Potential landscapes and the visual cortex: A study of brain wave entrainment using Neural Mass Models

Electroencephalography (EEG) signals emanate from ionic currents in macroscopic brain regions directly below the scalp. A spectral analysis of the signal shows that they are composed of many oscillations, often called brain waves. Of these the alpha frequency in the 8-12 Hz band is one of the best studied. Intriguingly the alpha frequency is capable of entrainment to a periodic visual signal of a similar frequency. The work presented here began with the observation that in human volunteers the entrained oscillations not only displayed higher harmonics, but also subharmonic oscillations. However, these could only be detected when the visual stimulus was at a 10 Hz frequency and was delivered at higher intensity. Intriguingly, subharmonics were not observed when the stimulating frequency was 6Hz. We analyze a physiologically inspired Neural Mass Model (NMM) and show that it was able to reproduce this observation. The bifurcation structure of the model implied a quasi-potential landscape that helped explain entrainment and subharmonics in the NMM, in agreement with observations. Our work [1] suggests that NMMs may be capturing features of underlying effective landscapes that help shape brainwaves and may affect sensory information processing.

[1] Phogat R, Parmananda P, Prasad A. Intensity dependence of sub-harmonics in cortical response to photic stimulation. J Neural Eng. 2022 Jul 29;19(4).