Over the past several years, the study of self-related cognition has garnered increasing interest amongst psychologists and cognitive neuroscientists. Concomitantly, lesion and neuroimaging studies have demonstrated the importance of intact cortico-cortical and cortico-subcortical connections for supporting high-level cognitive functions. Comissurotomy or “split-brain” patients provide unique insights into the role of the cerebral commissures in maintaining an individual’s sense of self, as well as into the unique self-representation capabilities of each cerebral hemisphere. Here we review empirical work examining the integrity of self-related processes in patients with various disconnection syndromes, focusing on studies of self-recognition, ownership, and agency. Taken together, this body of work suggests that an intact corpus callosum enabling interhemispheric transfer is necessary for some, but not all types of self-representations.
split-brain; commissurotomy; corpus callosum; self-recognition; self-awareness; brain network; brain connectivity; agency; alien hand; anarchic hand
One of the defining characteristics of individuals with autism spectrum disorder (ASD) is difficulty with social interaction and communication with others, or interpersonal interaction. Accordingly, the majority of research efforts to date have focused on understanding the brain mechanisms underlying the deficits in social cognition and language associated with ASD. However, recent empirical and theoretical work has begun to reveal increasing evidence for altered self-representation, or intrapersonal cognition in ASD. Here we review recent studies of the self in ASD, focusing on paradigms examining ‘physical’ aspects of the self, including self-recognition, agency and perspective taking, and ‘psychological’ aspects of the self, including self-knowledge and autobiographical memory. A review of the existing literature suggests that psychological, but not physical, aspects of self-representation are altered in ASD. One key brain region that has emerged as a potential locus of self-related deficits in ASD is the medial prefrontal cortex, part of a larger ‘default mode network’. Collectively, the findings from these studies provide a more comprehensive framework for understanding the complex social, cognitive, and affective symptomatology of ASD.
Autism spectrum disorders; Agency; Perspective taking; Social cognition; Self-recognition; Self-knowledge; Brain development; Autobiographical memory; Personality traits; Default mode network
Autism is a complex neurodevelopmental disorder of unknown etiology. While the past decade has witnessed a proliferation of neuroimaging studies of autism, theoretical approaches for understanding systems-level brain abnormalities remain poorly developed. We propose a novel anterior insula-based systems-level model for investigating the neural basis of autism, synthesizing recent advances in brain network functional connectivity with converging evidence from neuroimaging studies in autism. The anterior insula is involved in interoceptive, affective and empathic processes, and emerging evidence suggests it is part of a “salience network” integrating external sensory stimuli with internal states. Network analysis indicates that the anterior insula is uniquely positioned as a hub mediating interactions between large-scale networks involved in externally- and internally-oriented cognitive processing. A recent meta-analysis identifies the anterior insula as a consistent locus of hypoactivity in autism. We suggest that dysfunctional anterior insula connectivity plays an important role in autism. Critical examination of these abnormalities from a systems neuroscience perspective should be a priority for further research on the neurobiology of autism.
connectivity; empathy; autism spectrum disorders; network; von Economoneuron; fMRI
Autism spectrum disorders (ASD) are neurodevelopmental disorders with a prevalence of nearly 1:100. Structural imaging studies point to disruptions in multiple brain areas, yet the precise neuroanatomical nature of these disruptions remains unclear. Characterization of brain structural differences in children with ASD is critical for development of biomarkers that may eventually be used to improve diagnosis and monitor response to treatment.
We use voxel-based morphometry (VBM) along with a novel multivariate pattern analysis (MPA) approach and searchlight algorithm to classify structural magnetic resonance imaging data acquired from 24 children and adolescents with autism and 24 age-, gender-, and IQ-matched neurotypical participants.
Despite modest VBM differences, MPA revealed that the groups could be distinguished with accuracies of around 90% based on gray matter in the posterior cingulate cortex (PCC), medial prefrontal cortex, and bilateral medial temporal lobes, all regions within the default mode network (DMN). Abnormalities in the PCC were associated with impaired ADI-R communication scores. Gray matter in additional prefrontal, lateral temporal, and subcortical structures also discriminated between the two groups with accuracies between 81-90%. White matter in the inferior fronto-occipital and superior longitudinal fasciculi, and the genu and splenium of the corpus callosum, achieved up to 85% classification accuracy.
