Taxonomic structure in a set of abstract concepts

A large portion of human knowledge comprises "abstract" concepts that lack readily perceivable properties (e.g., "love" and "justice"). Since abstract concepts lack such properties, they have historically been treated as an undifferentiated category of knowledge in the psychology and neuropsychology literatures. More recently, the categorical structure of abstract concepts is often explored using paradigms that ask participants to make explicit judgments about a set of concepts along dimensions that are predetermined by the experimenter. Such methods require the experimenter to select dimensions that are relevant to the concepts and further that people make explicit judgments that accurately reflect their mental representations. We bypassed these requirements by collecting two large sets of non-verbal and implicit judgments about which dimensions are relevant to the similarity between pairs of 50 abstract nouns to determine the representational space of the concepts. We then identified categories within the representational space using a clustering procedure that required categories to replicate across two independent data sets. In a separate experiment, we used automatic semantic priming to further validate the categories and to show that they are an improvement over categories that were defined within the same set of abstract concepts using explicit ratings along predetermined dimensions. These results demonstrate that abstract concepts can be characterized beyond their negative relation to concrete concepts and that categories of abstract concepts can be defined without using a priori dimensions for the concepts or explicit judgments from participants.

A functional parcellation of the whole brain in individuals with autism spectrum disorder reveals atypical patterns of network organization

BACKGROUND

Researchers studying autism spectrum disorder (ASD) lack a comprehensive map of the functional network topography in the ASD brain. We used high-quality resting state functional MRI (rs-fMRI) connectivity data and a robust parcellation routine to provide a whole-brain map of functional networks in a group of seventy individuals with ASD and a group of seventy typically developing (TD) individuals.

METHODS

The rs-fMRI data were collected using an imaging sequence optimized to achieve high temporal signal-to-noise ratio (tSNR) across the whole-brain. We identified functional networks using a parcellation routine that intrinsically incorporates stability and replicability of the networks by keeping only network distinctions that agree across halves of the data over multiple random iterations in each group. The groups were tightly matched on tSNR, in-scanner motion, age, and IQ.

RESULTS

We compared the maps from each group and found that functional networks in the ASD group are atypical in three seemingly related ways: 1) whole-brain connectivity patterns are less stable across voxels within multiple functional networks, 2) the cerebellum, subcortex, and hippocampus show weaker differentiation of functional subnetworks, and 3) subcortical structures and the hippocampus are atypically integrated with the neocortex.

CONCLUSIONS

These results were statistically robust and suggest that patterns of network connectivity between the neocortex and the cerebellum, subcortical structures, and hippocampus are atypical in ASD individuals.

Atypical connectivity aids conversation in autism

It is well-established that individuals with autism exhibit atypical functional brain connectivity. However, the role this plays in naturalistic social settings has remained unclear. Atypical patterns may reflect core deficits or may instead compensate for deficits and promote adaptive behavior. Distinguishing these possibilities requires measuring the 'typicality' of spontaneous behavior and determining how connectivity relates to it. Thirty-nine male participants (19 autism, 20 typically-developed) engaged in 115 spontaneous conversations with an experimenter during fMRI scanning. A classifier algorithm was trained to distinguish participants by diagnosis based on 81 semantic, affective and linguistic dimensions derived from their use of language. The algorithm's graded likelihood of a participant's group membership (autism vs. typically-developed) was used as a measure of task performance and compared with functional connectivity levels. The algorithm accurately classified participants and its scores correlated with clinician-observed autism signs (ADOS-2). In support of a compensatory role, greater functional connectivity between right inferior frontal cortex and left-hemisphere social communication regions correlated with more typical language behavior, but only for the autism group. We conclude that right inferior frontal functional connectivity increases in autism during communication reflect a neural compensation strategy that can be quantified and tested even without an a priori behavioral standard.

Persistent Frustration-Induced Reconfigurations of Brain Networks Predict Individual Differences in Irritability

OBJECTIVE

Aberrant responses to frustration are central mechanisms of pediatric irritability, which is a common reason for psychiatric consultation and a risk factor for affective disorders and suicidality. This pilot study aimed to characterize brain network configuration during and after frustration and test whether characteristics of networks formed during or after frustration relate to irritability.

METHOD

During functional magnetic resonance imaging, a transdiagnostic sample enriched for irritability (N = 66, mean age = 14.0 years, 50% female participants) completed a frustration-induction task flanked by pretask and posttask resting-state scans. We first tested whether and how the organization of brain regions (ie, nodes) into networks (ie, modules) changes during and after frustration. Then, using a train/test/held-out procedure, we aimed to predict past-week irritability from global efficiency (E_glob) (ie, capacity for parallel information processing) of these modules.

RESULTS

Two modules present in the baseline pretask resting-state scan (one encompassing anterior default mode and temporolimbic regions and one consisting of frontoparietal regions) contributed most to brain circuit reorganization during and after frustration. Only E_glob of modules in the posttask resting-state scans (ie, after frustration) predicted irritability symptoms. Self-reported irritability was predicted by E_glob of a frontotemporal-limbic module. Parent-reported irritability was predicted by E_glob of ventral-prefrontal-subcortical and somatomotor-parietal modules.

CONCLUSION

These pilot results suggest the importance of the postfrustration recovery period in the pathophysiology of irritability. E_glob in 3 specific posttask modules, involved in emotion processing, reward processing, or motor function, predicted irritability. These findings, if replicated, could represent specific intervention targets for irritability.

Maladaptive Laterality in Cortical Networks Related to Social Communication in Autism Spectrum Disorder

Neuroimaging studies of individuals with autism spectrum disorders (ASDs) consistently find an aberrant pattern of reduced laterality in brain networks that support functions related to social communication and language. However, it is unclear how the underlying functional organization of these brain networks is altered in ASD individuals. We tested four models of reduced laterality in a social communication network in 70 ASD individuals (14 females) and a control group of the same number of tightly matched typically developing (TD) individuals (19 females) using high-quality resting-state fMRI data and a method of measuring patterns of functional laterality across the brain. We found that a functionally defined social communication network exhibited the typical pattern of left laterality in both groups, whereas there was a significant increase in within- relative to across-hemisphere connectivity of homotopic regions in the right hemisphere in ASD individuals. Furthermore, greater within- relative to across-hemisphere connectivity in the left hemisphere was positively correlated with a measure of verbal ability in both groups, whereas greater within- relative to across-hemisphere connectivity in the right hemisphere in ASD, but not TD, individuals was negatively correlated with the same verbal measure. Crucially, these differences in patterns of laterality were not found in two other functional networks and were specifically correlated to a measure of verbal ability but not metrics of other core components of the ASD phenotype. These results suggest that previous reports of reduced laterality in social communication regions in ASD is because of the two hemispheres functioning more independently than seen in TD individuals, with the atypical right-hemisphere network component being maladaptive.SIGNIFICANCE STATEMENT A consistent neuroimaging finding in individuals with ASD is an aberrant pattern of reduced laterality of the brain networks that support functions related to social communication and language. We tested four models of reduced laterality in a social communication network in ASD individuals and a TD control group using high-quality resting-state fMRI data. Our results suggest that reduced laterality of social communication regions in ASD may be because of the two hemispheres functioning more independently than seen in TD individuals, with atypically greater within- than across-hemisphere connectivity in the right hemisphere being maladaptive.

Effective connectivity underlying neural and behavioral components of prism adaptation

Prism adaptation (PA) is a form of visuomotor training that produces both sensorimotor and cognitive aftereffects depending on the direction of the visual displacement. Recently, a neural framework explaining both types of PA-induced aftereffects has been proposed, but direct evidence for it is lacking. We employed Structural Equation Modeling (SEM), a form of effective connectivity analysis, to establish directionality among connected nodes of the brain network thought to subserve PA. The findings reveal two distinct network branches: (1) a loop involving connections from the parietal cortices to the right parahippocampal gyrus, and (2) a branch linking the lateral premotor cortex to the parahippocampal gyrus via the cerebellum. Like the sensorimotor aftereffects, the first branch exhibited qualitatively different modulations for left versus right PA, and critically, changes in these connections were correlated with the magnitude of the sensorimotor aftereffects. Like the cognitive aftereffects, changes in the second branch were qualitatively similar for left and right PA, with greater change for left PA and a trend correlation with cognitive aftereffects. These results provide direct evidence that PA is supported by two functionally distinct subnetworks, a parietal–temporal network responsible for sensorimotor aftereffects and a fronto-cerebellar network responsible for cognitive aftereffects.

