Slower Binocular Rivalry in the Autistic Brain

Reviving Bistable Perception in Patients With Depression by Decreasing the Overestimation of Prior Precision

Slower perceptual alternations, a notable perceptual effect observed in psychiatric disorders, can be alleviated by antidepressant therapies that affect serotonin levels in the brain. While these phenomena have been well documented, the underlying neurocognitive mechanisms remain to be elucidated. Our study bridges this gap by employing a computational cognitive approach within a Bayesian predictive coding framework to explore these mechanisms in depression. We fitted a prediction error (PE) model to behavioral data from a binocular rivalry task, uncovering that significantly higher initial prior precision and lower PE led to a slower switch rate in patients with depression. Furthermore, serotonin-targeting antidepressant treatments significantly decreased the prior precision and increased PE, both of which were predictive of improvements in the perceptual alternation rate of depression patients. These findings indicated that the substantially slower perception switch rate in patients with depression was caused by the greater reliance on top-down priors and that serotonin treatment's efficacy was in its recalibration of these priors and enhancement of PE. Our study not only elucidates the cognitive underpinnings of depression, but also suggests computational modeling as a potent tool for integrating cognitive science with clinical psychology, advancing our understanding and treatment of cognitive impairments in depression.

Tug-of-Peace: Visual Rivalry and Atypical Visual Motion Processing in MECP2 Duplication Syndrome of Autism

Extracting common patterns of neural circuit computations in the autism spectrum and confirming them as a cause of specific core traits of autism is the first step toward identifying cell-level and circuit-level targets for effective clinical intervention. Studies in humans with autism have identified functional links and common anatomic substrates between core restricted behavioral repertoire, cognitive rigidity, and overstability of visual percepts during visual rivalry. To study these processes with single-cell precision and comprehensive neuronal population coverage, we developed the visual bistable perception paradigm for mice based on ambiguous moving plaid patterns consisting of two transparent gratings drifting at an angle of 120°. This results in spontaneous reversals of the perception between local component motion (plaid perceived as two separate moving grating components) and integrated global pattern motion (plaid perceived as a fused moving texture). This robust paradigm does not depend on the explicit report of the mouse, since the direction of the optokinetic nystagmus (OKN) is used to infer the dominant percept. Using this paradigm, we found that the rate of perceptual reversals between global and local motion interpretations is reduced in the methyl-CpG-binding protein 2 duplication syndrome (MECP2-ds) mouse model of autism. Moreover, the stability of local motion percepts is greatly increased in MECP2-ds mice at the expense of global motion percepts. Thus, our model reproduces a subclass of the core features in human autism (reduced rate of visual rivalry and atypical perception of visual motion). This further offers a well-controlled approach for dissecting neuronal circuits underlying these core features.

An Accumulating Neural Signal Underlying Binocular Rivalry Dynamics

During binocular rivalry, conflicting images are presented one to each eye and perception alternates stochastically between them. Despite stable percepts between alternations, modeling suggests that neural signals representing the two images change gradually, and that the duration of stable percepts are determined by the time required for these signals to reach a threshold that triggers an alternation. However, direct physiological evidence for such signals has been lacking. Here, we identify a neural signal in the human visual cortex that shows these predicted properties. We measured steady-state visual evoked potentials (SSVEPs) in 84 human participants (62 females, 22 males) who were presented with orthogonal gratings, one to each eye, flickering at different frequencies. Participants indicated their percept while EEG data were collected. The time courses of the SSVEP amplitudes at the two frequencies were then compared across different percept durations, within participants. For all durations, the amplitude of signals corresponding to the suppressed stimulus increased and the amplitude corresponding to the dominant stimulus decreased throughout the percept. Critically, longer percepts were characterized by more gradual increases in the suppressed signal and more gradual decreases of the dominant signal. Changes in signals were similar and rapid at the end of all percepts, presumably reflecting perceptual transitions. These features of the SSVEP time courses are well predicted by a model in which perceptual transitions are produced by the accumulation of noisy signals. Identification of this signal underlying binocular rivalry should allow strong tests of neural models of rivalry, bistable perception, and neural suppression.SIGNIFICANCE STATEMENT During binocular rivalry, two conflicting images are presented to the two eyes and perception alternates between them, with switches occurring at seemingly random times. Rivalry is an important and longstanding model system in neuroscience, used for understanding neural suppression, intrinsic neural dynamics, and even the neural correlates of consciousness. All models of rivalry propose that it depends on gradually changing neural activity that on reaching some threshold triggers the perceptual switches. This manuscript reports the first physiological measurement of neural signals with that set of properties in human participants. The signals, measured with EEG in human observers, closely match the predictions of recent models of rivalry, and should pave the way for much future work.

