Explaining event-related fields by a mechanistic model encapsulating the anatomical structure of auditory cortex

Abstract

Event-related fields of the magnetoencephalogram are triggered by sensory stimuli and appear as a series of waves extending hundreds of milliseconds after stimulus onset. They reflect the processing of the stimulus in cortex and have a highly subject-specific morphology. However, we still have an incomplete picture of how event-related fields are generated, what the various waves signify, and why they are so subject-specific. Here, we focus on this problem through the lens of a computational model which describes auditory cortex in terms of interconnected cortical columns as part of hierarchically placed fields of the core, belt, and parabelt areas. We develop an analytical approach arriving at solutions to the system dynamics in terms of normal modes: damped harmonic oscillators emerging out of the coupled excitation and inhibition in the system. Each normal mode is a global feature which depends on the anatomical structure of the entire auditory cortex. Further, normal modes are fundamental dynamical building blocks, in that the activity of each cortical column represents a combination of all normal modes. This approach allows us to replicate a typical auditory event-related response as a weighted sum of the single-column activities. Our work offers an alternative to the view that the event-related field arises out of spatially discrete, local generators. Rather, there is only a single generator process distributed over the entire network of the auditory cortex. We present predictions for testing to what degree subject-specificity is due to cross-subject variations in dynamical parameters rather than in the cortical surface morphology.

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

“…Thus, simulations are required to investigate how the anatomical connectivity pattern and other model parameters shape the ERF. To gain deeper insight into the confluence of stimulation, system parameters, and cortical dynamics generating the event‐related response, we recently developed a linear approximation of the model (for a full treatment, see Hajizadeh et al., 2019). This approach provides explicit solutions to the system dynamics and enables the characterization of AC activity in terms of normal modes.…”

“…This contained all lateral and long‐range (i.e., nondiagonal) connections, both excitatory and inhibitory. In practice, W AC was constructed by using Gaussians with stochastic terms to determine the connection strength as a function of the distance between the connecting columns on the tonotopic map (for details, see Hajizadeh et al., 2019).…”

“…As in Hajizadeh et al. (2019), we construct these multipliers by first defining three matrices K 1 , K 2 , and K 3 comprising multipliers according to connection type. K 1 modulates the contribution made by the excitatory connections in W AC , and therefore, has the same structure as W ee , which encapsulates how the 13 cortical fields are connected with each other (Figure 2a).…”

“…In our previous work, we addressed the impact of anatomical and dynamical contributions to the auditory ERF by using simulations of auditory cortex (Figure 10a,b in Hajizadeh et al., 2019). We found that when the modulating effect of the anatomy was varied while keeping the dynamics of the model fixed, the peak amplitude of the N1m became distributed across a wide range, whereas the peak latency of the N1m was little affected.…”

“…The aim of this work is to investigate why ERFs vary from subject to subject by testing the predictions of our computational model (Hajizadeh et al., 2019) in MEG measurements in human subjects. The current, largely unwritten understanding attributes the subject‐specificity of ERFs mainly to well‐established cross‐subject differences in the gross anatomy of cortex.…”