Working Memory Load-related Theta Power Decreases in Dorsolateral Prefrontal Cortex Predict Individual Differences in Performance
Abstract
Holding information in working memory (WM) is an active and effortful process that is accompanied by sustained load-dependent changes in oscillatory brain activity. These proportional power increases are often reported in EEG studies recording theta over frontal midline sites. Intracranial recordings, however, yield mixed results, depending on the brain area being recorded from. We recorded intracranial EEG with depth electrodes in 13 patients with epilepsy that were performing a Sternberg WM task. Here, we investigated patterns of theta power changes as a function of memory load during maintenance in three areas critical for WM: dorsolateral prefrontal cortex (DLPFC), dorsal ACC (dACC), and hippocampus. Theta frequency power in both hippocampus and dACC increased during maintenance. In contrast, theta frequency power in the DLPFC decreased during maintenance, and this decrease was proportional to memory load. Only the power decreases in DLPFC, but not the power increases in hippocampus and dACC, were predictive of behavior in a given trial. The extent of the load-related theta power decreases in the DLPFC in a given participant predicted a participant's RTs, revealing that DLPFC theta explains individual differences in WM ability between participants. Together, these data reveal a pattern of theta power decreases in the DLPFC that is predictive of behavior and that is opposite of that in other brain areas. This result suggests that theta band power changes serve different cognitive functions in different brain areas and specifically that theta power decreases in DLPFC have an important role in maintenance of information.
Additional Information
© 2019 Massachusetts Institute of Technology. Posted Online April 30, 2019. This paper is part of a Special Focus deriving from a symposium at the 2018 Annual Meeting of the Cognitive Neuroscience Society entitled "Episodic Memory Formation: From Neural Circuits to Behavior."Attached Files
Published - jocn_a_01417.pdf
Accepted Version - nihms-1038657.pdf
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Additional details
- PMCID
- PMC6669115
- Eprint ID
- 95229
- Resolver ID
- CaltechAUTHORS:20190506-082438654
- Created
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2019-05-06Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field