Hajizadeh Aida, Matysiak Artur, Brechmann André, König Reinhard, May Patrick J C
Leibniz Institute for Neurobiology, Research Group Comparative Neuroscience, Magdeburg, Germany.
Leibniz Institute for Neurobiology, Combinatorial NeuroImaging Core Facility, Magdeburg, Germany.
Psychophysiology. 2021 Apr;58(4):e13769. doi: 10.1111/psyp.13769. Epub 2021 Jan 21.
Auditory event-related fields (ERFs) measured with magnetoencephalography (MEG) are useful for studying the neuronal underpinnings of auditory cognition in human cortex. They have a highly subject-specific morphology, albeit certain characteristic deflections (e.g., P1m, N1m, and P2m) can be identified in most subjects. Here, we explore the reason for this subject-specificity through a combination of MEG measurements and computational modeling of auditory cortex. We test whether ERF subject-specificity can predominantly be explained in terms of each subject having an individual cortical gross anatomy, which modulates the MEG signal, or whether individual cortical dynamics is also at play. To our knowledge, this is the first time that tools to address this question are being presented. The effects of anatomical and dynamical variation on the MEG signal is simulated in a model describing the core-belt-parabelt structure of the auditory cortex, and with the dynamics based on the leaky-integrator neuron model. The experimental and simulated ERFs are characterized in terms of the N1m amplitude, latency, and width. Also, we examine the waveform grand-averaged across subjects, and the standard deviation of this grand average. The results show that the intersubject variability of the ERF arises out of both the anatomy and the dynamics of auditory cortex being specific to each subject. Moreover, our results suggest that the latency variation of the N1m is largely related to subject-specific dynamics. The findings are discussed in terms of how learning, plasticity, and sound detection are reflected in the auditory ERFs. The notion of the grand-averaged ERF is critically evaluated.
用脑磁图（MEG）测量的听觉事件相关场（ERF）有助于研究人类皮质中听觉认知的神经元基础。它们具有高度的个体特异性形态，尽管在大多数受试者中可以识别出某些特征性偏转（例如，P1m、N1m和P2m）。在这里，我们通过结合MEG测量和听觉皮质的计算模型来探索这种个体特异性的原因。我们测试ERF个体特异性是否主要可以通过每个受试者具有调节MEG信号的个体皮质大体解剖结构来解释，或者个体皮质动力学是否也起作用。据我们所知，这是首次提出解决这个问题的工具。在一个描述听觉皮质核心-带-旁带结构的模型中，基于泄漏积分神经元模型模拟了解剖和动力学变化对MEG信号的影响。实验和模拟的ERF根据N1m振幅、潜伏期和宽度进行表征。此外，我们检查了跨受试者的波形总体平均值以及该总体平均值的标准差。结果表明，ERF的个体间变异性源于听觉皮质的解剖结构和动力学对每个受试者都是特定的。此外，我们的结果表明，N1m的潜伏期变化在很大程度上与个体特异性动力学有关。从学习、可塑性和声音检测如何在听觉ERF中得到反映的角度对这些发现进行了讨论。对总体平均ERF的概念进行了批判性评估。