Rhythmic attentional sampling in autism

Individuals diagnosed with autism often display alterations in visual spatial attention toward visual stimuli, but the underlying cause of these differences remains unclear. Recent evidence has demonstrated that covert spatial attention, rather than remaining constant at a cued location, samples stimuli rhythmically at a frequency of 4-8 Hz (theta). Here we tested whether rhythmic sampling of attention is altered in autism. Participants were asked to monitor three locations to detect a brief target presented 300-1200 ms after a spatial cue. Visual attention was oriented to the cue and modified visual processing at the cued location, consistent with previous studies. We measured detection performance at different cue-target intervals when the target occurred at the cued location. Significant oscillations in detection performance were identified using both a traditional time-shuffled approach and a new autoregressive surrogate method developed by Brookshire in 2022. We found that attention enhances behavioral performance rhythmically at the same frequency in both autism and control group at the cued location. However, rhythmic temporal structure was not observed in a subgroup of autistic individuals with co-occurring attention-deficit/hyperactivity disorder (ADHD). Our results imply that intrinsic brain rhythms which organize neural activity into alternating attentional states is functional in autistic individuals, but may be altered in autistic participants who have a concurrent ADHD diagnosis.

The effects of abnormal visual experience on neurodevelopmental disorders

Normal visual development is supported by intrinsic neurobiological mechanisms and by appropriate stimulation from the environment, both of which facilitate the maturation of visual functions. However, an offset of this balance can give rise to visual disorders. Therefore, understanding the factors that support normal vision during development and in the mature brain is important, as vision guides movement, enables social interaction, and allows children to recognize and understand their environment. In this paper, we review fundamental mechanisms that support the maturation of visual functions and discuss and draw links between the perceptual and neurobiological impairments in autism spectrum disorder (ASD) and schizophrenia. We aim to explore how this is evident in the case of ASD, and how perceptual and neurobiological deficits further degrade social ability. Furthermore, we describe the altered perceptual experience of those with schizophrenia and evaluate theories of the underlying neural deficits that alter perception.

Measuring the reliability of binocular rivalry

Binocular rivalry is a widely used tool in sensory and cognitive neuroscience to investigate different aspects of vision and cognition. The dynamics of binocular rivalry (e.g., duration of perceptual dominance phases and mixed percept proportions) differ across individuals; based on rivalry dynamics, it is also possible to calculate an index of ocular dominance (by comparing the perceptual dominance of the images in the two eyes). In this study, we investigated the reliability of binocular rivalry dynamics using different methods for dichoptic stimulation and different rivalry stimuli. For the three main indices we defined (ocular dominance, phase durations and mixed percept proportions), we found a high test-retest reliability across sessions. Moreover, the test-retest reliability of the ocular dominance index was predictable from its internal consistency, supporting its stability over time. Phase durations and mixed percept proportions, in contrast, had worse test-retest reliability than expected based on internal consistency, indicating that these parameters are susceptible to state-dependent changes. Our results support the use of the ocular dominance index and binocular rivalry in the measurement of sensory eye dominance and its plasticity, but advise caution when investigating the association between phase durations or mixed percepts and stable characteristics like psychological traits or disorders.

SSVEP unsupervised adaptive feature recognition method based on self-similarity of same-frequency signals

Introduction

As an important human-computer interaction technology, steady-state visual evoked potential (SSVEP) plays a key role in the application of brain computer interface (BCI) systems by accurately decoding SSVEP signals. Currently, the majority SSVEP feature recognition methods use a static classifier. However, electroencephalogram (EEG) signals are non-stationary and time-varying. Hence, an adaptive classification method would be an alternative option to a static classifier for tracking the changes in EEG feature distribution, as its parameters can be re-estimated and updated with the input of new EEG data.

Methods

In this study, an unsupervised adaptive classification algorithm is designed based on the self-similarity of same-frequency signals. The proposed classification algorithm saves the EEG data that has undergone feature recognition as a template signal in accordance with its estimated label, and the new testing signal is superimposed with the template signals at each stimulus frequency as the new test signals to be analyzed. With the continuous input of EEG data, the template signals are continuously updated.

Results

By comparing the classification accuracy of the original testing signal and the testing signal superimposed with the template signals, this study demonstrates the effectiveness of using the self-similarity of same-frequency signals in the adaptive classification algorithm. The experimental results also show that the longer the SSVEP-BCI system is used, the better the responses of users on SSVEP are, and the more significantly the adaptive classification algorithm performs in terms of feature recognition. The testing results of two public datasets show that the adaptive classification algorithm outperforms the static classification method in terms of feature recognition.

Discussion

The proposed adaptive classification algorithm can update the parameters with the input of new EEG data, which is of favorable impact for the accurate analysis of EEG data with time-varying characteristics.

Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry

BACKGROUND

The development of machine learning models for aiding in the diagnosis of mental disorder is recognized as a significant breakthrough in the field of psychiatry. However, clinical practice of such models remains a challenge, with poor generalizability being a major limitation.

