Why do humans have unique auditory event‐related fields? Evidence from computational modeling and MEG experiments

• Published in: Psychophysiology Vol. 58; no. 4; pp. e13769 - n/a
• Main Authors: Hajizadeh, Aida, Matysiak, Artur, Brechmann, André, König, Reinhard, May, Patrick J. C.
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.04.2021
• Subjects: Anatomy; auditory cortex; Auditory Cortex - anatomy & histology; Auditory Cortex - physiology; Biological Variation, Population - physiology; Cognition; computational modeling; Computational neuroscience; Computer Simulation; Cortex (auditory); dynamics; ERF; event‐related field; Evoked Potentials, Auditory - physiology; Hearing; Humans; Latency; Magnetoencephalography; MEG; N1m; Neural Networks, Computer; Physical characteristics; dynamics; auditory cortex; event-related field; anatomy; latency; ERF; N1m; computational modeling; magnetoencephalography; MEG
• ISSN: 0048-5772; 1469-8986; 1469-8986; 1540-5958
• DOI: 10.1111/psyp.13769

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. This study addresses the fundamental but overlooked question of why auditory event‐related fields (ERFs) are highly specific to each subject. Using magnetoencephalography measurements and computational modeling of auditory cortex, we conclude that ERF subject‐specificity arises from both the cortical gross anatomy and the neural dynamics being specific to each subject.