Frequency-sensitivity and magnitude-sensitivity in decision-making : predictions of a theoretical model-based study

We theoretically study decision-making behaviour in a model-based analysis related to binary choices with pulsed stimuli. Assuming a strong coupling between external stimulus and its internal representation, we argue that the frequency of external periodic stimuli represents an important degree of freedom in decision-making which may modulate behavioural responses. We consider various different stimulus conditions, including varying overall magnitudes and magnitude ratios as well as varying overall frequencies and frequency ratios, and different duty cycles of the pulsed stimuli. Decision time distributions, mean decision times and choice probabilities are simulated and compared for two different models—a leaky competing accumulator model and a diffusion-type model with multiplicative noise. Our results reveal an interplay between the sensitivity of the model systems to both frequency and magnitude of the stimuli. In particular, we find that periodic stimuli may shape the decision time distributions resulting from both models by resembling the frequencies of the pulsed stimuli. We obtain significant frequency-sensitive effects on mean decision time and choice probability for a range of overall frequencies and frequency ratios. Our simulation analysis makes testable predictions that frequencies comparable with typical sensory processing and decision-making timescales may influence choice and response times in perceptual decisions. A possible experimental implementation is proposed.