METHODS

Here, we conducted a pre-registered meta-research assessment on neuroimaging-based models in the psychiatric literature, quantitatively examining global and regional sampling issues over recent decades, from a view that has been relatively underexplored. A total of 476 studies (n = 118,137) were included in the current assessment. Based on these findings, we built a comprehensive 5-star rating system to quantitatively evaluate the quality of existing machine learning models for psychiatric diagnoses.

RESULTS

A global sampling inequality in these models was revealed quantitatively (sampling Gini coefficient (G) = 0.81, p < .01), varying across different countries (regions) (e.g., China, G = 0.47; the USA, G = 0.58; Germany, G = 0.78; the UK, G = 0.87). Furthermore, the severity of this sampling inequality was significantly predicted by national economic levels (β =  - 2.75, p < .001, R²_adj = 0.40; r =  - .84, 95% CI: - .41 to - .97), and was plausibly predictable for model performance, with higher sampling inequality for reporting higher classification accuracy. Further analyses showed that lack of independent testing (84.24% of models, 95% CI: 81.0-87.5%), improper cross-validation (51.68% of models, 95% CI: 47.2-56.2%), and poor technical transparency (87.8% of models, 95% CI: 84.9-90.8%)/availability (80.88% of models, 95% CI: 77.3-84.4%) are prevailing in current diagnostic classifiers despite improvements over time. Relating to these observations, model performances were found decreased in studies with independent cross-country sampling validations (all p < .001, BF₁₀ > 15). In light of this, we proposed a purpose-built quantitative assessment checklist, which demonstrated that the overall ratings of these models increased by publication year but were negatively associated with model performance.

CONCLUSIONS

Together, improving sampling economic equality and hence the quality of machine learning models may be a crucial facet to plausibly translating neuroimaging-based diagnostic classifiers into clinical practice.

A theory of autism bridging across levels of description

Autism impacts a wide range of behaviors and neural functions. As such, theories of autism spectrum disorder (ASD) are numerous and span different levels of description, from neurocognitive to molecular. We propose how existent behavioral, computational, algorithmic, and neural accounts of ASD may relate to one another. Specifically, we argue that ASD may be cast as a disorder of causal inference (computational level). This computation relies on marginalization, which is thought to be subserved by divisive normalization (algorithmic level). In turn, divisive normalization may be impaired by excitatory-to-inhibitory imbalances (neural implementation level). We also discuss ASD within similar frameworks, those of predictive coding and circular inference. Together, we hope to motivate work unifying the different accounts of ASD.

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.

Severely Attenuated Visual Feedback Processing in Children on the Autism Spectrum

Individuals on the autism spectrum often exhibit atypicality in their sensory perception, but the neural underpinnings of these perceptual differences remain incompletely understood. One proposed mechanism is an imbalance in higher-order feedback re-entrant inputs to early sensory cortices during sensory perception, leading to increased propensity to focus on local object features over global context. We explored this theory by measuring visual evoked potentials during contour integration as considerable work has revealed that these processes are largely driven by feedback inputs from higher-order ventral visual stream regions. We tested the hypothesis that autistic individuals would have attenuated evoked responses to illusory contours compared with neurotypical controls. Electrophysiology was acquired while 29 autistic and 31 neurotypical children (7-17 years old, inclusive of both males and females) passively viewed a random series of Kanizsa figure stimuli, each consisting of four inducers that were aligned either at random rotational angles or such that contour integration would form an illusory square. Autistic children demonstrated attenuated automatic contour integration over lateral occipital regions relative to neurotypical controls. The data are discussed in terms of the role of predictive feedback processes on perception of global stimulus features and the notion that weakened "priors" may play a role in the visual processing anomalies seen in autism.SIGNIFICANCE STATEMENT Children on the autism spectrum differ from typically developing children in many aspects of their processing of sensory stimuli. One proposed mechanism for these differences is an imbalance in higher-order feedback to primary sensory regions, leading to an increased focus on local object features rather than global context. However, systematic investigation of these feedback mechanisms remains limited. Using EEG and a visual illusion paradigm that is highly dependent on intact feedback processing, we demonstrated significant disruptions to visual feedback processing in children with autism. This provides much needed experimental evidence that advances our understanding of the contribution of feedback processing to visual perception in autism spectrum disorder.

Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review

IMPORTANCE

Neuroimaging-based artificial intelligence (AI) diagnostic models have proliferated in psychiatry. However, their clinical applicability and reporting quality (ie, feasibility) for clinical practice have not been systematically evaluated.

OBJECTIVE

To systematically assess the risk of bias (ROB) and reporting quality of neuroimaging-based AI models for psychiatric diagnosis.

