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Beta-band modulation in the human hippocampus during a conflict response task.

Authors :
Chen KH
Gogia AS
Tang AM
Del Campo-Vera RM
Sebastian R
Nune G
Wong J
Liu CY
Kellis S
Lee B
Source :
Journal of neural engineering [J Neural Eng] 2020 Nov 11; Vol. 17 (6). Date of Electronic Publication: 2020 Nov 11.
Publication Year :
2020

Abstract

Objective . Identify the role of beta-band (13-30 Hz) power modulation in the human hippocampus during conflict processing. Approach . We investigated changes in the spectral power of the beta band (13-30 Hz) as measured by depth electrode leads in the hippocampus during a modified Stroop task in six patients with medically refractory epilepsy. Previous work done with direct electrophysiological recordings in humans has shown hippocampal theta-band (3-8 Hz) modulation during conflict processing. Local field potentials sampled at 2 k Hz were used for analysis and a non-parametric cluster-permutation t -test was used to identify the time period and frequency ranges of significant power change during cue processing (i.e. post-stimulus, pre-response). Main results . In five of the six patients, we observe a statistically significant increase in hippocampal beta-band power during successful conflict processing in the incongruent trial condition (cluster-based correction for multiple comparisons, p < 0.05). There was no significant beta-band power change observed during the cue-processing period of the congruent condition in the hippocampus of these patients. Significance . The beta-power changes during conflict processing represented here are consistent with previous studies suggesting that the hippocampus plays a role in conflict processing, but it is the first time that the beta band has been shown to be involved in humans with direct electrophysiological evidence. We propose that beta-band modulation plays a role in successful conflict detection and automatic response inhibition in the human hippocampus as studied during a conflict response task.<br /> (© 2020 IOP Publishing Ltd.)

Details

Language :
English
ISSN :
1741-2552
Volume :
17
Issue :
6
Database :
MEDLINE
Journal :
Journal of neural engineering
Publication Type :
Academic Journal
Accession number :
33059331
Full Text :
https://doi.org/10.1088/1741-2552/abc1b8