We combined anodal tDCS stimulation and simulated tDCS stimulation on a biophysical model of decision making. This computational neurostimulation approach allows us to test  how stimulation effects on behavioral data are related to changes in the interactions of neuronal populations.

Our biophysically realistic model of decision making (B) models choices in terms of increases in firing rates in two competing neuronal populations of neurons across time (D). Simulating the effects of anodal stimulation on this model, we postulate a decrease in choice accuracy due to a reduced impact of the expected value difference on decision making (F).

This postulated stimulation effect is confirmed in our behavioural stimulation study (E), when stimulating over medial prefrontal cortex (C).

A computational neurostimulation approach is in particular relevant when trying to predict the effect of stimulation on brains that have changed e.g. with ageing.