"Frequency-specific coactivation patterns in resting-state and their al" by Hang Yang, Hong Zhang et al.
 

Frequency-specific coactivation patterns in resting-state and their alterations in schizophrenia: An fMRI study

Document Type

Article

Publication Date

8-15-2022

Abstract

The resting-state human brain is a dynamic system that shows frequency-dependent characteristics. Recent studies demonstrate that coactivation pattern (CAP) analysis can identify recurring brain states with similar coactivation configurations. However, it is unclear whether and how CAPs depend on the frequency bands. The current study investigated the spatial and temporal characteristics of CAPs in the four frequency sub-bands from slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), slow-3 (0.073–0.198 Hz), to slow-2 (0.198–0.25 Hz), in addition to the typical low-frequency range (0.01–0.08 Hz). In the healthy subjects, six CAP states were obtained at each frequency band in line with our prior study. Similar spatial patterns with the typical range were observed in slow-5, 4, and 3, but not in slow-2. While the frequency increased, all CAP states displayed shorter persistence, which caused more between-state transitions. Specifically, from slow-5 to slow-4, the coactivation not only changed significantly in distributed cortical networks, but also increased in the basal ganglia as well as the amygdala. Schizophrenia patients showed significant alteration in the persistence of CAPs of slow-5. Using leave-one-pair-out, hold-out and resampling validations, the highest classification accuracy (84%) was achieved by slow-4 among different frequency bands. In conclusion, our findings provide novel information about spatial and temporal characteristics of CAP states at different frequency bands, which contributes to a better understanding of the frequency aspect of biomarkers for schizophrenia and other disorders.

Identifier

85128824326 (Scopus)

Publication Title

Human Brain Mapping

External Full Text Location

https://doi.org/10.1002/hbm.25884

e-ISSN

10970193

ISSN

10659471

PubMed ID

35475569

First Page

3792

Last Page

3808

Issue

12

Volume

43

Grant

61871420

Fund Ref

National Natural Science Foundation of China

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