EVIDENCE REVIEW

PubMed was searched for peer-reviewed, full-length articles published between January 1, 1990, and March 16, 2022. Studies aimed at developing or validating neuroimaging-based AI models for clinical diagnosis of psychiatric disorders were included. Reference lists were further searched for suitable original studies. Data extraction followed the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. A closed-loop cross-sequential design was used for quality control. The PROBAST (Prediction Model Risk of Bias Assessment Tool) and modified CLEAR (Checklist for Evaluation of Image-Based Artificial Intelligence Reports) benchmarks were used to systematically evaluate ROB and reporting quality.

FINDINGS

A total of 517 studies presenting 555 AI models were included and evaluated. Of these models, 461 (83.1%; 95% CI, 80.0%-86.2%) were rated as having a high overall ROB based on the PROBAST. The ROB was particular high in the analysis domain, including inadequate sample size (398 of 555 models [71.7%; 95% CI, 68.0%-75.6%]), poor model performance examination (with 100% of models lacking calibration examination), and lack of handling data complexity (550 of 555 models [99.1%; 95% CI, 98.3%-99.9%]). None of the AI models was perceived to be applicable to clinical practices. Overall reporting completeness (ie, number of reported items/number of total items) for the AI models was 61.2% (95% CI, 60.6%-61.8%), and the completeness was poorest for the technical assessment domain with 39.9% (95% CI, 38.8%-41.1%).

CONCLUSIONS AND RELEVANCE

This systematic review found that the clinical applicability and feasibility of neuroimaging-based AI models for psychiatric diagnosis were challenged by a high ROB and poor reporting quality. Particularly in the analysis domain, ROB in AI diagnostic models should be addressed before clinical application.

Visual Cortical Plasticity: Molecular Mechanisms as Revealed by Induction Paradigms in Rodents

Assessing the molecular mechanism of synaptic plasticity in the cortex is vital for identifying potential targets in conditions marked by defective plasticity. In plasticity research, the visual cortex represents a target model for intense investigation, partly due to the availability of different in vivo plasticity-induction protocols. Here, we review two major protocols: ocular-dominance (OD) and cross-modal (CM) plasticity in rodents, highlighting the molecular signaling pathways involved. Each plasticity paradigm has also revealed the contribution of different populations of inhibitory and excitatory neurons at different time points. Since defective synaptic plasticity is common to various neurodevelopmental disorders, the potentially disrupted molecular and circuit alterations are discussed. Finally, new plasticity paradigms are presented, based on recent evidence. Stimulus-selective response potentiation (SRP) is one of the paradigms addressed. These options may provide answers to unsolved neurodevelopmental questions and offer tools to repair plasticity defects.

Technologies to support the diagnosis and/or treatment of neurodevelopmental disorders: A systematic review

In recent years, there has been a great interest in utilizing technology in mental health research. The rapid technological development has encouraged researchers to apply technology as a part of a diagnostic process or treatment of Neurodevelopmental Disorders (NDDs). With the large number of studies being published comes an urgent need to inform clinicians and researchers about the latest advances in this field. Here, we methodically explore and summarize findings from studies published between August 2019 and February 2022. A search strategy led to the identification of 4108 records from PubMed and APA PsycInfo databases. 221 quantitative studies were included, covering a wide range of technologies used for diagnosis and/or treatment of NDDs, with the biggest focus on Autism Spectrum Disorder (ASD). The most popular technologies included machine learning, functional magnetic resonance imaging, electroencephalogram, magnetic resonance imaging, and neurofeedback. The results of the review indicate that technology-based diagnosis and intervention for NDD population is promising. However, given a high risk of bias of many studies, more high-quality research is needed.

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.

Priming and reversals of the perceived ambiguous orientation of a structure-from-motion shape and relation to personality traits

We demonstrate contributions of top-down and bottom-up influences in perception as explored by priming and counts of perceived reversals and mixed percepts, as probed by an ambiguously slanted structure-from-motion (SFM) test-cylinder. We included three different disambiguated primes: a SFM cylinder, a still image of a cylinder, and an imagined cylinder. In Experiment 1 where the prime and test sequentially occupied the same location, we also administered questionnaires with the Big-5 trait openness and vividness of visual imagery to probe possible relations to top-down driven priming. Since influences of gaze or position in the prime conditions in Experiment 1 could not be ruled out completely, Experiment 2 was conducted where the test cylinder appeared at a randomly chosen position after the prime. In Experiment 2 we also measured the number of perceptual reversals and mixed percepts during prolonged viewing of our ambiguous SFM-cylinder, and administered questionnaires to measure all Big-5 traits, autism, spatial and object imagery, and rational or experiential cognitive styles, associated with bottom-up and top-down processes. The results revealed contributions of position-invariant and cue-invariant priming. In addition, residual contributions of low-level priming was found when the prime and test were both defined by SFM, and were presented at the same location, and the correlation between the SFM priming and the other two priming conditions were weaker than between the pictorial and imagery priming. As previously found with ambiguous binocular rivalry stimuli, we found positive correlations between mixed percepts and the Big-5 dimension openness to experience, and between reversals, mixed percepts and neuroticism. Surprisingly, no correlations between the scores from the vividness of imagery questionnaires and influence from any of the primes were obtained. An intriguing finding was the significant differences between the positive correlation from the experiential cognitive style scores, and the negative correlation between rational style and the cue invariant priming. Among other results, negative correlations between agreeableness and all priming conditions were obtained. These results not only support the notion of multiple processes involved in the perception of ambiguous SFM, but also link these processes in perception to specific personality traits.

