Evidence map›Paper›PMID 36138909›Full record

ArticleBrain sciences2022

A Method for the Study of Cerebellar Cognitive Function-Re-Cognition and Validation of Error-Related Potentials.

Bo Mu, Chang Niu, Jingping Shi, Rumei Li, Chao Yu, Kuiying Yin

Abstract read
In one paragraph

Article in Brain sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Bo MuNanjing Research Institute of Electronic Technology, Nanjing 210019, China.
Chang NiuNanjing Research Institute of Electronic Technology, Nanjing 210019, China.
Jingping ShiNeurology Department of the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China.
Rumei LiNanjing Research Institute of Electronic Technology, Nanjing 210019, China.
Chao YuNanjing Research Institute of Electronic Technology, Nanjing 210019, China.
Kuiying YinNanjing Research Institute of Electronic Technology, Nanjing 210019, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The cerebellar region has four times as many brain cells as the brain, but whether the cerebellum functions in cognition, and how it does so, remain unexplored. In order to verify whether the cerebellum is involved in cognition, we chose to investigate whether the cerebellum is involved in the process of error judgment. We designed an experiment in which we could activate the subject's error-related potentials (ErrP). We recruited 26 subjects and asked them to wear EEG caps with cerebellar regions designed by us to participate in the experiment so that we could record their EEG activity throughout the experiment. We successfully mitigated the majority of noise interference after a series of pre-processing of the data collected from each subject. Our analysis of the preprocessed data revealed that our experiment successfully activated ErrP, and that the EEG signals, including the cerebellum, were significantly different when subjects made errors compared to when they made correct judgments. We designed a feature extraction method that requires selecting channels with large differences under different classifications, firstly by extracting the time-frequency features of these channels, and then screening these features with sequence backward feature (SBS) selection. We use the extracted features as the input and different event types in EEG data as the labels for multiple classifiers to classify the data in the executive and feedback segments, where the average accuracy for two-class classification of executive segments can reach 80.5%. The major contribution of our study is the discovery of the presence of ErrP in cerebellar regions and the extraction of an effective feature extraction method for EEG data.

Indexed as

cerebellar regionsclassification methodelectroencephalography (EEG)error-related potentials (ErrP)

Identifiers

PMID36138909
PMCPMC9497277

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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.