Evidence map›Paper›PMID 38853875›Full record

ArticlemedRxiv : the preprint server for health sciences2024

High-gamma and beta bursts in the Left Supramarginal Gyrus can accurately differentiate verbal memory states and performance.

Nicolás Sawczuk, Daniel Y Rubinstein, Michael R Sperling, Katrina Wendel-Mitoraj, Petar Djuric, Diego F Slezak, Juan Kamienkowski, Shennan A Weiss

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Nicolás SawczukDepartment of Computer Science, University of Buenos Aires, Buenos Aires, Argentina.
Daniel Y RubinsteinDepartment of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, PA 19107, USA.ORCID 0000-0002-6292-7392
Michael R SperlingDepartment of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, PA 19107, USA.ORCID 0000-0003-0708-6006
Katrina Wendel-MitorajSoenia by Braincare Oy, Tampere, Finland.ORCID 0009-0002-9689-213X
Petar DjuricDept. of Electrical & Computer Engineering, Stony Brook, New York, 11794 USA.
Diego F SlezakDepartment of Computer Science, University of Buenos Aires, Buenos Aires, Argentina.ORCID 0000-0001-6348-1559
Juan KamienkowskiDepartment of Computer Science, University of Buenos Aires, Buenos Aires, Argentina.ORCID 0000-0002-5725-6539
Shennan A WeissDepartment of Neurology, Stony Brook University, Stony Brook, New York, 11790 USA.ORCID 0000-0003-0825-8439

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The left supramarginal gyrus (LSMG) may mediate attention to memory, and gauge memory state and performance. We performed a secondary analysis of 142 verbal delayed free recall experiments, in patients with medically-refractory epilepsy with electrode contacts implanted in the LSMG. In 14 of 142 experiments (in 14 of 113 patients), the cross-validated convolutional neural networks (CNNs) that used 1-dimensional(1-D) pairs of convolved high-gamma and beta tensors, derived from the LSMG recordings, could label recalled words with an area under the receiver operating curve (AUROC) of greater than 60% [range: 60-90%]. These 14 patients were distinguished by: 1) higher amplitudes of high-gamma bursts; 2) distinct electrode placement within the LSMG; and 3) superior performance compared with a CNN that used a 1-D tensor of the broadband recordings in the LSMG. In a pilot study of 7 of these patients, we also cross-validated CNNs using paired 1-D convolved high-gamma and beta tensors, from the LSMG, to: a) distinguish word encoding epochs from free recall epochs [AUC 0.6-1]; and distinguish better performance from poor performance during delayed free recall [AUC 0.5-0.86]. These experiments show that bursts of high-gamma and beta generated in the LSMG are biomarkers of verbal memory state and performance.

Indexed as

beta oscillationsconvolutional neural networkhigh-gamma oscillationssupramarginal gyrusVerbal memory

Identifiers

PMID38853875
PMCPMC11160814

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.