Youth with Down syndrome display widespread increased functional connectivity during rest

Studies of resting-state functional connectivity in young people with Down syndrome (DS) have yielded conflicting results. Some studies have found increased connectivity while others have found a mix of increased and decreased connectivity. No studies have examined whole-brain connectivity at the voxel level in youth with DS during an eyes-open resting-state design. Additionally, no studies have examined the relationship between connectivity and network selectivity in youth with DS. Thus, the current study sought to fill this gap in the literature. Nineteen youth with DS (Mage = 16.5; range 7-23; 13 F) and 33 typically developing (TD) youth (Mage = 17.5; range 6-24; 18 F), matched on age and sex, completed a 5.25-min eyes-open resting-state fMRI scan. Whole-brain functional connectivity (average Pearson correlation of each voxel with every other voxel) was calculated for each individual and compared between groups. Network selectivity was then calculated and correlated with functional connectivity for the DS group. Results revealed that whole-brain functional connectivity was significantly higher in youth with DS compared to TD controls in widespread regions throughout the brain. Additionally, participants with DS had significantly reduced network selectivity compared to TD peers, and selectivity was significantly related to connectivity in all participants. Exploratory behavioral analyses revealed that regions showing increased connectivity in DS predicted Verbal IQ, suggesting differences in connectivity may be related to verbal abilities. These results indicate that network organization is disrupted in youth with DS such that disparate networks are overly connected and less selective, suggesting a potential target for clinical interventions.

A Comparison of Single- and Multi-Echo Processing of Functional MRI Data During Overt Autobiographical Recall

Recent years have seen an increase in the use of multi-echo fMRI designs by cognitive neuroscientists. Acquiring multiple echoes allows one to increase contrast-to-noise; reduce signal dropout and thermal noise; and identify nuisance signal components in BOLD data. At the same time, multi-echo acquisitions increase data processing complexity and may incur a cost to the temporal and spatial resolution of the acquired data. Here, we re-examine a multi-echo dataset previously analyzed using multi-echo independent components analysis (ME-ICA) and focused on hippocampal activity during the overtly spoken recall of recent and remote autobiographical memories. The goal of the present series of analyses was to determine if ME-ICA’s theoretical denoising benefits might lead to a practical difference in the overall conclusions reached. Compared to single-echo (SE) data, ME-ICA led to qualitatively different findings regarding hippocampal contributions to autobiographical recall: whereas the SE analysis largely failed to reveal hippocampal activity relative to an active baseline, ME-ICA results supported predictions of the Standard Model of Consolidation and a time limited hippocampal involvement. These data provide a practical example of the benefits multi-echo denoising in a naturalistic memory paradigm and demonstrate how they can be used to address long-standing theoretical questions.

Resting-State Correlations of Fatigue Following Military Deployment

OBJECTIVE

Persistent fatigue is common among military servicemembers returning from deployment, especially those with a history of mild traumatic brain injury (mTBI). The purpose of this study was to characterize fatigue following deployment using the Multidimensional Fatigue Inventory (MFI), a multidimensional self-report instrument. The study was developed to test the hypothesis that if fatigue involves disrupted effort/reward processing, this should manifest as altered basal ganglia functional connectivity as observed in other amotivational states.

METHODS

Twenty-eight current and former servicemembers were recruited and completed the MFI. All 28 participants had a history of at least one mTBI during deployment. Twenty-six participants underwent resting-state functional MRI. To test the hypothesis that fatigue was associated with basal ganglia functional connectivity, the investigators measured correlations between MFI subscale scores and the functional connectivity of the left and right caudate, the putamen, and the globus pallidus with the rest of the brain, adjusting for the presence of depression.

RESULTS

The investigators found a significant correlation between functional connectivity of the left putamen and bilateral superior frontal gyri and mental fatigue scores. No correlations with the other MFI subscales survived multiple comparisons correction.

CONCLUSIONS

This exploratory study suggests that mental fatigue in military servicemembers with a history of deployment with at least one mTBI may be related to increased striatal-prefrontal functional connectivity, independent of depression. A finding of effort/reward mismatch may guide future treatment approaches.

Resting-State Functional Connectivity and Psychopathology in Klinefelter Syndrome (47, XXY)

Klinefelter syndrome (47, XXY; henceforth: XXY syndrome) is a high-impact but poorly understood genetic risk factor for neuropsychiatric impairment. Here, we provide the first study to map alterations of functional brain connectivity in XXY syndrome and relate these changes to brain anatomy and psychopathology. We used resting-state functional magnetic resonance imaging data from 75 individuals with XXY and 84 healthy XY males to 1) implement a brain-wide screen for altered global resting-state functional connectivity (rsFC) in XXY versus XY males and 2) decompose these alterations through seed-based analysis. We then compared these rsFC findings with measures of regional brain anatomy, psychopathology, and cognition. XXY syndrome was characterized by increased global rsFC in the left dorsolateral prefrontal cortex (DLPFC)-reflecting DLPFC overconnectivity with diverse rsFC networks. Functional overconnectivity was partly coupled to co-occurring regional volumetric changes in XXY syndrome, and variation in DLPFC-precuneus rsFC was correlated with the severity of psychopathology. By providing the first view of altered rsFC in XXY syndrome and contextualizing observed changes relative to neuroanatomy and behavior, our study helps to advance biological understanding of XXY syndrome-both as a disorder in its own right and more broadly as a model of genetic risk for psychopathology.

A Data-Driven Functional Mapping of the Anterior Temporal Lobes

Although the anterior temporal lobe (ATL) comprises several anatomic and functional subdivisions, it is often reduced to a homogeneous theoretical entity, such as a domain-general convergence zone, or "hub," for semantic information. Methodological limitations are largely to blame for the imprecise mapping of function to structure in the ATL. There are two major obstacles to using fMRI to identify the precise functional organization of the ATL: the difficult choice of stimuli and tasks to activate, and dissociate, specific regions within the ATL; and poor signal quality because of magnetic field distortions near the sinuses. To circumvent these difficulties, we developed a data-driven parcellation routine using resting-state fMRI data (24 females, 64 males) acquired using a sequence that was optimized to enhance signal in the ATL. Focusing on patterns of functional connectivity between each ATL voxel and the rest of the brain, we found that the ATL comprises at least 34 distinct functional parcels that are arranged into bands along the lateral and ventral cortical surfaces, extending from the posterior temporal lobes into the temporal poles. In addition, the anterior region of the fusiform gyrus, most often cited as the location of the semantic hub, was found to be part of a domain-specific network associated with face and social processing, rather than a domain-general semantic hub. These findings offer a fine-grained functional map of the ATL and offer an initial step toward using more precise language to describe the locations of functional responses in this heterogeneous region of human cortex.SIGNIFICANCE STATEMENT The functional role of the anterior aspects of the temporal lobes (ATL) is a contentious issue. While it is likely that different regions within the ATL subserve unique cognitive functions, most studies revert to vaguely referring to particular functional regions as "the ATL," and, thus, the mapping of function to anatomy remains unclear. We used resting-state fMRI connectivity patterns between the ATL and the rest of the brain to reveal that the ATL comprises at least 34 distinct functional parcels that are organized into a three-level functional hierarchy. These results provide a detailed functional map of the anterior temporal lobes that can guide future research on how distinct regions within the ATL support diverse cognitive functions.

Enhanced inter-regional coupling of neural responses and repetition suppression provide separate contributions to long-term behavioral priming

Stimulus identification commonly improves with repetition over long delays ("repetition priming"), whereas neural activity commonly decreases ("repetition suppression"). Multiple models have been proposed to explain this brain-behavior relationship, predicting alterations in functional and/or effective connectivity (Synchrony and Predictive Coding models), in the latency of neural responses (Facilitation model), and in the relative similarity of neural representations (Sharpening model). Here, we test these predictions with fMRI during overt and covert naming of repeated and novel objects. While we find partial support for predictions of the Facilitation and Sharpening models in the left fusiform gyrus and left frontal cortex, the data were most consistent with the Synchrony model, with increased coupling between right temporoparietal and anterior cingulate cortex for repeated objects that correlated with priming magnitude across participants. Increased coupling and repetition suppression varied independently, each explaining unique variance in priming and requiring modifications of all current models.

