Brain dynamics in ASD during movie-watching show idiosyncratic functional integration and segregation

Unraveling the developmental dynamic of visual exploration of social interactions in autism

Atypical deployment of social gaze is present early on in toddlers with autism spectrum disorders (ASDs). Yet, studies characterizing the developmental dynamic behind it are scarce. Here, we used a data-driven method to delineate the developmental change in visual exploration of social interaction over childhood years in autism. Longitudinal eye-tracking data were acquired as children with ASD and their typically developing (TD) peers freely explored a short cartoon movie. We found divergent moment-to-moment gaze patterns in children with ASD compared to their TD peers. This divergence was particularly evident in sequences that displayed social interactions between characters and even more so in children with lower developmental and functional levels. The basic visual properties of the animated scene did not account for the enhanced divergence. Over childhood years, these differences dramatically increased to become more idiosyncratic. These findings suggest that social attention should be targeted early in clinical treatments.

Cognitive and perceptual load have opposing effects on brain network efficiency and behavioral variability in ADHD

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder associated with suboptimal outcomes throughout the life-span. Extant work suggests that ADHD-related deficits in task performance may be magnified under high cognitive load and minimized under high perceptual load, but these effects have yet to be systematically examined, and the neural mechanisms that undergird these effects are as yet unknown. Herein, we report results from three experiments investigating how performance in ADHD is modulated by cognitive load and perceptual load during a naturalistic task. Results indicate that cognitive load and perceptual load influence task performance, reaction time variability (RTV), and brain network topology in an ADHD-specific fashion. Increasing cognitive load resulted in reduced performance, greater RTV, and reduced brain network efficiency in individuals with ADHD relative to those without. In contrast, increased perceptual load led to relatively greater performance, reduced RTV, and greater brain network efficiency in ADHD. These results provide converging evidence that brain network efficiency and intraindividual variability in ADHD are modulated by both cognitive and perceptual load during naturalistic task performance.

Hippocampus-Centered Network Is Associated With Positive Symptom Alleviation in Patients With First-Episode Psychosis

BACKGROUND

Previous functional magnetic resonance imaging studies have reported widespread brain functional connectivity alterations in patients with psychosis. These studies have mostly used either resting-state or simple-task paradigms, thereby compromising experimental control or ecological validity, respectively. Additionally, in a conventional functional magnetic resonance imaging intrasubject functional connectivity analysis, it is difficult to identify which connections relate to extrinsic (stimulus-induced) and which connections relate to intrinsic (non-stimulus-related) neural processes.

METHODS

To mitigate these limitations, we used intersubject functional connectivity (ISFC) to analyze longitudinal functional magnetic resonance imaging data collected while 36 individuals with first-episode psychosis (FEP) and 29 age- and sex-matched population control participants watched scenes from the fantasy movie Alice in Wonderland at baseline and again at 1-year follow-up. Furthermore, to allow unconfounded comparison and to overcome possible circularity of ISFC, we introduced a novel approach wherein ISFC in both the FEP and population control groups was calculated with respect to an independent group of participants (not included in the analyses).

RESULTS

Using this independent-reference ISFC approach, we found an interaction effect wherein the independent-reference ISFC in individuals with FEP, but not in the control group participants, was significantly stronger at baseline than at follow-up in a network centered in the hippocampus and involving thalamic, striatal, and cortical regions, such as the orbitofrontal cortex. Alleviation of positive symptoms, particularly delusions, from baseline to follow-up was correlated with decreased network connectivity in patients with FEP.

CONCLUSIONS

These findings link deviation of naturalistic information processing in the hippocampus-centered network to positive symptoms.

The abilities of movie-watching functional connectivity in individual identifications and individualized predictions

Quite a few studies have been performed based on movie-watching functional connectivity (FC). As compared to its resting-state counterpart, however, there is still much to know about its abilities in individual identifications and individualized predictions. To pave the way for appropriate usage of movie-watching FC, we systemically evaluated the minimum number of time points, as well as the exact functional networks, supporting individual identifications and individualized predictions of apparent traits based on it. We performed the study based on the 7T movie-watching fMRI data included in the HCP S1200 Release, and took IQ as the test case for the prediction analyses. The results indicate that movie-watching FC based on only 15 time points can support successful individual identifications (99.47%), and the connectivity contributed more to identifications were much associated with higher-order cognitive processes (the secondary visual network, the frontoparietal network and the posterior multimodal network). For individualized predictions of IQ, it was found that successful predictions necessitated 60 time points (predicted vs. actual IQ correlation significant at P < 0.05, based on 5,000 permutations), and the prediction accuracy increased logarithmically with the number of time points used for connectivity calculation. Furthermore, the connectivity that contributed more to individual identifications exhibited the strongest prediction ability. Collectively, our findings demonstrate that movie-watching FC can capture rich information about human brain function, and its ability in individualized predictions depends heavily on the length of fMRI scans.

Partner similarity and social cognitive traits predict social interaction success among strangers

Social interactions are a ubiquitous part of engaging in the world around us, and determining what makes an interaction successful is necessary for social well-being. This study examined the separate contributions of individual social cognitive ability and partner similarity to social interaction success among strangers, measured by a cooperative communication task and self-reported interaction quality. Sixty participants engaged in a 1-h virtual social interaction with an unfamiliar partner (a laboratory confederate) including a 30-min cooperative 'mind-reading' game and then completed several individual tasks and surveys. They then underwent a separate functional MRI session in which they passively viewed video clips that varied in content. The neural responses to these videos were correlated with those of their confederate interaction partners to yield a measure of pairwise neural similarity. We found that trait empathy (assessed by the interpersonal reactivity index) and neural similarity to partner both predicted communication success in the mind-reading game. In contrast, perceived similarity to partner and (to a much lesser extent) trait mind-reading motivation predicted self-reported interaction quality. These results highlight the importance of sharing perspectives in successful communication as well as differences between neurobiological similarity and perceived similarity in supporting different types of interaction success.

