Hemanth Mohan, PhD

Areas of Interest

Research Interests

Overview:

Your ability to scroll through this page relies on the precise perception of sensory information arriving through your eyes and fingers, the integration of these inputs to make appropriate decisions, and the generation of motor commands to execute the resulting actions. This seamless transformation of sensory inputs into motor outputs, along with their reciprocal modulation, is a fundamental basis of all behavior. Computations governing these mechanisms are orchestrated by intricate neuronal circuits that span the brain and spinal cord. At the Mohan Lab, we leverage state-of-the-art techniques in molecular and systems neuroscience, neuroanatomy, genetics, behavior analysis, machine learning, and AI to uncover the neural circuit mechanisms and principles driving this sensorimotor transformation process.

The Problem:

Sensorimotor transformation is a fundamental mechanism underlying the execution of most goal directed behaviors. Sensory inputs from peripheral organs, such as the skin, are relayed through neurons that synapse at various levels of the nervous system, including the spinal cord, brainstem, midbrain, thalamus, and ultimately, the cortex. Within cortical circuits, these sensory signals integrate with higher-order cognitive information to generate motor commands depending on the goal and environmental conditions. Neurons in the cortex perform these computations by communicating with other regions, both within the cortex and across the brain, through axonal projections. These communication pathways process specialized information depending on the regions they connect to and the required computations. This diversity in projection patterns can be used to classify distinct cortical cell types, which serve as fundamental building blocks of cortical circuits.

Despite advances in understanding these circuits, several critical questions remain unanswered. What unique information is processed by these cell types? How do they contribute to the encoding of specific behavioral features? What is the neural code, network dynamics, and computational mechanisms that underlie their interactions? Addressing these is key to unraveling the principles governing sensorimotor control.

The Approach:

We aim to understand these principles by measuring, manipulating and modeling neural activity and circuit connectivity of projection-defined cortical neurons during naturalistic behaviors in awake, head-fixed mice. Mice are trained to perform naturalistic behavioral tasks requiring online sensorimotor control, such as hand-to-mouth feeding, oromanual manipulation, and reach-to-grasp tasks under head-fixed condition. We integrate state-of-the-art genetic, molecular and viral strategies with advanced techniques such as widefield and two-photon imaging, high-density electrophysiology and high-speed video recording to measure single-cell, population-level and inter-areal network dynamic of specific cell types in behaving mice. High resolution neuroanatomical tracing approaches are used to reveal circuit connectivity, while chemogenetic and optogenetic tools allow precise manipulation of neural activity. Machine learning and AI techniques are used to analyze the high dimensional neural and behavior data, and computational modeling approaches are used to test hypotheses and interpret results.