent a better model of human Rett syndrome patients, and Ure et al. found that female rescue mice showed smaller improvements than the males.

These data suggest that when a brain is missing Mecp2 everywhere, as in male Mecp2-null mice, turning on Mecp2 in inhibitory neurons can make the brain network nearly normal and prevent most Rett-syndrome-like symptoms. However, the brains of female rescue mice contain both normal cells and cells with mutated Mecp2. This mixture of normal and abnormal cells appears to cause abnormalities that cannot be overcome by rescuing just the activity of the inhibitory neurons. These findings also highlight the importance of doing future studies in female mice to better understand the development of Rett syndrome.

The next challenge is to test different ways of activating the inhibitory neurons in the female mouse brain, for example by using drugs that target these neurons. It is hoped these methods will help researchers to refine a path toward potential new treatments for Rett syndrome patients. Finally, in a related study, Meng et al. asked how deleting or activating Mecp2 only in the excitatory neurons of mice affected Rett-syndrome-like symptoms.

DOI:http://dx.doi.org/10.7554/eLife.14198.002

Synaptic Wnt/GSK3β Signaling Hub in Autism

Hundreds of genes have been associated with autism spectrum disorders (ASDs) and the interaction of weak and de novo variants derive from distinct autistic phenotypes thus making up the “spectrum.” The convergence of these variants in networks of genes associated with synaptic function warrants the study of cell signaling pathways involved in the regulation of the synapse. The Wnt/β-catenin signaling pathway plays a central role in the development and regulation of the central nervous system and several genes belonging to the cascade have been genetically associated with ASDs. In the present paper, we review basic information regarding the role of Wnt/β-catenin signaling in excitatory/inhibitory balance (E/I balance) through the regulation of pre- and postsynaptic compartments. Furthermore, we integrate information supporting the role of the glycogen synthase kinase 3β (GSK3β) in the onset/development of ASDs through direct modulation of Wnt/β-catenin signaling. Finally, given GSK3β activity as key modulator of synaptic plasticity, we explore the potential of this kinase as a therapeutic target for ASD.

Reduced perceptual exclusivity during object and grating rivalry in autism

The dynamics of binocular rivalry may be a behavioral footprint of excitatory and inhibitory neural transmission in visual cortex. Given the presence of atypical visual features in Autism Spectrum Conditions (ASC), and the growing evidence in support of the idea of an imbalance in excitatory/inhibitory neural transmission in animal and genetic models of ASC, we hypothesized that binocular rivalry might prove a simple behavioral marker of such a transmission imbalance in the autistic brain. In support of this hypothesis, we previously reported a slower rate of rivalry in ASC, driven by longer transitional states between dominant percepts. We tested whether atypical dynamics of binocular rivalry in ASC are specific to certain stimulus features. 53 participants (26 with ASC, matched for age, sex, and IQ) participated in a binocular rivalry experiment in which the dynamics of rivalry were measured at two levels of stimulus complexity, low (grayscale gratings) and high (colored objects). Individuals with ASC experienced a slower rate of binocular rivalry, driven by longer transitional states between dominant percepts. These exaggerated transitional states were present at both low and high levels of stimulus complexity (gratings and objects), suggesting that atypical binocular dynamics in autism are robust with respect to stimulus choice. Interactions between stimulus properties and rivalry dynamics in autism indicate that achromatic grating stimuli produce stronger group differences. These results confirm the finding of atypical dynamics of binocular rivalry in ASC. These dynamics were present for stimuli of both low and high levels of visual complexity, suggesting a pervasive imbalance in competitive interactions throughout the visual system of individuals with ASC.

Cortical variability in the sensory-evoked response in autism

Previous findings have shown that individuals with autism spectrum disorder (ASD) evince greater intra-individual variability (IIV) in their sensory-evoked fMRI responses compared to typical control participants. We explore the robustness of this finding with a new sample of high-functioning adults with autism. Participants were presented with visual, somatosensory and auditory stimuli in the scanner whilst they completed a one-back task. While ASD and control participants were statistically indistinguishable with respect to behavioral responses, the new ASD group exhibited greater IIV relative to controls. We also show that the IIV was equivalent across hemispheres and remained stable over the duration of the experiment. This suggests that greater cortical IIV may be a replicable characteristic of sensory systems in autism.

