Response of neuronal populations to phase-locked stimulation: model-based predictions and validation

Abstract

BackgroundModulation of neuronal oscillations holds promise for the treatment of neurological disorders. Nonetheless, stimulating neuronal populations in a continuous open-loop manner can lead to side effects and suboptimal efficiency. Closed-loop strategies such as phase-locked stimulation aim to address these shortcomings by offering a more targeted modulation. While theories have been developed to understand the neural response to stimulation, their predictions have not been thoroughly tested using experimental data. ObjectiveWe aimed to test the predictions of a mathematical model regarding the response of neuronal populations to phase-locked stimulation. MethodsUsing a coupled oscillator model, we expanded on two key predictions describing the response to stimulation as a function of the phase and amplitude of ongoing neural activity. To investigate these predictions, we analyzed electrocorticogram (ECoG) recordings from a previously conducted study in Parkinsonian rats, and extracted the corresponding phase and response curves. ResultsWe demonstrated that the amplitude response to stimulation is strongly correlated to the derivative of the phase response ({rho} > 0.8) in all animals except one, thereby validating a key model prediction. The second prediction postulated that the stimulation becomes ineffective when the network synchrony is high, a trend that appeared missing in the data. Our analysis explained this discrepancy by showing that the neural populations in Parkinsonian rats did not reach the level of synchrony for which the theory would predict ineffective stimulation. ConclusionsOur results highlight the potential of fine-tuning stimulation paradigms informed by mathematical models that consider both the ongoing phase and amplitude of the targeted neural oscillation.