Multiple brain regions, including those belonging to the DMN, exhibit aberrant structural organization in children with autism. Brain-based biomarkers derived from structural MRI data may eventually contribute to identification of the neuroanatomical basis of symptom heterogeneity and to the development of more targeted early intervention.
voxel-based morphometry; autism spectrum disorders; default mode network; multivariate pattern analysis; support vector machine; biomarker
The inferior parietal lobule (IPL) of the human brain is a heterogeneous region involved in visuospatial attention, memory, and mathematical cognition. Detailed description of connectivity profiles of subdivisions within the IPL is critical for accurate interpretation of functional neuroimaging studies involving this region. We separately examined functional and structural connectivity of the angular gyrus (AG) and the intraparietal sulcus (IPS) using probabilistic cytoarchitectonic maps. Regions-of-interest (ROIs) included anterior and posterior AG subregions (PGa, PGp) and 3 IPS subregions (hIP2, hIP1, and hIP3). Resting-state functional connectivity analyses showed that PGa was more strongly linked to basal ganglia, ventral premotor areas, and ventrolateral prefrontal cortex, while PGp was more strongly connected with ventromedial prefrontal cortex, posterior cingulate, and hippocampus—regions comprising the default mode network. The anterior-most IPS ROIs, hIP2 and hIP1, were linked with ventral premotor and middle frontal gyrus, while the posterior-most IPS ROI, hIP3, showed connectivity with extrastriate visual areas. In addition, hIP1 was connected with the insula. Tractography using diffusion tensor imaging revealed structural connectivity between most of these functionally connected regions. Our findings provide evidence for functional heterogeneity of cytoarchitectonically defined subdivisions within IPL and offer a novel framework for synthesis and interpretation of the task-related activations and deactivations involving the IPL during cognition.
attention; Brodmann area 39; default mode network; inferior parietal lobule; mathematical cognition
Functional and structural maturation of networks comprised of discrete regions is an important aspect of brain development. The default-mode network (DMN) is a prominent network which includes the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), medial temporal lobes (MTL), and angular gyrus (AG). Despite increasing interest in DMN function, little is known about its maturation from childhood to adulthood. Here we examine developmental changes in DMN connectivity using a multimodal imaging approach by combining resting-state fMRI, voxel-based morphometry and diffusion tensor imaging-based tractography. We found that the DMN undergoes significant developmental changes in functional and structural connectivity, but these changes are not uniform across all DMN nodes. Convergent structural and functional connectivity analyses suggest that PCC-mPFC connectivity along the cingulum bundle is the most immature link in the DMN of children. Both PCC and mPFC also showed gray matter volume differences, as well as prominent macrostructural and microstructural differences in the dorsal cingulum bundle linking these regions. Notably, structural connectivity between PCC and left MTL was either weak or non-existent in children, even though functional connectivity did not differ from that of adults. These results imply that functional connectivity in children can reach adult-like levels despite weak structural connectivity. We propose that maturation of PCC-mPFC structural connectivity plays an important role in the development of self-related and social-cognitive functions that emerge during adolescence. More generally, our study demonstrates how quantitative multimodal analysis of anatomy and connectivity allows us to better characterize the heterogeneous development and maturation of brain networks.
