Evaluation of Differences in Temporal Synchrony Between Brain Regions in Individuals With Autism and Typical Development

King, Jace B.; Prigge, Molly B.D.; King, Carolyn K.; Morgan, Jubel; Dean, Douglas C.; Freeman, Abigail; Villaruz, Joaquin Alfonso M.; Kane, Karen; Bigler, Erin D.; Alexander, Andrew L.; Lange, Nicholas; Zielinski, Brandon A.; Lainhart, Janet E.; Anderson, Jeffrey S.

doi:10.1001/jamanetworkopen.2018.4777

Cited by 27 publications

(27 citation statements)

References 57 publications

(99 reference statements)

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“…It is very possible that replicable results could be found when considering the very same data at a different scale or resolution, or with that data analyzed in a different way. For example, King and colleagues (King et al, 2018) found replicable atypical temporal dynamics in rs-fMRI timecourse. Holiga et al…”

Section: Discussionmentioning

confidence: 99%

Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies

Byrge

Kennedy

2020

Human Brain Mapping

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A rapidly growing number of studies on autism spectrum disorder (ASD) have used resting‐state fMRI to identify alterations of functional connectivity, with the hope of identifying clinical biomarkers or underlying neural mechanisms. However, results have been largely inconsistent across studies, and there remains a pressing need to determine the primary factors influencing replicability. Here, we used resting‐state fMRI data from the Autism Brain Imaging Data Exchange to investigate two potential factors: denoising strategy and data site (which differ in terms of sample, data acquisition, etc.). We examined the similarity of both group‐averaged functional connectomes and group‐level differences (ASD vs. control) across 33 denoising pipelines and four independently‐acquired datasets. The group‐averaged connectomes were highly consistent across pipelines (r = 0.92 ± 0.06) and sites (r = 0.88 ± 0.02). However, the group differences, while still consistent within site across pipelines (r = 0.76 ± 0.12), were highly inconsistent across sites regardless of choice of denoising strategies (r = 0.07 ± 0.04), suggesting lack of replication may be strongly influenced by site and/or cohort differences. Across‐site similarity remained low even when considering the data at a large‐scale network level or when considering only the most significant edges. We further show through an extensive literature survey that the parameters chosen in the current study (i.e., sample size, age range, preprocessing methods) are quite representative of the published literature. These results highlight the importance of examining replicability in future studies of ASD, and, more generally, call for extra caution when interpreting alterations in functional connectivity across groups of individuals.

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Section: Discussionmentioning

confidence: 99%

Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies

Byrge

Kennedy

2020

Human Brain Mapping

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“…There are also other recent papers reporting variations in time‐varying patterns in autism. King et al found increased durations of functional connections in both individual brain regions and distributed networks in autism, which were associated with metrics of disease severity [King et al, ]. They used a complementary method of analysis by introducing the width of cross‐correlation curves between resting‐state fMRI time series as a metric of relative duration of synchronous activity between brain regions (“sustained connectivity”) [King & Anderson, ].…”

Section: Discussionmentioning

confidence: 99%

“…They used a complementary method of analysis by introducing the width of cross‐correlation curves between resting‐state fMRI time series as a metric of relative duration of synchronous activity between brain regions (“sustained connectivity”) [King & Anderson, ]. The persistence of brain connectivity in autism may limit the ability to rapidly shift from one brain state to another [King et al, ]. Moreover, it has been also shown that there exists a negative correlation between processing speed and sustained connectivity [King & Anderson, ].…”

Section: Discussionmentioning

confidence: 99%

Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder

et al. 2019

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This study investigated whole‐brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting‐state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P‐value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default‐mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large‐scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244–258. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. Lay Summary Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra‐fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default‐mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder.

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“…The human neocortex has greatly expanded in size and complexity relative to that of other mammals (1,2). Along with neocortical expansion are increased abilities such as language and reasoning which are disrupted in human diseases like autism and schizophrenia (3,4). This structure contains billions of cells grouped into dozens, if not hundreds, of molecularly distinguishable cell types (5)(6)(7)(8), many with unknown roles because specific genetic tools for their study have been lacking.…”

Section: Main Textmentioning

confidence: 99%

Functional enhancer elements drive subclass-selective expression from mouse to primate neocortex

Mich

Graybuck

Hess

et al. 2019

Preprint

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Evaluation of Differences in Temporal Synchrony Between Brain Regions in Individuals With Autism and Typical Development

Cited by 27 publications

References 57 publications

Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies

Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies

Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder

Functional enhancer elements drive subclass-selective expression from mouse to primate neocortex

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