» Articles » PMID: 28549798

Whole-brain Connectivity Dynamics Reflect Both Task-specific and Individual-specific Modulation: A Multitask Study

Overview
Journal Neuroimage
Specialty Radiology
Date 2017 May 28
PMID 28549798
Citations 31
Authors
Affiliations
Soon will be listed here.
Abstract

Functional connectivity (FC) has been widely used to study the functional organization of temporally correlated and spatially distributed brain regions. Recent studies of FC dynamics, quantified by windowed correlations, provide new insights to analyze dynamic, context-dependent reconfiguration of brain networks. A set of reoccurring whole-brain connectivity patterns at rest, referred to as FC states, have been identified, hypothetically reflecting underlying cognitive processes or mental states. We posit that the mean FC information for a given subject represents a significant contribution to the group-level FC dynamics. We show that the subject-specific FC profile, termed as FC individuality, can be removed to increase sensitivity to cognitively relevant FC states. To assess the impact of the FC individuality and task-specific FC modulation on the group-level FC dynamics analysis, we generate and analyze group studies of four subjects engaging in four cognitive conditions (rest, simple math, two-back memory, and visual attention task). We also propose a model to quantitatively evaluate the effect of two factors, namely, subject-specific and task-specific modulation on FC dynamics. We show that FC individuality is a predominant factor in group-level FC variability, and the embedded cognitively relevant FC states are clearly visible after removing the individual's connectivity profile. Our results challenge the current understanding of FC states and emphasize the importance of individual heterogeneity in connectivity dynamics analysis.

Citing Articles

Within-Individual Precision Mapping of Brain Networks Exclusively Using Task Data.

Du J, Elliott M, Ladopoulou J, Eldaief M, Buckner R bioRxiv. 2025; .

PMID: 40060474 PMC: 11888310. DOI: 10.1101/2025.02.25.640090.


An information-theoretic analysis of resting-state versus task fMRI.

Tuominen J, Specht K, Vaisvilaite L, Zeidman P Netw Neurosci. 2023; 7(2):769-786.

PMID: 37397893 PMC: 10312267. DOI: 10.1162/netn_a_00302.


Altered static and dynamic spontaneous neural activity in patients with ischemic pontine stroke.

Wang X, Wang C, Liu J, Guo J, Miao P, Wei Y Front Neurosci. 2023; 17:1131062.

PMID: 37008224 PMC: 10060846. DOI: 10.3389/fnins.2023.1131062.


Abnormal cerebellar-prefrontal cortical pathways in obstructive sleep apnea with/without mild cognitive impairment.

Shu Y, Chen L, Li K, Li H, Kong L, Liu X Front Neurosci. 2022; 16:1002184.

PMID: 36340771 PMC: 9630600. DOI: 10.3389/fnins.2022.1002184.


A tale of two connectivities: intra- and inter-subject functional connectivity jointly enable better prediction of social abilities.

Xie H, Redcay E Front Neurosci. 2022; 16:875828.

PMID: 36117636 PMC: 9475068. DOI: 10.3389/fnins.2022.875828.


References
1.
Vergara V, Mayer A, Damaraju E, Hutchison K, Calhoun V . The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA. Neuroimage. 2016; 145(Pt B):365-376. PMC: 5035165. DOI: 10.1016/j.neuroimage.2016.03.038. View

2.
Damaraju E, Allen E, Belger A, Ford J, McEwen S, Mathalon D . Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia. Neuroimage Clin. 2014; 5:298-308. PMC: 4141977. DOI: 10.1016/j.nicl.2014.07.003. View

3.
Grabner R, Ansari D, Reishofer G, Stern E, Ebner F, Neuper C . Individual differences in mathematical competence predict parietal brain activation during mental calculation. Neuroimage. 2007; 38(2):346-56. DOI: 10.1016/j.neuroimage.2007.07.041. View

4.
Calhoun V, Adali T . Multisubject independent component analysis of fMRI: a decade of intrinsic networks, default mode, and neurodiagnostic discovery. IEEE Rev Biomed Eng. 2012; 5:60-73. PMC: 4433055. DOI: 10.1109/RBME.2012.2211076. View

5.
Mueller S, Wang D, Fox M, Yeo B, Sepulcre J, Sabuncu M . Individual variability in functional connectivity architecture of the human brain. Neuron. 2013; 77(3):586-95. PMC: 3746075. DOI: 10.1016/j.neuron.2012.12.028. View