Testosterone and Resting State Connectivity of the Parahippocampal Gyrus in Men With History of Deployment-Related Mild Traumatic Brain Injury

INTRODUCTION

The purpose of this study was to explore the effect of low testosterone level on whole-brain resting state (RS) connectivity in male veterans with symptoms such as sleep disturbance, fatiguability, pain, anxiety, irritability, or aggressiveness persisting after mild traumatic brain injury (mTBI). Follow-up analyses were performed to determine if sleep scores affected the results.

MATERIALS AND METHODS

In our cross-sectional design study, RS magnetic resonance imaging scans on 28 veterans were performed, and testosterone, sleep quality, mood, and post-traumatic stress symptoms were measured. For each participant, we computed the average correlation of each voxel's time-series with the rest of the voxels in the brain, then used AFNI's 3dttest++ on the group data to determine whether the effects of testosterone level on whole-brain connectivity were significant. We then performed follow-up region of interest-based RS analyses of testosterone, with and without sleep quality as a covariate. The study protocol was approved by the National Institute of Health's Combined Neuroscience Institutional Review Board.

RESULTS

Sixteen participants reported repeated blast exposure in theater, leading to symptoms; the rest reported exposure to a single blast or a nonblast TBI. Thirty-three percent had testosterone levels <300 ng/dL. Testosterone level was lower in participants who screened positive for post-traumatic stress disorder compared to those who screened negative, but it did not reach statistical significance. Whole-brain connectivity and testosterone level were positively correlated in the left parahippocampal gyrus (LPhG), especially in its connectivity with frontal areas, the lingual gyrus, cingulate, insula, caudate, and right parahippocampal gyrus. Further analysis revealed that the effect of testosterone on LPhG connectivity is only partially mediated by sleep quality. Sleep quality by itself had an effect on connectivity of the thalamus, cerebellum, precuneus, and posterior cingulate.

CONCLUSION

Lower testosterone levels were correlated with lower connectivity of the LPhG. Weaknesses of this study include a retrospective design based on self-report of mTBI and the lack of a control group without TBI. Without a control group or pre-injury testosterone measures, we were not able to attribute the rate of low testosterone in our participants to TBI per se. Also testosterone levels were checked only once. The high rate of low testosterone level that we found suggests there may be an association between low testosterone level and greater post-traumatic stress disorder symptoms following deployment, but the causality of the relationships between TBI and deployment stress, testosterone level, behavioral symptomatology, and LPhG connectivity remains to be determined. Our study on men with persistent symptoms postdeployment and post-mTBI may help us understand the role of low testosterone and sleep quality in persistent symptoms and may be important in developing therapeutic interventions. Our results highlight the role of the LPhG, as we found that whole-brain connectivity in that region was positively associated with testosterone level, with only a limited portion of that effect attributable to sleep quality.

Dynamic Content Reactivation Supports Naturalistic Autobiographical Recall in Humans

Humans can vividly recall and re-experience events from their past, and these are commonly referred to as episodic or autobiographical memories. fMRI experiments reliably associate autobiographical event recall with activity in a network of "default" or "core" brain regions. However, as prior studies have relied on covert (silent) recall procedures, current understanding may be hampered by methodological limitations that obscure dynamic effects supporting moment-to-moment content retrieval. Here, fMRI participants (N = 40) overtly (verbally) recalled memories for ∼2 min periods. The content of spoken descriptions was categorized using a variant of the Autobiographical Interview (AI) procedure (Levine et al., 2002) and temporally re-aligned with BOLD data so activity accompanying the recall of different details could be measured. Replicating prior work, sustained effects associated with autobiographical recall periods (which are insensitive to the moment-to-moment content of retrieval) fell primarily within canonical default network regions. Spoken descriptions were rich in episodic details, frequently focusing on physical entities, their ongoing activities, and their appearances. Critically, neural activity associated with recalling specific details (e.g., those related to people or places) was transient, broadly distributed, and grounded in category-selective cortex (e.g., regions related to social cognition or scene processing). Thus, although a single network may generally support the process of vivid event reconstruction, the structures required to provide detail-related information shift in a predictable manner that respects domain-level representations across the cortex.SIGNIFICANCE STATEMENT Humans can vividly recall memories of autobiographical episodes, a process thought to involve the reconstruction of numerous distinct event details. Yet how the brain represents a complex episode as it unfolds over time remains unclear and appears inconsistent across experimental traditions. One hurdle is the use of covert (silent) in-scanner recall to study autobiographical memory, which prevents experimenter knowledge of what information is being retrieved, and when, throughout the remembering process. In this experiment, participants overtly described autobiographical memories while undergoing fMRI. Activity associated with the recall and description of specific details was transient, broadly distributed, and grounded in category-selective cortex. Thus, it appears that as events unfold mentally, structures are dynamically reactivated to support vivid recollection.

Callosal anisotropy predicts attentional network changes after parietal inhibitory stimulation

Hemispatial neglect is thought to result from disruption of interhemispheric equilibrium. Right hemisphere lesions deactivate the right frontoparietal network and hyperactivate the left via release from interhemispheric inhibition. Support for this putative mechanism comes from neuropsychological evidence as well as transcranial magnetic stimulation (TMS) studies in healthy subjects, in whom right posterior parietal cortex (PPC) inhibition causes neglect-like, rightward, visuospatial bias. Concurrent TMS and fMRI after right PPC TMS show task-dependent changes but may fail to identify effects of stimulation in areas not directly activated by the specific task, complicating interpretations. We used resting-state functional connectivity (RSFC) after inhibitory TMS over the right PPC to examine changes in the networks underlying visuospatial attention and used diffusion-weighted imaging to measure the structural properties of relevant white matter pathways. In a crossover experiment in healthy individuals, we delivered continuous theta burst TMS to the right PPC and vertex as control condition. We hypothesized that PPC inhibitory stimulation would result in a rightward visuospatial bias, decrease frontoparietal RSFC, and increase the PPC RSFC with the attentional network in the left hemisphere. We also expected that individual differences in fractional anisotropy (FA) of the frontoparietal network and the callosal pathway between the PPCs would account for variability of the TMS-induced RSFC changes. As hypothesized, TMS over the right PPC caused a rightward shift in line bisection judgment and increased RSFC between the right PPC and the left superior temporal gyrus. This effect was inversely related to FA in the posterior corpus callosum. Local inhibition of the right PPC reshapes connectivity in the attentional network and depends significantly on interhemispheric connections.

Fast detection and reduction of local transient artifacts in resting-state fMRI

Image quality control (QC) is a critical and computationally intensive component of functional magnetic resonance imaging (fMRI). Artifacts caused by physiologic signals or hardware malfunctions are usually identified and removed during data processing offline, well after scanning sessions are complete. A system with the computational efficiency to identify and remove artifacts during image acquisition would permit rapid adjustment of protocols as issues arise during experiments. To improve the speed and accuracy of QC and functional image correction, we developed Fast Anatomy-Based Image Correction (Fast ANATICOR) with newly implemented nuisance models and an improved pipeline. We validated its performance on a dataset consisting of normal scans and scans containing known hardware-driven artifacts. Fast ANATICOR's increased processing speed may make real-time QC and image correction feasible as compared with the existing offline method.

Prism Adaptation Modulates Connectivity of the Intraparietal Sulcus with Multiple Brain Networks

Prism adaptation (PA) alters spatial cognition according to the direction of visual displacement by temporarily modifying sensorimotor mapping. Right-shifting prisms (right PA) improve neglect of left visual field in patients, possibly by decreasing activity in the left hemisphere and increasing it in the right. Left PA shifts attention rightward in healthy individuals by an opposite mechanism. However, functional imaging studies of PA are inconsistent, perhaps because of differing activation tasks. We measured resting-state functional connectivity (RSFC) in healthy individuals before and after PA. When contrasted, right versus left PA decreased RSFC in the spatial navigation network defined by the right posterior parietal cortex (PPC), hippocampus, and cerebellum. Within-PA-direction comparisons showed that right PA increased RSFC in subregions of the PPCs and between the PPCs and the right middle frontal gyrus and left PA decreased RSFC between these regions. Both right and left PA decreased RSFC between the PPCs and bilateral temporal areas. In summary, right PA increases connectivity in the right frontoparietal network and left PA produces essentially opposite effects. Furthermore, right, compared with left, PA modulates RSFC in the right hemisphere navigation network.