Narrative simulation of social experiences in naturalistic context - A neurocinematic approach

Narratives may be regarded as simulations of everyday social situations. They are key to studying the human mind in socio-culturally determined contexts as they allow anchoring to the common ground of embodied and environmentally-engaged cognition. Here we review recent findings from naturalistic neuroscience on neural functions in conditions that mimic lifelike situations. We will focus particularly on neurocinematics, a research field that applies mediated narratives as stimuli for neuroimaging experiments. During the last two decades, this paradigm has contributed to an accumulation of insights about the neural underpinnings of behavior and sense-making in various narratively contextualized situations particularly pertaining to socio-emotional encounters. One of the key questions in neurocinematics is, how do intersubjectively synchronized brain activations relate to subjective experiences? Another question we address is how to bring natural contexts into experimental studies. Seeking to respond to both questions, we suggest neurocinematic studies to examine three manifestations of the same phenomenon side-by-side: subjective experiences of narrative situations, unfolding of narrative stimulus structure, and neural processes that co-constitute the experience. This approach facilitates identifying experientially meaningful activity patterns in the brain and points out what they may mean in relation to shared and communicable contents. Via rich-featured and temporally contextualized narrative stimuli, neurocinematics attempts to contribute to emerging holistic theories of neural dynamics and connectomics explaining typical and atypical interindividual variability.

EEG Correlates of Cognitive Functions in a Child with ASD and White Matter Signal Abnormalities: A Case Report with Two-and-a-Half-Year Follow-Up

This research aimed to examine the EEG correlates of different stimuli processing instances in a child with ASD and white matter signal abnormalities and to investigate their relationship to the results of behavioral tests. The prospective case study reports two and a half years of follow-up data from a child aged 38 to 66 months. Cognitive, speech-language, sensory, and EEG correlates of auditory-verbal and auditory-visual-verbal information processing were recorded during five test periods, and their mutual interrelation was analyzed. EEG findings revealed no functional theta frequency range redistribution in the frontal regions favoring the left hemisphere during speech processing. The results pointed to a positive linear trend in the relative theta frequency range and a negative linear trend in the relative alpha frequency range when listening to and watching the cartoon. There was a statistically significant correlation between EEG signals and behavioral test results. Based on the obtained results, it may be concluded that EEG signals and their association with the results of behavioral tests should be evaluated with certain restraints considering the characteristics of the stimuli during EEG recording.

Autism Detection in Children using Common Spatial Patterns of MEG Signals

Autism exhibits a wide range of developmental disabilities and is associated with aberrant anatomical and functional neural patterns. To detect autism in young children (4-7 years) in an automatic and non-invasive fashion, we have recorded magnetoencephalogram (MEG) signals from 30 autistic and 30 age-matched typically developing (TD) children. We have used a machine learning classification framework with common spatial pattern (CSP)-based logarithmic band power (LBP) features. When comparing the LBP feature to the conventional logarithmic variance (LV) spatial pattern, CSP + LBP (92.77%) has performed better than CSP + LV (90.66%) in the 1-100 Hz frequency range for distinguishing autistic children from TD children. In frequency band-wise analysis using our proposed method, the high gamma frequency band (50-100 Hz) has shown the highest classification accuracy (97.14%). Our findings reveal that the occipital lobe exhibits the most distinct spatial pattern in autistic children over the whole frequency range. This study shows that spatial brain activation patterns can be utilized as potential biomarkers of autism in young children. The improved performance signifies the clinical relevance of the work for autism detection using MEG signals.

Are inter-subject functional correlations consistent across different movies?

Movie fMRI has been increasingly used in investigations of human brain function. Inter-subject functional correlation (ISFC), which evaluates stimulus-dependent inter-regional synchrony between brains exposed to the same stimulus, is emerging as an influencing measure for movie fMRI data analyses. Before the wide application of ISFC analyses, it will be useful to investigate the degree to which they are similar and different across different movies. Based on the four movie fMRI runs of 178 subjects included in the "human connectome project (HCP) S1200 Release", we evaluated ISFCs throughout the brain and analyzed their consistency across different movies using intra-class correlation (ICC). We also investigated the generalizability of ISFC-based predictive models, which is closely related to their consistency, with sex classification and grip strength prediction used as test cases. The results showed that the intensity of ISFCs was generally weak (0.047). Except a few within-network ones (e.g., ICC of ISFC in the PON was 0.402), ISFCs throughout the brain exhibited low consistency, as indicated by a mean ICC of 0.130. The accuracies for inter-run predictions (60.7-72.8% for sex classification, and R = 0.122-0.275 for grip strength prediction) were much lower than those for intra-run predictions (73.2-83.0% for sex classification, and R = 0.325-0.403 for grip strength prediction), and this indicates poor generalizability of predictive models based on ISFCs. According to these findings, ISFC analyses capture aspects of brain function that are specific to each individual movie, and this specificity should be taken into account (in some cases might be especially useful) in future naturalistic studies.

Atypical gaze patterns in autistic adults are heterogeneous across but reliable within individuals

BACKGROUND

Across behavioral studies, autistic individuals show greater variability than typically developing individuals. However, it remains unknown to what extent this variability arises from heterogeneity across individuals, or from unreliability within individuals. Here, we focus on eye tracking, which provides rich dependent measures that have been used extensively in studies of autism. Autistic individuals have an atypical gaze onto both static visual images and dynamic videos that could be leveraged for diagnostic purposes if the above open question could be addressed.

