Adaptive modeling and inference of higher-order coordination in neuronal assemblies: a dynamic greedy estimation approach.

ABSTRACT: Central in the study of population codes, coordinated ensemble spiking activity is widely observable in neural recordings with hypothesized roles in robust stimulus representation, interareal communication, and learning and memory formation. Model-free measures of synchrony characterize coherent pairwise activity but not higher-order interactions, a limitation transcended by statistical models of ensemble spiking activity. However, existing model-based analyses often impose assumptions about the relevance of higher-order interactions and require repeated trials to characterize dynamics in the correlational structure of ensemble activity. To address these shortcomings, we propose an adaptive greedy filtering algorithm based on a discretized mark point-process model of ensemble spiking and a

SUBMITTER: Mukherjee S 

PROVIDER: S-EPMC10614874 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature