ScienceNeurosciencePeer-reviewed journal article
Local Connectivity and Synaptic Dynamics in Mouse and Human Neocortex
Luke CampagnolaiD, Stephanie C. SeemaniD, Thomas ChartrandiD, Lisa KimiD, Alex HoggarthiD, Clare Ruth GamliniD, Shinya ItoiD, Jessica TrinhiD, Pasha A. DavoudianiD, Cristina RadaelliiD, Mean-Hwan KimiD, Travis A HageiD, Thomas BrauniD, Lauren AlfileriD, Julia AndradeiD, Phillip BohniD, Rachel A. DalleyiD, Alex M. HenryiD, Sara KebedeiD, Alice MukoraiD, David SandmaniD, Grace WilliamsiD, Rachael LarseniD, Corinne TeeteriD, Tanya L. DaigleiD, , Tim JarskyiD
Abstract
To elucidate cortical microcircuit structure and synaptic properties we present a unique, extensive, and public synaptic physiology dataset and analysis platform. Through its application, we reveal principles that relate cell type to synapse properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Despite these associations, synaptic properties are heterogeneous in most subclass to subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, while the strength axis accounts for significant heterogeneity within the subclass. In human cortex, excitatory to excitatory synapse dynamics are distinct from those in mouse and short-term plasticity varies with depth across layers 2 and 3. With a novel connectivity analysis that enables fair comparisons between circuit elements, we find that intralaminar connection probability among cell subclasses exhibits a strong layer dependence.These and other findings combined with the analysis platform create new opportunities for the neuroscience community to advance our understanding of cortical microcircuits.
- organism: mouse
- organism: human
- assay: electronic health records
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 362
- FWCI
- 32.22
- Field percentile
- top 1%
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