METHODS

We tested three competing hypotheses: (1) that gaze patterns of autistic individuals are less reliable or noisier than those of controls, (2) that atypical gaze patterns are individually reliable but heterogeneous across autistic individuals, or (3) that atypical gaze patterns are individually reliable and also homogeneous among autistic individuals. We collected desktop-based eye tracking data from two different full-length television sitcom episodes, at two independent sites (Caltech and Indiana University), in a total of over 150 adult participants (N = 48 autistic individuals with IQ in the normal range, 105 controls) and quantified gaze onto features of the videos using automated computer vision-based feature extraction.

RESULTS

We found support for the second of these hypotheses. Autistic people and controls showed equivalently reliable gaze onto specific features of videos, such as faces, so much so that individuals could be identified significantly above chance using a fingerprinting approach from video epochs as short as 2 min. However, classification of participants into diagnostic groups based on their eye tracking data failed to produce clear group classifications, due to heterogeneity in the autistic group.

LIMITATIONS

Three limitations are the relatively small sample size, assessment across only two videos (from the same television series), and the absence of other dependent measures (e.g., neuroimaging or genetics) that might have revealed individual-level variability that was not evident with eye tracking. Future studies should expand to larger samples across longer longitudinal epochs, an aim that is now becoming feasible with Internet- and phone-based eye tracking.

CONCLUSIONS

These findings pave the way for the investigation of autism subtypes, and for elucidating the specific visual features that best discriminate gaze patterns-directions that will also combine with and inform neuroimaging and genetic studies of this complex disorder.

A tale of two connectivities: intra- and inter-subject functional connectivity jointly enable better prediction of social abilities

Naturalistic functional magnetic resonance imaging (fMRI) paradigms, such as movie viewing, are attracting increased attention, given their ability to mimic the real-world cognitive demands on attention and multimodal sensory integration. Moreover, naturalistic paradigms allow for characterizing brain network responses associated with dynamic social cognition in a model-free manner using inter-subject functional connectivity (ISFC). While intra-subject functional connectivity (FC) characterizes the individual’s brain functional architecture, ISFC characterizes the neural coupling driven by time-locked extrinsic dynamic stimuli across individuals. Here, we hypothesized that ISFC and FC provide distinct and complementary information about individual differences in social cognition. To test this hypothesis, we examined a public movie-viewing fMRI dataset with 32 healthy adults and 90 typically developing children. Building three partial least squares regression (PLS) models to predict social abilities using FC and/or ISFC, we compared predictive performance to determine whether combining two connectivity measures could improve the prediction accuracy of individuals’ social-cognitive abilities measured by a Theory of Mind (ToM) assessment. Our results indicated that the joint model (ISFC + FC) yielded the highest predictive accuracy and significantly predicted individuals’ social cognitive abilities (rho = 0.34, p < 0.001). We also confirmed that the improved accuracy was not due to the increased feature dimensionality. In conclusion, we demonstrated that intra-/inter-subject connectivity encodes unique information about social abilities, and a joint investigation could help us gain a more complete understanding of the complex processes supporting social cognition.

Detection of Brain Network Communities During Natural Speech Comprehension From Functionally Aligned EEG Sources

In recent years, electroencephalograph (EEG) studies on speech comprehension have been extended from a controlled paradigm to a natural paradigm. Under the hypothesis that the brain can be approximated as a linear time-invariant system, the neural response to natural speech has been investigated extensively using temporal response functions (TRFs). However, most studies have modeled TRFs in the electrode space, which is a mixture of brain sources and thus cannot fully reveal the functional mechanism underlying speech comprehension. In this paper, we propose methods for investigating the brain networks of natural speech comprehension using TRFs on the basis of EEG source reconstruction. We first propose a functional hyper-alignment method with an additive average method to reduce EEG noise. Then, we reconstruct neural sources within the brain based on the EEG signals to estimate TRFs from speech stimuli to source areas, and then investigate the brain networks in the neural source space on the basis of the community detection method. To evaluate TRF-based brain networks, EEG data were recorded in story listening tasks with normal speech and time-reversed speech. To obtain reliable structures of brain networks, we detected TRF-based communities from multiple scales. As a result, the proposed functional hyper-alignment method could effectively reduce the noise caused by individual settings in an EEG experiment and thus improve the accuracy of source reconstruction. The detected brain networks for normal speech comprehension were clearly distinctive from those for non-semantically driven (time-reversed speech) audio processing. Our result indicates that the proposed source TRFs can reflect the cognitive processing of spoken language and that the multi-scale community detection method is powerful for investigating brain networks.

Sensorimotor Responses in Post-Stroke Hemiplegic Patients Modulated by Acupuncture at Yanglingquan (GB34): A fMRI Study Using Intersubject Functional Correlation (ISFC) Analysis

Motor dysfunction is common in patients with stroke. Acupuncture has become an acceptable alternative method for stroke rehabilitation. Previous studies have shown various functional connectivity changes activated by acupuncture. We introduced intersubject correlation (ISC) and intersubject functional correlation (ISFC) analyses into the functional magnetic resonance imaging (fMRI) for ischemic stroke to seek a common activation and suppression pattern triggered by acupuncture. In this study, 63 ischemic stroke patients with motor dysfunction and 42 normal controls were analyzed. Three functional scans were conducted during the resting state, motor task, and acupuncture at Yanglingquan (GB34) task. Twenty-two sensory, motor, and movement-imagination cortices in the bilateral hemispheres were selected as the region of interest (ROI). We performed ISC and ISFC analyses among these ROIs in three fMRI runs on patients and controls. Subgroup analyses by course or severity were also conducted. The results showed that acupuncture at GB34 triggered ISFC among upper limb motor, upper limb/hand/face, lower limb, tongue/larynx sensory, and movement imagination regions in the patient group. Subgroup ISC and ISFC analyses showed that patients tended to have increasing responses in the early stage of stroke (within 1 month) and decreasing responses afterward (1–3 months). Patients with mild clinical functional damage (NIHSS 2–4) tended to generate more responses via acupuncture than those with moderate damage (NIHSS 5–15). Our findings may help understand the clinical effects and modulatory features of acupuncture based on the group-level post-stroke neuroplasticity.

