Work

Decoding the Spatiotemporal Dynamics of Neural Response Similarity in Auditory Processing: A Multivariate Analysis Based on OPM ‐ MEG

Year: 2025

Type: article

Abstract: The brain represents information through the encoding of neural populations, where the activity patterns of these neural groups constitute the content of this information. Understanding these activity patterns and their dynamic changes is of significant importance to cognitive neuroscience and related research areas. Current studies focus more on brain regions that show differential responses to stimuli, but they lack the ability to capture information about the representational or process-level dynamics within these regions. In this study, we recorded neural data from 10 healthy participants during auditory experiments using optically pumped magnetometer magnetoencephalography (OPM-MEG) and electroencephalography (EEG). We constructed representational similarity matrices (RSMs) to investigate the similarity of neural response patterns during auditory decoding. The results indicate that RSA can reveal the dynamic changes in pattern similarity during different stages of auditory processing through the neural activity patterns reflected by OPM-MEG. Comparisons with EEG results showed that both techniques captured the same processes during the early stages of auditory decoding. However, differences in sensitivity at later stages highlighted both common and distinct aspects of neural representation between the two modalities. Further analysis indicated that this process involved widespread neural network activation, including the Heschl's gyrus, superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, parahippocampal gyrus, and orbitofrontal gyrus. This study demonstrates that the combination of OPM-MEG and RSA is sufficiently sensitive to detect changes in pattern similarity during neural representation processes and to identify their anatomical origins, offering new insights and references for the future application of RSA and other multivariate pattern analysis methods in the MEG field.

Source: Human Brain Mapping

DOI: 10.1002/hbm.70175

Authors: Changzeng Liu, Yuyu Ma, Xiaoyu Liang, Min Xiang, Huanqi Wu, Xiaolin Ning

Institutions: Beihang University, Shandong University

Language: English

Topic: Neuroscience and Music Perception

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $3,520

Funders: Shandong University, Key Technology Research and Development Program of Shandong, Beijing Municipal Natural Science Foundation