Latency analysis of resting-state BOLD-fMRI reveals traveling waves in visual cortex linking task-positive and task-negative networks

R. Hindriks, Mantini R, Gravel N, Deco G

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Due to the low temporal resolution of BOLD-fMRI, imaging studies on human brain function have almost exclusively focused on instantaneous correlations within the data. Developments in hardware and acquisition protocols, however, are offering data with higher sampling rates that allow investigating the latency structure of BOLD-fMRI data. In this study we describe a method for analyzing the latency structure within BOLD-fMRI data and apply it to resting-state data of 94 participants from the Human Connectome Project. The method shows that task-positive and task-negative networks are integrated through traveling BOLD waves within early visual cortex. The waves are initiated at the periphery of the visual field and propagate towards the fovea. This observation suggests a mechanism for the functional integration of task-positive and task-negative networks, argues for an eccentricity-based view on visual information processing, and contributes to the emerging view that resting-state BOLD-fMRI fluctuations are superpositions of inherently spatiotemporal patterns.

Original languageEnglish
Pages (from-to)259-274
Number of pages16
JournalNeuroImage
Volume200
DOIs
Publication statusPublished - 15 Oct 2019

Fingerprint

Visual Cortex
Magnetic Resonance Imaging
Connectome
Visual Fields
Automatic Data Processing
Brain

Cite this

@article{7a98a787854f46868114a523cdb8bfa6,
title = "Latency analysis of resting-state BOLD-fMRI reveals traveling waves in visual cortex linking task-positive and task-negative networks",
abstract = "Due to the low temporal resolution of BOLD-fMRI, imaging studies on human brain function have almost exclusively focused on instantaneous correlations within the data. Developments in hardware and acquisition protocols, however, are offering data with higher sampling rates that allow investigating the latency structure of BOLD-fMRI data. In this study we describe a method for analyzing the latency structure within BOLD-fMRI data and apply it to resting-state data of 94 participants from the Human Connectome Project. The method shows that task-positive and task-negative networks are integrated through traveling BOLD waves within early visual cortex. The waves are initiated at the periphery of the visual field and propagate towards the fovea. This observation suggests a mechanism for the functional integration of task-positive and task-negative networks, argues for an eccentricity-based view on visual information processing, and contributes to the emerging view that resting-state BOLD-fMRI fluctuations are superpositions of inherently spatiotemporal patterns.",
author = "R. Hindriks and Mantini R and Gravel N and Deco G",
year = "2019",
month = "10",
day = "15",
doi = "10.1016/j.neuroimage.2019.06.007",
language = "English",
volume = "200",
pages = "259--274",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Academic Press Inc.",

}

Latency analysis of resting-state BOLD-fMRI reveals traveling waves in visual cortex linking task-positive and task-negative networks. / Hindriks, R.; R, Mantini; N, Gravel; G, Deco.

In: NeuroImage, Vol. 200, 15.10.2019, p. 259-274.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Latency analysis of resting-state BOLD-fMRI reveals traveling waves in visual cortex linking task-positive and task-negative networks

AU - Hindriks, R.

AU - R, Mantini

AU - N, Gravel

AU - G, Deco

PY - 2019/10/15

Y1 - 2019/10/15

N2 - Due to the low temporal resolution of BOLD-fMRI, imaging studies on human brain function have almost exclusively focused on instantaneous correlations within the data. Developments in hardware and acquisition protocols, however, are offering data with higher sampling rates that allow investigating the latency structure of BOLD-fMRI data. In this study we describe a method for analyzing the latency structure within BOLD-fMRI data and apply it to resting-state data of 94 participants from the Human Connectome Project. The method shows that task-positive and task-negative networks are integrated through traveling BOLD waves within early visual cortex. The waves are initiated at the periphery of the visual field and propagate towards the fovea. This observation suggests a mechanism for the functional integration of task-positive and task-negative networks, argues for an eccentricity-based view on visual information processing, and contributes to the emerging view that resting-state BOLD-fMRI fluctuations are superpositions of inherently spatiotemporal patterns.

AB - Due to the low temporal resolution of BOLD-fMRI, imaging studies on human brain function have almost exclusively focused on instantaneous correlations within the data. Developments in hardware and acquisition protocols, however, are offering data with higher sampling rates that allow investigating the latency structure of BOLD-fMRI data. In this study we describe a method for analyzing the latency structure within BOLD-fMRI data and apply it to resting-state data of 94 participants from the Human Connectome Project. The method shows that task-positive and task-negative networks are integrated through traveling BOLD waves within early visual cortex. The waves are initiated at the periphery of the visual field and propagate towards the fovea. This observation suggests a mechanism for the functional integration of task-positive and task-negative networks, argues for an eccentricity-based view on visual information processing, and contributes to the emerging view that resting-state BOLD-fMRI fluctuations are superpositions of inherently spatiotemporal patterns.

UR - http://www.scopus.com/inward/record.url?scp=85068116545&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85068116545&partnerID=8YFLogxK

U2 - 10.1016/j.neuroimage.2019.06.007

DO - 10.1016/j.neuroimage.2019.06.007

M3 - Article

VL - 200

SP - 259

EP - 274

JO - NeuroImage

JF - NeuroImage

SN - 1053-8119

ER -