Separating Stimulus-Induced and Background Components of Dynamic Functional Connectivity in Naturalistic fMRI

We consider the challenges in extracting stimulus-related neural dynamics from other intrinsic processes and noise in naturalistic functional magnetic resonance imaging (fMRI). Most studies rely on inter-subject correlations (ISC) of low-level regional activity and neglect varying responses in individuals. We propose a novel, data-driven approach based on low-rank plus sparse ( [Formula: see text]) decomposition to isolate stimulus-driven dynamic changes in brain functional connectivity (FC) from the background noise, by exploiting shared network structure among subjects receiving the same naturalistic stimuli. The time-resolved multi-subject FC matrices are modeled as a sum of a low-rank component of correlated FC patterns across subjects, and a sparse component of subject-specific, idiosyncratic background activities. To recover the shared low-rank subspace, we introduce a fused version of principal component pursuit (PCP) by adding a fusion-type penalty on the differences between the columns of the low-rank matrix. The method improves the detection of stimulus-induced group-level homogeneity in the FC profile while capturing inter-subject variability. We develop an efficient algorithm via a linearized alternating direction method of multipliers to solve the fused-PCP. Simulations show accurate recovery by the fused-PCP even when a large fraction of FC edges are severely corrupted. When applied to natural fMRI data, our method reveals FC changes that were time-locked to auditory processing during movie watching, with dynamic engagement of sensorimotor systems for speech-in-noise. It also provides a better mapping to auditory content in the movie than ISC.

Movie Events Detecting Reveals Inter-Subject Synchrony Difference of Functional Brain Activity in Autism Spectrum Disorder

Recently, movie-watching fMRI has been recognized as a novel method to explore brain working patterns. Previous researchers correlated natural stimuli with brain responses to explore brain functional specialization by “reverse correlation” methods, which were based on within-group analysis. However, what external stimuli drove significantly different brain responses in two groups of different subjects were still unknown. To address this, sliding time windows technique combined with inter-Subject functional correlation (ISFC) was proposed to detect movie events with significant group differences between autism spectrum disorder (ASD) and typical development (TD) subjects. Then, using inter-Subject correlation (ISC) and ISFC analysis, we found that in three movie events involving character emotions, the ASD group showed significantly lower ISC in the middle temporal gyrus, temporal pole, cerebellum, caudate, precuneus, and showed decreased functional connectivity between large scale networks than that in TD. Under the movie event focusing on objects and scenes shot, the dorsal and ventral attentional networks of ASD had a strong synchronous response. Meanwhile, ASD also displayed increased functional connectivity between the frontoparietal network (FPN) and dorsal attention network (DAN), FPN, and sensorimotor network (SMN) than TD. ASD has its own unique synchronous response rather than being “unresponsive” in natural movie-watching. Our findings provide a new method and valuable insight for exploring the inconsistency of the brain “tick collectively” to same natural stimuli. This analytic approach has the potential to explore pathological mechanisms and promote training methods of ASD.

Discovering hidden brain network responses to naturalistic stimuli via tensor component analysis of multi-subject fMRI data

The study of brain network interactions during naturalistic stimuli facilitates a deeper understanding of human brain function. To estimate large-scale brain networks evoked with naturalistic stimuli, a tensor component analysis (TCA) based framework was used to characterize shared spatio-temporal patterns across subjects in a purely data-driven manner. In this framework, a third-order tensor is constructed from the timeseries extracted from all brain regions from a given parcellation, for all participants, with modes of the tensor corresponding to spatial distribution, time series and participants. TCA then reveals spatially and temporally shared components, i.e., evoked networks with the naturalistic stimuli, their time courses of activity and subject loadings of each component. To enhance the reproducibility of the estimation with the adaptive TCA algorithm, a novel spectral clustering method, tensor spectral clustering, was proposed and applied to evaluate the stability of the TCA algorithm. We demonstrated the effectiveness of the proposed framework via simulations and real fMRI data collected during a motor task with a traditional fMRI study design. We also applied the proposed framework to fMRI data collected during passive movie watching to illustrate how reproducible brain networks are evoked by naturalistic movie viewing.

Is it time to put rest to rest?

The so-called resting state, in which participants lie quietly with no particular inputs or outputs, represented a paradigm shift from conventional task-based studies in human neuroimaging. Our foray into rest was fruitful from both a scientific and methodological perspective, but at this point, how much more can we learn from rest on its own? While rest still dominates in many subfields, data from tasks have empirically demonstrated benefits, as well as the potential to provide insights about the mind in addition to the brain. I argue that we can accelerate progress in human neuroscience by de-emphasizing rest in favor of more grounded experiments, including promising integrated designs that respect the prominence of self-generated activity while offering enhanced control and interpretability.

