The idiosyncratic brain: distortion of spontaneous connectivity patterns in autism spectrum disorder

Hahamy, Avital; Behrmann, Marlene; Malach, Rafael

doi:10.1038/nn.3919

Cited by 350 publications

(353 citation statements)

References 51 publications

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“…However, they show that the idiosyncrasy in brain responses previously reported across ASD subjects in stationary computational settings (Hasson et al, 2009; Hahamy, Behrmann, & Malach, 2015; Salmi et al, 2013) concerns precisely timed movie events involving functional integration and segregation.…”

Section: Discussionmentioning

confidence: 85%

Brain dynamics in ASD during movie‐watching show idiosyncratic functional integration and segregation

Bolton

Jochaut

Giraud

et al. 2018

Human Brain Mapping

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To refine our understanding of autism spectrum disorders (ASD), studies of the brain in dynamic, multimodal and ecological experimental settings are required. One way to achieve this is to compare the neural responses of ASD and typically developing (TD) individuals when viewing a naturalistic movie, but the temporal complexity of the stimulus hampers this task, and the presence of intrinsic functional connectivity (FC) may overshadow movie‐driven fluctuations. Here, we detected inter‐subject functional correlation (ISFC) transients to disentangle movie‐induced functional changes from underlying resting‐state activity while probing FC dynamically. When considering the number of significant ISFC excursions triggered by the movie across the brain, connections between remote functional modules were more heterogeneously engaged in the ASD population. Dynamically tracking the temporal profiles of those ISFC changes and tying them to specific movie subparts, this idiosyncrasy in ASD responses was then shown to involve functional integration and segregation mechanisms such as response inhibition, background suppression, or multisensory integration, while low‐level visual processing was spared. Through the application of a new framework for the study of dynamic experimental paradigms, our results reveal a temporally localized idiosyncrasy in ASD responses, specific to short‐lived episodes of long‐range functional interplays.

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Section: Discussionmentioning

confidence: 85%

Brain dynamics in ASD during movie‐watching show idiosyncratic functional integration and segregation

Bolton

Jochaut

Giraud

et al. 2018

Human Brain Mapping

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“…These investigators also reported that weaker FC between the PCC and superior frontal gyrus was correlated with reduced social functioning in ASD participants. One study found that idiosyncratic distortions in FC related to ASD symptom severity, whereby greater distortions from a typical canonical template of FC were associated with greater symptom severity as measured by the ADOS (Hahamy et al, 2015). Recent studies of relationships between dynamic FC and ASD behaviours reported positive correlations between temporal variability and ADOS .…”

Section: Relationships Between Fc and Behaviourmentioning

confidence: 99%

“…Hahamy et al, 2015;Keown et al, 2013;Lee et al, 2016;Monk et al, 2009;Uddin et al, 2013b). Defining subtypes of ASD based on FC metrics has the potential to resolve some of the current discrepancies in the literature regarding the nature of FC abnormalities in individuals with this disorder, as well as to shed light on the complex relationships between FC and behaviour, which may differ between meaningful subtypes.…”

Section: Introductionmentioning

confidence: 99%

Functional connectivity-based subtypes of individuals with and without autism spectrum disorder

Easson

Fatima

McIntosh

2017

Preprint

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Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder that is characterized by impairments in social communication and restricted and repetitive behaviours.Neuroimaging studies of individuals with ASD have shown complex patterns of functional connectivity (FC), with no clear consensus on defining brain-behaviour attributes of different subtypes of the disorder. In these studies, "static FC", a metric that considers correlations across the entire time series for a given region, was used. Emerging evidence shows that FC changes over time; this "dynamic FC" can allow for unique detection of the temporal variability of functional connections over time. Here, we used k-means clustering, an unsupervised machine learning algorithm, to characterize two subtypes of ASD based on distinct patterns of static and dynamic FC. A multivariate statistical approach was then implemented to determine optimal relationships between FC patterns and group membership or behaviour. The main objective was to characterize differences in static and dynamic FC between subtypes of ASD defined in a fully data-driven manner, and between subtypes and typically developing individuals. Subtype 2 was defined by increased FC within resting-state networks and decreased FC across networks for static FC, global increases in temporal stability of dynamic FC, and robust relationships between FC and several behaviours, relative to Subtype 1. Further, both ASD subtypes exhibited different patterns of static and dynamic FC compared to controls, particularly within default mode, sensorimotor, and occipital networks. Static and dynamic FC metrics provided both overlapping and unique information about the nature of FC differences between subtypes, and between both subtypes and controls. Our results demonstrate the value of considering FC-based subtypes of ASD to elucidate different relationships between brain and behaviour among individuals with this disorder, and have important clinical implications for catering treatments and behavioural interventions to specific subtypes.

