Effective connectivity measured using optogenetically evoked hemodynamic signals exhibits topography distinct from resting state functional connectivity in the mouse

Adam Q Bauer, Andrew W Kraft, Grant A Baxter, Patrick W Wright, Matthew D Reisman, Annie R Bice, Jasmine J Park, Michael R Bruchas, Abraham Z Snyder, Jin-Moo Lee, Joseph P Culver. Cerebral Cortex, Volume 28, Issue 1, 2018, Pages 370-386 Read More

Abstract

Brain connectomics has expanded from histological assessment of axonal projection connectivity (APC) to encompass resting state functional connectivity (RS-FC). RS-FC analyses are efficient for whole-brain mapping, but attempts to explain aspects of RS-FC (e.g., interhemispheric RS-FC) based on APC have been only partially successful. Neuroimaging with hemoglobin alone lacks specificity for determining how activity in a population of cells contributes to RS-FC. Wide-field mapping of optogenetically defined connectivity could provide insights into the brain’s structure–function relationship. We combined optogenetics with optical intrinsic signal imaging to create an efficient, optogenetic effective connectivity (Opto-EC) mapping assay. We examined EC patterns of excitatory neurons in awake, Thy1-ChR2 transgenic mice. These Thy1-based EC (Thy1-EC) patterns were evaluated against RS-FC over the cortex. Compared to RS-FC, Thy1-EC exhibited increased spatial specificity, reduced interhemispheric connectivity in regions with strong RS-FC, and appreciable connection strength asymmetry. Comparing the topography of Thy1-EC and RS-FC patterns to maps of APC revealed that Thy1-EC more closely resembled APC than did RS-FC. The more general method of Opto-EC mapping with hemoglobin can be determined for 100 sites in single animals in under an hour, and is amenable to other neuroimaging modalities. Opto-EC mapping represents a powerful strategy for examining evolving connectivity-related circuit plasticity. © The Author 2017.

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Posted on May 25, 2018
Posted in: Axon Injury & Repair, Clocks & Sleep, HPAN, Lysosome, Neurodegeneration, Neurogenetics & Transcriptomics, Publications Authors: ,