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. 2024 Apr 24;44(17):e1119232024.
doi: 10.1523/JNEUROSCI.1119-23.2024.

Neuronal Modeling of Cross-Sensory Visual Evoked Magnetoencephalography Responses in the Auditory Cortex

Affiliations

Neuronal Modeling of Cross-Sensory Visual Evoked Magnetoencephalography Responses in the Auditory Cortex

Kaisu Lankinen et al. J Neurosci. .

Abstract

Previous studies have demonstrated that auditory cortex activity can be influenced by cross-sensory visual inputs. Intracortical laminar recordings in nonhuman primates have suggested a feedforward (FF) type profile for auditory evoked but feedback (FB) type for visual evoked activity in the auditory cortex. To test whether cross-sensory visual evoked activity in the auditory cortex is associated with FB inputs also in humans, we analyzed magnetoencephalography (MEG) responses from eight human subjects (six females) evoked by simple auditory or visual stimuli. In the estimated MEG source waveforms for auditory cortex regions of interest, auditory evoked response showed peaks at 37 and 90 ms and visual evoked response at 125 ms. The inputs to the auditory cortex were modeled through FF- and FB-type connections targeting different cortical layers using the Human Neocortical Neurosolver (HNN), which links cellular- and circuit-level mechanisms to MEG signals. HNN modeling suggested that the experimentally observed auditory response could be explained by an FF input followed by an FB input, whereas the cross-sensory visual response could be adequately explained by just an FB input. Thus, the combined MEG and HNN results support the hypothesis that cross-sensory visual input in the auditory cortex is of FB type. The results also illustrate how the dynamic patterns of the estimated MEG source activity can provide information about the characteristics of the input into a cortical area in terms of the hierarchical organization among areas.

Keywords: MEG; computational modeling; cross-sensory; feedforward/feedback.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1.
Figure 1.
Source estimation and computational modeling of MEG data. A, An example of MEG data. Auditory evoked MEG sensor data (left) in one subject at 50 ms after auditory stimulus onset (isocontour line step 5.0 fT) are shown with the corresponding noise-normalized MNE (dSPM) source estimate over an inflated cortical surface (middle) and the estimated time course for the left hemisphere auditory cortex (right, vertical line at 50 ms). B, The HNN model. The MEG response is modeled using a network of neurons in a local cortical area (left). Local network structure (right) consists of pyramidal cells (blue) and interneurons (orange). Excitatory and inhibitory coupling is indicated by a circle and a bar, respectively. The network is activated by proximal (red) and distal (green) drives by input spike trains. Modified from Neymotin et al. (2020).
Figure 2.
Figure 2.
MEG source activity in the auditory cortex. The estimated source waveforms in response to the auditory (blue) and visual (orange) stimuli: mean and standard deviation (colored shading) across subjects, hemispheres, and experiments. Positive and negative values correspond to upward and downward cortical currents, flowing in the direction toward the pial matter and the white matter, respectively. The gray shading indicates time points that differed significantly from zero (t-test, p < 0.05, Bonferroni adjusted).
Figure 3.
Figure 3.
MEG source waveforms in the left and right hemisphere auditory cortex in response to auditory and visual stimulation, shown separately for the noise/checkerboard and letter experiments. The source waveforms were averaged over subjects. The locations of the functional ROIs morphed to common anatomical space (“fsaverage” from FreeSurfer) are shown in the middle; the color bar indicates how many subjects’ individual ROIs overlapped at each cortical location. The black lines illustrate the Heschl's gyrus (anterior), Heschl's sulcus (middle), and part of planum temporale (posterior).
Figure 4.
Figure 4.
Individual variability of the estimated MEG source waveforms. A, Noise/checkerboard experiment. B, Letter experiment. Continuous lines and shading, mean ± standard deviation across subjects; black dots, response magnitudes for individual subjects, calculated as the average over ±10 ms time windows around the peak latencies in the grand average data. LH, left hemisphere; RH, right hemisphere.
Figure 5.
Figure 5.
Evaluation of potential artifactual spatial spread in the estimated MEG source activity from visual cortex to the auditory ROIs. A, Source time courses (MNE, averaged across subjects and experiments) in response to visual stimuli for occipital areas V1, V2, MT (green), and the auditory cortices (V AC, orange). B, Spatial maps of the MNE source estimate for the visual evoked activity at the time of the largest peak in the response to visual stimuli in the auditory cortex.
Figure 6.
Figure 6.
HNN simulations of the auditory cortex activity in response to auditory (left) and visual (right) stimuli. A, Simulated source waveforms (gray) overlaid with the experimentally observed grand average MEG source waveforms (blue, auditory; orange, visual). Simulated waveforms with the optimized (thick gray, average; thin gray, 10 individual simulation runs) model parameters are shown. B, Histograms of the timing of the inputs sampled from a Gaussian distribution with a model-specific mean and standard deviation (red, FF; green, FB). C, Layer-specific contributions to the simulated source waveforms after optimization (green, layer 2/3; purple, layer 5; gray, 10 respective individual simulation runs). Positive values correspond to upward (toward pial surface) and negative values to downward (toward white matter) flowing intracellular currents within the model pyramidal cells. D, Spiking activity of the pyramidal and basket cells in layers 2/3 and layer 5 (10 simulation runs).
Figure 7.
Figure 7.
Alternative models for auditory (A) and visual (B) responses. The main models (auditory, FF + FB, and visual, FB) are framed. The experimentally observed MEG source waveforms (blue, auditory stimulus; orange, visual stimulus) are overlayed with the simulated waveforms (thin gray, 10 individual simulation runs; thick gray, average of the individual runs). Histograms below the waveforms show the temporal distribution of FF (red) and FB (green) inputs to the HNN model of the auditory cortex neural circuit. In rightmost column, FF only simulations are additionally scaled (auditory ×100, visual ×15) to illustrate their waveforms compared with the MEG signal: However, the optimal non-negative scaling factor in these cases was actually 0 (dashed line).
Figure 8.
Figure 8.
Evaluation of the model fit for auditory (left panels, blue) and visual (right panels, orange) models. A, Resampled MEG source waveforms; the black line shows the average of the resamples. B, Resampled simulations for the FF + FB and FB models (in color), together with the MEG average (black). C, Histograms of the MEG null distributions, calculated as the RMSE between the resampled simulations and the MEG average source waveforms, superimposed with histograms of the RMSE for the HNN models. The histograms are visualized as kernel density plots (continuous probability density curve). The vertical dashed lines indicate the 5th and 95th percentiles of the MEG null distributions.

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