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“…In addition, neurodevelopmental mechanisms extending into late prenatal/postnatal life include reduced synapse formation and delayed myelination [40,56,57]. The latter result in abnormal neuronal wiring, which was previously believed to be characterized by long-range hypoconnectivity and local hyperconnectivity [58], but more recently has been shown to be a highly individualized mix of hyper-and hypoconnectivity specific to each single patient with ASD [59]. These abnormalities have been associated with deficits in multiple behavioral tasks that relate to social behavior, such as empathy, theory of mind, joint attention, and face and emotion The intracellular degradation of AEA is due to a fatty acid amide hydrolase (FAAH) that generates ethanolamine (EtNH 2 ) and arachidonic acid (AA).…”

Section: Autism Spectrum Disorder: Clinical Traits Neuropsychologicamentioning

confidence: 99%

Endocannabinoid Signaling in Autism

et al. 2015

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Autism spectrum disorder (ASD) is a complex behavioral condition with onset during early childhood and a lifelong course in the vast majority of cases. To date, no behavioral, genetic, brain imaging, or electrophysiological test can specifically validate a clinical diagnosis of ASD. However, these medical procedures are often implemented in order to screen for syndromic forms of the disorder (i.e., autism comorbid with known medical conditions). In the last 25 years a good deal of information has been accumulated on the main components of the Bendocannabinoid (eCB) system^, a rather complex ensemble of lipid signals (Bendocannabinoids^), their target receptors, purported transporters, and metabolic enzymes. It has been clearly documented that eCB signaling plays a key role in many human health and disease conditions of the central nervous system, thus opening the avenue to the therapeutic exploitation of eCB-oriented drugs for the treatment of psychiatric, neurodegenerative, and neuroinflammatory disorders. Here we present a modern view of the eCB system, and alterations of its main components in human patients and animal models relevant to ASD. This review will thus provide a critical perspective necessary to explore the potential exploitation of distinct elements of eCB system as targets of innovative therapeutics against ASD.Key Words Autism spectrum disorder . endocannabinoid system . fragile X syndrome . metabolic regulation . reward system The Endocannabinoid SystemTwenty-five years after the cloning and expression of a complementary DNA that encoded a G protein-coupled receptor, named type-1 cannabinoid (CB 1 ) receptor [1], there is a good deal of information on the main components of the so-called Bendocannabinoid (eCB) system^, as well as on its role in controlling cannabinergic signaling in human health and disease [2][3][4]. Anandamide (AEA) and 2-arachidonoylglycerol (2-AG) are the most active eCBs as yet identified, although this family of bioactive lipids includes other arachidonic acid (AA) derivatives with cannabimimetic properties (i.e., noladin ether, virodhamine, N-arachidonoyldopamine, to name but a few). The classical dogma that eCBs are synthesized and released Bon demand^upon (patho)physiological stimuli has been recently revisited on the basis of unexpected evidence for intracellular reservoirs and transporters of eCBs. These new entities have been shown to drive intracellular trafficking of eCBs, adding a new dimension to the regulation of their biological activity [5]. To date, several metabolic routes have B. Chakrabarti, A. Persico and N. Battista are equal first authors.

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The idiosyncratic brain: distortion of spontaneous connectivity patterns in autism spectrum disorder

Cited by 350 publications

References 51 publications

Brain dynamics in ASD during movie‐watching show idiosyncratic functional integration and segregation

Brain dynamics in ASD during movie‐watching show idiosyncratic functional integration and segregation

Functional connectivity-based subtypes of individuals with and without autism spectrum disorder

Endocannabinoid Signaling in Autism

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