Modelling the effects of transcranial alternating current stimulation on the neural processing of speech in noise
Authors: Mikolaj Kegler1 & Tobias Reichenbach1
1Department of Bioengineering and Centre for Neurotechnology, Imperial College London, South
Kensington Campus, SW7 2BU, London, United Kingdom
The brain processes speech partly through entrainment of cortical oscillations to the amplitude fluctuations in the acoustic signal. Because cortical oscillations can be modulated non-invasively through transcranial alternating current stimulation (tACS), this type of neuromodulation may influence speech processing. Recent studies showed indeed that tACS with a waveform derived from speech envelope could modulate, and even improve, the comprehension of speech in noise. However, the mechanisms through which tACS influences cortical activity underlying speech-in-noise comprehension remain poorly understood.
We employed an existing computational model of a spiking neuronal network that encoded natural speech through cortical oscillations. We then explored how background noise influenced speech encoding in the model. In particular, we used the spiking output obtained from the model simulations to decode speech in different levels of background noise. Subsequently, we investigated how different types of tACS influenced the neural network activity as well as the speech-in-noise decoding accuracy.
We found that the speech-in-noise decoding accuracy in the model was affected by the background noise in a similar way as the speech-in-noise comprehension of human listeners. We further found that tACS could alter the decoding of speech in noise, based on the model’s output, by up to a few percent, comparable to the reported effects of tACS on speech-in-noise comprehension. By employing a range of different stimulation waveforms and parameters, we were able to identify the main factors contributing to the tACS-induced modulation of speech-in-noise processing in the model.
The proposed model suggests how tACS may influence neural mechanisms associated with speech processing and give rise to the modulation of comprehension that has been observed experimentally. The model can be applied to rapidly screen broad ranges of stimulation parameters, as well as to prototype and design novel, complex tACS paradigms.