Pre-stimulus network responses affect information coding in neural variability quenching

Abstract

Neural responding variability to the same stimulus typically decreases after a stimulus presented. During neural variability quenching, the pre-stimulus neural activities interact with the post-stimulus neural responses. However, whether these interactions have influences on information coding remains unclear. In this paper, we construct a two-layer k-winner-take-all (k-WTA) spiking network which simulates primary visual cortical neural responses through probabilistic inference. Generating the phenomenon of neural variability quenching, the network could reflect interactions between pre- and post-stimulus neural responses consistent with experimental observations. During neural variability quenching, pre-stimulus neural responding variability and complexity are considered as factors for the post-stimulus neural responses. Simulations to given stimuli are classified with each varying factor, respectively. Neural responding dimensionality measures the capacity of information coding to given stimuli. Over classified simulations, both of two factors could modify interactions between pre- and post-stimulus neural responses, leading to different neural responding dimensionalities. During neural variability quenching, the temporal structure of stimuli performs as another factor which also could modify neural interactions and induce the varying neural responding dimension. Our model provides the possible interpretation to how the pre-stimulus neural responses participate in neural variability quenching and affect the information coding.