Changes in human brain dynamics during behavioral priming and repetition suppression

Behavioral responses to a perceptual stimulus are typically faster with repeated exposure to the stimulus (behavioral priming). This implicit learning mechanism is critical for survival but impaired in a variety of neurological disorders, including Alzheimer's disease. Many studies of the neural bases for behavioral priming have encountered an interesting paradox: in spite of faster behavioral responses, repeated stimuli usually elicit weaker neural responses (repetition suppression). Several neurophysiological models have been proposed to resolve this paradox, but noninvasive techniques for human studies have had insufficient spatial-temporal precision for testing their predictions. Here, we used the unparalleled precision of electrocorticography (ECoG) to analyze the timing and magnitude of task-related changes in neural activation and propagation while patients named novel vs repeated visual objects. Stimulus repetition was associated with faster verbal responses and decreased neural activation (repetition suppression) in ventral occipito-temporal cortex (VOTC) and left prefrontal cortex (LPFC). Interestingly, we also observed increased neural activation (repetition enhancement) in LPFC and other recording sites. Moreover, with analysis of high gamma propagation we observed increased top-down propagation from LPFC into VOTC, preceding repetition suppression. The latter results indicate that repetition suppression and behavioral priming are associated with strengthening of top-down network influences on perceptual processing, consistent with predictive coding models of repetition suppression, and they support a central role for changes in large-scale cortical dynamics in achieving more efficient and rapid behavioral responses.

Brain networks, dimensionality, and global signal averaging in resting-state fMRI: Hierarchical network structure results in low-dimensional spatiotemporal dynamics

One of the most controversial practices in resting-state fMRI functional connectivity studies is whether or not to regress out the global average brain signal (GS) during artifact removal. Some groups have argued that it is absolutely essential to regress out the GS in order to fully remove head motion, respiration, and other global imaging artifacts. Others have argued that removing the GS distorts the resulting correlation matrices and inappropriately alters the results of group comparisons and relationships to behavior. At the core of this argument is the assessment of dimensionality in terms of the number of brain networks with uncorrelated time series. If the dimensionality is high, then the distortions due to GS removal could be effectively negligible. In the current paper, we examine the dimensionality of resting-state fMRI data using principal component analyses (PCA) and network clustering analyses. In two independent datasets (Set 1: N = 62, Set 2: N = 32), scree plots of the eigenvalues level off at or prior to 10 principal components, with prominent elbows at 3 and 7 components. While network clustering analyses have previously demonstrated that numerous networks can be distinguished with high thresholding of the voxel-wise correlation matrices, lower thresholding reveals a lower-dimensional hierarchical structure, with the first prominent branch at 2 networks (corresponding to the previously described "task-positive"/"task-negative" distinction) and further stable subdivisions at 4, 7 and 17. Since inter-correlated time series within these larger branches do not cancel to zero when averaged, the hierarchical nature of the correlation structure results in low effective dimensionality. Consistent with this, partial correlation analyses revealed that network-specific variance remains present in the GS at each level of the hierarchy, accounting for at least 14-18% of the overall GS variance in each dataset. These results demonstrate that GS regression is expected to remove substantial portions of network-specific brain signals along with artifacts, not simply whole-brain signals corresponding to arousal levels. We highlight alternative means of controlling for residual global artifacts when not removing the GS.

Sex Differences in Resting-State Functional Connectivity of the Cerebellum in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is more prevalent in males than females, but the underlying neurobiology of this sex bias remains unclear. Given its involvement in ASD, its role in sensorimotor, cognitive, and socio-affective processes, and its developmental sensitivity to sex hormones, the cerebellum is a candidate for understanding this sex difference. The current study used resting-state functional magnetic resonance imaging (fMRI) to investigate sex-dependent differences in cortico-cerebellar organization in ASD. We collected resting-state fMRI scans from 47 females (23 ASD, 24 controls) and 120 males (56 ASD, 65 controls). Using a measure of global functional connectivity (FC), we ran a linear mixed effects analysis to determine whether there was a sex-by-diagnosis interaction in resting-state FC. Subsequent seed-based analyses from the resulting clusters were run to clarify the global connectivity effects. Two clusters in the bilateral cerebellum exhibited a diagnosis-by-sex interaction in global connectivity. These cerebellar clusters further showed a pattern of interaction with regions in the cortex, including bilateral fusiform, middle occipital, middle frontal, and precentral gyri, cingulate cortex, and precuneus. Post hoc tests revealed a pattern of cortico-cerebellar hyperconnectivity in ASD females and a pattern of hypoconnectivity in ASD males. Furthermore, cortico-cerebellar FC in females more closely resembled that of control males than that of control females. These results shed light on the sex-specific pathophysiology of ASD and are indicative of potentially divergent neurodevelopmental trajectories for each sex. This sex-dependent, aberrant cerebellar connectivity in ASD might also underlie some of the motor and/or socio-affective difficulties experienced by members of this population, but the symptomatic correlate(s) of these brain findings remain unknown.

Clinical Trial Registration: www.ClinicalTrials.gov, NIH Clinical Study Protocol 10-M-0027 (ZIA MH002920-09) identifier #NCT01031407

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

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

Overt social interaction and resting state in young adult males with autism: core and contextual neural features

Conversation is an important and ubiquitous social behaviour. Individuals with autism spectrum disorder (autism) without intellectual disability often have normal structural language abilities but deficits in social aspects of communication like pragmatics, prosody, and eye contact. Previous studies of resting state activity suggest that intrinsic connections among neural circuits involved with social processing are disrupted in autism, but to date no neuroimaging study has examined neural activity during the most commonplace yet challenging social task: spontaneous conversation. Here we used functional MRI to scan autistic males (n = 19) without intellectual disability and age- and IQ-matched typically developing control subjects (n = 20) while they engaged in a total of 193 face-to-face interactions. Participants completed two kinds of tasks: conversation, which had high social demand, and repetition, which had low social demand. Autistic individuals showed abnormally increased task-driven interregional temporal correlation relative to controls, especially among social processing regions and during high social demand. Furthermore, these increased correlations were associated with parent ratings of participants' social impairments. These results were then compared with previously-acquired resting state data (56 autism, 62 control subjects). While some interregional correlation levels varied by task or rest context, others were strikingly similar across both task and rest, namely increased correlation among the thalamus, dorsal and ventral striatum, somatomotor, temporal and prefrontal cortex in the autistic individuals, relative to the control groups. These results suggest a basic distinction. Autistic cortico-cortical interactions vary by context, tending to increase relative to controls during task and decrease during test. In contrast, striato- and thalamocortical relationships with socially engaged brain regions are increased in both task and rest, and may be core to the condition of autism.

Identifying task-general effects of stimulus familiarity in the parietal memory network

Studies of human memory have implicated a "parietal memory network" in the recognition of familiar stimuli. However, the automatic vs. top-down nature of information processing within this network is not yet understood. If the network processes stimuli automatically, one can expect repetition-related changes both when familiarity is central to an ongoing task and when it is task-irrelevant. Here, we tested this prediction in a group of 40 human subjects using fMRI. Subjects initially named 100 objects aloud in the scanner. They then repeated the same task with novel and previously-named objects intermixed (where familiarity was not task-relevant) and separately were asked to make old/new recognition decisions in response to pictures of novel and previously-named objects (where familiarity was central to task completion). Accuracy was matched across conditions, and voice reaction times reflected typical behavioral priming effects. Repetition enhancement effects were restricted primarily to parietal cortex-and in particular, the parietal memory network-and were task-general in nature, whereas repetition suppression effects were task-dependent and occurred primarily in frontal and ventral temporal cortex. Task context effects were also present in the parietal memory network and impacted responses to both novel and familiar items. We conclude by discussing implications of these findings with respect to current hypotheses regarding parietal contributions to memory retrieval.

