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Cortical GABAergic interneurons are critical components of neural circuitry, and their dysfunction has been linked to neurodevelopmental diseases. Although the diversity of interneurons is not disputed, both the extent of their heterogeneity and the gene regulatory mechanisms that drive it remain unclear. Recent advances in single cell RNA-sequencing technology have shed new light on this issue, enabling the prediction of novel interneuron subtypes based on gene expression. Cross-species meta-analysis would provide key insight into conserved mechanisms of interneuron diversity.

Playing a game of chess, driving a car, or even reading this sentence all require that the brain retain and integrate information over short periods of time. This retaining and integration of information is accomplished by working memory. The same underlying mechanisms may also allow us to hold and compare our thoughts and enable us to create a coherent awareness about our self and the world. Further, understanding how information is retained during working memory is a critical step in understanding the pathological basis of impaired working memory in advanced age.

The human cerebral cortex is a complex structure comprised of distinct areas with specialized functions and connectivity patterns. Recent advances in single-cell sequencing have started to illuminate additional cell type diversity that exists in both mouse and human brains, with significant transcriptional areal differences between otherwise corresponding excitatory cell types.

The central goal of the BRAIN Initiative is to understand the structure and function of human brain circuits.

This proposed project focuses on quantifying the spatial and temporal diversity in cortical oxygen metabolism and neurovascular coupling, and informing next generation of biophysical models of the Blood Oxygen Level Dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) measurements by integrating new technological and conceptual approaches.

The ability to learn and think about complex situations is central to a range of human cognitive functions, including navigation, reasoning, and decision making. Numerous theories across these domains rely on representations of states of these external and internal environments, but how they acquire such representations remains unknown. My overall goal is to understand how animals, including humans, can reason and learn in such complex environments.

The mammalian brain is believed to be optimally designed for robust and adaptable computation of the sensory inputs from the world, with respect to both its hardware (network structure) and software (network dynamics). The precise connections between the intricate structural connectivity and the rich network dynamics, however, are yet unknown. Moreover, our understanding of how the network structure and dynamics shape (or are shaped by) underlying coding principles in the brain network, is limited.

Optogenetics and chemo-optogenetics are powerful tools for modulating cell activities with light. These tools accelerate neuroscience research by providing the necessary means for interrogating neural circuit function. Clinical trials of optogenetic therapy for retinal diseases are already underway.

Hippocampal microcircuits are comprised of excitatory pyramidal cells, which integrate information and innervate downstream brain regions, and inhibitory interneurons, which function locally to regulate pyramidal cell activity and synchronicity. In the ventral hippocampus (vHipp), microcircuit dysfunction has been associated with a variety of neurological disorders, including neurodegenerative diseases, neurodevelopmental disorders, and psychiatric illnesses.

The goal of this project is to study the cellular basis of active sensation. A crucial function of all nervous systems is to distinguish between sensory stimuli originating from the external world and that generated by our own movements. This task relies on brain circuits that integrate sensory information with an internal model, or expectation, of self-generated movements. The complexity and intractability of many models used to study active sensing means that translating insights from these studies to failures of normal nervous system function remains challenging.