Project 4: Neuronal Interactions

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Project Summary: Project 4, Anatomical and Physiological Assays of Neuronal Interactions Working memory, the ability to temporarily hold multiple pieces of information in mind for manipulation, is central to virtually all cognitive abilities. This multi-component research project aims to comprehensively dissect the neural circuit mechanisms of this ability across multiple brain areas. The overall goal is to construct a neural circuit model of working memory and decision­making across multiple brain regions, constrained by neural activity, inactivation results, and connectivity. The model is already constrained by preliminary data showing choice­-specific activity sequences in posterior cortical neurons in an evidence­-accumulation task. This modeling will generate predictions, which will be tested by several techniques. The first approach will compare neural coding properties with anatomical connectivity by combining calcium imaging with serial-­section electron microscopy. This aim will benefit from the Seung laboratory’s dramatic recent progress in automation by artificial intelligence, which will make it feasible to find connectomes of millimeter­scale cortical volumes. The second approach will compare neural coding with physiological connectivity by combining calcium imaging with optogenetic perturbation at cellular resolution. This aim will leverage the Tank laboratory’s recent work on all­optical assays of connectivity. The third approach will be to study the role of interactions between cortical areas by performing calcium imaging in one area during optogenetic inactivation of another area. Much of this project focuses on retrosplenial cortex, which is of special interest because choice­specific activity sequences are more linear in this part of cortex than in other cortical areas. Furthermore, temporally specific inactivation of retrosplenial cortex causes behavior that mimics the response to deletion of incoming evidence. The first two approaches will test the example prediction that the local circuitry underlying activity sequences will exhibit sequential connectivity, that is, that connections from earlier to later neurons will be stronger or more frequent than those from later to earlier neurons. The third approach will test a second example prediction, that inactivation of the anterior M2 region of cortex will lead to reduction in non­specific excitation in posterior cortices and alter sequence timing. Importantly, these example predictions are not intended to be comprehensive. Instead the generality of these techniques will enable researchers to test a wide variety of predictions that emerge from the neural circuit models that will be generated and refined based on data from these experiments and other components of the project.