AUTHOR=Samiei Toktam , Zou Zhuowen , Imani Mohsen , Nozari Erfan 

TITLE=Optimal decoding of neural dynamics occurs at mesoscale spatial and temporal resolutions

JOURNAL=Frontiers in Cellular Neuroscience

VOLUME=Volume 18 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/cellular-neuroscience/articles/10.3389/fncel.2024.1287123

DOI=10.3389/fncel.2024.1287123

ISSN=1662-5102

ABSTRACT=Introduction: Understanding the neural code has been one of the central aims of neuroscience research for decades. Spikes are commonly referred to as the units of information transfer, but multi-unit activity (MUA) recordings are routinely analyzed in aggregate forms such as binned spike counts, peri-stimulus time histograms, firing rates, or population codes. Various forms of averaging also occur in the brain, from the spatial averaging of spikes within dendritic trees to their temporal averaging through synaptic dynamics. However, how these forms of averaging are related to each other or to the spatial and temporal units of information representation within the neural code has remained poorly understood.Discussion: Our findings corroborate existing empirical practices of spatiotemporal binning and averaging in MUA data analysis, and provide a rigorous computational framework for optimizing the level of such aggregations. Our findings can also synthesize these empirical practices with existing knowledge of the various sources of biological averaging in the brain into a new theory of neural information processing in which the unit of information varies dynamically based on neuronal signal and noise correlations across space and time.