Single-neuron models linking electrophysiology, morphology, and transcriptomics across cortical cell types.

ABSTRACT: Which cell types constitute brain circuits is a fundamental question, but establishing the correspondence across cellular data modalities is challenging. Bio-realistic models allow probing cause-and-effect and linking seemingly disparate modalities. Here, we introduce a computational optimization workflow to generate 9,200 single-neuron models with active conductances. These models are based on 230 in vitro electrophysiological experiments followed by morphological reconstruction from the mouse visual cortex. We show that, in contrast to current belief, the generated models are robust representations of individual experiments and cortical cell types as defined via cellular electrophysiology or transcriptomics. Next, we show that differences in specific conductances predicted from the model

SUBMITTER: Nandi A 

PROVIDER: S-EPMC9793758 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature