Statistics of Piano major participants.

This study aimed to investigate how neural activation patterns differ between pianists and non-pianist musicians during piano performance tasks, using an LSTM-Autoencoder model applied to fNIRS data. A total of 22 participants, comprising both piano-majors and non-piano-majors, were involved in this study. Each participant’s performance data, collected during Score-based playing and improvisation tasks, was analyzed using a Long Short-Term Memory (LSTM) Autoencoder model. Reconstruction errors in specific brain channels, measured through Functional Near-Infrared Spectroscopy (fNIRS), showed group-level patterns—particularly in channels 1 and 15 (app. BA 45L, BA 45R)—but these differences did not reach statistical significance in inferential tests. These findings are therefore reported as exploratory and suggest distinct neural engagement patterns associated with varying levels of musical expertise.本研究旨在探究钢琴演奏者与非钢琴演奏音乐人在执行钢琴演奏任务时的神经激活模式差异，采用长短期记忆自动编码器（Long Short-Term Memory Autoencoder, LSTM-Autoencoder）对功能性近红外光谱（Functional Near-Infrared Spectroscopy, fNIRS）数据开展分析。本研究共纳入22名受试者，涵盖钢琴专业与非钢琴专业人群。针对每位受试者在视谱演奏与即兴创作任务中采集的演奏数据，本研究采用长短期记忆（LSTM）自动编码器模型进行分析。通过fNIRS测得的特定脑通道重构误差，呈现出群体层面的模式差异，尤其在通道1与通道15（大致对应布罗德曼区45左、布罗德曼区45右）处，但该差异在推断统计检验中未达到统计学显著性。因此本研究将上述发现作为探索性结果进行报道，其表明与不同音乐专业水平相关的神经参与模式存在差异。