This work presents a fractional-order Wilson-Cowan model derivation under Caputo’s formalism, considering an order of 0 < α ≤ 1. To that end, we propose memory-dependent response functions and average neuronal excitation functions that permit us to naturally arrive to a fractional-order model that incorporates past dynamics into the description of synaptically coupled neuronal populations' activity. We then focus on a particular example to analyze the fractional-order dynamics of the disinhibited cortex. This system mimics cortical activity during neurological disorders such as epileptic seizures, which allows brain dynamics to transition to a hyperexcited activity state. In the first-order mathematical model, we recover traditional results showing a transition from a low-level activity state to a plausibly pathological high-level activity state as an external factor modifies cortical inhibition. On the other hand, under the fractional-order formulation, we establish novel results showing that the system resists such transition as the order is decreased, permitting the possibility of staying in the low-activity state even with increased disinhibition. Furthermore, considering the memory index interpretation of the fractional-order model motivation here developed, our results establish that by increasing the memory index, the system becomes more resistant to transitioning towards the high-level activity state. That is, a possible effect of the memory index is to stabilize neuronal activity. To summarize our results, we present a two-parameter structural portrait describing the system’s dynamics dependent on a proposed disinhibition parameter and the order. We also explore numerical model simulations to validate our results.