Neural Mechanisms Underlying Human Auditory Evoked Responses Revealed By Human Neocortical Neurosolver

Abstract

Auditory evoked fields (AEFs) are commonly studied, yet their underlying neural mechanisms remain poorly understood. Here, we used the biophysical modelling software Human Neocortical Neurosolver (HNN) whose foundation is a canonical neocortical circuit model to interpret the cell and network mechanisms contributing to macroscale AEFs elicited by a simple tone, measured with magnetoencephalography. We found that AEFs can be reproduced by activating the neocortical circuit through a layer specific sequence of feedforward and feedback excitatory synaptic drives, similar to prior simulation of somatosensory evoked responses, supporting the notion that basic structures and activation patterns are preserved across sensory regions. We also applied the modeling framework to develop and test predictions on neural mechanisms underlying AEF differences in the left and right hemispheres, as well as in hemispheres contralateral and ipsilateral to the presentation of the auditory stimulus. We found that increasing the strength of the excitatory synaptic cortical feedback inputs to supragranular layers simulates the commonly observed right hemisphere dominance, while decreasing the input latencies and simultaneously increasing the number of cells contributing to the signal accounted for the contralateral dominance. These results provide a direct link between human data and prior animal studies and lay the foundation for future translational research examining the mechanisms underlying alteration in this fundamental biomarker of auditory processing in healthy cognition and neuropathology.

Keywords: AEF; Auditory processing; Biophysical model; HNN; MEG.

Fig. 1

HNN Model schematics. a Pyramidal neurons in layer II/III and V, and inhibitory fast-spiking basket cells (empty circles). Excitatory and inhibitory synaptic coupling is indicated by black lines with filled circles and bars respectively. Within-layer excitatory–excitatory and inhibitory–inhibitory connections are not shown, but exist for each cell type (see Table S2). b Visualization of the spatial alignment of a network of layer II/III and V pyramidal neurons. c, d The network is activated by proximal/feedforward (c) and distal/feedback (d) inputs which deliver trains of action potentials via canonical pathways

Fig. 2

Source-localized grand average AEFs: a, b AEF waveforms in the left (a) and right (b), as well as the contralateral (blue) and ipsilateral (red) hemisphere. Inserts show average source locations. c For ease of comparison, (c) shows left (dotted line, corresponding to blue line in (a) and right (solid line, corresponding to blue line in (b) contralateral AEFs overlaid. Shaded areas indicate SE. *Significant differences in N100m amplitude at p < 0.05. d, e Magnetic field patterns (at 100 ms) of one example subject in the left (d) and right (e), as well as contralateral (blue) and ipsilateral (red) hemispheres

Fig. 3

Means of empirical and simulated AEFs for each quantified N100m characteristic and each condition. p values are displayed for each ANOVA. Effects demonstrated in both empirical and simulated AEFs are printed in bold. Statistics associated with simulated AEFs are printed in gray as the limited variability in simulations does not allow for direct comparison with tests performed on empirical data. Error bars indicate standard error. *p < 0.05; ***p < 0.001. a N100m amplitude, b N100m latency, c P50-N100m slope, d N100m-N200m slope (Color figure online)

Fig. 4

HNN simulation of the AEF recorded in response to contralateral tone presentation over the right hemisphere (right panels) and over the left hemisphere (left panels): a, d Input sequence: Input spikes are sampled from a Gaussian distribution (mean and sd are defined by input time and sd, see Table 1) on each trial. The resulting temporal profile of the spiking activity arriving into the network is displayed in red (proximal) and green (distal) histograms. A proximal input drives the network, before a distal input and a second proximal input arrive (see Fig. 1c, d for proximal/distal inputs). Corresponding input parameter values are displayed in Table 1. b, e Dipole Simulation: mean AEF model (dark blue) as well as 10 individual trial simulations (gray). The empirical AEF (here: contralateral AEF) is displayed in light blue (cf. Fig. 2). Insert at the bottom right shows the dipoles of layer II/III and layer V separately. Left inset in b shows model fit of manually fitted model (with no automatic optimization applied). All dipoles were smoothed using the default settings in HNN (30 ms Hamming window; see Table S2). An unsmoothed equivalent to panel e is displayed in Fig. S2. c, f Simulated spiking activity: spiking associated with the dipole displayed in (b) (one example trial selected) (Color figure online)

Fig. 5

Alternative simulations for left hemisphere AEFs: left hemisphere AEFs (contralateral) are displayed in light blue, while model simulations are displayed in dark blue dotted lines. Individual simulations are displayed in gray. Inserts show the dipoles associated with layer II/III and layer V separately. The fit provided by the alternative simulations was noticeably worse than that of the initial model, which only adjusted input parameters (cf. Fig. 4b). a Synaptic gains were decreased in all connections targeting inhibitory interneurons. b Layer V pyramidal calcium channel densities were decreased. All other parameters were equal to the model of the right hemisphere AEF (see Fig. 4d–f; Table 1) (Color figure online)

Fig. 6

HNN simulation of the contralateral dominance effect for the right hemisphere (right panel) and the left hemisphere (left panel) AEF. Average simulations (based on 10 individual trial simulations) of contralateral AEFs (dark blue, cf. Fig. 4) and ipsilateral (dark red) AEFs. Ipsilateral responses were generated by decreasing the model scaling factor, representing the number of cells contributing to the signal, and increasing the input latencies, as compared to the contralateral simulations. Empirical AEFs are shown in light colors (cf. Fig. 2) to indicate model fit (Color figure online)