Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data.

IF 3.8 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

PLoS Computational Biology Pub Date : 2025-01-21 eCollection Date: 2025-01-01 DOI:10.1371/journal.pcbi.1012765

Fernando A Najman, Antonio Galves, Marcela Svarc, Claudia D Vargas

引用次数: 0

Abstract

It has been classically conjectured that the brain assigns probabilistic models to sequences of stimuli. An important issue associated with this conjecture is the identification of the classes of models used by the brain to perform this task. We address this issue by using a new clustering procedure for sets of electroencephalographic (EEG) data recorded from participants exposed to a sequence of auditory stimuli generated by a stochastic chain. This clustering procedure indicates that the brain uses the recurrent occurrences of a regular auditory stimulus in order to build a model.

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从电生理数据中提取随机节奏性听觉刺激序列指纹图谱。

经典的推测是，大脑为刺激序列分配了概率模型。与这一猜想相关的一个重要问题是识别大脑执行这一任务所使用的模型类别。我们通过使用新的聚类程序来解决这个问题，这些聚类程序记录了参与者暴露于随机链产生的听觉刺激序列的脑电图（EEG）数据集。这种聚类过程表明，大脑利用常规听觉刺激的反复出现来建立一个模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY

CiteScore

7.10

自引率

4.70%

发文量

820

审稿时长

2.5 months

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