My research program uses the fruit fly Drosophila to investigate neural circuits at the cellular and molecular levels. In this context, we predominantly study circuits involved in visual processing, particularly motion detection, as well as the sensorimotor transformations that underpin visually-guided locomotion. The development of novel molecular techniques is crucial for this work.
How do cells in our nervous system develop highly specialized functions after birth, and how do they degenerate as we age? An emerging molecular mechanism is 3D genome architecture—the folding of 6 billion base pairs of DNA (~2 meters) into a tiny cell nucleus (~10 microns). This folding can strategically position genes and their regulatory elements in 3D to orchestrate dynamic gene expression, and has been implicated in many developmental and degenerative diseases (e.g., autism, schizophrenia, Alzheimer’s).
The goal of our research is to understand the algorithms the brain uses to learn. A fundamental feature of our neural circuits is their plasticity, or ability to change. How does the brain use this plasticity to tune its own performance? What are the learning rules that determine whether a neural circuit changes in response to a given experience, and which specific neurons or synapses are altered? Our research integrates molecular, cellular, systems and computational neuroscience approaches in mice to uncover the logic of how the cerebellum implements learning.
Our specific main goals are to: 1. Discover strategies for halting and reversing vision loss in blinding diseases. 2. Understand how visual perceptions and arousal states are integrated to impact behavioral responses. We use a large range of state-of-the-art tools: virtual reality, gene therapy, anatomy, electrophysiology and imaging and behavioral analyses.
Nirao Shah's lab is interested in understanding the molecular and neural networks that regulate sexually dimorphic social behaviors.
Our laboratory studies the mechanisms by which highly complex behaviors are mediated at the neuronal level, mainly focusing on the example of dynamic social interactions and the neural circuits that drive them. From dyadic interactions to group dynamics and collective decision making, the lab seeks a mechanistic understanding for the fundamental building blocks of societies, such as cooperation, empathy, fairness and reciprocity. The computations underlying social interactions are highly distributed across many brain areas.
