Cortical signatures of auditory object binding in children with autism spectrum disorder are anomalous in concordance with behavior and diagnosis.

Organizing sensory information into coherent perceptual objects is fundamental to everyday perception and communication. In the visual domain, indirect evidence from cortical responses suggests that children with autism spectrum disorder (ASD) have anomalous figure-ground segregation. While auditory processing abnormalities are common in ASD, especially in environments with multiple sound sources, to date, the question of scene segregation in ASD has not been directly investigated in audition. Using magnetoencephalography, we measured cortical responses to unattended (passively experienced) auditory stimuli while parametrically manipulating the degree of temporal coherence that facilitates auditory figure-ground segregation. Results from 21 children with ASD (aged 7-17 years) and 26 age- and IQ-matched typically developing children provide evidence that children with ASD show anomalous growth of cortical neural responses with increasing temporal coherence of the auditory figure. The documented neurophysiological abnormalities did not depend on age, and were reflected both in the response evoked by changes in temporal coherence of the auditory scene and in the associated induced gamma rhythms. Furthermore, the individual neural measures were predictive of diagnosis (83% accuracy) and also correlated with behavioral measures of ASD severity and auditory processing abnormalities. These findings offer new insight into the neural mechanisms underlying auditory perceptual deficits and sensory overload in ASD, and suggest that temporal-coherence-based auditory scene analysis and suprathreshold processing of coherent auditory objects may be atypical in ASD.

Both stronger and weaker cerebro-cerebellar functional connectivity patterns during processing of spoken sentences in autism spectrum disorder.

Cerebellar differences have long been documented in autism spectrum disorder (ASD), yet the extent to which such differences might impact language processing in ASD remains unknown. To investigate this, we recorded brain activity with magnetoencephalography (MEG) while ASD and age-matched typically developing (TD) children passively processed spoken meaningful English and meaningless Jabberwocky sentences. Using a novel source localization approach that allows higher resolution MEG source localization of cerebellar activity, we found that, unlike TD children, ASD children showed no difference between evoked responses to meaningful versus meaningless sentences in right cerebellar lobule VI. ASD children also had atypically weak functional connectivity in the meaningful versus meaningless speech condition between right cerebellar lobule VI and several left-hemisphere sensorimotor and language regions in later time windows. In contrast, ASD children had atypically strong functional connectivity for in the meaningful versus meaningless speech condition between right cerebellar lobule VI and primary auditory cortical areas in an earlier time window. The atypical functional connectivity patterns in ASD correlated with ASD severity and the ability to inhibit involuntary attention. These findings align with a model where cerebro-cerebellar speech processing mechanisms in ASD are impacted by aberrant stimulus-driven attention, which could result from atypical temporal information and predictions of auditory sensory events by right cerebellar lobule VI.

Discrepancy between high non-verbal intelligence and low accuracy at reading emotional expressions in the eyes reflects the magnitude of social-emotional difficulties in autism.

Many so-called "high functioning" autistic individuals struggle with daily living skills, and have poorer than expected adult outcomes in employment, relationships, and quality of life. Significant discrepancies between non-verbal intelligence and emotional processing can be observed in autism, but the role of the magnitude of this gap in achieving potential psychosocial outcome is not known. Here, we show in a large group of participants (n = 107), that only among those with an autism diagnosis (n = 33), the gap between non-verbal intelligence (as measured by Raven's matrices) and the ability to perform the Reading the Mind in the Eyes test significantly predicts self-perceived emotional/social difficulties as assessed by the Empathy Quotient. Our results suggest that it is specifically the magnitude of the gap between (high) levels of abstract reasoning skills and poor proficiency in reading emotions expressed by the eyes that predicts self-perceived difficulties in emotional and social interactions among adults with autism. A better understanding of the underlying causes of the discrepancy between potential and actual psychosocial outcomes is the first step toward developing the most appropriate support for this vulnerable population, and our study offers some potentially important insights in this regard.

Maturation trajectories of cortical resting-state networks depend on the mediating frequency band.

The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30 Hz) and gamma (31-80 Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediated networks, while local segregation increased with age in beta band mediated networks. Spatially, the hubs that changed in importance with age in the beta band mediated networks had relatively little overlap with those that showed the greatest changes in the gamma band mediated networks. These findings are relevant for our understanding of the neural mechanisms of cortical maturation, in both typical and atypical development.

Maturational trajectories of local and long-range functional connectivity in autism during face processing.

