Temporally delayed linear modelling (TDLM) measures replay in both animals and humans.

ABSTRACT: There are rich structures in off-task neural activity which are hypothesized to reflect fundamental computations across a broad spectrum of cognitive functions. Here, we develop an analysis toolkit - temporal delayed linear modelling (TDLM) - for analysing such activity. TDLM is a domain-general method for finding neural sequences that respect a pre-specified transition graph. It combines nonlinear classification and linear temporal modelling to test for statistical regularities in sequences of task-related reactivations. TDLM is developed on the non-invasive neuroimaging data and is designed to take care of confounds and maximize sequence detection ability. Notably, as a linear framework, TDLM can be easily extended, without loss of generality, to capture rodent replay in electrophysiolog

SUBMITTER: Liu Y 

PROVIDER: S-EPMC8318595 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature