Bionic larva
RoundHD
Taxis

Welcome to Sensory Systems and Behavior Lab

Overview

The research of my group aims to understand how odor tracking (chemotaxis) comes about in terms of neural-circuit computations. We tackle this problem in the fruit fly Drosophila melanogaster larva, which possesses fewer than 10,000 neurons organized in a central brain. Using a combination of computational and experimental methods that include high-resolution behavioral analysis, electrophysiology and optogenetics, we follow an integrative approach to model the algorithms that direct navigation in odor gradients and to unravel the neural implementation of these algorithms. We are seeking to map and to functionally characterize the neural circuits participating in the conversion of olfactory information into navigational decisions. Our long-term goal is to conduct a comparative analysis of the neural-circuit computations underlying differences in chemotactic behaviors in the Drosophila group. We believe that understanding how perceptual decision-making is organized in a small insect brain will provide conceptual building blocks to study similar processes in higher-order organisms.

Our Approach

Studying the brain is at the crossroad between different disciplines. To rise to this challenge, our lab embraces interdisciplinary approaches. Molecular neurogenetics permits us to label and manipulate the activity of single neurons in the fly nervous system. Bioengineering inspires new assays that mimic natural environments or create virtual sensory realities. We borrow tools and concepts from Physics to model the emergence of perception and decision making from the activity of circuits of neurons. To reach a mechanistic understanding of brain functions, our strategy is twofold. First, we let animals guide us toward essential problems that their brains have evolved to solve. For this reason, we view behavior as the cornerstone of systems neuroscience. Second, progress in neuroscience requires treating the brain as a complex dynamical system. We use computational modeling to integrate data pertaining to different scales —from macroscopic motor responses all the way down to the spiking activity of a single cell— in a mathematical framework where mechanistic hypotheses can be rigorously formulated and tested. Our lab members bring their individual expertise together to study the brain of a larva in all its complexity through an interplay between experimentation and theory. The beauty of this integrative approach is that answers to seemingly intricate questions often reveal principles common to a large class of systems.

Join the Louis Lab

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