Autism spectrum disorder (ASD) is characterized neurophysiologically by, among other things, functional connectivity abnormalities in the brain. Recent evidence suggests that the nature of these functional connectivity abnormalities might not be uniform throughout maturation. Comparing between adolescents and young adults (ages 14-21) with ASD and age- and IQ-matched typically developing (TD) individuals, we previously documented, using magnetoencephalography (MEG) data, that local functional connectivity in the fusiform face areas (FFA) and long-range functional connectivity between FFA and three higher order cortical areas were all reduced in ASD. Given the findings on abnormal maturation trajectories in ASD, we tested whether these results extend to preadolescent children (ages 7-13). We found that both local and long-range functional connectivity were in fact normal in this younger age group in ASD. Combining the two age groups, we found that local and long-range functional connectivity measures were positively correlated with age in TD, but negatively correlated with age in ASD. Last, we showed that local functional connectivity was the primary feature in predicting age in ASD group, but not in the TD group. Furthermore, local functional connectivity was only correlated with ASD severity in the older group. These results suggest that the direction of maturation of functional connectivity for processing of faces from childhood to young adulthood is itself abnormal in ASD, and that during the processing of faces, these trajectory abnormalities are more pronounced for local functional connectivity measures than they are for long-range functional connectivity measures.

The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository.

The main objective of the multi-site Pediatric Imaging, Neurocognition, and Genetics (PING) study was to create a large repository of standardized measurements of behavioral and imaging phenotypes accompanied by whole genome genotyping acquired from typically-developing children varying widely in age (3 to 20 years). This cross-sectional study produced sharable data from 1493 children, and these data have been described in several publications focusing on brain and cognitive development. Researchers may gain access to these data by applying for an account on the PING portal and filing a data use agreement. Here we describe the recruiting and screening of the children and give a brief overview of the assessments performed, the imaging methods applied, the genetic data produced, and the numbers of cases for whom different data types are available. We also cite sources of more detailed information about the methods and data. Finally we describe the procedures for accessing the data and for using the PING data exploration portal.

Somatosensory cortex functional connectivity abnormalities in autism show opposite trends, depending on direction and spatial scale.

Functional connectivity is abnormal in autism, but the nature of these abnormalities remains elusive. Different studies, mostly using functional magnetic resonance imaging, have found increased, decreased, or even mixed pattern functional connectivity abnormalities in autism, but no unifying framework has emerged to date. We measured functional connectivity in individuals with autism and in controls using magnetoencephalography, which allowed us to resolve both the directionality (feedforward versus feedback) and spatial scale (local or long-range) of functional connectivity. Specifically, we measured the cortical response and functional connectivity during a passive 25-Hz vibrotactile stimulation in the somatosensory cortex of 20 typically developing individuals and 15 individuals with autism, all males and right-handed, aged 8-18, and the mu-rhythm during resting state in a subset of these participants (12 per group, same age range). Two major significant group differences emerged in the response to the vibrotactile stimulus. First, the 50-Hz phase locking component of the cortical response, generated locally in the primary (S1) and secondary (S2) somatosensory cortex, was reduced in the autism group (P < 0.003, corrected). Second, feedforward functional connectivity between S1 and S2 was increased in the autism group (P < 0.004, corrected). During resting state, there was no group difference in the mu-α rhythm. In contrast, the mu-ß rhythm, which has been associated with feedback connectivity, was significantly reduced in the autism group (P < 0.04, corrected). Furthermore, the strength of the mu-ß was correlated to the relative strength of 50 Hz component of the response to the vibrotactile stimulus (r = 0.78, P < 0.00005), indicating a shared aetiology for these seemingly unrelated abnormalities. These magnetoencephalography-derived measures were correlated with two different behavioural sensory processing scores (P < 0.01 and P < 0.02 for the autism group, P < 0.01 and P < 0.0001 for the typical group), with autism severity (P < 0.03), and with diagnosis (89% accuracy). A biophysically realistic computational model using data driven feedforward and feedback parameters replicated the magnetoencephalography data faithfully. The direct observation of both abnormally increased and abnormally decreased functional connectivity in autism occurring simultaneously in different functional connectivity streams, offers a potential unifying framework for the unexplained discrepancies in current findings. Given that cortical feedback, whether local or long-range, is intrinsically non-linear, while cortical feedforward is generally linear relative to the stimulus, the present results suggest decreased non-linearity alongside an increased veridical component of the cortical response in autism.

Local and long-range functional connectivity is reduced in concert in autism spectrum disorders.

