Large-scale functional networks connect differently for processing words and symbol strings

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Large-scale functional networks connect differently for processing words and symbol strings. / Liljeström, Mia; Vartiainen, Johanna; Kujala, Jan; Salmelin, Riitta.

In: PloS one, Vol. 13, No. 5, e0196773, 01.05.2018, p. 1-19.

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@article{451c212a56f241daa2ef4765cf1a1bd6,
title = "Large-scale functional networks connect differently for processing words and symbol strings",
abstract = "Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalog-raphy (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8–13 Hz) and high gamma (60–90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21–29 Hz) and low gamma (30–45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.",
author = "Mia Liljestr{\"o}m and Johanna Vartiainen and Jan Kujala and Riitta Salmelin",
year = "2018",
month = "5",
day = "1",
doi = "10.1371/journal.pone.0196773",
language = "English",
volume = "13",
pages = "1--19",
journal = "PloS one",
issn = "1932-6203",
number = "5",

}

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TY - JOUR

T1 - Large-scale functional networks connect differently for processing words and symbol strings

AU - Liljeström, Mia

AU - Vartiainen, Johanna

AU - Kujala, Jan

AU - Salmelin, Riitta

PY - 2018/5/1

Y1 - 2018/5/1

N2 - Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalog-raphy (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8–13 Hz) and high gamma (60–90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21–29 Hz) and low gamma (30–45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

AB - Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalog-raphy (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8–13 Hz) and high gamma (60–90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21–29 Hz) and low gamma (30–45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

UR - http://www.scopus.com/inward/record.url?scp=85046418342&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0196773

DO - 10.1371/journal.pone.0196773

M3 - Article

VL - 13

SP - 1

EP - 19

JO - PloS one

JF - PloS one

SN - 1932-6203

IS - 5

M1 - e0196773

ER -

ID: 21094468