Mouse pups lacking collapsin response mediator protein 4 manifest impaired olfactory function and hyperactivity in the olfactory bulb

Members of the collapsin response mediator protein (CRMP) family are reported to be involved in the pathogenesis of various neuronal disorders, including schizophrenia and autism. One of them, CRMP4, is reported to participate in aspects of neuronal development, such as axonal guidance and dendritic development. However, no physiological or behavioral phenotypes in Crmp4 knockout (Crmp4-KO) mice have been identified, making it difficult to elucidate the in vivo roles of CRMP4. Focusing on the olfaction process because of the previous study showing strong expression of Crmp4 mRNA in the olfactory bulb (OB) during the early postnatal period, it was aimed to test the hypothesis that Crmp4-KO pups would exhibit abnormal olfaction. Based on measurements of their ultrasonic vocalizations, impaired olfactory ability in Crmp4-KO pups was found. In addition, c-Fos expression, a marker of neuron activity, revealed hyperactivity in the OB of Crmp4-KO pups compared with wild-types following exposure to an odorant. Moreover, the mRNA and protein expression levels of glutamate receptor 1 (GluR1) and 2 (GluR2) were exaggerated in Crmp4-KO pups relative to other excitatory and inhibitory receptors and transporters, raising the possibility that enhanced expression of these excitatory receptors contributes to the hyperactivity phenotype and impairs olfactory ability. This study provides evidence for an animal model for elucidating the roles of CRMP4 in the development of higher brain functions as well as for elucidating the developmental regulatory mechanisms controlling the activity of the neural circuitry.

Social Behavioral Deficits Coincide with the Onset of Seizure Susceptibility in Mice Lacking Serotonin Receptor 2c

The development of social behavior is strongly influenced by the serotonin system. Serotonin 2c receptor (5-HT_2cR) is particularly interesting in this context considering that pharmacological modulation of 5-HT_2cR activity alters social interaction in adult rodents. However, the role of 5-HT_2cR in the development of social behavior is unexplored. Here we address this using Htr2c knockout mice, which lack 5-HT_2cR. We found that these animals exhibit social behavior deficits as adults but not as juveniles. Moreover, we found that the age of onset of these deficits displays similar timing as the onset of susceptibility to spontaneous death and audiogenic-seizures, consistent with the hypothesis that imbalanced excitation and inhibition (E/I) may contribute to social behavioral deficits. Given that autism spectrum disorder (ASD) features social behavioral deficits and is often co-morbid with epilepsy, and given that 5-HT_2cR physically interacts with Pten, we tested whether a second site mutation in the ASD risk gene Pten can modify these phenotypes. The age of spontaneous death is accelerated in mice double mutant for Pten and Htr2c relative to single mutants. We hypothesized that pharmacological antagonism of 5-HT_2cR activity in adult animals, which does not cause seizures, might modify social behavioral deficits in Pten haploinsufficient mice. SB 242084, a 5-HT_2cR selective antagonist, can reverse the social behavior deficits observed in Pten haploinsufficient mice. Together, these results elucidate a role of 5-HT_2cR in the modulation of social behavior and seizure susceptibility in the context of normal development and Pten haploinsufficiency.

Multifactoriality in Psychiatric Disorders: A Computational Study of Schizophrenia