Involvement of retinoic acid receptor α in the autistic-like behavior of rats with vitamin A deficiency by regulating neurexin 1 in the visual cortex: a mechanism study

OBJECTIVES

To study the mechanism of retinoic acid receptor α (RARα) signal change to regulate neurexin 1 (NRXN1) in the visual cortex and participate in the autistic-like behavior in rats with vitamin A deficiency (VAD).

METHODS

The models of vitamin A normal (VAN) and VAD pregnant rats were established, and some VAD maternal and offspring rats were given vitamin A supplement (VAS) in the early postnatal period. Behavioral tests were performed on 20 offspring rats in each group at the age of 6 weeks. The three-chamber test and the open-field test were used to observe social behavior and repetitive stereotyped behavior. High-performance liquid chromatography was used to measure the serum level of retinol in the offspring rats in each group. Electrophysiological experiments were used to measure the long-term potentiation (LTP) level of the visual cortex in the offspring rats. Quantitative real-time PCR and Western blot were used to measure the expression levels of RARα, NRXN1, and N-methyl-D-aspartate receptor 1 (NMDAR1). Chromatin co-immunoprecipitation was used to measure the enrichment of RARα transcription factor in the promoter region of the NRXN1 gene.

RESULTS

The offspring rats in the VAD group had autistic-like behaviors such as impaired social interactions and repetitive stereotypical behaviors, and VAS started immediately after birth improved most of the behavioral deficits in offspring rats. The offspring rats in the VAD group had a significantly lower serum level of retinol than those in the VAN and VAS groups (P<0.05). Compared with the offspring rats in the VAN and VAS groups, the offspring rats in the VAD group had significant reductions in the mRNA and protein expression levels of NMDAR1, RARα, and NRXN1 and the LTP level of the visual cortex (P<0.05). The offspring rats in the VAD group had a significant reduction in the enrichment of RARα transcription factor in the promoter region of the NRXN1 gene in the visual cortex compared with those in the VAN and VAS groups (P<0.05).

CONCLUSIONS

RARα affects the synaptic plasticity of the visual cortex in VAD rats by regulating NRXN1, thereby participating in the formation of autistic-like behaviors in VAD rats.

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.

Association between resting-state functional brain connectivity and gene expression is altered in autism spectrum disorder

Gene expression covaries with brain activity as measured by resting state functional magnetic resonance imaging (MRI). However, it is unclear how genomic differences driven by disease state can affect this relationship. Here, we integrate from the ABIDE I and II imaging cohorts with datasets of gene expression in brains of neurotypical individuals and individuals with autism spectrum disorder (ASD) with regionally matched brain activity measurements from fMRI datasets. We identify genes linked with brain activity whose association is disrupted in ASD. We identified a subset of genes that showed a differential developmental trajectory in individuals with ASD compared with controls. These genes are enriched in voltage-gated ion channels and inhibitory neurons, pointing to excitation-inhibition imbalance in ASD. We further assessed differences at the regional level showing that the primary visual cortex is the most affected region in ASD. Our results link disrupted brain expression patterns of individuals with ASD to brain activity and show developmental, cell type, and regional enrichment of activity linked genes.

Gene expression patterns have been associated with functional activity patterns in the brain. Here the authors determine how gene expression patterns in the human brain supports brain phenotypes obtained from resting state fMRI imaging, identifying brain regions and genes relevant to autism.

Cross-subject spatial filter transfer method for SSVEP-EEG feature recognition

Objective.Steady-state visual evoked potential (SSVEP) is an important control method of the brain-computer interface (BCI) system. The development of an efficient SSVEP feature decoding algorithm is the core issue in SSVEP-BCI. It has been proposed to use user training data to reduce the spontaneous electroencephalogram activity interference on SSVEP response, thereby improving the feature recognition accuracy of the SSVEP signal. Nevertheless, the tedious data collection process increases the mental fatigue of the user and severely affects the applicability of the BCI system.Approach.A cross-subject spatial filter transfer (CSSFT) method that transfer the existing user model with good SSVEP response to the new user test data without collecting any training data from the new user is proposed.Main results.Experimental results demonstrate that the transfer model increases the distinction of the feature discriminant coefficient between the gaze following target and the non-gaze following target and accurately identifies the wrong target in the fundamental algorithm model. The public datasets show that the CSSFT method significantly increases the recognition performance of canonical correlation analysis (CCA) and filter bank CCA. Additionally, when the data used to calculate the transfer model contains one data block only, the CSSFT method retains its effective feature recognition capabilities.Significance.The proposed method requires no tedious data calibration process for new users, provides an effective technical solution for the transfer of the cross-subject model, and has potential application value for promoting the application of the BCI system.

