Clustering and control for adaptation uncovers time-warped spike time patterns in cortical networks in vivo

• Main Authors: James B. Isbister, Vicente Reyes-Puerta, Jyh-Jang Sun, Illia Horenko, Heiko J. Luhmann
• Format: Article
• Language: English
• Published: Nature Publishing Group 2021-07-01
• Series: Scientific Reports
• Online Access: https://doi.org/10.1038/s41598-021-94002-0

Abstract How information in the nervous system is encoded by patterns of action potentials (i.e. spikes) remains an open question. Multi-neuron patterns of single spikes are a prime candidate for spike time encoding but their temporal variability requires further characterisation. Here we show how known sources of spike count variability affect stimulus-evoked spike time patterns between neurons separated over multiple layers and columns of adult rat somatosensory cortex in vivo. On subsets of trials (clusters) and after controlling for stimulus-response adaptation, spike time differences between pairs of neurons are “time-warped” (compressed/stretched) by trial-to-trial changes in shared excitability, explaining why fixed spike time patterns and noise correlations are seldom reported. We show that predicted cortical state is correlated between groups of 4 neurons, introducing the possibility of spike time pattern modulation by population-wide trial-to-trial changes in excitability (i.e. cortical state). Under the assumption of state-dependent coding, we propose an improved potential encoding capacity.