Bilateral functional connectivity at rest predicts apraxic symptoms after left hemisphere stroke

Increasing evidence indicates that focal lesions following stroke cause alterations in connectivity among functional brain networks. Functional connectivity between hemispheres has been shown to be particularly critical for predicting stroke-related behavioral deficits and recovery of motor function and attention. Much less is known, however, about the relevance of interhemispheric functional connectivity for cognitive abilities like praxis that rely on strongly lateralized brain networks. In the current study, we examine correlations between symptoms of apraxia-a disorder of skilled action that cannot be attributed to lower-level sensory or motor impairments-and spontaneous, resting brain activity in functional MRI in chronic left hemisphere stroke patients and neurologically-intact control participants. Using a data-driven approach, we identified 32 regions-of-interest in which pairwise functional connectivity correlated with two distinct measures of apraxia, even when controlling for age, head motion, lesion volume, and other artifacts: overall ability to pantomime the typical use of a tool, and disproportionate difficulty pantomiming the use of tools associated with different, competing use and grasp-to-move actions (e.g., setting a kitchen timer versus picking it up). Better performance on both measures correlated with stronger interhemispheric functional connectivity. Relevant regions in the right hemisphere were often homologous to left hemisphere areas associated with tool use and action. Additionally, relative to overall pantomime accuracy, disproportionate difficulty pantomiming the use of tools associated with competing use and grasp actions was associated with weakened functional connectivity among a more strongly left-lateralized and peri-Sylvian set of brain regions. Finally, patient performance on both measures of apraxia was best predicted by a model that incorporated information about lesion location and functional connectivity, and functional connectivity continued to explain unique variance in behavior even after accounting for lesion loci. These results indicate that interhemispheric functional connectivity is relevant even for a strongly lateralized cognitive ability like praxis and emphasize the importance of the right hemisphere in skilled action.

Attenuated resting-state functional connectivity in patients with childhood- and adult-onset schizophrenia

BACKGROUND

Childhood-onset schizophrenia (COS) is a rare, severe form of the adult-onset disorder (AOS). Our previous resting-state fMRI study identified attenuated functional connectivity in COS compared with controls. Here, we ask whether COS and AOS patients and their siblings exhibit similar abnormalities of functional connectivity.

METHODS

A whole-brain, data-driven approach was used to assess resting-state functional connectivity differences in COS (patients/siblings/controls, n: 26/28/33) and AOS (n: 19/28/30). There were no significant differences in age, sex, or head motion across groups in each dataset and as designed, the COS dataset has a significantly lower age than the AOS.

RESULTS

Both COS and AOS patients showed decreased functional connectivity relative to controls among a wide set of brain regions (P<0.05, corrected), but their siblings did not. Decreased connectivity in COS and AOS patients showed no amplitude differences and was not modulated by age-at-onset or medication doses. Cluster analysis revealed that these regions fell into two large-scale networks: one sensorimotor network and one centered on default-mode network regions, but including higher-order cognitive areas only in COS. Decreased connectivity between these two networks was notable (P<0.05, corrected) for both patient groups.

CONCLUSIONS

A shared pattern of attenuated functional connectivity was found in COS and AOS, supporting the continuity of childhood-onset and adult-onset schizophrenia. Connections were altered between sensorimotor areas and default-mode areas in both COS and AOS, suggesting potential abnormalities in processes of self-monitoring and sensory prediction. The absence of substantial dysconnectivity in siblings indicates that attenuation is state-related.

Spatial Mechanisms within the Dorsal Visual Pathway Contribute to the Configural Processing of Faces

Human face recognition is often attributed to configural processing; namely, processing the spatial relationships among the features of a face. If configural processing depends on fine-grained spatial information, do visuospatial mechanisms within the dorsal visual pathway contribute to this process? We explored this question in human adults using functional magnetic resonance imaging and transcranial magnetic stimulation (TMS) in a same-different face detection task. Within localized, spatial-processing regions of the posterior parietal cortex, configural face differences led to significantly stronger activation compared to featural face differences, and the magnitude of this activation correlated with behavioral performance. In addition, detection of configural relative to featural face differences led to significantly stronger functional connectivity between the right FFA and the spatial processing regions of the dorsal stream, whereas detection of featural relative to configural face differences led to stronger functional connectivity between the right FFA and left FFA. Critically, TMS centered on these parietal regions impaired performance on configural but not featural face difference detections. We conclude that spatial mechanisms within the dorsal visual pathway contribute to the configural processing of facial features and, more broadly, that the dorsal stream may contribute to the veridical perception of faces.

Neural correlates of taste reactivity in autism spectrum disorder

Selective or 'picky' eating habits are common among those with autism spectrum disorder (ASD). These behaviors are often related to aberrant sensory experience in individuals with ASD, including heightened reactivity to food taste and texture. However, very little is known about the neural mechanisms that underlie taste reactivity in ASD. In the present study, food-related neural responses were evaluated in 21 young adult and adolescent males diagnosed with ASD without intellectual disability, and 21 typically-developing (TD) controls. Taste reactivity was assessed using the Adolescent/Adult Sensory Profile, a clinical self-report measure. Functional magnetic resonance imaging was used to evaluate hemodynamic responses to sweet (vs. neutral) tastants and food pictures. Subjects also underwent resting-state functional connectivity scans.The ASD and TD individuals did not differ in their hemodynamic response to gustatory stimuli. However, the ASD subjects, but not the controls, exhibited a positive association between self-reported taste reactivity and the response to sweet tastants within the insular cortex and multiple brain regions associated with gustatory perception and reward. There was a strong interaction between diagnostic group and taste reactivity on tastant response in brain regions associated with ASD pathophysiology, including the bilateral anterior superior temporal sulcus (STS). This interaction of diagnosis and taste reactivity was also observed in the resting state functional connectivity between the anterior STS and dorsal mid-insula (i.e., gustatory cortex).These results suggest that self-reported heightened taste reactivity in ASD is associated with heightened brain responses to food-related stimuli and atypical functional connectivity of primary gustatory cortex, which may predispose these individuals to maladaptive and unhealthy patterns of selective eating behavior.

Trial registration

(clinicaltrials.gov identifier) NCT01031407. Registered: December 14, 2009.

A theoretical rut: revisiting and critically evaluating the generalized under/over-connectivity hypothesis of autism

In 2004, two papers proposed that pervasive functional under-connectivity (Just et al., ) or a trade-off between excessive local connectivity at the cost of distal under-connectivity (Belmonte et al., ) characterizes atypical brain organization in autism. Here, we take stock of the most recent and rigorous functional and structural connectivity findings with a careful eye toward evaluating the extent to which they support these original hypotheses. Indeed, the empirical data do not support them. From rsfMRI studies in adolescents and adults, there is an emerging consensus regarding long-range functional connections indicating cortico-cortical under-connectivity, specifically involving the temporal lobes, combined with subcortical-cortical over-connectivity. In contrast, there is little to no consensus regarding local functional connectivity or findings from task-based functional connectivity studies. The structural connectivity data suggest that white matter tracts are pervasively weak, particularly in the temporal lobe. Together, these findings are revealing how deeply complex the story is regarding atypical neural network organization in autism. In other words, distance and strength of connectivity as individual factors or as interacting factors do not consistently explain the patterns of atypical neural connectivity in autism. Therefore, we make several methodological recommendations and highlight developmental considerations that will help researchers in the field cultivate new hypotheses about the nature and mechanisms of potentially aberrant functional and structural connectivity in autism.

Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback

The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants’ awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns.

Even when we are at rest, our brains are always active. For example, areas of the brain involved in vision remain active in complete darkness. Different brain regions that connect together to perform a given task often show coordinated activity at rest. Past studies have shown that these resting connections are different in people with conditions such as autism. Some brain regions are more weakly connected while others are more strongly connected in people with autism spectrum disorder compared to those without. Furthermore, people with more severe symptoms seem to have more abnormal connections.

