Large-scale differences in functional organization of left- and right-handed individuals using whole-brain, data-driven analysis of connectivity

NeuroImage, Journal Year: 2022, Volume and Issue: 252, P. 119040 - 119040

Published: March 8, 2022

Handedness influences differences in lateralization of language areas as well dominance motor and somatosensory cortices. However, whole-brain functional connectivity (i.e., connectomes) due to handedness have been relatively understudied beyond pre-specified networks interest. Here, we compared connectomes left- right-handed individuals at the whole brain level. We explored previously established regions interest, showed between primarily motor, somatosensory, using connectivity. then proceeded investigate these found that are not specific but extend across every region brain. In particular, connections within cerebellum show distinct patterns To put effects into context, effect sizes associated with account for a similar amount individual connectome sex differences. Together results shed light on those traditionally contribute organization underscore neurobiologically meaningful addition being statistically significant.

Language: Английский

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How do tasks impact the reliability of fMRI functional connectivity?

Human Brain Mapping, Journal Year: 2024, Volume and Issue: 45(3)

Published: Feb. 13, 2024

Abstract While there is growing interest in the use of functional magnetic resonance imaging‐functional connectivity (fMRI‐FC) for biomarker research, low measurement reliability conventional acquisitions may limit applications. Factors known to impact FC include scan length, head motion, signal properties, such as temporal signal‐to‐noise ratio (tSNR), and acquisition state or task. As tasks a region‐wise fashion, they likely differently across brain, making task an important decision study design. Here, we densely sampled Midnight Scan Club (MSC) dataset, comprising 5 h rest 6 fMRI data 10 healthy adults, investigate regional effects on reliability. We further considered how BOLD properties contributing tSNR, that is, mean (tMean) standard deviation (tSD), vary associate with reliability, are modulated by tasks. found that, relative rest, enhanced increased tSD specific task‐engaged regions. However, variability broadly dampened during outside From our analyses, observed was strongest driver Overall, findings suggest choice can have should be relation maximizing networks part

Language: Английский

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Network and state specificity in connectivity‐based predictions of individual behavior

Human Brain Mapping, Journal Year: 2024, Volume and Issue: 45(8)

Published: June 1, 2024

Predicting individual behavior from brain functional connectivity (FC) patterns can contribute to our understanding of human functioning. This may apply in particular if predictions are based on features derived circumscribed, a priori defined networks, which improves interpretability. Furthermore, some evidence suggests that task-based FC data yield more successful than resting-state data. Here, we comprehensively examined what extent the correspondence network priors and task states with behavioral target domains influences predictability performance cognitive, social, affective tasks. To this end, used Human Connectome Project for large-scale out-of-sample abilities working memory (WM), theory-of-mind cognition (SOCIAL), emotion processing (EMO) corresponding non-corresponding (WM/SOCIAL/EMO/resting-state) networks (WM/SOCIAL/EMO/whole-brain connectome). Using root mean squared error coefficient determination evaluate model fit revealed predictive was rather poor overall. Predictions whole-brain were slightly better those task-specific slight benefit versus resting state observed WM domain. Beyond that, did not find any significant effects network, state, domains. Together, these results suggest multivariate during both contain little information levels, calling reconsideration how mediates differences mental abilities.

Language: Английский

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GEFF: Graph embedding for functional fingerprinting

NeuroImage, Journal Year: 2020, Volume and Issue: 221, P. 117181 - 117181

Published: July 20, 2020

It has been well established that Functional Connectomes (FCs), as estimated from functional MRI (fMRI) data, have an individual fingerprint can be used to identify a population (subject-identification). Although identification rate is high when using resting-state FCs, other tasks show moderate low values. Furthermore, task-dependent, and distinct cognitive states, captured by different fMRI tasks, are compared. Here we propose embedding framework, GEFF (Graph Embedding for Fingerprinting), based on group-level decomposition of FCs into eigenvectors. creates eigenspace representation group subjects one or more task (Learning Stage). In the Identification Stage, compare new instances Learning within this (validation dataset). The validation dataset contains either same remaining were not included in Learning. Assessment results significantly increased subject-identification rates all tested potentially task-independent fingerprinting process. noteworthy combining with Stage covers most space subject identification. Thus, while designing experiment, could choose ask specific question combine it extract maximum differentiability GEFF. addition subject-identification, was also i.e. associated given FC, regardless being already (subject-independent task-identification). addition, eigenvectors characterized task- subject-dominant, subject-dominant neither, two-way ANOVA their corresponding loadings, providing deeper insight extent variance connectivity across individuals states.