Investigation of functional brain network reconfiguration during exposure to naturalistic stimuli using graph-theoretical analysis

Objective.One of the most significant features of the human brain is that it can dynamically reconfigure itself to adapt to a changing environment. However, dynamic interaction characteristics of the brain networks in naturalistic scenes remain unclear.Approach.We used open-source functional magnetic resonance imaging (fMRI) data from 15 participants who underwent fMRI scans while watching an audio-visual movie 'Forrest Gump'. The community detection algorithm based on inter-subject functional correlation was used to study the time-varying functional networks only induced by the movie stimuli. The whole brain reconfiguration patterns were quantified by the temporal co-occurrence matrix that describes the probability of two brain regions engage in the same community (or putative functional module) across time and the time-varying brain modularity. Four graph metrics of integration, recruitment, spatio-temporal diversity and within-community normalised centrality were further calculated to summarise the brain network dynamic roles and hub features in their spatio-temporal topology.Main results.Our results suggest that the networks that were involved in attention and audio-visual information processing, such as the visual network, auditory network, and dorsal attention network, were considered to play a role of 'stable loners'. By contrast, 'unstable loner' networks such as the default mode network (DMN) and fronto-parietal network tended to interact more flexibly with the other networks. In addition, global brain network showed significant fluctuations in modularity. The 'stable loner' networks always maintained high functional connectivity (FC) strength while 'unstable loner' networks, especially the DMN, exhibited high intra- and inter-network FC only during a low modularity period. Finally, changes in brain modularity were significantly associated with variations in emotions induced by the movie.Significance.Our findings provide new insight for understanding the dynamic interaction characteristics of functional brain networks during naturalistic stimuli.

Naturalistic Stimuli in Affective Neuroimaging: A Review

Naturalistic stimuli such as movies, music, and spoken and written stories elicit strong emotions and allow brain imaging of emotions in close-to-real-life conditions. Emotions are multi-component phenomena: relevant stimuli lead to automatic changes in multiple functional components including perception, physiology, behavior, and conscious experiences. Brain activity during naturalistic stimuli reflects all these changes, suggesting that parsing emotion-related processing during such complex stimulation is not a straightforward task. Here, I review affective neuroimaging studies that have employed naturalistic stimuli to study emotional processing, focusing especially on experienced emotions. I argue that to investigate emotions with naturalistic stimuli, we need to define and extract emotion features from both the stimulus and the observer.

Movie-watching outperforms rest for functional connectivity-based prediction of behavior

A major goal of human neuroscience is to relate differences in brain function to differences in behavior across people. Recent work has established that whole-brain functional connectivity patterns are relatively stable within individuals and unique across individuals, and that features of these patterns predict various traits. However, while functional connectivity is most often measured at rest, certain tasks may enhance individual signals and improve sensitivity to behavior differences. Here, we show that compared to the resting state, functional connectivity measured during naturalistic viewing—i.e., movie watching—yields more accurate predictions of trait-like phenotypes in the domains of both cognition and emotion. Traits could be predicted using less than three minutes of data from single video clips, and clips with highly social content gave the most accurate predictions. Results suggest that naturalistic stimuli amplify individual differences in behaviorally relevant brain networks.

Examining the relationship between measures of autistic traits and neural synchrony during movies in children with and without autism

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Neural synchrony during movie watching was measured in children with and without ASD.

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The ASD group had significantly less neural synchrony across the whole brain.

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The ASD group also had significantly less synchrony in the theory of mind network.

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Autistic traits did not predict neural synchrony in non-ASD children.

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These results suggest children with ASD process movies in a unique way.

Children who have been diagnosed with autism spectrum disorder (ASD) often show a marked deficit in measures of social cognition. In autistic adults, measures of social cognition have been shown to relate to differences in brain synchronization (as measured by fMRI) when individuals are processing naturalistic stimuli, such as movies. However, whether children who differ in their degree of autistic traits, with or without a diagnosis of ASD, differ in their neural responses to movies has not yet been investigated. In the current study, neural synchrony, measured using fMRI, was examined in three groups of children aged 7 to 12, who differed with respect to scores on a measure of autistic traits associated with social impairment and whether or not they had been diagnosed with ASD. While watching the movie ‘Despicable Me’, those diagnosed with ASD had significantly less neural synchrony in areas that have been previously shown to be associated with social cognition (e.g. areas related to ‘theory of mind’), and plot following (e.g. the lateral prefrontal cortex), than those who did not have an ASD diagnosis. In contrast, two groups who differed in their degree of autistic traits, but did not have a diagnosis of ASD, showed no significant differences in neural synchrony across the whole brain. These results shed some light on how autistic traits may contribute to an individual’s conscious experience of the world, and how, for children with ASD, that experience may differ markedly from that of those without ASD.

Processing of pragmatic communication in ASD: a video-based brain imaging study

Social and pragmatic difficulties in autism spectrum disorder (ASD) are widely recognized, although their underlying neural level processing is not well understood. The aim of this study was to examine the activity of the brain network components linked to social and pragmatic understanding in order to reveal whether complex socio-pragmatic events evoke differences in brain activity between the ASD and control groups. Nineteen young adults (mean age 23.6 years) with ASD and 19 controls (mean age 22.7 years) were recruited for the study. The stimulus data consisted of video clips showing complex social events that demanded processing of pragmatic communication. In the analysis, the functional magnetic resonance imaging signal responses of the selected brain network components linked to social and pragmatic information processing were compared. Although the processing of the young adults with ASD was similar to that of the control group during the majority of the social scenes, differences between the groups were found in the activity of the social brain network components when the participants were observing situations with concurrent verbal and non-verbal communication events. The results suggest that the ASD group had challenges in processing concurrent multimodal cues in complex pragmatic communication situations.