“Neurofeedback training” is a method of changing the resting connections between different brain regions. Scientists measure a brain signal – the connection between different brain regions – from a person in real time. They then provide positive feedback to the person if this signal improves. For example, if a connection that is too weak becomes stronger, the scientists might reinforce this by providing feedback on the success. Previous work has shown that neurofeedback training may even change people’s behaviour. However, it has not yet been explored as a method of treating the abnormal connections seen in people with autism when their brains are at rest.

To address this, Ramot et al. used a technique known as “functional magnetic resonance imaging” (or fMRI for short) to measure brain activity in young men with autism. First, certain brain regions were identified as having abnormal resting connections with each other. The participants were then asked to look at a blank screen and to try to reveal a picture hidden underneath. Whenever the connections between the chosen brain regions improved, part of the picture was revealed on the screen, accompanied by an upbeat sound. The participants were unaware that it was their brain signals causing this positive feedback.

This form of neurofeedback training successfully changed the abnormal brain connections in most of the participants with autism, making their connections more similar to those seen in the wider population. These effects lasted up to a year after training. Early results also suggest that these changes were related to improvements in symptoms, although further work is needed to see if doctors could reliably use this method as a therapy. These findings show that neurofeedback training could potentially help treat not only autism spectrum disorder, but a range of other disorders that involve abnormal brain connections, including depression and schizophrenia.

Intrinsic frequency biases and profiles across human cortex

Recent findings in monkeys suggest that intrinsic periodic spiking activity in selective cortical areas occurs at timescales that follow a sensory or lower order-to-higher order processing hierarchy (Murray JD, Bernacchia A, Freedman DJ, Romo R, Wallis JD, Cai X, Padoa-Schioppa C, Pasternak T, Seo H, Lee D, Wang XJ. Nat Neurosci 17: 1661-1663, 2014). It has not yet been fully explored if a similar timescale hierarchy is present in humans. Additionally, these measures in the monkey studies have not addressed findings that rhythmic activity within a brain area can occur at multiple frequencies. In this study we investigate in humans if regions may be biased toward particular frequencies of intrinsic activity and if a full cortical mapping still reveals an organization that follows this hierarchy. We examined the spectral power in multiple frequency bands (0.5-150 Hz) from task-independent data using magnetoencephalography (MEG). We compared standardized power across bands to find regional frequency biases. Our results demonstrate a mix of lower and higher frequency biases across sensory and higher order regions. Thus they suggest a more complex cortical organization that does not simply follow this hierarchy. Additionally, some regions do not display a bias for a single band, and a data-driven clustering analysis reveals a regional organization with high standardized power in multiple bands. Specifically, theta and beta are both high in dorsal frontal cortex, whereas delta and gamma are high in ventral frontal cortex and temporal cortex. Occipital and parietal regions are biased more narrowly toward alpha power, and ventral temporal lobe displays specific biases toward gamma. Thus intrinsic rhythmic neural activity displays a regional organization but one that is not necessarily hierarchical.NEW & NOTEWORTHY The organization of rhythmic neural activity is not well understood. Whereas it has been postulated that rhythms are organized in a hierarchical manner across brain regions, our novel analysis allows comparison of full cortical maps across different frequency bands, which demonstrate that the rhythmic organization is more complex. Additionally, data-driven methods show that rhythms of multiple frequencies or timescales occur within a particular region and that this nonhierarchical organization is widespread.

Convergent gustatory and viscerosensory processing in the human dorsal mid-insula

The homeostatic regulation of feeding behavior requires an organism to be able to integrate information from its internal environment, including peripheral visceral signals about the body's current energy needs, with information from its external environment, such as the palatability of energy-rich food stimuli. The insula, which serves as the brain's primary sensory cortex for representing both visceral signals from the body and taste signals from the mouth and tongue, is a likely candidate region in which this integration might occur. However, to date it has been unclear whether information from these two homeostatically critical faculties is merely co-represented in the human insula, or actually integrated there. Recent functional neuroimaging evidence of a common substrate for visceral interoception and taste perception within the human dorsal mid-insula suggests a model whereby a single population of neurons may integrate viscerosensory and gustatory signals. To test this model, we used fMRI-Adaptation to identify whether insula regions that exhibit repetition suppression following repeated interoception trials would then also exhibit adapted responses to subsequent gustatory stimuli. Multiple mid and anterior regions of the insula exhibited adaptation to interoceptive trials specifically, but only the dorsal mid-insula regions exhibited an adapted gustatory response following interoception. The discovery of this gustatory-interoceptive convergence within the neurons of the human insula supports the existence of a heretofore-undocumented neural pathway by which visceral signals from the periphery modulate the activity of brain regions involved in feeding behavior. Hum Brain Mapp 38:2150-2164, 2017. © 2017 Wiley Periodicals, Inc.

Canonical Cortical Circuit Model Explains Rivalry, Intermittent Rivalry, and Rivalry Memory

It has been shown that the same canonical cortical circuit model with mutual inhibition and a fatigue process can explain perceptual rivalry and other neurophysiological responses to a range of static stimuli. However, it has been proposed that this model cannot explain responses to dynamic inputs such as found in intermittent rivalry and rivalry memory, where maintenance of a percept when the stimulus is absent is required. This challenges the universality of the basic canonical cortical circuit. Here, we show that by including an overlooked realistic small nonspecific background neural activity, the same basic model can reproduce intermittent rivalry and rivalry memory without compromising static rivalry and other cortical phenomena. The background activity induces a mutual-inhibition mechanism for short-term memory, which is robust to noise and where fine-tuning of recurrent excitation or inclusion of sub-threshold currents or synaptic facilitation is unnecessary. We prove existence conditions for the mechanism and show that it can explain experimental results from the quartet apparent motion illusion, which is a prototypical intermittent rivalry stimulus.

When the brain is presented with an ambiguous stimulus like the Necker cube or what is known as the quartet illusion, the perception will alternate or rival between the possible interpretations. There are neurons in the brain whose activity is correlated with the perception and not the stimulus. Hence, perceptual rivalry provides a unique probe of cortical function and could possibly serve as a diagnostic tool for cognitive disorders such as autism. A mathematical model based on the known biology of the brain has been developed to account for perceptual rivalry when the stimulus is static. The basic model also accounts for other neural responses to stimuli that do not elicit rivalry. However, these models cannot explain illusions where the stimulus is intermittently switched on and off and the same perception returns after an off period because there is no built-in mechanism to hold the memory. Here, we show that the inclusion of experimentally observed low-level background neural activity is sufficient to explain rivalry for static inputs, and rivalry for intermittent inputs. We validate the model with new experiments.

Disrupted sensorimotor and social-cognitive networks underlie symptoms in childhood-onset schizophrenia

Schizophrenia is increasingly recognized as a neurodevelopmental disorder with altered connectivity among brain networks. In the current study we examined large-scale network interactions in childhood-onset schizophrenia, a severe form of the disease with salient genetic and neurobiological abnormalities. Using a data-driven analysis of resting-state functional magnetic resonance imaging fluctuations, we characterized data from 19 patients with schizophrenia and 26 typically developing controls, group matched for age, sex, handedness, and magnitude of head motion during scanning. This approach identified 26 regions with decreased functional correlations in schizophrenia compared to controls. These regions were found to organize into two function-related networks, the first with regions associated with social and higher-level cognitive processing, and the second with regions involved in somatosensory and motor processing. Analyses of across- and within-network regional interactions revealed pronounced across-network decreases in functional connectivity in the schizophrenia group, as well as a set of across-network relationships with overall negative coupling indicating competitive or opponent network dynamics. Critically, across-network decreases in functional connectivity in schizophrenia predicted the severity of positive symptoms in the disorder, such as hallucinations and delusions. By contrast, decreases in functional connectivity within the social-cognitive network of regions predicted the severity of negative symptoms, such as impoverished speech and flattened affect. These results point toward the role that abnormal integration of sensorimotor and social-cognitive processing may play in the pathophysiology and symptomatology of schizophrenia.

Insistence on sameness relates to increased covariance of gray matter structure in autism spectrum disorder

Background

Autism spectrum disorder (ASD) is characterized by atypical development of cortical and subcortical gray matter volume. Subcortical structural changes have been associated with restricted and repetitive behavior (RRB), a core component of ASD. Behavioral studies have identified insistence on sameness (IS) as a separable RRB dimension prominent in high-functioning ASD, though no simple brain-behavior relationship has emerged. Structural covariance, a measure of morphological coupling among brain regions using magnetic resonance imaging (MRI), has proven an informative measure of anatomical relationships in typical development and neurodevelopmental disorders. In this study, we use this measure to characterize the relationship between brain structure and IS.

Methods

We quantified the structural covariance of cortical and subcortical gray matter volume in 55 individuals with high-functioning ASD using 3T MRI. We then related these structural metrics to individual IS scores, as assessed by the Repetitive Behavior Scale-Revised (RBS-R).

Results

We found that increased coupling among subcortical regions and between subcortical and cortical regions related to greater IS symptom severity. Most pronounced, the striatum and amygdala participated in a plurality of identified relationships, indicating a central role for these structures in IS symptomatology. These structural associations were specific to IS and did not relate to any of the other RRB subcomponents measured by the RBS-R.

Conclusions

This study indicates that behavioral dimensions in ASD can relate to the coordination of development across multiple brain regions, which might be otherwise obscured using typical brain-behavior correlations. It also expands the structures traditionally related to RRB in ASD and provides neuroanatomical evidence supportive of IS as a separate RRB dimension.

Trial registration

ClinicalTrials.gov NCT01031407

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-015-0047-7) contains supplementary material, which is available to authorized users.

Object identification leads to a conceptual broadening of object representations in lateral prefrontal cortex

Recent experience identifying objects leads to later improvements in both speed and accuracy ("repetition priming"), along with simultaneous reductions of neural activity ("repetition suppression"). A popular interpretation of these joint behavioral and neural phenomena is that object representations become perceptually "sharper" with stimulus repetition, eliminating cells that are poorly stimulus-selective and responsive and reducing support for competing representations downstream. Here, we test this hypothesis in an fMRI-adaptation experiment using pictures of objects. Prior to fMRI, participants repeatedly named a set of object pictures. During fMRI, participants viewed adaptation sequences composed of rapidly repeated objects (3-6 repetitions over several seconds) that were either named previously or that were new for the fMRI session, followed by single "deviant" object pictures used to measure recovery from adaptation and that shared a relationship to the adapted picture (a different exemplar of the same object, a conceptual associate, or an unrelated picture). Effects of adaptation and recovery were found throughout visually responsive brain regions. Occipitotemporal cortical regions displayed repetition suppression to previously named relative to new adapters but failed to exhibit pronounced changes in neural tuning. In contrast, changes in the slope of the recovery curves were found in the left lateral prefrontal cortex: Greater residual adaptation was observed to exemplar stimuli and conceptual associates following previously named adapting stimuli, consistent with greater rather than reduced neural overlap among representations of conceptually related objects. Furthermore, this change in neural tuning was directly related to the proportion of conceptual errors made by participants in the naming sessions pre- and post-fMRI, establishing that the experience-dependent conceptual broadening of object representations seen in fMRI is also manifest in behavior. In a follow-up behavioral experiment, we further show that recent naming experience leads to greater semantic priming when using the previously named pictures as briefly presented primes. Taken together, our results fail to support perceptual sharpening as the primary mediator between repetition suppression and behavioral priming at durations typically used to study priming and instead highlight an experience-dependent broadening of conceptual representations. We suggest that alternative mechanisms, such as increases in neural synchronization, are more promising in explaining priming in the face of repetition suppression.

Practice structure improves unconscious transitional memories by increasing synchrony in a premotor network

Sequence learning relies on formation of unconscious transitional and conscious ordinal memories. The influence of practice type on formation of these memories that compose skill and systems level neural substrates is not known. Here, we studied learning of transitional and ordinal memories in participants trained on motor sequences while scanned using fMRI. Practice structure was varied or grouped (mixing or grouping sequences during training, respectively). Memory was assessed 30 min and 1 week later. Varied practice improved transitional memory and enhanced coupling of the dorsal premotor cortex with thalamus, cerebellum, and lingual and cingulate regions and greater transitional memory correlated with this coupling. Thus, varied practice improves unconscious transitional memories in proportion to coupling within a cortico-subcortical network linked to premotor cortex. This result indicates that practice structure influences unconscious transitional memory formation and identifies underlying systems level mechanisms.

Cerebro-cerebellar connectivity is increased in primary lateral sclerosis

Increased functional connectivity in resting state networks was found in several studies of patients with motor neuron disorders, although diffusion tensor imaging studies consistently show loss of white matter integrity. To understand the relationship between structural connectivity and functional connectivity, we examined the structural connections between regions with altered functional connectivity in patients with primary lateral sclerosis (PLS), a long-lived motor neuron disease. Connectivity matrices were constructed from resting state fMRI in 16 PLS patients to identify areas of differing connectivity between patients and healthy controls. Probabilistic fiber tracking was used to examine structural connections between regions of differing connectivity. PLS patients had 12 regions with increased functional connectivity compared to controls, with a predominance of cerebro-cerebellar connections. Increased functional connectivity was strongest between the cerebellum and cortical motor areas and between the cerebellum and frontal and temporal cortex. Fiber tracking detected no difference in connections between regions with increased functional connectivity. We conclude that functional connectivity changes are not strongly based in structural connectivity. Increased functional connectivity may be caused by common inputs, or by reduced selectivity of cortical activation, which could result from loss of intracortical inhibition when cortical afferents are intact.

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Functional connectivity is increased in primary lateral sclerosis.

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Functional connections with the cerebellum were prominent.

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Cortico-cerebellar connectivity correlated with clinical measures.

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No corresponding changes occurred in structural connectivity.

The nature and role of cortical feedback in perception, imagery, and synesthesia

In his Discussion Paper, Seth makes the case for counterfactual richness of predictive processing models in explaining perceptual presence and its absence in synesthetic concurrent percepts. Here, we question the relevance of counterfactual richness for these and related phenomena, and we argue that alternative theories of perception that incorporate top-down/bottom-up facilitatory interactions are at no relative disadvantage in addressing them.

Category-specific integration of homeostatic signals in caudal but not rostral human insula

Prevailing theories hold that the insula is functionally organized along its caudal-to-rostral axis, with posterior regions coding lower-level sensory information, and anterior regions coding higher-level stimulus significance relative to the body’s homeostatic needs. Contrary to predictions of this model, the response of the taste-sensitive region of the caudal, but not rostral, insula to food images was directly related to the body’s homeostatic state as indexed by levels of peripheral glucose.

Correcting brain-wide correlation differences in resting-state FMRI

Brain function in "resting" state has been extensively studied with functional magnetic resonance imaging (FMRI). However, drawing valid inferences, particularly for group comparisons, is fraught with pitfalls. Differing levels of brain-wide correlations can confound group comparisons. Global signal regression (GSReg) attempts to reduce this confound and is commonly used, even though it differentially biases correlations over brain regions, potentially leading to false group differences. We propose to use average brain-wide correlations as a measure of global correlation (GCOR), and examine the circumstances under which it can be used to identify or correct for differences in global fluctuations. In the process, we show the bias induced by GSReg to be a function only of the data's covariance matrix, and use simulations to compare corrections with GCOR as covariate to GSReg under various scenarios. We find that unlike GSReg, GCOR is a conservative approach that can reduce global variations, while avoiding the introduction of false significant differences, as GSReg can. However, as with GSReg, one cannot escape the interaction effect between the grouping variable and GCOR covariate on effect size. While GCOR is a complementary measure for resting state-FMRI applicable to legacy data, it is a lesser substitute for proper level-I denoising. We also assess the applicability of GCOR to empirical data with motion-based subject grouping and compare group differences to those using GSReg. We find that, while GCOR reduced correlation differences between high and low movers, it is doubtful that motion was the sole driver behind the differences in the first place.