Autism Spectrum Disorder: Focus on Glutamatergic Neurotransmission

Disturbances in the glutamatergic system have been increasingly documented in several neuropsychiatric disorders, including autism spectrum disorder (ASD). Glutamate-centered theories of ASD are based on evidence from patient samples and postmortem studies, as well as from studies documenting abnormalities in glutamatergic gene expression and metabolic pathways, including changes in the gut microbiota glutamate metabolism in patients with ASD. In addition, preclinical studies on animal models have demonstrated glutamatergic neurotransmission deficits and altered expression of glutamate synaptic proteins. At present, there are no approved glutamatergic drugs for ASD, but several ongoing clinical trials are currently focusing on evaluating in autistic patients glutamatergic pharmaceuticals already approved for other conditions. In this review, we provide an overview of the literature concerning the role of glutamatergic neurotransmission in the pathophysiology of ASD and as a potential target for novel treatments.

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.

Neural oscillations promoting perceptual stability and perceptual memory during bistable perception

Ambiguous images elicit bistable perception, wherein periods of momentary perceptual stability are interrupted by sudden perceptual switches. When intermittently presented, ambiguous images trigger a perceptual memory trace in the intervening blank periods. Understanding the neural bases of perceptual stability and perceptual memory during bistable perception may hold clues for explaining the apparent stability of visual experience in the natural world, where ambiguous and fleeting images are prevalent. Motivated by recent work showing the involvement of the right inferior frontal gyrus (rIFG) in bistable perception, we conducted a transcranial direct-current stimulation (tDCS) study with a double-blind, within-subject cross-over design to test a potential causal role of rIFG in these processes. Subjects viewed ambiguous images presented continuously or intermittently while under EEG recording. We did not find any significant tDCS effect on perceptual behavior. However, the fluctuations of oscillatory power in the alpha and beta bands predicted perceptual stability, with higher power corresponding to longer percept durations. In addition, higher alpha and beta power predicted enhanced perceptual memory during intermittent viewing. These results reveal a unified neurophysiological mechanism sustaining perceptual stability and perceptual memory when the visual system is faced with ambiguous input.

The amplitude of fNIRS hemodynamic response in the visual cortex unmasks autistic traits in typically developing children

Autistic traits represent a continuum dimension across the population, with autism spectrum disorder (ASD) being the extreme end of the distribution. Accumulating evidence shows that neuroanatomical and neurofunctional profiles described in relatives of ASD individuals reflect an intermediate neurobiological pattern between the clinical population and healthy controls. This suggests that quantitative measures detecting autistic traits in the general population represent potential candidates for the development of biomarkers identifying early pathophysiological processes associated with ASD. Functional near-infrared spectroscopy (fNIRS) has been extensively employed to investigate neural development and function. In contrast, the potential of fNIRS to define reliable biomarkers of brain activity has been barely explored. Features of non-invasiveness, portability, ease of administration, and low-operating costs make fNIRS a suitable instrument to assess brain function for differential diagnosis, follow-up, analysis of treatment outcomes, and personalized medicine in several neurological conditions. Here, we introduce a novel standardized procedure with high entertaining value to measure hemodynamic responses (HDR) in the occipital cortex of adult subjects and children. We found that the variability of evoked HDR correlates with the autistic traits of children, assessed by the Autism-Spectrum Quotient. Interestingly, HDR amplitude was especially linked to social and communication features, representing the core symptoms of ASD. These findings establish a quick and easy strategy for measuring visually-evoked cortical activity with fNIRS that optimize the compliance of young subjects, setting the background for testing the diagnostic value of fNIRS visual measurements in the ASD clinical population.

Alternative female and male developmental trajectories in the dynamic balance of human visual perception

The numerous multistable phenomena in vision, hearing and touch attest that the inner workings of perception are prone to instability. We investigated a visual example-binocular rivalry-with an accurate no-report paradigm, and uncovered developmental and maturational lifespan trajectories that were specific for age and sex. To interpret these trajectories, we hypothesized that conflicting objectives of visual perception-such as stability of appearance, sensitivity to visual detail, and exploration of fundamental alternatives-change in relative importance over the lifespan. Computational modelling of our empirical results allowed us to estimate this putative development of stability, sensitivity, and exploration over the lifespan. Our results confirmed prior findings of developmental psychology and appear to quantify important aspects of neurocognitive phenotype. Additionally, we report atypical function of binocular rivalry in autism spectrum disorder and borderline personality disorder. Our computational approach offers new ways of quantifying neurocognitive phenotypes both in development and in dysfunction.

