Circuit-Based Understanding of Fine Spatial Scale Clustering of Orientation Tuning in Mouse Visual Cortex

In sensory cortex of brain it is often the case that neurons are spatially organized by their functional properties. A hallmark of primary visual cortex (V1) in higher mammals is a columnar functional map, where neurons tuned to different stimuli features are regularly organized in space. However, rodent visual cortex is at odds with this rule and lacks any spatially ordered functional architecture, and rather neuron feature preference is haphazardly organized in patterns termed 'salt-and-pepper'. This sharp contrast in feature organization between the visual cortices of rodents and higher mammals has been a persistent mystery, fueled in part by abundant evidence of conserved cortical physiology between species. In this work, we applied a novel GCaMP indicator that are localized in the nucleus of neurons during two-photon imaging in mouse V1, which enabled us to overcome most spurious spatially correlated activity due to fluorescence contamination, and to ensure a faithful observation of functional organization over space. We found that the orientation tuning properties of distant neuron pairs ( $$ ) are irregularly and randomly organized, while neuron pairs that are extremely close $$ have strongly correlated orientation tuning, indicating a narrow yet strong spatially clustered organization of orientation preference, which we term 'micro-clustered' organization. Exploring a circuit-based model of recurrently coupled mouse V1 we derived two key predictions for the 'micro-cluster': spatially localized recurrent connections over a comparable narrow spatial scale, and common relative spatial spreads of balanced excitation and inhibition in the network over broad spatial scales. These predictions are validated by both anatomical and optogenetic-based physiological circuit mapping experiments. Altogether, our work takes an important step in building a circuit-based theory of visual processing in mouse V1 over spatial scales that are often ignored, yet contain powerful synaptic interactions.