The search for biological causes of mental disorders has up to now met with limited success, leading to growing dissatisfaction with diagnostic classifications. However, it is questionable whether most clinical syndromes should be expected to correspond to specific microscale brain alterations, as multiple low-level causes could lead to similar symptoms in different individuals. In order to evaluate the potential multifactoriality of alterations related to psychiatric illness, we performed a parametric exploration of published computational models of schizophrenia. By varying multiple parameters simultaneously, such as receptor conductances, connectivity patterns, and background excitation, we generated 5625 different versions of an attractor-based network model of schizophrenia symptoms. Among networks presenting activity within valid ranges, 154 parameter combinations out of 3002 (5.1%) presented a phenotype reminiscent of schizophrenia symptoms as defined in the original publication. We repeated this analysis in a model of schizophrenia-related deficits in spatial working memory, building 3125 different networks, and found that 41 (4.9%) out of 834 networks with valid activity presented schizophrenia-like alterations. In isolation, none of the parameters in either model showed adequate sensitivity or specificity to identify schizophrenia-like networks. Thus, in computational models of schizophrenia, even simple network phenotypes related to the disorder can be produced by a myriad of causes at the molecular and circuit levels. This suggests that unified explanations for either the full syndrome or its behavioral and network endophenotypes are unlikely to be expected at the genetic and molecular levels.

Modeling possible effects of atypical cerebellar processing on eyeblink conditioning in autism

Autism is unique among other disorders in that acquisition of conditioned eyeblink responses is enhanced in children, occurring in a fraction of the trials required for control participants. The timing of learned responses is, however, atypical. Two animal models of autism display a similar phenotype. Researchers have hypothesized that these differences in conditioning reflect cerebellar abnormalities. The present study used computer simulations of the cerebellar cortex, including inhibition by the molecular layer interneurons, to more closely examine whether atypical cerebellar processing can account for faster conditioning in individuals with autism. In particular, the effects of inhibitory levels on delay eyeblink conditioning were simulated, as were the effects of learning-related synaptic changes at either parallel fibers or ascending branch synapses from granule cells to Purkinje cells. Results from these simulations predict that whether molecular layer inhibition results in an enhancement or an impairment of acquisition, or changes in timing, may depend on (1) the sources of inhibition, (2) the levels of inhibition, and (3) the locations of learning-related changes (parallel vs. ascending branch synapses). Overall, the simulations predict that a disruption in the balance or an overall increase of inhibition within the cerebellar cortex may contribute to atypical eyeblink conditioning in children with autism and in animal models of autism.

Orientation-specific surround suppression in the primary visual cortex varies as a function of autistic tendency

Individuals with autism spectrum disorder (ASD) exhibit superior performance on tasks that rely on local details in an image, and they exhibit deficits in tasks that require integration of local elements into a unified whole. These perceptual abnormalities have been proposed to underlie many of the characteristic features of ASD, but the underlying neural mechanisms are poorly understood. Here, we investigated the degree to which orientation-specific surround suppression, a well-known form of contextual modulation in visual cortex, is associated with autistic tendency in neurotypical (NT) individuals. Surround suppression refers to the phenomenon that the response to a stimulus in the receptive field of a neuron is suppressed when it is surrounded by stimuli just outside the receptive field. The suppression is greatest when the center and surrounding stimuli share perceptual features such as orientation. Surround suppression underlies a number of fundamental perceptual processes that are known to be atypical in individuals with ASD, including perceptual grouping and perceptual pop-out. However, whether surround suppression in the primary visual cortex (V1) is related to autistic traits has not been directly tested before. We used fMRI to measure the neural response to a center Gabor when it was surrounded by Gabors having the same or orthogonal orientation, and calculated a suppression index (SI) for each participant that denoted the magnitude of suppression in the same vs. orthogonal conditions. SI was positively correlated with degree of autistic tendency in each individual, as measured by the Autism Quotient (AQ) scale, a questionnaire designed to assess autistic traits in the general population. Age also correlated with SI and with autistic tendency in our sample, but did not account for the correlation between SI and autistic tendency. These results suggest a reduction in orientation-specific surround suppression in V1 with increasing autistic tendency.

Autism-specific covariation in perceptual performances: "g" or "p" factor?

Background

Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination) and mid-level (e.g., pattern matching) tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals.

Methods

We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ) and Raven Progressive Matrices (RPM). We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence.

Results

In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism.

Conclusions

Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or “g” factor). Instead, this residual covariation is accounted for by a common perceptual process (or “p” factor), which may drive perceptual abilities differently in autistic and non-autistic individuals.