Long-range cortical functional connectivity is often reduced in autism spectrum disorders (ASD), but the nature of local cortical functional connectivity in ASD has remained elusive. We used magnetoencephalography to measure task-related local functional connectivity, as manifested by coupling between the phase of alpha oscillations and the amplitude of gamma oscillations, in the fusiform face area (FFA) of individuals diagnosed with ASD and typically developing individuals while they viewed neutral faces, emotional faces, and houses. We also measured task-related long-range functional connectivity between the FFA and the rest of the cortex during the same paradigm. In agreement with earlier studies, long-range functional connectivity between the FFA and three distant cortical regions was reduced in the ASD group. However, contrary to the prevailing hypothesis in the field, we found that local functional connectivity within the FFA was also reduced in individuals with ASD when viewing faces. Furthermore, the strength of long-range functional connectivity was directly correlated to the strength of local functional connectivity in both groups; thus, long-range and local connectivity were reduced proportionally in the ASD group. Finally, the magnitude of local functional connectivity correlated with ASD severity, and statistical classification using local and long-range functional connectivity data identified ASD diagnosis with 90% accuracy. These results suggest that failure to entrain neuronal assemblies fully both within and across cortical regions may be characteristic of ASD.

Multimodal imaging of the self-regulating developing brain.

Self-regulation refers to the ability to control behavior, cognition, and emotions, and self-regulation failure is related to a range of neuropsychiatric problems. It is poorly understood how structural maturation of the brain brings about the gradual improvement in self-regulation during childhood. In a large-scale multicenter effort, 735 children (4-21 y) underwent structural MRI for quantification of cortical thickness and surface area and diffusion tensor imaging for quantification of the quality of major fiber connections. Brain development was related to a standardized measure of cognitive control (the flanker task from the National Institutes of Health Toolbox), a critical component of self-regulation. Ability to inhibit responses and impose cognitive control increased rapidly during preteen years. Surface area of the anterior cingulate cortex accounted for a significant proportion of the variance in cognitive performance. This finding is intriguing, because characteristics of the anterior cingulum are shown to be related to impulse, attention, and executive problems in neurodevelopmental disorders, indicating a neural foundation for self-regulation abilities along a continuum from normality to pathology. The relationship was strongest in the younger children. Properties of large-fiber connections added to the picture by explaining additional variance in cognitive control. Although cognitive control was related to surface area of the anterior cingulate independently of basic processes of mental speed, the relationship between white matter quality and cognitive control could be fully accounted for by speed. The results underscore the need for integration of different aspects of brain maturation to understand the foundations of cognitive development.

Association of common genetic variants in GPCPD1 with scaling of visual cortical surface area in humans.

Visual cortical surface area varies two- to threefold between human individuals, is highly heritable, and has been correlated with visual acuity and visual perception. However, it is still largely unknown what specific genetic and environmental factors contribute to normal variation in the area of visual cortex. To identify SNPs associated with the proportional surface area of visual cortex, we performed a genome-wide association study followed by replication in two independent cohorts. We identified one SNP (rs6116869) that replicated in both cohorts and had genome-wide significant association (P(combined) = 3.2 × 10(-8)). Furthermore, a metaanalysis of imputed SNPs in this genomic region identified a more significantly associated SNP (rs238295; P = 6.5 × 10(-9)) that was in strong linkage disequilibrium with rs6116869. These SNPs are located within 4 kb of the 5' UTR of GPCPD1, glycerophosphocholine phosphodiesterase GDE1 homolog (Saccharomyces cerevisiae), which in humans, is more highly expressed in occipital cortex compared with the remainder of cortex than 99.9% of genes genome-wide. Based on these findings, we conclude that this common genetic variation contributes to the proportional area of human visual cortex. We suggest that identifying genes that contribute to normal cortical architecture provides a first step to understanding genetic mechanisms that underlie visual perception.

Atypical cortical processing of bottom-up speech binding cues in children with autism spectrum disorders.

Individuals with autism spectrum disorder (ASD) commonly display speech processing abnormalities. Binding of acoustic features of speech distributed across different frequencies into coherent speech objects is fundamental in speech perception. Here, we tested the hypothesis that the cortical processing of bottom-up acoustic cues for speech binding may be anomalous in ASD. We recorded magnetoencephalography while ASD children (ages 7-17) and typically developing peers heard sentences of sine-wave speech (SWS) and modulated SWS (MSS) where binding cues were restored through increased temporal coherence of the acoustic components and the introduction of harmonicity. The ASD group showed increased long-range feedforward functional connectivity from left auditory to parietal cortex with concurrent decreased local functional connectivity within the parietal region during MSS relative to SWS. As the parietal region has been implicated in auditory object binding, our findings support our hypothesis of atypical bottom-up speech binding in ASD. Furthermore, the long-range functional connectivity correlated with behaviorally measured auditory processing abnormalities, confirming the relevance of these atypical cortical signatures to the ASD phenotype. Lastly, the group difference in the local functional connectivity was driven by the youngest participants, suggesting that impaired speech binding in ASD might be ameliorated upon entering adolescence.