brain development; default mode network; DTI; functional brain connectivity; structural brain connectivity
Resting-state functional magnetic resonance imaging (fMRI) has provided a novel approach for examining interhemispheric interaction, demonstrating a high degree of functional connectivity between homotopic regions in opposite hemispheres. However, heterotopic resting state functional connectivity (RSFC) remains relatively uncharacterized. In the present study, we examine non-homotopic regions, characterizing heterotopic RSFC and comparing it to intrahemispheric RSFC, to examine the impact of hemispheric separation on the integration and segregation of processing in the brain. Resting-state fMRI scans were acquired from 59 healthy participants to examine interregional correlations in spontaneous low frequency fluctuations in BOLD signal. Using a probabilistic atlas, we correlated probability-weighted time series from 112 regions (56 per hemisphere) distributed throughout the entire cerebrum. We compared RSFC for pairings of non-homologous regions located in different hemispheres (heterotopic connectivity) to RSFC for the same pairings when located within hemisphere (intrahemispheric connectivity). For positive connections, connectivity strength was greater within each hemisphere, consistent with integrated intrahemispheric processing. However, for negative connections, RSFC strength was greater between the hemispheres, consistent with segregated interhemispheric processing. These patterns were particularly notable for connections involving frontal and heteromodal regions. The distribution of positive and negative connectivity was nearly identical within and between the hemispheres, though we demonstrated detailed regional variation in distribution. We discuss implications for leading models of interhemispheric interaction. The future application of our analyses may provide important insight into impaired interhemispheric processing in clinical and aging populations.
Brodmann areas 6, 44, and 45 in the ventrolateral frontal cortex of the left hemisphere of the human brain constitute the anterior language production zone. The anatomic connectivity of these areas with parietal and temporal cortical regions was recently examined in an autoradiographic tract-tracing study in the macaque monkey. Studies suggest strong correspondence between human resting state functional connectivity (RSFC) based on functional magnetic resonance imaging data and experimentally demonstrated anatomical connections in non-human primates. Accordingly, we hypothesized that areas 6, 44 and 45 of the human brain would exhibit patterns of RSFC consistent with patterns of anatomical connectivity observed in the macaque. In a primary analysis, we examined the RSFC associated with regions-of-interest placed in ventrolateral frontal areas 6, 44 and 45, on the basis of local sulcal and gyral anatomy. We validated the results of the primary hypothesis-driven analysis with a data-driven partitioning of ventrolateral frontal cortex into regions exhibiting distinct RSFC patterns, using a spectral clustering algorithm. The RSFC of ventrolateral frontal areas 6, 44 and 45 was consistent with patterns of anatomical connectivity shown in the macaque. We observed a striking dissociation between RSFC for the ventral part of area 6 that is involved in orofacial motor control and RSFC associated with Broca’s region (areas 44 and 45). These findings indicate rich and differential RSFC patterns for the ventrolateral frontal areas controlling language production, consistent with known anatomical connectivity in the macaque brain, and suggest conservation of connectivity during the evolution of the primate brain.
fMRI; resting state; inferior frontal gyrus; language; clustering
Based on the increased recognition of the dimensional nature of autistic traits, we examined their neural correlates in neurotypical individuals using the Social Responsiveness Scale-Adult version (SRS-A). The SRS-A measures autistic traits that are continuously distributed in the general population. Here, we establish a novel approach to examining the neural basis of autistic traits, attempting to directly relate SRS-A scores to patterns of functional connectivity observed for the pregenual anterior cingulate cortex (pgACC), a region commonly implicated in social cognition.
Resting state fMRI scans were collected in 25 neurotypical individuals (26.4 ± 5.6 y) who provided SRS-A completed by an informant who knew the participant in natural social settings. Whole brain corrected connectivity analyses were then conducted using the SRS-A as a covariate of interest.
We found a significant negative relationship between SRS-A and pgACC functional connectivity with the anterior portion of mid-insula (Z > 2.3; p < .05, corrected). Specifically, low levels of autistic traits were observed when a substantial portion of the anterior mid-insula showed positive connectivity with pgACC. In contrast, elevated levels of autistic traits were associated with negative connectivity between the pgACC and the anterior mid-insula.
Resting state functional connectivity of the pgACC-insula social network was related to autistic traits in neurotypical adults. Application of this approach in samples with autism spectrum disorders is needed to confirm whether the pgACC- anterior mid insula circuit is dimensionally related to the severity of autistic traits in clinical populations.
Autism - AJP0006; Brain Imaging Techniques - AJP0068
Functional neuroimaging studies of autism spectrum disorders (ASD) have examined social and non-social paradigms, although rarely in the same study. Here, we provide an objective, unbiased survey of functional brain abnormalities in ASD, related to both social and non-social processing.
We conducted two separate voxel-wise activation likelihood estimation meta-analyses of 39 functional neuroimaging studies consisting of 24 studies examining social processes (e.g., theory of mind, face perception), and 15 studies examining non-social processes (e.g., attention control, working memory). Voxel-wise significance threshold was p< 0.05, corrected by false discovery rate.
Compared to neurotypical controls (NC), ASD showed greater likelihood of hypoactivation in two medial wall regions: perigenual anterior cingulate cortex (ACC) in social tasks only, and dorsal ACC in non-social studies. Further, right anterior insula, recently linked to social cognition, was more likely to be hypoactivated in ASD in the analyses of social studies. In non-social studies, group comparisons showed greater likelihood of activation for the ASD group in the rostral ACC region that is typically suppressed during attentionally demanding tasks.
Despite substantial heterogeneity of tasks, the rapidly increasing functional imaging literature showed ASD-related patterns of hypofunction and aberrant activation that depended on the specific cognitive domain, i.e., social and versus non-social. These results provide a basis for targeted extensions of these findings with younger subjects and a range of paradigms, including analyses of default mode network regulation in ASD.
autism; pervasive developmental disorders (PDD); anterior cingulate cortex; insula; social cognition; cognitive control; meta-analysis; functional magnetic resonance imaging (fMRI); positron emission tomography (PET); default mode network
The insula is a brain structure implicated in disparate cognitive, affective, and regulatory functions, including interoceptive awareness, emotional responses, and empathic processes. While classically considered a limbic region, recent evidence from network analysis suggests a critical role for the insula, particularly the anterior division, in high-level cognitive control and attentional processes. The crucial insight and view we present here is of the anterior insula as an integral hub in mediating dynamic interactions between other large-scale brain networks involved in externally oriented attention and internally oriented or self-related cognition. The model we present postulates that the insula is sensitive to salient events, and that its core function is to mark such events for additional processing and initiate appropriate control signals. The anterior insula and the anterior cingulate cortex form a “salience network” that functions to segregate the most relevant among internal and extrapersonal stimuli in order to guide behavior. Within the framework of our network model, the disparate functions ascribed to the insula can be conceptualized by a few basic mechanisms: (1) bottom–up detection of salient events, (2) switching between other large-scale networks to facilitate access to attention and working memory resources when a salient event is detected, (3) interaction of the anterior and posterior insula to modulate autonomic reactivity to salient stimuli, and (4) strong functional coupling with the anterior cingulate cortex that facilitates rapid access to the motor system. In this manner, with the insula as its integral hub, the salience network assists target brain regions in the generation of appropriate behavioral responses to salient stimuli. We suggest that this framework provides a parsimonious account of insula function in neurotypical adults, and may provide novel insights into the neural basis of disorders of affective and social cognition.
Functional connectivity; Brain networks; Resting-state fMRI; Granger causality; Anterior insula; Diffusing tensor imaging
The amygdala is composed of structurally and functionally distinct nuclei that contribute to the processing of emotion through interactions with other subcortical and cortical structures. While these circuits have been studied extensively in animals, human neuroimaging investigations of amygdala-based networks have typically considered the amygdala as a single structure, which likely masks contributions of individual amygdala subdivisions. The present study uses resting state functional magnetic resonance imaging (fMRI) to test whether distinct functional connectivity patterns, like those observed in animal studies, can be detected across three amygdala subdivisions: laterobasal, centromedial, and superficial. In a sample of 65 healthy adults, voxelwise regression analyses demonstrated positively-predicted ventral and negatively-predicted dorsal networks associated with the total amygdala, consistent with previous animal and human studies. Investigation of individual amygdala subdivisions revealed distinct differences in connectivity patterns within the amygdala and throughout the brain. Spontaneous activity in the laterobasal subdivision predicted activity in temporal and frontal regions, while activity in the centromedial nuclei predicted activity primarily in striatum. Activity in the superficial subdivision positively predicted activity throughout the limbic lobe. These findings suggest that resting state fMRI can be used to investigate human amygdala networks at a greater level of detail than previously appreciated, allowing for the further advancement of translational models.