Language: Английский

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Multitask brain network reconfiguration is inversely associated with human intelligence

Cerebral Cortex, Journal Year: 2021, Volume and Issue: 32(19), P. 4172 - 4182

Published: Nov. 22, 2021

Intelligence describes the general cognitive ability level of a person. It is one most fundamental concepts in psychological science and crucial for effective adaption behavior to varying environmental demands. Changing external task demands have been shown induce reconfiguration functional brain networks. However, whether neural between different tasks associated with intelligence has not yet investigated. We used magnetic resonance imaging data from 812 subjects show that higher scores are related less network resting state seven states as well tasks. This association holds all networks except motor system replicates two independent samples (n = 138 n 184). Our findings suggest intrinsic architecture individuals closer required by various Multitask may, therefore, represent reflection behavioral positive manifold - essence concept intelligence. Finally, our results support efficiency theories reveal insights into human an emergent property distributed multitask network.

Language: Английский

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Large-scale functional brain networks of maladaptive childhood aggression identified by connectome-based predictive modeling

Molecular Psychiatry, Journal Year: 2021, Volume and Issue: 27(2), P. 985 - 999

Published: Oct. 25, 2021

Language: Английский

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Predicting response time variability from task and resting-state functional connectivity in the aging brain

NeuroImage, Journal Year: 2022, Volume and Issue: 250, P. 118890 - 118890

Published: Jan. 8, 2022

Aging is associated with declines in a host of cognitive functions, including attentional control, inhibitory episodic memory, processing speed, and executive functioning. Theoretical models attribute the age-related decline functioning to deficits goal maintenance inhibition. Despite these well-documented control resources, older adults endorse fewer episodes mind-wandering when assessed using task-embedded thought probes. Furthermore, previous work on neural basis has mostly focused young studies predominantly focusing activity connectivity select few canonical networks. However, whole-brain functional networks aging have not yet been characterized. In this study, response time variability—the trial-to-trial fluctuations behavioral responses—as an indirect marker or "out-of-the-zone" state representing suboptimal performance, we show that brain-based predictive variability can be derived from task connectivity. contrast, resting-state alone did predict individual variability. Finally, despite successful within-sample prediction variability, our generalize independent cohorts Overall, findings provide evidence for utility task-based predicting aging. Future research needed derive more robust generalizable models.

Language: Английский

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The Role of Visual Experience in Individual Differences of Brain Connectivity

Journal of Neuroscience, Journal Year: 2022, Volume and Issue: 42(25), P. 5070 - 5084

Published: May 19, 2022

Visual cortex organization is highly consistent across individuals. But to what degree does this consistency depend on life experience, in particular sensory experience? In study, we asked whether visual reorganization congenital blindness results connectivity patterns that are particularly variable individuals, focusing resting-state functional (RSFC) from the primary cortex. We show absence of shared experience more RSFC blind individuals than sighted controls. Increased variability specifically found areas a group difference between and their RSFC. These findings reveal relationship brain plasticity individual variability; manifests variably further investigated different blind, showing frontal regions, proposed have role toward higher cognitive roles, variable. Further, link some visual-to-frontal another environmental factor—duration formal education. Together, these postnatal socioeconomic imposing organization. By revealing idiosyncratic nature neural reorganization, highlight importance considering differences fitting aids restoration approaches for vision loss. SIGNIFICANCE STATEMENT The typical system What origins consistency? Comparing people born people, showed variability, suggesting key impact changed following were variable, resulting diverse reorganization. Individual also directly affected by nonvisual experiences (years education). creating endorse use profiles rehabilitation

Language: Английский

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Functional connectome stability and optimality are markers of cognitive performance

Cerebral Cortex, Journal Year: 2022, Volume and Issue: 33(8), P. 5025 - 5041

Published: Nov. 19, 2022

Patterns of whole-brain fMRI functional connectivity, or connectomes, are unique to individuals. Previous work has identified subsets connections within these patterns whose strength predicts aspects attention and cognition. However, overall features such as how stable they over time similar a group-average (typical) high-performance (optimal) connectivity pattern, may also reflect cognitive attentional abilities. Here, we test whether individuals who express more stable, typical, optimal, distinctive perform better on tasks using data from three independent samples. We find that with task-based working memory tasks, even when controlling for behavioral performance stability. Additionally, initial evidence typical optimal tasks. These results demonstrate connectome stability similarity across individual differences in

Language: Английский

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Masked features of task states found in individual brain networks

Cerebral Cortex, Journal Year: 2022, Volume and Issue: 33(6), P. 2879 - 2900

Published: July 8, 2022

Abstract Completing complex tasks requires that we flexibly integrate information across brain areas. While studies have shown how functional networks are altered during different tasks, this work has generally focused on a cross-subject approach, emphasizing features common people. Here used extended sampling “precision” fMRI data to test the extent which task states generalize people or individually specific. We trained classifiers decode state using network in single-person datasets 5 diverse states. Classifiers were then tested either independent from same person new individuals. Individualized able participants. However, classification performance was significantly higher within person, pattern consistent model types, people, feature subsets, and even for decoding very similar conditions. Notably, these findings also replicated dataset. These results suggest individual-focused approaches can uncover robust of states, including obscured analyses. Individual-focused potential deepen our understanding interactions cognition.

Language: Английский

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