No Differences in Auditory Steady-State Responses in Children with Autism Spectrum Disorder and Typically Developing Children.

Auditory steady-state response (ASSR) has been studied as a potential biomarker for abnormal auditory sensory processing in autism spectrum disorder (ASD), with mixed results. Motivated by prior somatosensory findings of group differences in inter-trial coherence (ITC) between ASD and typically developing (TD) individuals at twice the steady-state stimulation frequency, we examined ASSR at 25 and 50 as well as 43 and 86 Hz in response to 25-Hz and 43-Hz auditory stimuli, respectively, using magnetoencephalography. Data were recorded from 22 ASD and 31 TD children, ages 6-17 years. ITC measures showed prominent ASSRs at the stimulation and double frequencies, without significant group differences. These results do not support ASSR as a robust ASD biomarker of abnormal auditory processing in ASD. Furthermore, the previously observed atypical double-frequency somatosensory response in ASD did not generalize to the auditory modality. Thus, the hypothesis about modality-independent abnormal local connectivity in ASD was not supported.

Disconnectivity of the cortical ocular motor control network in autism spectrum disorders.

Response inhibition, or the suppression of prepotent but contextually inappropriate behaviors, is essential to adaptive, flexible responding. Individuals with autism spectrum disorders (ASD) consistently show deficient response inhibition during antisaccades. In our prior functional MRI study, impaired antisaccade performance was accompanied by reduced functional connectivity between the frontal eye field (FEF) and dorsal anterior cingulate cortex (dACC), regions critical to volitional ocular motor control. Here we employed magnetoencephalography (MEG) to examine the spectral characteristics of this reduced connectivity. We focused on coherence between FEF and dACC during the preparatory period of antisaccade and prosaccade trials, which occurs after the presentation of the task cue and before the imperative stimulus. We found significant group differences in alpha band mediated coherence. Specifically, neurotypical participants showed significant alpha band coherence between the right inferior FEF and right dACC and between the left superior FEF and bilateral dACC across antisaccade, prosaccade, and fixation conditions. Relative to the neurotypical group, ASD participants showed reduced coherence between these regions in all three conditions. Moreover, while neurotypical participants showed increased coherence between the right inferior FEF and the right dACC in preparation for an antisaccade compared to a prosaccade or fixation, ASD participants failed to show a similar increase in preparation for the more demanding antisaccade. These findings demonstrate reduced long-range functional connectivity in ASD, specifically in the alpha band. The failure in the ASD group to increase alpha band coherence with increasing task demand may reflect deficient top-down recruitment of additional neural resources in preparation to perform a difficult task.

Functional Significance of Human Resting-State Networks Hubs Identified Using MEG During the Transition From Childhood to Adulthood.

Cortical hubs identified within resting-state networks (RSNs), areas of the cortex that have a higher-than-average number of connections, are known to be critical to typical cognitive functioning and are often implicated in disorders leading to abnormal cognitive functioning. Functionally defined cortical hubs are also known to change with age in the developing, maturing brain, mostly based on studies carried out using fMRI. We have recently used magnetoencephalography (MEG) to study the maturation trajectories of RSNs and their hubs from age 7 to 29 in 131 healthy participants with high temporal resolution. We found that maturation trajectories diverge as a function of the underlying cortical rhythm. Specifically, we found the beta band (13-30 Hz)-mediated RSNs became more locally efficient with maturation, i.e., more organized into clusters and connected with nearby regions, while gamma (31-80 Hz)-mediated RSNs became more globally efficient with maturation, i.e., prioritizing faster signal transmission between distant cortical regions. We also found that different sets of hubs were associated with each of these networks. To better understand the functional significance of this divergence, we wanted to examine the cortical functions associated with the identified hubs that grew or shrunk with maturation within each of these networks. To that end, we analyzed the results of the prior study using Neurosynth, a platform for large-scale, automated synthesis of fMRI data that links brain coordinates with their probabilistically associated terms. By mapping the Neurosynth terms associated with each of these hubs, we found that maturing hubs identified in the gamma band RSNs were more likely to be associated with bottom-up processes while maturing hubs identified in the beta band RSNs were more likely to be associated with top-down functions. The results were consistent with the idea that beta band-mediated networks preferentially support the maturation of top-down processing, while the gamma band-mediated networks preferentially support the maturation of bottom-up processing.