Perceptual category learning in autism spectrum disorder: Truth and consequences

The ability to categorize is fundamental to cognitive development. Some categories emerge effortlessly and rapidly while others can take years of experience to acquire. Children with autism spectrum disorder (ASD) are often able to name and sort objects, suggesting that their categorization abilities are largely intact. However, recent experimental work shows that the categories formed by individuals with ASD may diverge substantially from those that most people learn. This review considers how atypical perceptual category learning can affect cognitive development in children with ASD and how atypical categorization may contribute to many of the socially problematic symptoms associated with this disorder. Theoretical approaches to understanding perceptual processing and category learning at both the behavioral and neural levels are assessed in relation to known alterations in perceptual category learning associated with ASD. Mismatches between the ways in which children learn to organize perceived events relative to their peers and adults can accumulate over time, leading to difficulties in communication, social interactions, academic performance, and behavioral flexibility.

A naturalistic neuroimaging database for understanding the brain using ecological stimuli

Neuroimaging has advanced our understanding of human psychology using reductionist stimuli that often do not resemble information the brain naturally encounters. It has improved our understanding of the network organization of the brain mostly through analyses of 'resting-state' data for which the functions of networks cannot be verifiably labelled. We make a 'Naturalistic Neuroimaging Database' (NNDb v1.0) publically available to allow for a more complete understanding of the brain under more ecological conditions during which networks can be labelled. Eighty-six participants underwent behavioural testing and watched one of 10 full-length movies while functional magnetic resonance imaging was acquired. Resulting timeseries data are shown to be of high quality, with good signal-to-noise ratio, few outliers and low movement. Data-driven functional analyses provide further evidence of data quality. They also demonstrate accurate timeseries/movie alignment and how movie annotations might be used to label networks. The NNDb can be used to answer questions previously unaddressed with standard neuroimaging approaches, progressing our knowledge of how the brain works in the real world.

Idiosynchrony: From shared responses to individual differences during naturalistic neuroimaging

Two ongoing movements in human cognitive neuroscience have researchers shifting focus from group-level inferences to characterizing single subjects, and complementing tightly controlled tasks with rich, dynamic paradigms such as movies and stories. Yet relatively little work combines these two, perhaps because traditional analysis approaches for naturalistic imaging data are geared toward detecting shared responses rather than between-subject variability. Here, we review recent work using naturalistic stimuli to study individual differences, and advance a framework for detecting structure in idiosyncratic patterns of brain activity, or "idiosynchrony". Specifically, we outline the emerging technique of inter-subject representational similarity analysis (IS-RSA), including its theoretical motivation and an empirical demonstration of how it recovers brain-behavior relationships during movie watching using data from the Human Connectome Project. We also consider how stimulus choice may affect the individual signal and discuss areas for future research. We argue that naturalistic neuroimaging paradigms have the potential to reveal meaningful individual differences above and beyond those observed during traditional tasks or at rest.

Toward Neurosubtypes in Autism

There is a consensus that substantial heterogeneity underlies the neurobiology of autism spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of variation at the molecular, cellular, and brain network domains is a prerequisite for identifying biomarkers. Neuroimaging has been widely used to characterize atypical brain patterns in ASD, although findings have varied across studies. This is due, at least in part, to a failure to account for neurobiological heterogeneity. Here, we summarize emerging data-driven efforts to delineate more homogeneous ASD subgroups at the level of brain structure and function-that is, neurosubtyping. We break this pursuit into key methodological steps: the selection of diagnostic samples, neuroimaging features, algorithms, and validation approaches. Although preliminary and methodologically diverse, current studies generally agree that at least 2 to 4 distinct ASD neurosubtypes may exist. Their identification improved symptom prediction and diagnostic label accuracy above and beyond group average comparisons. Yet, this nascent literature has shed light onto challenges and gaps. These include 1) the need for wider and more deeply transdiagnostic samples collected while minimizing artifacts (e.g., head motion), 2) quantitative and unbiased methods for feature selection and multimodal fusion, 3) greater emphasis on algorithms' ability to capture hybrid dimensional and categorical models of ASD, and 4) systematic independent replications and validations that integrate different units of analyses across multiple scales. Solutions aimed to address these challenges and gaps are discussed for future avenues leading toward a comprehensive understanding of the mechanisms underlying ASD heterogeneity.

Processing of Real-World, Dynamic Natural Stimuli in Autism is Linked to Corticobasal Function

Many individuals with autism spectrum disorder (ASD) have been shown to perceive everyday sensory information differently compared to peers without autism. Research examining these sensory differences has primarily utilized nonnatural stimuli or natural stimuli using static photos with few having utilized dynamic, real-world nonverbal stimuli. Therefore, in this study, we used functional magnetic resonance imaging to characterize brain activation of individuals with high-functioning autism when viewing and listening to a video of a real-world scene (a person bouncing a ball) and anticipating the bounce. We investigated both multisensory and unisensory processing and hypothesized that individuals with ASD would show differential activation in (a) primary auditory and visual sensory cortical and association areas, and in (b) cortical and subcortical regions where auditory and visual information is integrated (e.g. temporal-parietal junction, pulvinar, superior colliculus). Contrary to our hypotheses, the whole-brain analysis revealed similar activation between the groups in these brain regions. However, compared to controls the ASD group showed significant hypoactivation in the left intraparietal sulcus and left putamen/globus pallidus. We theorize that this hypoactivation reflected underconnectivity for mediating spatiotemporal processing of the visual biological motion stimuli with the task demands of anticipating the timing of the bounce event. The paradigm thus may have tapped into a specific left-lateralized aberrant corticobasal circuit or loop involved in initiating or inhibiting motor responses. This was consistent with a dual "when versus where" psychophysical model of corticobasal function, which may reflect core differences in sensory processing of real-world, nonverbal natural stimuli in ASD. Autism Res 2020, 13: 539-549. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: To understand how individuals with autism perceive the real-world, using magnetic resonance imaging we examined brain activation in individuals with autism while watching a video of someone bouncing a basketball. Those with autism had similar activation to controls in auditory and visual sensory brain regions, but less activation in an area that processes information about body movements and in a region involved in modulating movements. These areas are important for understanding the actions of others and developing social skills.