SSVEP-EEG Feature Enhancement Method Using an Image Sharpening Filter

Steady-state visual evoked potential (SSVEP) is widely used in brain computer interface (BCI), medical detection, and neuroscience, so there is significant interest in enhancing SSVEP features via signal processing for better performance. In this study, an image processing method was combined with brain signal analysis and a sharpening filter was used to extract image details and features for the enhancement of SSVEP features. The results demonstrated that sharpening filter could eliminate the SSVEP signal trend term and suppress its low-frequency component. Meanwhile, sharpening filter effectively enhanced the signal-to-noise ratios (SNRs) of the single-channel and multi-channel fused signals. Image sharpening filter also significantly improved the recognition accuracy of canonical correlation analysis (CCA), filter bank canonical correlation analysis (FBCCA), and task-related component analysis (TRCA). The tools developed here effectively enhanced the SSVEP signal features, suggesting that image processing methods can be considered for improved brain signal analysis.

SSVEP-EEG Denoising via Image Filtering Methods

Steady-state visual evoked potential (SSVEP) is widely used in electroencephalogram (EEG) control, medical detection, cognitive neuroscience, and other fields. However, successful application requires improving the detection performance of SSVEP signal frequency characteristics. Most strategies to enhance the signal-to-noise ratio of SSVEP utilize application of a spatial filter. Here, we propose a method for image filtering denoising (IFD) of the SSVEP signal from the perspective of image analysis, as a preprocessing step for signal analysis. Arithmetic mean, geometric mean, Gaussian, and non-local means filtering methods were tested, and the experimental results show that image filtering of SSVEP cannot effectively remove the noise. Thus, we proposed a reverse solution in which the SSVEP noise signal was obtained by image filtering, and then the noise was subtracted from the original signal. Comparison of the recognition accuracy of the SSVEP signal before and after denoising was used to evaluate the denoising performance for stimuli of different duration. After IFD processing, SSVEP exhibited higher recognition accuracy, indicating the effectiveness of this proposed denoising method. Application of this method improves the detection performance of SSVEP signal frequency characteristics, combines image processing and brain signal analysis, and expands the research scope of brain signal analysis for widespread application.

Moderate Alcohol Intake Changes Visual Perception by Enhancing V1 Inhibitory Surround Interactions

Moderate alcohol consumption is considered to enhance the cortical GABA-ergic inhibitory system and it also variously affects visual perception. However, little behavioral evidence indicates changes of visual perception due to V1 modulated by alcohol intoxication. In this study, we investigated this issue by using center-surround tilt illusion (TI) as a probe of V1 inhibitory interactions, by taking into account possible higher-order effects. Participants conducted TI measures under sober, moderate alcohol intoxication, and placebo states. We found alcohol significantly increased repulsive TI effect and weakened orientation discrimination performance, which is consistent with the increase of lateral inhibition between orientation sensitive V1 neurons caused by alcohol intoxication. We also observed no visible changes in the data for global orientation processing but a presence of global attentional modulation. Thus, our results provide psychophysics evidence that alcohol changed V1 processing, which affects visual perception of contextual stimuli.

Does Cortical Inhibition Explain the Correlation Between Bistable Perception Paradigms?

When observers view a perceptually bistable stimulus, their perception changes stochastically. Various studies have shown across-observer correlations in the percept durations for different bistable stimuli including binocular rivalry stimuli and bistable moving plaids. Previous work on binocular rivalry posits that neural inhibition in the visual hierarchy is a factor involved in the perceptual fluctuations in that paradigm. Here, in order to investigate whether between-observer variability in cortical inhibition underlies correlated percept durations between binocular rivalry and bistable moving plaid perception, we used center-surround suppression as a behavioral measure of cortical inhibition. We recruited 217 participants in a test battery that included bistable perception paradigms as well as a center-surround suppression paradigm. While we were able to successfully replicate the correlations between binocular rivalry and bistable moving plaid perception, we did not find a correlation between center-surround suppression strength and percept durations for any form of bistable perception. Moreover, the results from a mediation analysis indicate that center-surround suppression is not the mediating factor in the correlation between binocular rivalry and bistable moving plaids. These results do not support the idea that cortical inhibition can explain the between-observer correlation in mean percept duration between binocular rivalry and bistable moving plaid perception.