Magnetoencephalography and electroencephalography can both detect differences in cortical responses to vibrotactile stimuli in individuals on the autism spectrum.

Autism Spectrum (AS) is defined primarily by differences in social interactions, with impairments in sensory processing also characterizing the condition. In the search for neurophysiological biomarkers associated with traits relevant to the condition, focusing on sensory processing offers a path that is likely to be translatable across populations with different degrees of ability, as well as into animal models and across imaging modalities. In a prior study, a somatosensory neurophysiological signature of AS was identified using magnetoencephalography (MEG). Specifically, source estimation results showed differences between AS and neurotypically developing (NTD) subjects in the brain response to 25-Hz vibrotactile stimulation of the right fingertips, with lower inter-trial coherence (ITC) observed in the AS group. Here, we examined whether these group differences can be detected without source estimation using scalp electroencephalography (EEG), which is more commonly available in clinical settings than MEG, and therefore offers a greater potential for clinical translation. To that end, we recorded simultaneous whole-head MEG and EEG in 14 AS and 10 NTD subjects (age 15-28 years) using the same vibrotactile paradigm. Based on the scalp topographies, small sets of left hemisphere MEG and EEG sensors showing the maximum overall ITC were selected for group comparisons. Significant differences between the AS and NTD groups in ITC at 25 Hz as well as at 50 Hz were recorded in both MEG and EEG sensor data. For each measure, the mean ITC was lower in the AS than in the NTD group. EEG ITC values correlated with behaviorally assessed somatosensory sensation avoiding scores. The results show that information about ITC from MEG and EEG signals have substantial overlap, and thus EEG sensor-based ITC measures of the AS somatosensory processing biomarker previously identified using source localized MEG data have a potential to be developed into clinical use in AS, thanks to the higher accessibility to EEG in clinical settings.

Altered maturation and atypical cortical processing of spoken sentences in autism spectrum disorder.

Autism spectrum disorder (ASD) is associated with widespread receptive language impairments, yet the neural mechanisms underlying these deficits are poorly understood. Neuroimaging has shown that processing of socially-relevant sounds, including speech and non-speech, is atypical in ASD. However, it is unclear how the presence of lexical-semantic meaning affects speech processing in ASD. Here, we recorded magnetoencephalography data from individuals with ASD (N = 22, ages 7-17, 4 females) and typically developing (TD) peers (N = 30, ages 7-17, 5 females) during unattended listening to meaningful auditory speech sentences and meaningless jabberwocky sentences. After adjusting for age, ASD individuals showed stronger responses to meaningless jabberwocky sentences than to meaningful speech sentences in the same left temporal and parietal language regions where TD individuals exhibited stronger responses to meaningful speech. Maturational trajectories of meaningful speech responses were atypical in temporal, but not parietal, regions in ASD. Temporal responses were associated with ASD severity, while parietal responses were associated with aberrant involuntary attentional shifting in ASD. Our findings suggest a receptive speech processing dysfunction in ASD, wherein unattended meaningful speech elicits abnormal engagement of the language system, while unattended meaningless speech, filtered out in TD individuals, engages the language system through involuntary attention capture.

Children with autism spectrum disorder show altered functional connectivity and abnormal maturation trajectories in response to inverted faces.

The processing of information conveyed by faces is a critical component of social communication. While the neurophysiology of processing upright faces has been studied extensively in autism spectrum disorder (ASD), less is known about the neurophysiological abnormalities associated with processing inverted faces in ASD. We used magnetoencephalography (MEG) to study both long-range and local functional connectivity, with the latter assessed using local cross-frequency coupling, in response to inverted faces stimuli, in 7-18 years old individuals with ASD and age and IQ matched typically developing (TD) individuals. We found abnormally reduced coupling between the phase of the alpha rhythm and the amplitude of the gamma rhythm in the fusiform face area (FFA) in response to inverted faces, as well as reduced long-range functional connectivity between the FFA and the inferior frontal gyrus (IFG) in response to inverted faces in the ASD group. These group differences were absent in response to upright faces. The magnitude of functional connectivity between the FFA and the IFG was significantly correlated with the severity of ASD, and FFA-IFG long-range functional connectivity increased with age in TD group, but not in the ASD group. Our findings suggest that both local and long-range functional connectivity are abnormally reduced in children with ASD when processing inverted faces, and that the pattern of abnormalities associated with the processing of inverted faces differs from the pattern of upright faces in ASD, likely due to the presumed greater reliance on top-down regulations necessary for efficient processing of inverted faces. LAY SUMMARY: We found alterations in the neurophysiological responses to inverted faces in children with ASD, that were not reflected in the evoked responses, and were not observed in the responses to upright faces. These alterations included reduced local functional connectivity in the fusiform face area (FFA), and decreased long-range alpha-band modulated functional connectivity between the FFA and the left IFG. The magnitude of long-range functional connectivity between the FFA and the inferior frontal gyrus was correlated with the severity of ASD.

