Neocortical inhibitory interneuron subtypes are differentially attuned to synchrony- and rate-coded information

Abstract

Neurons can carry information with both the synchrony and rate of their spikes. However, it is unknown whether distinct subtypes of neurons are more sensitive to information carried by synchrony versus rate, or vice versa. Here, we address this question using patterned optical stimulation in slices of somatosensory cortex from mouse lines labelling fast-spiking (FS) and regular-spiking (RS) interneurons. We used optical stimulation in layer 2/3 to encode a 1-bit signal using either the synchrony or rate of activity. We then examined the mutual information between this signal and the interneuron responses. We found that for a synchrony encoding, FS interneurons carried more information in the first five milliseconds, while both interneuron subtypes carried more information than excitatory neurons in later responses. For a rate encoding, we found that RS interneurons carried more information after several milliseconds. These data demonstrate that distinct interneuron subtypes in the neocortex have distinct sensitivities to synchrony versus rate codes.

Functional network properties derived from wide-field calcium imaging differ with wakefulness and across cell type

“…This pattern is evident in both seed-based correlation analyses and graph theory metrics, where SOM cells show a higher CPL and transitivity, as well as a lower global efficiency, indicating less cortex wide communication and more segregation, than SLC, PV or VIP cells. A distinguishing phenotype of different cell populations is their spike frequency profile ( Prince et al, 2021 ). Although the characteristic high frequency spiking of interneurons (30-50Hz) cannot be directly captured with our 10Hz sampling rate, it has been suggested that lower frequency bands may still reflect some high frequency contributions ( Ali and Kwan, 2019 ).…”

Functional network properties derived from wide-field calcium imaging differ with wakefulness and across cell type

“…This pattern is evident in both seed-based correlation analyses and graph theory metrics, where SOM cells show a higher CPL and transitivity, as well as a lower global efficiency, than SLC, PV or VIP cells. A distinguishing phenotype of different cell populations is their spike frequency profile [73]. Although the characteristic high frequency spiking of interneurons (30-50Hz) cannot be directly captured with our 10Hz sampling rate, it has been suggested that lower frequency bands may still reflect some high frequency contributions [74].…”

Measures of Information Content during Anesthesia and Emergence in the Caenorhabditis elegans Nervous System

“…Mutual information can also be understood as the amount of information provided by one signal about another, a formulation that is frequently applied to the quantification and modeling of coherence between neural signals, from unit spiking to EEG. [3][4][5][6] The basic mathematical details of entropy, joint entropy, and mutual information are reviewed in the appendix, accompanied by a valuable and extensible graphical analogy.…”

“…1 Shannon established the system-agnostic paradigm for analyzing the transmission of information that now underpins all modern digital communications and machine learning 2 and that has since been applied to investigate biologic information encoding in neuroscience and anesthesia. [3][4][5][6][7][8] Shannon's conceptualization of "entropy" as a measure of the overall information content of a given signal has been particularly useful in the investigation of communication within nervous systems. Entropy measures the information content of an individual signal, but further metrics derive naturally to quantify the information transfer between two signals.…”