The perils of global signal regression for group comparisons: a case study of Autism Spectrum Disorders

We have previously argued from a theoretical basis that the standard practice of regression of the Global Signal from the fMRI time series in functional connectivity studies is ill advised, particularly when comparing groups of participants. Here, we demonstrate in resting-state data from participants with an Autism Spectrum Disorder and matched controls that these concerns are also well founded in real data. Using the prior theoretical work to formulate predictions, we show: (1) rather than simply altering the mean or range of correlation values amongst pairs of brain regions, Global Signal Regression systematically alters the rank ordering of values in addition to introducing negative values, (2) it leads to a reversal in the direction of group correlation differences relative to other preprocessing approaches, with a higher incidence of both long-range and local correlation differences that favor the Autism Spectrum Disorder group, (3) the strongest group differences under other preprocessing approaches are the ones most altered by Global Signal Regression, and (4) locations showing group differences no longer agree with those showing correlations with behavioral symptoms within the Autism Spectrum Disorder group. The correlation matrices of both participant groups under Global Signal Regression were well predicted by our previous mathematical analyses, demonstrating that there is nothing mysterious about these results. Finally, when independent physiological nuisance measures are lacking, we provide a simple alternative approach for assessing and lessening the influence of global correlations on group comparisons that replicates our previous findings. While this alternative performs less well for symptom correlations than our favored preprocessing approach that includes removal of independent physiological measures, it is preferable to the use of Global Signal Regression, which prevents unequivocal conclusions about the direction or location of group differences.

Effective Preprocessing Procedures Virtually Eliminate Distance-Dependent Motion Artifacts in Resting State FMRI

Artifactual sources of resting-state (RS) FMRI can originate from head motion, physiology, and hardware. Of these sources, motion has received considerable attention and was found to induce corrupting effects by differentially biasing correlations between regions depending on their distance. Numerous corrective approaches have relied on the identification and censoring of high-motion time points and the use of the brain-wide average time series as a nuisance regressor to which the data are orthogonalized (Global Signal Regression, GSReg). We first replicate the previously reported head-motion bias on correlation coefficients using data generously contributed by Power et al. (2012). We then show that while motion can be the source of artifact in correlations, the distance-dependent bias-taken to be a manifestation of the motion effect on correlation-is exacerbated by the use of GSReg. Put differently, correlation estimates obtained after GSReg are more susceptible to the presence of motion and by extension to the levels of censoring. More generally, the effect of motion on correlation estimates depends on the preprocessing steps leading to the correlation estimate, with certain approaches performing markedly worse than others. For this purpose, we consider various models for RS FMRI preprocessing and show that WMe_LOCAL, as subset of the ANATICOR discussed by Jo et al. (2010), denoising approach results in minimal sensitivity to motion and reduces by extension the dependence of correlation results on censoring.

A procedure for testing across-condition rhythmic spike-field association change

Many experiments in neuroscience have compared the strength of association between neural spike trains and rhythms present in local field potential (LFP) recordings. The measure employed in these comparisons, "spike-field coherence", is a frequency dependent measure of linear association, and is shown to depend on overall neural activity (Lepage et al., 2011). Dependence upon overall neural activity, that is, dependence upon the total number of spikes, renders comparison of spike-field coherence across experimental context difficult. In this paper, an inferential procedure based upon a generalized linear model is shown to be capable of separating the effects of overall neural activity from spike train-LFP oscillatory coupling. This separation provides a means to compare the strength of oscillatory association between spike train-LFP pairs independent of differences in spike counts. Following a review of the generalized linear modelling framework of point process neural activity a specific class of generalized linear models are introduced. This model class, using either a piece-wise constant link function, or an exponential function to relate an LFP rhythm to neural response, is used to develop hypothesis tests capable of detecting changes in spike train-LFP oscillatory coupling. The performance of these tests is validated, both in simulation and on real data. The proposed method of inference provides a principled statistical procedure by which across-context change in spike train-LFP rhythmic association can be directly inferred that explicitly handles between-condition differences in total spike count.

Quantifying agreement between anatomical and functional interhemispheric correspondences in the resting brain

The human brain is composed of two broadly symmetric cerebral hemispheres, with an abundance of reciprocal anatomical connections between homotopic locations. However, to date, studies of hemispheric symmetries have not identified correspondency precisely due to variable cortical folding patterns. Here we present a method to establish accurate correspondency using position on the unfolded cortical surface relative to gyral and sulcal landmarks. The landmark method is shown to outperform the method of reversing standard volume coordinates, and it is used to quantify the functional symmetry in resting fMRI data throughout the cortex. Resting brain activity was found to be maximally correlated with locations less than 1 cm away on the cortical surface from the corresponding anatomical location in nearly half of the cortex. While select locations exhibited asymmetric patterns, precise symmetric relationships were found to be the norm, with fine-grained symmetric functional maps demonstrated in motor, occipital, and inferior frontal cortex.

Social perception in autism spectrum disorders: impaired category selectivity for dynamic but not static images in ventral temporal cortex

Studies of autism spectrum disorders (ASDs) reveal dysfunction in the neural systems mediating object processing (particularly faces) and social cognition, but few investigations have systematically assessed the specificity of the dysfunction. We compared cortical responses in typically developing adolescents and those with ASD to stimuli from distinct conceptual domains known to elicit category-related activity in separate neural systems. In Experiment 1, subjects made category decisions to photographs, videos, and point-light displays of people and tools. In Experiment 2, subjects interpreted displays of simple, geometric shapes in motion depicting social or mechanical interactions. In both experiments, we found a selective deficit in the ASD subjects for dynamic social stimuli (videos and point-light displays of people, moving geometric shapes), but not static images, in the functionally localized lateral region of the right fusiform gyrus, including the fusiform face area. In contrast, no group differences were found in response to either static images or dynamic stimuli in other brain regions associated with face and social processing (e.g. posterior superior temporal sulcus, amygdala), suggesting disordered connectivity between these regions and the fusiform gyrus in ASD. This possibility was confirmed by functional connectivity analysis.

Trouble at rest: how correlation patterns and group differences become distorted after global signal regression

Resting-state functional magnetic resonance imaging (RS-FMRI) holds the promise of revealing brain functional connectivity without requiring specific tasks targeting particular brain systems. RS-FMRI is being used to find differences between populations even when a specific candidate target for traditional inferences is lacking. However, the problem with RS-FMRI is a lacking definition of what constitutes noise and signal. RS-FMRI is easy to acquire but is not easy to analyze or draw inferences from. In this commentary we discuss a problem that is still treated lightly despite its significant impact on RS-FMRI inferences; global signal regression (GSReg), the practice of projecting out signal averaged over the entire brain, can change resting-state correlations in ways that dramatically alter correlation patterns and hence conclusions about brain functional connectedness. Although Murphy et al. in 2009 demonstrated that GSReg negatively biases correlations, the approach remains in wide use. We revisit this issue to argue the problem that GSReg is more than negative bias or the interpretability of negative correlations. Its usage can fundamentally alter interregional correlations within a group, or their differences between groups. We used an illustrative model to clearly convey our objections and derived equations formalizing our conclusions. We hope this creates a clear context in which counterarguments can be made. We conclude that GSReg should not be used when studying RS-FMRI because GSReg biases correlations differently in different regions depending on the underlying true interregional correlation structure. GSReg can alter local and long-range correlations, potentially spreading underlying group differences to regions that may never have had any. Conclusions also apply to substitutions of GSReg for denoising with decompositions of signals aggregated over the network's regions to the extent they cannot separate signals of interest from noise. We touch on the need for careful accounting of nuisance parameters when making group comparisons of correlation maps.

Fractionation of social brain circuits in autism spectrum disorders

Autism spectrum disorders are developmental disorders characterized by impairments in social and communication abilities and repetitive behaviours. Converging neuroscientific evidence has suggested that the neuropathology of autism spectrum disorders is widely distributed, involving impaired connectivity throughout the brain. Here, we evaluate the hypothesis that decreased connectivity in high-functioning adolescents with an autism spectrum disorder relative to typically developing adolescents is concentrated within domain-specific circuits that are specialized for social processing. Using a novel whole-brain connectivity approach in functional magnetic resonance imaging, we found that not only are decreases in connectivity most pronounced between regions of the social brain but also they are selective to connections between limbic-related brain regions involved in affective aspects of social processing from other parts of the social brain that support language and sensorimotor processes. This selective pattern was independently obtained for correlations with measures of social symptom severity, implying a fractionation of the social brain in autism spectrum disorders at the level of whole circuits.