Classification of evoked responses to inverted faces reveals both spatial and temporal cortical response abnormalities in Autism spectrum disorder.

The neurophysiology of face processing has been studied extensively in the context of social impairments associated with autism spectrum disorder (ASD), but the existing studies have concentrated mainly on univariate analyses of responses to upright faces, and, less frequently, inverted faces. The small number of existing studies on neurophysiological responses to inverted face in ASD have used univariate approaches, with divergent results. Here, we used a data-driven, classification-based, multivariate machine learning decoding approach to investigate the temporal and spatial properties of the neurophysiological evoked response for upright and inverted faces, relative to the neurophysiological evoked response for houses, a neutral stimulus. 21 (2 females) ASD and 29 (4 females) TD participants ages 7 to 19 took part in this study. Group level classification accuracies were obtained for each condition, using first the temporal domain of the evoked responses, and then the spatial distribution of the evoked responses on the cortical surface, each separately. We found that classification of responses to inverted neutral faces vs. houses was less accurate in ASD compared to TD, in both the temporal and spatial domains. In contrast, there were no group differences in the classification of evoked responses to upright neutral faces relative to houses. Using the classification in the temporal domain, lower decoding accuracies in ASD were found around 120 ms and 170 ms, corresponding the known components of the evoked responses to faces. Using the classification in the spatial domain, lower decoding accuracies in ASD were found in the right superior marginal gyrus (SMG), intra-parietal sulcus (IPS) and posterior superior temporal sulcus (pSTS), but not in core face processing areas. Importantly, individual classification accuracies from both the temporal and spatial classifiers correlated with ASD severity, confirming the relevance of the results to the ASD phenotype.

Spontaneously emerging cortical representations of visual attributes.

Spontaneous cortical activity--ongoing activity in the absence of intentional sensory input--has been studied extensively, using methods ranging from EEG (electroencephalography), through voltage sensitive dye imaging, down to recordings from single neurons. Ongoing cortical activity has been shown to play a critical role in development, and must also be essential for processing sensory perception, because it modulates stimulus-evoked activity, and is correlated with behaviour. Yet its role in the processing of external information and its relationship to internal representations of sensory attributes remains unknown. Using voltage sensitive dye imaging, we previously established a close link between ongoing activity in the visual cortex of anaesthetized cats and the spontaneous firing of a single neuron. Here we report that such activity encompasses a set of dynamically switching cortical states, many of which correspond closely to orientation maps. When such an orientation state emerged spontaneously, it spanned several hypercolumns and was often followed by a state corresponding to a proximal orientation. We suggest that dynamically switching cortical states could represent the brain's internal context, and therefore reflect or influence memory, perception and behaviour.

Permutation Statistics for Connectivity Analysis between Regions of Interest in EEG and MEG Data.

Connectivity estimates based on electroencephalography (EEG) and magnetoencephalography (MEG) are unique in their ability to provide neurophysiologically meaningful spectral and temporal information non-invasively. This multi-dimensional aspect of the MEG/EEG based connectivity increases the challenges of the analysis and interpretation of the data. Many MEG/EEG studies address this complexity by using a hypothesis-driven approach, which focuses on particular regions of interest (ROI). However, if an effect is distributed unevenly over a large ROI and variable across subjects, it may not be detectable using conventional methods. Here, we propose a novel approach, which enhances the statistical power for weak and spatially discontinuous effects. This results in the ability to identify statistically significant connectivity patterns with spectral, temporal, and spatial specificity while correcting for multiple comparisons using nonparametric permutation methods. We call this new approach the Permutation Statistics for Connectivity Analysis between ROI (PeSCAR). We demonstrate the processing steps with simulated and real human data. The open-source Matlab code implementing PeSCAR are provided online.