Mental arithmetic / rest

EEGMAT: EEG decoding results

Name: BCI Report: results on EEGMAT
Creator: BCI Report
License: https://creativecommons.org/licenses/by/4.0/

EEGMAT (EEG During Mental Arithmetic Tasks) is a PhysioNet database, version 1.0.0 published December 2018, with two 60-second artifact-free EEG recordings from each of 36 participants: one before and one during a serial-subtraction task. Contributed from Igor Sikorsky Kyiv Polytechnic Institute and described by Zyma et al. in Data (2019).

Also known as EEGMAT · EEG During Mental Arithmetic Tasks · Electroencephalograms during Mental Arithmetic Task Performance · Zyma et al. (2019)

Description sources physionet.org · doi.org

Where it appears

Published results

Every figure below is copied from a reviewed download, not recomputed for this page. Read each group with its protocol on the linked page.

Core matrix · arithmetic & rest

Read with its protocol: Core matrix (home page) · Chance level 50.0% · experiments.json

Spectral ridge

56.8% (54.6%–58.9%)

LaBraM

64.6% (60.5%–68.6%)

CBraMod

62.3% (58.1%–66.5%)

EEGNet

67.6% (62.8%–72.5%)

Balanced accuracy, 4 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
Spectral ridge	Serial subtraction versus resting EEG	Balanced accuracy	56.8%54.6%–58.9%	36
LaBraM	Serial subtraction versus resting EEG	Balanced accuracy	64.6%60.5%–68.6%	36
CBraMod	Serial subtraction versus resting EEG	Balanced accuracy	62.3%58.1%–66.5%	36
EEGNet	Serial subtraction versus resting EEG	Balanced accuracy	67.6%62.8%–72.5%	36

Pretraining · fixed readout

Read with its protocol: Does pretraining help? · deployment-topics.json

Method	Condition	Metric	Value	People
LaBraM	Mental workload · pretrained	Balanced accuracy	64.6%	36
LaBraM	Mental workload · random initialization (mean)	Balanced accuracy	56.5%	36
CBraMod	Mental workload · pretrained	Balanced accuracy	62.3%	36
CBraMod	Mental workload · random initialization (mean)	Balanced accuracy	56.4%	36

Pretraining · train-selected readout

Read with its protocol: Does pretraining help? · deployment-topics.json

Method	Condition	Metric	Value	People
LaBraM	Mental workload · pretrained	Balanced accuracy	64.4%	36
LaBraM	Mental workload · random initialization (mean)	Balanced accuracy	56.5%	36
CBraMod	Mental workload · pretrained	Balanced accuracy	68.4%	36
CBraMod	Mental workload · random initialization (mean)	Balanced accuracy	61.7%	36

Pretraining · fixed classical control

Read with its protocol: Does pretraining help? · deployment-topics.json

Method	Condition	Metric	Value	People
Log-covariance ridge	Mental workload	Balanced accuracy	61.9%56.2%–67.6%	36

Source and licence

EEGMAT

Credit Igor Zyma, Ivan Seleznov, Anton Popov, Mariia Chernykh, Oleksii Shpenkov · EEG During Mental Arithmetic Tasks 1.0.0, PhysioNet, doi:10.13026/C2JQ1P. Study: Zyma et al. (2019), doi:10.3390/data4010014. PhysioNet platform: Pollard et al. (2026), doi:10.1038/s44360-026-00096-z.

Open Data Commons Attribution License 1.0 ↗ · Dataset record ↗

BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data belong to the people credited.

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