Topic: principal component

Inhibitory interneurons in cortex consist of many subtypes that differ in, e.g., connectivity and physiology. Recently, it was shown that —in layers 1-3 of mouse primary visual cortex— interneuron subtypes differ systematically in their modulation with an animal’s behavioural state, and that this state modulation can be predicted from the first principal component (PC) of the gene expression matrix (Bugeon et al. 2022). Here, we ask if this link between transcriptome and state-dependent processing is a general principle that extends across layers, areas, and species. To this end, we analysed

Single neurons show complex responses during cognitive tasks and dimensionality reduction has been a successful approach for finding structure in heterogeneous neural activity. When applied to neural response patterns in a population state space, where each axis represents activity of one neuron, dimensionality reduction methods often reveal low-dimensional manifolds encoding behaviorally relevant variables. Alternatively, when the same responses are viewed in a selectivity space, where each axis represents a response feature (e.g., task condition or time), dimensionality reduction methods can