Functional connectivity decreases in autism in emotion, self, and face circuits identified by knowledge-based enrichment analysis

A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity

Revisiting non-linear functional brain co-activations: directed, dynamic and delayed

The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In previous work we first demonstrated that the relatively stronger BOLD activations contain most of the information relevant to understand functional connectivity and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this work we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different perspective in the analysis of brain co-activation patterns. In this paper we provide for a proof of concept, based on replicating and completing existing results on an Autism database, to discuss the main features and advantages of the proposed strategy for the study of brain functional correlations. These results show new interpretations of the correlations found on this sample.Comment: 12 pages, 8 figure

Identifying Brain Network Topology Changes in Task Processes and Psychiatric Disorders

Hervorming Sociale Regelgevin

Gray matter abnormalities follow non-random patterns of co-alteration in autism: Meta-connectomic evidence

•We present an innovative connectomic approach based on voxel-based morphometry (VBM) meta-data.•We mapped the topological configuration of gray matter abnormalities in autism spectrum disorder (ASD).•ASD co-alteration network tends to overlap with the pathways of structural brain connectivity.•Recognizable cerebral pathological hubs were captured by graph-analysis.•A core sub-network was identified, which provides insight into our understanding of ASD. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical brain anatomy and connectivity. Graph-theoretical methods have mainly been applied to detect altered patterns of white matter tracts and functional brain activation in individuals with ASD. The network topology of gray matter (GM) abnormalities in ASD remains relatively unexplored. An innovative meta-connectomic analysis on voxel-based morphometry data (45 experiments, 1,786 subjects with ASD) was performed in order to investigate whether GM variations can develop in a distinct pattern of co-alteration across the brain. This pattern was then compared with normative profiles of structural and genetic co-expression maps. Graph measures of centrality and clustering were also applied to identify brain areas with the highest topological hierarchy and core sub-graph components within the co-alteration network observed in ASD. Individuals with ASD exhibit a distinctive and topologically defined pattern of GM co-alteration that moderately follows the structural connectivity constraints. This was not observed with respect to the pattern of genetic co-expression. Hub regions of the co-alteration network were mainly left-lateralized, encompassing the precuneus, ventral anterior cingulate, and middle occipital gyrus. Regions of the default mode network appear to be central in the topology of co-alterations. These findings shed new light on the pathobiology of ASD, suggesting a network-level dysfunction among spatially distributed GM regions. At the same time, this study supports pathoconnectomics as an insightful approach to better understand neuropsychiatric disorders

Estimating feedforward and feedback effective connections from fMRI time series: Assessments of statistical methods

We test the adequacies of several proposed and two new statistical methods for recovering the causal structure of systems with feedback from synthetic BOLD time series. We compare an adaptation of the first correct method for recovering cyclic linear systems; Granger causal regression; a multivariate autoregressive model with a permutation test; the Group Iterative Multiple Model Estimation (GIMME) algorithm; the Ramsey et al. non-Gaussian methods; two non-Gaussian methods by Hyvärinen and Smith; a method due to Patel et al.; and the GlobalMIT algorithm. We introduce and also compare two new methods, Fast Adjacency Skewness (FASK) and Two-Step, both of which exploit non-Gaussian features of the BOLD signal. We give theoretical justifications for the latter two algorithms. Our test models include feedback structures with and without direct feedback (2-cycles), excitatory and inhibitory feedback, models using experimentally determined structural connectivities of macaques, and empirical human resting-state and task data. We find that averaged over all of our simulations, including those with 2-cycles, several of these methods have a better than 80% orientation precision (i.e., the probability of a directed edge is in the true structure given that a procedure estimates it to be so) and the two new methods also have better than 80% recall (probability of recovering an orientation in the true structure)

How Do Mental Health Professionals Provide Therapy to Couples in Neurodiverse Relationships A Constructivist Grounded Theory Study

This study examines the social processes mental health professionals use to counsel neurodiverse couples. While the prevalence of autism continues to rise in all areas of society, therapists are in uncharted waters in the world of couples therapy. Neurodiverse couples are the nascent challenge in mixed relationships, where one partner is on the spectrum and the other partner is neurotypical. Some partners with autism may not know they have autism. Neurodiverse couples have unique challenges not found in other relationship dyads. National guidelines have not yet been established. A constructivist grounded theory framework uses guided interviews to understand the processes therapists use to develop effective therapy. Key categories emerged including belief systems, training, and communication, and which served as underpinnings that guided therapists. This study uncovers a duality of pathways inspired by personal epistemologies which drive decision-making. A social-justice component emerges from the data that is unexpected. This research highlights disparities associated with how therapists understand and assimilate the complexities of neurodiverse relationships. The findings demonstrate a need for professional guidelines for practice. They show a need for professional certification of skills specializing in autism-informed knowledge for mental-health practitioners. Professional agencies lack a global reference of autism-informed knowledge and evidence-based strategies for adults with autism. This highlights the implications from this research. Service professionals who work with people need autism-informed knowledge to practice competently and effectively, and to prevent unintentional harm. Nursing programs that prepare nurses with autism-informed knowledge will forge a significant, positive experiential impact on healthcare and outcomes for patients with autism, neurodiverse couples, and their families. Nurses at the frontline of healthcare will have the skill set and tools to provide tailored neurodevelopmental-specific care, collaborate with autism-informed multidisciplinary teams, and advocate for the diagnosed and undiagnosed neurodiverse patient population