Over the past several decades, structural MRI studies have provided remarkable insights into human brain development by revealing the trajectory of gray and white matter maturation from childhood to adolescence and adulthood. In parallel, functional MRI studies have demonstrated changes in brain activation patterns accompanying cognitive development. Despite these advances, studying the maturation of functional brain networks underlying brain development continues to present unique scientific and methodological challenges. Resting-state fMRI (rsfMRI) has emerged as a novel method for investigating the development of large-scale functional brain networks in infants and young children. We review existing rsfMRI developmental studies and discuss how this method has begun to make significant contributions to our understanding of maturing brain organization. In particular, rsfMRI has been used to complement studies in other modalities investigating the emergence of functional segregation and integration across short and long-range connections spanning the entire brain. We show that rsfMRI studies help to clarify and reveal important principles of functional brain development, including a shift from diffuse to focal activation patterns, and simultaneous pruning of local connectivity and strengthening of long-range connectivity with age. The insights gained from these studies also shed light on potentially disrupted functional networks underlying atypical cognitive development associated with neurodevelopmental disorders. We conclude by identifying critical gaps in the current literature, discussing methodological issues, and suggesting avenues for future research.
functional connectivity; brain maturation; resting-state fMRI; cognitive development; autism spectrum disorders; attention-deficit/hyperactivity disorder
Pathophysiological models of Attention-Deficit/Hyperactivity Disorder (ADHD) have focused on frontal-striatal circuitry with alternative hypotheses relatively unexplored. Based on evidence that negative interactions between frontal foci involved in cognitive control and the non-goal directed ‘default-mode’ network prevent attentional lapses, we hypothesized abnormalities in functional connectivity of these circuits in ADHD.
Resting state BOLD fMRI scans were obtained at 3.0 Tesla in 20 adults with ADHD and 20 age- and sex-matched healthy volunteers.
Examination of healthy controls verified presence of an antiphasic or negative relationship between activity in dorsal anterior cingulate cortex (centered at x=8, y=7, z=38) and in default-mode network components. Group analyses revealed ADHD-related compromises in this relationship, with decreases in the functional connectivity between the anterior cingulate and precuneus/posterior cingulate cortex regions (p<.0004, corrected). Secondary analyses revealed an extensive pattern of ADHD-related decreases in connectivity between precuneus and other default-mode network components, including ventromedial prefrontal cortex (p<3×10−11, corrected) and portions of posterior cingulate (p<.02, corrected).
Together with prior unbiased anatomic evidence of posterior volumetric abnormalities, our findings suggest that the long-range connections linking dorsal anterior cingulate to posterior cingulate and precuneus should be considered as a candidate locus of dysfunction in ADHD.
There is evidence that the right hemisphere is involved in processing self-related stimuli. Previous brain imaging research has found a network of right-lateralized brain regions that preferentially respond to seeing one's own face rather than a familiar other. Given that the self is an abstract multimodal concept, we tested whether these brain regions would also discriminate the sound of one's own voice compared to a friend's voice. Participants were shown photographs of their own face and friend's face, and also listened to recordings of their own voice and a friend's voice during fMRI scanning. Consistent with previous studies, seeing one's own face activated regions in the inferior frontal gyrus (IFG), inferior parietal lobe and inferior occipital cortex in the right hemisphere. In addition, listening to one's voice also showed increased activity in the right IFG. These data suggest that the right IFG is concerned with processing self-related stimuli across multiple sensory modalities and that it may contribute to an abstract self-representation.