Time-resolved effective connectivity in task fMRI: Psychophysiological interactions of Co-Activation patterns

Investigating context-dependent modulations of Functional Connectivity (FC) with functional magnetic resonance imaging is crucial to reveal the neurological underpinnings of cognitive processing. Most current analysis methods hypothesise sustained FC within the duration of a task, but this assumption has been shown too limiting by recent imaging studies. While several methods have been proposed to study functional dynamics during rest, task-based studies are yet to fully disentangle network modulations. Here, we propose a seed-based method to probe task-dependent modulations of brain activity by revealing Psychophysiological Interactions of Co-activation Patterns (PPI-CAPs). This point process-based approach temporally decomposes task-modulated connectivity into dynamic building blocks which cannot be captured by current methods, such as PPI or Dynamic Causal Modelling. Additionally, it identifies the occurrence of co-activation patterns at single frame resolution as opposed to window-based methods. In a naturalistic setting where participants watched a TV program, we retrieved several patterns of co-activation with a posterior cingulate cortex seed whose occurrence rates and polarity varied depending on the context; on the seed activity; or on an interaction between the two. Moreover, our method exposed the consistency in effective connectivity patterns across subjects and time, allowing us to uncover links between PPI-CAPs and specific stimuli contained in the video. Our study reveals that explicitly tracking connectivity pattern transients is paramount to advance our understanding of how different brain areas dynamically communicate when presented with a set of cues.

Neural responses in autism during movie watching: Inter-individual response variability co-varies with symptomatology

Naturalistic movie paradigms are exquisitely dynamic by nature, yet dedicated analytical methods typically remain static. Here, we deployed a dynamic inter-subject functional correlation (ISFC) analysis to study movie-driven functional brain changes in a population of male young adults diagnosed with autism spectrum disorder (ASD). We took inspiration from the resting-state research field in generating a set of whole-brain ISFC states expressed by the analysed ASD and typically developing (TD) subjects along time. Change points of state expression often involved transitions between different scenes of the movie, resulting in the reorganisation of whole-brain ISFC patterns to recruit different functional networks. Both subject populations showed idiosyncratic state expression at dedicated time points, but only TD subjects were also characterised by episodes of homogeneous recruitment. The temporal fluctuations in both quantities, as well as in cross-population dissimilarity, were tied to contextual movie cues. The prominent idiosyncrasy seen in ASD subjects was linked to individual symptomatology by partial least squares analysis, as different temporal sequences of ISFC states were expressed by subjects suffering from social and verbal communication impairments, as opposed to nonverbal communication deficits and stereotypic behaviours. Furthermore, the temporal expression of several of these states was correlated with the movie context, the presence of faces on screen, or overall luminosity. Overall, our results support the use of dynamic analytical frameworks to fully exploit the information obtained by naturalistic stimulation paradigms. They also show that autism should be understood as a multi-faceted disorder, in which the functional brain alterations seen in a given subject will vary as a function of the extent and balance of expressed symptoms.

ADHD desynchronizes brain activity during watching a distracted multi-talker conversation

Individuals with attention-deficit/hyperactivity disorder (ADHD) have difficulties navigating dynamic everyday situations that contain multiple sensory inputs that need to either be attended to or ignored. As conventional experimental tasks lack this type of everyday complexity, we administered a film-based multi-talker condition with auditory distractors in the background. ADHD-related aberrant brain responses to this naturalistic stimulus were identified using intersubject correlations (ISCs) in functional magnetic resonance imaging (fMRI) data collected from 51 adults with ADHD and 29 healthy controls. A novel permutation-based approach introducing studentized statistics and subject-wise voxel-level null-distributions revealed that several areas in cerebral attention networks and sensory cortices were desynchronized in participants with ADHD (n = 20) relative to healthy controls (n = 20). Specifically, desynchronization of the posterior parietal cortex occurred when irrelevant speech or music was presented in the background, but not when irrelevant white noise was presented, or when there were no distractors. We also show regionally distinct ISC signatures for inattention and impulsivity. Finally, post-scan recall of the film contents was associated with stronger ISCs in the default-mode network for the ADHD and in the dorsal attention network for healthy controls. The present study shows that ISCs can further our understanding of how a complex environment influences brain states in ADHD.

The brain's functional connectome in young children with prenatal alcohol exposure

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We used fMRI to study young children with prenatal alcohol exposure (PAE).

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We measured the functional connectome and its stability within and across participants.

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The PAE group had similar graph theory metrics to controls.

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The PAE group, but not controls, had increasing intra-participant stability with age.

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Controls, but not the PAE group, had increasing inter-participant stability with age.

Prenatal alcohol exposure (PAE) can lead to altered brain function and structure, as well as lifelong cognitive, behavioral, and mental health difficulties. Previous research has shown reduced brain network efficiency in older children and adolescents with PAE, but no imaging studies have examined brain differences in young children with PAE, at an age when cognitive and behavioral problems often first become apparent. The present study aimed to investigate the brain's functional connectome in young children with PAE using passive viewing fMRI. We analyzed 34 datasets from 26 children with PAE aged 2–7 years and 215 datasets from 87 unexposed typically-developing children in the same age range. The whole brain functional connectome was constructed using functional connectivity analysis across 90 regions for each dataset. We examined intra- and inter-participant stability of the functional connectome, graph theoretical measurements, and their correlations with age. Children with PAE had similar inter- and intra-participant stability to controls. However, children with PAE, but not controls, showed increasing intra-participant stability with age, suggesting a lack of variability of intrinsic brain activity over time. Inter-participant stability increased with age in controls but not in children with PAE, indicating more variability of brain function across the PAE population. Global graph metrics were similar between children with PAE and controls, in line with previous studies in older children. This study characterizes the functional connectome in young children with PAE for the first time, suggesting that the increased brain variability seen in older children develops early in childhood, when participants with PAE fail to show the expected age-related increases in inter-individual stability.

