■在各种认知负荷下对音乐刺激的反应中解码个体隐藏的大脑状态可以释放开发非侵入性闭环脑机接口(CLBMI)的潜力。为了进行初步研究并调查CLBMI背景下的大脑反应,在存在个性化音乐刺激的情况下,我们在工作记忆实验中收集多模态生理信号和行为数据。
■参与者在平静的音乐和令人兴奋的音乐面前进行称为n-back任务的工作记忆实验。利用皮肤电导信号和行为数据,我们解码大脑的认知唤醒和表现状态,分别。我们确定氧合血红蛋白(HbO)数据与性能状态的关联。此外,我们评估每个音乐时段的总血红蛋白(HbT)信号能量。
■在任务难度方面观察到相对较低的唤醒变化,而唤醒基线相对于音乐类型有很大变化。总的来说,在激动人心的会议中,绩效指数得到了提高。在所有参与者的较高认知负荷(3-back任务)中,观察到HbO浓度与表现之间的最高正相关。此外,HbT信号能量峰值出现在激励会话内。
■研究结果可能强调了使用音乐作为干预来调节大脑认知状态的潜力。此外,该实验提供了包含多个生理信号的各种数据,这些信号可用于大脑状态解码器范式,以阐明人类在环实验并了解听觉刺激的网络级机制。
UNASSIGNED: Decoding an individual\'s hidden brain states in responses to musical stimuli under various cognitive loads can unleash the potential of developing a non-invasive closed-loop brain-machine interface (CLBMI). To perform a pilot study and investigate the brain response in the context of CLBMI, we collect multimodal physiological signals and behavioral data within the working memory experiment in the presence of personalized musical stimuli.
UNASSIGNED: Participants perform a working memory experiment called the n-back task in the presence of calming music and exciting music. Utilizing the skin conductance signal and behavioral data, we decode the brain\'s cognitive arousal and performance states, respectively. We determine the association of oxygenated hemoglobin (HbO) data with performance state. Furthermore, we evaluate the total hemoglobin (HbT) signal energy over each music session.
UNASSIGNED: A relatively low arousal variation was observed with respect to task difficulty, while the arousal baseline changes considerably with respect to the type of music. Overall, the performance index is enhanced within the exciting session. The highest positive correlation between the HbO concentration and performance was observed within the higher cognitive loads (3-back task) for all of the participants. Also, the HbT signal energy peak occurs within the exciting session.
UNASSIGNED: Findings may underline the potential of using music as an intervention to regulate the brain cognitive states. Additionally, the experiment provides a diverse array of data encompassing multiple physiological signals that can be used in the brain state decoder paradigm to shed light on the human-in-the-loop experiments and understand the network-level mechanisms of auditory stimulation.