self; self-recognition; fMRI; face; voice
Poor mathematical abilities adversely affect academic and career opportunities. The neuroanatomical basis of developmental dyscalculia (DD), a specific learning deficit with prevalence rates exceeding 5%, is poorly understood. We used structural MRI and diffusion tensor imaging (DTI) to examine macro- and micro-structural impairments in 7- to 9-year-old children with DD, compared to a group of typically developing (TD) children matched on age, gender, intelligence, reading abilities and working memory capacity. Voxel-based morphometry (VBM) revealed reduced grey matter (GM) bilaterally in superior parietal lobule, intra-parietal sulcus, fusiform gyrus, parahippocampal gyrus and right anterior temporal cortex in children with DD. VBM analysis also showed reduced white matter (WM) volume in right temporal-parietal cortex. DTI revealed reduced fractional anisotropy (FA) in this WM region, pointing to significant right hemisphere micro-structural impairments. Furthermore, FA in this region was correlated with numerical operations but not verbal mathematical reasoning or word reading. Atlas-based tract mapping identified the inferior longitudinal fasciculus, inferior fronto-occipital fasciculus and caudal forceps major as key pathways impaired in DD. DTI tractography suggests that long-range WM projection fibers linking the right fusiform gyrus with temporal-parietal WM are a specific source of vulnerability in DD. Network and classification analysis suggest that DD in children may be characterized by multiple dysfunctional circuits arising from a core WM deficit. Our findings link GM and WM abnormalities in children with DD and they point to macro- and micro-structural abnormalities in right hemisphere temporal-parietal WM, and pathways associated with it, as key neuroanatomical correlates of DD.
mathematical disability; white matter; grey matter; diffusion tensor imaging; voxel-based morphometry; development
Autism is a developmental disorder characterized by decreased interest and engagement in social interactions and by enhanced self-focus. While previous theoretical approaches to understanding autism have emphasized social impairments and altered interpersonal interactions, there is a recent shift towards understanding the nature of the representation of the self in individuals with autism spectrum disorders (ASD). Still, the neural mechanisms subserving self-representations in ASD are relatively unexplored.
We used event-related fMRI to investigate brain responsiveness to images of the subjects' own face and to faces of others. Children with ASD and typically developing (TD) children viewed randomly presented digital morphs between their own face and a gender-matched other face, and made “self/other” judgments. Both groups of children activated a right premotor/prefrontal system when identifying images containing a greater percentage of the self face. However, while TD children showed activation of this system during both self- and other-processing, children with ASD only recruited this system while viewing images containing mostly their own face.
This functional dissociation between the representation of self versus others points to a potential neural substrate for the characteristic self-focus and decreased social understanding exhibited by these individuals, and suggests that individuals with ASD lack the shared neural representations for self and others that TD children and adults possess and may use to understand others.
Self–other discrimination is fundamental to social interaction, however, little is known about the neural systems underlying this ability. In a previous functional magnetic resonance imaging study, we demonstrated that a right fronto-parietal network is activated during viewing of self-faces as compared with the faces of familiar others. Here we used image-guided repetitive transcranial magnetic stimulation (rTMS) to create a ’virtual lesion’ over the parietal component of this network to test whether this region is necessary for discriminating self-faces from other familiar faces. The current results indeed show that 1 Hz rTMS to the right inferior parietal lobule (IPL) selectively disrupts performance on a self–other discrimination task. Applying 1 Hz rTMS to the left IPL had no effect. It appears that activity in the right IPL is essential to the task, thus providing for the first time evidence for a causal relation between a human brain area and this high-level cognitive capacity.
self-awareness; self-recognition; social cognition; inferior parietal lobule; mirror neurons
Self–other discrimination is fundamental to social interaction, however, little is known about the neural systems underlying this ability. In a previous functional magnetic resonance imaging study, we demonstrated that a right fronto-parietal network is activated during viewing of self-faces as compared with the faces of familiar others. Here we used image-guided repetitive transcranial magnetic stimulation (rTMS) to create a ‘virtual lesion’ over the parietal component of this network to test whether this region is necessary for discriminating self-faces from other familiar faces. The current results indeed show that 1 Hz rTMS to the right inferior parietal lobule (IPL) selectively disrupts performance on a self–other discrimination task. Applying 1 Hz rTMS to the left IPL had no effect. It appears that activity in the right IPL is essential to the task, thus providing for the first time evidence for a causal relation between a human brain area and this high-level cognitive capacity.
self-awareness; self-recognition; social cognition; inferior parietal lobule; mirror neurons