Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.15.341131v1?rss=1 Authors: Yates, J. L., Scholl, B. Abstract: Synaptic inputs onto single cortical neurons in vivo exhibit substantial functional diversity with respect to sensory-driven activity. However, it is unclear what this diversity reflects, appearing counter-productive in generating tuned responses to specific stimuli. We propose that functional diversity naturally arises if neurons extract information encoded from noisy input populations. Focusing on a single sensory variable, orientation, we construct a probabilistic decoder that estimates orientation from the responses of a realistic hypothetical input population of neurons. Analytically derived weights exhibit diversity when input populations consist of noisy, correlated, and heterogeneous neurons. Weight diversity was necessary to accurately decode orientation. Further, in silico weight diversity matched the functional heterogeneity of dendritic spines imaged in vivo. This suggests that synaptic diversity is expected when information is extracted from realistic input populations, highlighting the importance of studying weighting structures in population coding theory and consideration in pursuits of the cortical connectome. Copy rights belong to original authors. Visit the link for more info