Resting state functional connectivity reveals intrinsic, spontaneous networks that elucidate the functional architecture of the human brain. However, valid statistical analysis used to identify such networks must address sources of noise in order to avoid possible confounds such as spurious correlations based on non-neuronal sources. We have developed a functional connectivity toolbox Conn (www.nitrc.org/projects/conn) that implements the component-based noise correction method (CompCor) strategy for physiological and other noise source reduction, additional removal of movement, and temporal covariates, temporal filtering and windowing of the residual blood oxygen level-dependent (BOLD) contrast signal, first-level estimation of multiple standard functional connectivity magnetic resonance imaging (fcMRI) measures, and second-level random-effect analysis for resting state as well as task-related data. Compared to methods that rely on global signal regression, the CompCor noise reduction method all...

Conn: A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks

Large-scale brain networks and psychopathology: a unifying triple network model

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

/pdf/the-autism-brain-imaging-data-exchange-towards-a-large-scale-32vwazsr5n.pdf

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism

The posterior cingulate cortex is a highly connected and metabolically active brain region. Recent studies suggest it has an important cognitive role, although there is no consensus about what this is. The region is typically discussed as having a unitary function because of a common pattern of relative deactivation observed during attentionally demanding tasks. One influential hypothesis is that the posterior cingulate cortex has a central role in supporting internally-directed cognition. It is a key node in the default mode network and shows increased activity when individuals retrieve autobiographical memories or plan for the future, as well as during unconstrained ‘rest’ when activity in the brain is ‘free-wheeling’. However, other evidence suggests that the region is highly heterogeneous and may play a direct role in regulating the focus of attention. In addition, its activity varies with arousal state and its interactions with other brain networks may be important for conscious awareness. Understanding posterior cingulate cortex function is likely to be of clinical importance. It is well protected against ischaemic stroke, and so there is relatively little neuropsychological data about the consequences of focal lesions. However, in other conditions abnormalities in the region are clearly linked to disease. For example, amyloid deposition and reduced metabolism is seen early in Alzheimer’s disease. Functional neuroimaging studies show abnormalities in a range of neurological and psychiatric disorders including Alzheimer’s disease, schizophrenia, autism, depression and attention deficit hyperactivity disorder, as well as ageing. Our own work has consistently shown abnormal posterior cingulate cortex function following traumatic brain injury, which predicts attentional impairments. Here we review the anatomy and physiology of the region and how it is affected in a range of clinical conditions, before discussing its proposed functions. We synthesize key findings into a novel model of the region’s function (the ‘Arousal, Balance and Breadth of Attention’ model). Dorsal and ventral subcomponents are functionally separated and differences in regional activity are explained by considering: (i) arousal state; (ii) whether attention is focused internally or externally; and (iii) the breadth of attentional focus. The predictions of the model can be tested within the framework of complex dynamic systems theory, and we propose that the dorsal posterior cingulate cortex influences attentional focus by ‘tuning’ whole-brain metastability and so adjusts how stable brain network activity is over time.

/pdf/the-role-of-the-posterior-cingulate-cortex-in-cognition-and-k3skjitecz.pdf

The role of the posterior cingulate cortex in cognition and disease.

During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI). The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI) and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm.

/pdf/clinical-applications-of-resting-state-functional-26plh29pd8.pdf

Clinical Applications of Resting State Functional Connectivity

http://www.brainm.com/software/pubs/dg/AbnIntrinsicFunctConnectivity-Autism_Monk.pdf

Abnormalities of intrinsic functional connectivity in autism spectrum disorders.

Alterations of resting state functional connectivity in the default network in adolescents with autism spectrum disorders

Background: Autism spectrum disorders (ASD) are associated with severe impairments in social functioning. Because faces provide nonverbal cues that support social interactions, many studies of ASD have examined neural structures that process faces, including the amygdala, ventromedial prefrontal cortex and superior and middle temporal gyri. However, increases or decreases in activation are often contingent on the cognitive task. Specifically, the cognitive domain of attention influences group differences in brain activation. We investigated brain function abnormalities in participants with ASD using a task that monitored attention bias to emotional faces. Methods: Twenty-four participants (12 with ASD, 12 controls) completed a functional magnetic resonance imaging study while performing an attention cuing task with emotional (happy, sad, angry) and neutral faces. Results: In response to emotional faces, those in the ASD group showed greater right amygdala activation than those in the control group. A preliminary psychophysiological connectivity analysis showed that ASD participants had stronger positive right amygdala and ventromedial prefrontal cortex coupling and weaker positive right amygdala and temporal lobe coupling than controls. There were no group differences in the behavioural measure of attention bias to the emotional faces. Limitations: The small sample size may have affected our ability to detect additional group differences. Conclusion: When attention bias to emotional faces was equivalent between ASD and control groups, ASD was associated with greater amygdala activation. Preliminary analyses showed that ASD participants had stronger connectivity between the amygdala ventromedial prefrontal cortex (a network implicated in emotional modulation) and weaker connectivity between the amygdala and temporal lobe (a pathway involved in the identification of facial expressions, although areas of group differences were generally in a more anterior region of the temporal lobe than what is typically reported for emotional face processing). These alterations in connectivity are consistent with emotion and face processing disturbances in ASD.

https://www.jpn.ca/content/jpn/35/2/105.full.pdf

Neural circuitry of emotional face processing in autism spectrum disorders.

Background: Autism spectrum disorders (ASD) involve a core deficit in social functioning and impairments in the ability to recognize face emotions. In an emotional faces task designed to constrain group differences in attention, the present study used functional MRI to characterize activation in the amygdala, ventral prefrontal cortex (vPFC), and striatum, three structures involved in socio-emotional processing in adolescents with ASD. Methods: Twenty-two adolescents with ASD and 20 healthy adolescents viewed facial expressions (happy, fearful, sad and neutral) that were briefly presented (250 ms) during functional MRI acquisition. To monitor attention, subjects pressed a button to identify the gender of each face. Results: The ASD group showed greater activation to the faces relative to the control group in the amygdala, vPFC and striatum. Follow-up analyses indicated that the ASD relative to control group showed greater activation in the amygdala, vPFC and striatum (p < .05 small volume corrected), particularly to sad faces. Moreover, in the ASD group, there was a negative correlation between developmental variables (age and pubertal status) and mean activation from the whole bilateral amygdala; younger adolescents showed greater activation than older adolescents. There were no group differences in accuracy or reaction time in the gender identification task. Conclusions: When group differences in attention to facial expressions were limited, adolescents with ASD showed greater activation in structures involved in socio-emotional processing. Keywords: Autism, adolescents, fMRI, faces, emotion.

/pdf/neural-activation-to-emotional-faces-in-adolescents-with-46vilxn5gj.pdf

Shih Jen Weng

Papers

Abnormalities of intrinsic functional connectivity in autism spectrum disorders.

Alterations of resting state functional connectivity in the default network in adolescents with autism spectrum disorders

Neural circuitry of emotional face processing in autism spectrum disorders.

Neural Activation to Emotional Faces in Adolescents with Autism Spectrum Disorders

Using a self-organizing map algorithm to detect age-related changes in functional connectivity during rest in autism spectrum disorders.