Active probing to highlight approaching transitions to ictal states in coupled neural mass models

The extraction of electrophysiological features that reliably forecast the occurrence of seizures is one of the most challenging goals in epilepsy research. Among possible approaches to tackle this problem is the use of active probing paradigms in which responses to stimuli are used to detect underlying system changes leading up to seizures. This work evaluates the theoretical and mechanistic underpinnings of this strategy using two coupled populations of the well-studied Wendling neural mass model. Different model settings are evaluated, shifting parameters (excitability, slow inhibition, or inter-population coupling gains) from normal towards ictal states while probing stimuli are applied every 2 seconds to the input of either one or both populations. The correlation between the extracted features and the ictogenic parameter shifting indicates if the impending transition to the ictal state may be identified in advance. Results show that not only can the response to the probing stimuli forecast seizures but this is true regardless of the altered ictogenic parameter. That is, similar feature changes are highlighted by probing stimuli responses in advance of the seizure including: increased response variance and lag-1 autocorrelation, decreased skewness, and increased mutual information between the outputs of both model subsets. These changes were mostly restricted to the stimulated population, showing a local effect of this perturbational approach. The transition latencies from normal activity to sustained discharges of spikes were not affected, suggesting that stimuli had no pro-ictal effects. However, stimuli were found to elicit interictal-like spikes just before the transition to the ictal state. Furthermore, the observed feature changes highlighted by probing the neuronal populations may reflect the phenomenon of critical slowing down, where increased recovery times from perturbations may signal the loss of a systems' resilience and are common hallmarks of an impending critical transition. These results provide more evidence that active probing approaches highlight information about underlying system changes involved in ictogenesis and may be able to play a role in assisting seizure forecasting methods which can be incorporated into early-warning systems that ultimately enable closing the loop for targeted seizure-controlling interventions.

Binocular rivalry dynamics associated with high levels of self-reported autistic traits suggest an imbalance of cortical excitation and inhibition

An imbalance in cortical excitation and inhibition (E/I) may underlie both social and non-social symptoms of autism spectrum conditions (ASC). Recent work suggests that an E/I imbalance may underlie some of the sensory differences that are characteristic of ASCs such as anomalous perception. Binocular rivalry dynamics are thought to reflect the balance of E/I in the brain and could serve as a behavioural biomarker for ASC. Previous studies of clinical ASC populations have found a slower rate of binocular rivalry transitions; increased duration of the mixed percept and reduced perceptual suppression. There are some mixed reports of altered rivalry dynamics in the neurotypical population with high self-reported levels of autistic traits. Therefore, we used simple grating stimuli to measure binocular rivalry dynamics in a sample of seventy-nine adults aged 18-55 years. We additionally measured the level of autistic traits with the AQ-10 and used CAPS as a measure of anomalous perception. Bayesian correlations showed that those with higher AQ scores had a slower rate of perceptual switching and a longer mixed percept duration. Significant regression models with CAPS and AQ score revealed that AQ score was a significant predictor of switch rate and mixed percept duration, whereas CAPS was not. We also report that CAPS significantly predicted perceptual suppression, whereas AQ score did not. Overall, our findings suggest that in a non-clinical population, autistic traits are a predictor of binocular rivalry dynamics and the cortical E/I imbalance thought to underlie symptoms of ASC may extend to the broader phenotype.

GABAergic Inhibition Gates Perceptual Awareness During Binocular Rivalry

Binocular rivalry is a classic experimental tool to probe the neural machinery of perceptual awareness. During rivalry, perception alternates between the two eyes, and the ebb and flow of perception is modeled to rely on the strength of inhibitory interactions between competitive neuronal populations in visual cortex. As a result, rivalry has been suggested as a noninvasive perceptual marker of inhibitory signaling in visual cortex, and its putative disturbance in psychiatric conditions, including autism. Yet, direct evidence causally implicating inhibitory signaling in the dynamics of binocular rivalry is currently lacking. We previously found that people with higher GABA levels in visual cortex, measured using magnetic resonance spectroscopy, have stronger perceptual suppression during rivalry. Here, we present direct causal tests of the impact of GABAergic inhibition on rivalry dynamics, and the contribution of specific GABA receptors to these dynamics. In a crossover pharmacological design with male and female adult participants, we found that drugs that modulate the two dominant GABA receptor types in the brain, GABA_A (clobazam) and GABA_B (arbaclofen), increase perceptual suppression during rivalry relative to a placebo. Crucially, these results could not be explained by changes in reaction times or response criteria, as determined through rivalry simulation trials, suggesting a direct and specific influence of GABA on perceptual suppression. A full replication study of the GABA_B modulator reinforces these findings. These results provide causal evidence for a link between the strength of inhibition in the brain and perceptual suppression during rivalry and have implications for psychiatric conditions including autism.SIGNIFICANCE STATEMENT How does the brain accomplish perceptual gating? Here we use a direct and causal pharmacological manipulation to present insight into the neural machinery of a classic illusion of perceptual awareness: binocular rivalry. We show that drugs that increase GABAergic inhibition in the brain, clobazam (GABA_A modulator) and arbaclofen (GABA_B modulator), increase perceptual suppression during rivalry relative to a placebo. These results present the first causal link between GABAergic inhibition and binocular rivalry in humans, complementing classic models of binocular rivalry, and have implications for our understanding of psychiatric conditions, such as autism, where binocular rivalry is posited as a behavioral marker of disruptions in inhibitory signaling in the brain.