Literature DB >> 30884018

The spatial chronnectome reveals a dynamic interplay between functional segregation and integration.

Armin Iraji1, Thomas P Deramus1, Noah Lewis1, Maziar Yaesoubi1, Julia M Stephen1, Erik Erhardt2, Aysneil Belger3, Judith M Ford4,5, Sarah McEwen6, Daniel H Mathalon4,5, Bryon A Mueller7, Godfrey D Pearlson8, Steven G Potkin9, Adrian Preda9, Jessica A Turner10, Jatin G Vaidya11, Theo G M van Erp12, Vince D Calhoun1,8,13.   

Abstract

The brain is highly dynamic, reorganizing its activity at different interacting spatial and temporal scales, including variation within and between brain networks. The chronnectome is a model of the brain in which nodal activity and connectivity patterns change in fundamental and recurring ways over time. Most literature assumes fixed spatial nodes/networks, ignoring the possibility that spatial nodes/networks may vary in time. Here, we introduce an approach to calculate a spatially fluid chronnectome (called the spatial chronnectome for clarity), which focuses on the variations of networks coupling at the voxel level, and identify a novel set of spatially dynamic features. Results reveal transient spatially fluid interactions between intra- and internetwork relationships in which brain networks transiently merge and separate, emphasizing dynamic segregation and integration. Brain networks also exhibit distinct spatial patterns with unique temporal characteristics, potentially explaining a broad spectrum of inconsistencies in previous studies that assumed static networks. Moreover, we show anticorrelative connections to brain networks are transient as opposed to constant across the entire scan. Preliminary assessments using a multi-site dataset reveal the ability of the approach to obtain new information and nuanced alterations that remain undetected during static analysis. Patients with schizophrenia (SZ) display transient decreases in voxel-wise network coupling within visual and auditory networks, and higher intradomain coupling variability. In summary, the spatial chronnectome represents a new direction of research enabling the study of functional networks which are transient at the voxel level, and the identification of mechanisms for within- and between-subject spatial variability.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  brain spatial dynamics; dynamic segregation and integration; large-scale networks; resting state fMRI (rsfMRI); schizophrenia; spatial chronnectome; spatial coupling; spatial states; spatiotemporal transition matrix

Mesh:

Year:  2019        PMID: 30884018      PMCID: PMC6548674          DOI: 10.1002/hbm.24580

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.399


  101 in total

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2.  Validating the independent components of neuroimaging time series via clustering and visualization.

Authors:  Johan Himberg; Aapo Hyvärinen; Fabrizio Esposito
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3.  Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain.

Authors:  Martijn P van den Heuvel; René C W Mandl; René S Kahn; Hilleke E Hulshoff Pol
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5.  Functional-anatomic fractionation of the brain's default network.

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6.  Group information guided ICA for fMRI data analysis.

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7.  Functional System and Areal Organization of a Highly Sampled Individual Human Brain.

Authors:  Timothy O Laumann; Evan M Gordon; Babatunde Adeyemo; Abraham Z Snyder; Sung Jun Joo; Mei-Yen Chen; Adrian W Gilmore; Kathleen B McDermott; Steven M Nelson; Nico U F Dosenbach; Bradley L Schlaggar; Jeanette A Mumford; Russell A Poldrack; Steven E Petersen
Journal:  Neuron       Date:  2015-07-23       Impact factor: 17.173

8.  Auditory hallucinations in schizophrenia are associated with reduced functional connectivity of the temporo-parietal area.

Authors:  Ans Vercammen; Henderikus Knegtering; Johann A den Boer; Edith J Liemburg; André Aleman
Journal:  Biol Psychiatry       Date:  2010-01-08       Impact factor: 13.382

9.  Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

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Journal:  EBioMedicine       Date:  2018-03-23       Impact factor: 8.143

10.  Performance of blind source separation algorithms for fMRI analysis using a group ICA method.

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  19 in total

1.  A strategy of model space search for dynamic causal modeling in task fMRI data exploratory analysis.

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2.  Multi-spatial-scale dynamic interactions between functional sources reveal sex-specific changes in schizophrenia.

Authors:  Armin Iraji; Ashkan Faghiri; Zening Fu; Srinivas Rachakonda; Peter Kochunov; Aysenil Belger; Judy M Ford; Sarah McEwen; Daniel H Mathalon; Bryon A Mueller; Godfrey D Pearlson; Steven G Potkin; Adrian Preda; Jessica A Turner; Theodorus G M van Erp; Vince D Calhoun
Journal:  Netw Neurosci       Date:  2022-06-01

Review 3.  Space: A Missing Piece of the Dynamic Puzzle.

Authors:  Armin Iraji; Robyn Miller; Tulay Adali; Vince D Calhoun
Journal:  Trends Cogn Sci       Date:  2020-01-23       Impact factor: 20.229

Review 4.  Principles and open questions in functional brain network reconstruction.

Authors:  Onerva Korhonen; Massimiliano Zanin; David Papo
Journal:  Hum Brain Mapp       Date:  2021-05-20       Impact factor: 5.038

5.  Graph-theoretical analysis identifies transient spatial states of resting-state dynamic functional network connectivity and reveals dysconnectivity in schizophrenia.

Authors:  Qunfang Long; Suchita Bhinge; Vince D Calhoun; Tülay Adali
Journal:  J Neurosci Methods       Date:  2020-12-25       Impact factor: 2.390

6.  Prediction of Seizure Recurrence. A Note of Caution.

Authors:  William J Bosl; Alan Leviton; Tobias Loddenkemper
Journal:  Front Neurol       Date:  2021-05-13       Impact factor: 4.003

7.  The spatial chronnectome reveals a dynamic interplay between functional segregation and integration.

Authors:  Armin Iraji; Thomas P Deramus; Noah Lewis; Maziar Yaesoubi; Julia M Stephen; Erik Erhardt; Aysneil Belger; Judith M Ford; Sarah McEwen; Daniel H Mathalon; Bryon A Mueller; Godfrey D Pearlson; Steven G Potkin; Adrian Preda; Jessica A Turner; Jatin G Vaidya; Theo G M van Erp; Vince D Calhoun
Journal:  Hum Brain Mapp       Date:  2019-03-18       Impact factor: 5.399

8.  Relationship between Dynamic Blood-Oxygen-Level-Dependent Activity and Functional Network Connectivity: Characterization of Schizophrenia Subgroups.

Authors:  Qunfang Long; Suchita Bhinge; Vince D Calhoun; Tülay Adali
Journal:  Brain Connect       Date:  2021-04-22

9.  Weighted average of shared trajectory: A new estimator for dynamic functional connectivity efficiently estimates both rapid and slow changes over time.

Authors:  Ashkan Faghiri; Armin Iraji; Eswar Damaraju; Aysenil Belger; Judy Ford; Daniel Mathalon; Sarah Mcewen; Bryon Mueller; Godfrey Pearlson; Adrian Preda; Jessica Turner; Jatin G Vaidya; Theo G M Van Erp; Vince D Calhoun
Journal:  J Neurosci Methods       Date:  2020-01-21       Impact factor: 2.390

10.  Lag Analysis of Fast fMRI Reveals Delayed Information Flow Between the Default Mode and Other Networks in Narcolepsy.

Authors:  M Järvelä; V Raatikainen; A Kotila; J Kananen; V Korhonen; L Q Uddin; H Ansakorpi; V Kiviniemi
Journal:  Cereb Cortex Commun       Date:  2020-10-10
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