Modelling the effects of transcranial alternating current stimulation on the neural encoding of speech in noise

Transcranial alternating current stimulation (tACS) can non-invasively modulate neuronal activity in the cerebral cortex, particular at frequency of applied stimulation. Such modulation matter for speech processing, since latter involves tracking slow amplitude fluctuations by cortical activity. tACS with a signal that follows envelope stimulus has indeed been found to influence and comprehension background noise. However, how exactly influences speech-related activity, it causes observed effects on comprehension, remains poorly understood. A computational model processing biophysically plausible spiking neural network recently proposed. Here we extended investigate different types waveforms, similar those previously experimental studies, We assessed well could be decoded from when paired exogenous that, absence stimulation, speech-in-noise decoding accuracy was comparable noise human listeners. further alter few percent, comprehension. Our simulations allowed us identify parameters waveforms yielded largest enhancement encoding. thereby provides insight into potential mechanisms which weak may allows screen large range their effect processing.