Dynamic causal modelling of fluctuating connectivity in resting-state EEG

Functional and effective connectivity are known to change systematically over time. These changes might be explained by several factors, including intrinsic fluctuations in activity-dependent neuronal coupling and contextual factors, like experimental condition and time. Furthermore, contextual effects may be subject-specific or conserved over subjects. To characterize fluctuations in effective connectivity, we used dynamic causal modelling (DCM) of cross spectral responses over 1- min of electroencephalogram (EEG) recordings during rest, divided into 1-sec windows. We focused on two intrinsic networks: the default mode and the saliency network. DCM was applied to estimate connectivity in each time-window for both networks. Fluctuations in DCM connectivity parameters were assessed using hierarchical parametric empirical Bayes (PEB). Within-subject, between-window effects were modelled with a second-level linear model with temporal basis functions as regressors. This procedure was conducted for every subject separately. Bayesian model reduction was then used to assess which (combination of) temporal basis functions best explain dynamic connectivity over windows. A third (between-subject) level model was used to infer which dynamic connectivity parameters are conserved over subjects. Our results indicate that connectivity fluctuations in the default mode network and to a lesser extent the saliency network comprised both subject-specific components and a common component. For both networks, connections to higher order regions appear to monotonically increase during the 1- min period. These results not only establish the predictive validity of dynamic connectivity estimates - in virtue of detecting systematic changes over subjects - they also suggest a network-specific dissociation in the relative contribution of fluctuations in connectivity that depend upon experimental context. We envisage these procedures could be useful for characterizing brain state transitions that may be explained by their cognitive or neuropathological underpinnings.

Movies in the magnet: Naturalistic paradigms in developmental functional neuroimaging

The use of movie-watching as an acquisition state for functional connectivity (FC) MRI has recently enabled multiple groups to obtain rich data sets in younger children with both substantial sample sizes and scan durations. Using naturalistic paradigms such as movies has also provided analytic flexibility for these developmental studies that extends beyond conventional resting state approaches. This review highlights the advantages and challenges of using movies for developmental neuroimaging and explores some of the methodological issues involved in designing pediatric studies with movies. Emerging themes from movie-watching studies are discussed, including an emphasis on intersubject correlations, developmental changes in network interactions under complex naturalistic conditions, and dynamic age-related changes in both sensory and higher-order network FC even in narrow age ranges. Converging evidence suggests an enhanced ability to identify brain-behavior correlations in children when using movie-watching data relative to both resting state and conventional tasks. Future directions and cautionary notes highlight the potential and the limitations of using movies to study FC in pediatric populations.

Brain imaging of locomotion in neurological conditions

Impaired locomotion is a frequent and major source of disability in patients with neurological conditions. Different neuroimaging methods have been used to understand the brain substrates of locomotion in various neurological diseases (mainly in Parkinson's disease) during actual walking, and while resting (using mental imagery of gait, or brain-behavior correlation analyses). These studies, using structural (i.e., MRI) or functional (i.e., functional MRI or functional near infra-red spectroscopy) brain imaging, electrophysiology (i.e., EEG), non-invasive brain stimulation (i.e., transcranial magnetic stimulation, or transcranial direct current stimulation) or molecular imaging methods (i.e., PET, or SPECT) reveal extended brain networks involving both grey and white matters in key cortical (i.e., prefrontal cortex) and subcortical (basal ganglia and cerebellum) regions associated with locomotion. However, the specific roles of the various pathophysiological mechanisms encountered in each neurological condition on the phenotype of gait disorders still remains unclear. After reviewing the results of individual brain imaging techniques across the common neurological conditions, such as Parkinson's disease, dementia, stroke, or multiple sclerosis, we will discuss how the development of new imaging techniques and computational analyses that integrate multivariate correlations in "large enough datasets" might help to understand how individual pathophysiological mechanisms express clinically as an abnormal gait. Finally, we will explore how these new analytic methods could drive our rehabilitative strategies.

Brain dynamics in ASD during movie-watching show idiosyncratic functional integration and segregation

To refine our understanding of autism spectrum disorders (ASD), studies of the brain in dynamic, multimodal and ecological experimental settings are required. One way to achieve this is to compare the neural responses of ASD and typically developing (TD) individuals when viewing a naturalistic movie, but the temporal complexity of the stimulus hampers this task, and the presence of intrinsic functional connectivity (FC) may overshadow movie‐driven fluctuations. Here, we detected inter‐subject functional correlation (ISFC) transients to disentangle movie‐induced functional changes from underlying resting‐state activity while probing FC dynamically. When considering the number of significant ISFC excursions triggered by the movie across the brain, connections between remote functional modules were more heterogeneously engaged in the ASD population. Dynamically tracking the temporal profiles of those ISFC changes and tying them to specific movie subparts, this idiosyncrasy in ASD responses was then shown to involve functional integration and segregation mechanisms such as response inhibition, background suppression, or multisensory integration, while low‐level visual processing was spared. Through the application of a new framework for the study of dynamic experimental paradigms, our results reveal a temporally localized idiosyncrasy in ASD responses, specific to short‐lived episodes of long‐range functional interplays.