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Cell Lineage Directs teh Precise Assembly of Excitatory Neocortical Circuits

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Ecker,  AS
Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Cadwell, C., Jiang, X., Sinz, F., Berens, P., Fahey, P., Yatsenko, D., et al. (2016). Cell Lineage Directs teh Precise Assembly of Excitatory Neocortical Circuits. Poster presented at AREADNE 2016: Research in Encoding And Decoding of Neural Ensembles, Santorini, Greece.


Cite as: https://hdl.handle.net/21.11116/0000-0000-7B72-6
Abstract
The neocortex carries out complex mental processes such as perception and cognition through the interactions of billions of neurons connected by trillions of synapses. Recent studies suggest that excitatory cortical neurons with a shared developmental lineage are more likely to be synaptically connected to each other than to nearby, unrelated neurons [1, 2]. However, the precise wiring diagram between clonally related neurons is unknown, and the impact of cell lineage on neural computation remains controversial. Here we show that vertical connections linking neurons across cortical layers are specifically enhanced between clonally related neurons (Fig. 1). In contrast, lateral connections within a cortical layer preferentially occur between unrelated neurons (Fig. 1). Importantly, we observed these connection biases for distantly related cousin cells, suggesting that cell lineage influences a larger fraction of connections than previously thought. A simple quantitative model of cortical connectivity based on our empirically measured connection probabilities reveals that both increased vertical connectivity and decreased lateral connectivity between cousins promote the convergence of shared input onto clonally related neurons, providing a novel circuit-level mechanism by which clonal units form functional cell assemblies with similar tuning properties [3, 4]. Taken together, our data suggest that the integration of feedforward, intra-columnar input with lateral, inter-columnar information may represent a fundamental principle of cortical computation that is established, at least initially, by developmental programs.