Research Focus
I am a final year PhD student at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany. Under the co-supervision of Dr. Jennifer Li and Dr. Drew Robson, my research delves into unraveling the neural mechanisms underlying internal states.
Specifically, I investigate the neural substrates responsible for maintaining and triggering substates of zebrafish quiescence. This work combines advanced imaging techniques, behavioral analysis, and computational modeling to understand how the brain orchestrates state transitions and maintains internal stability.
Research Interests
Neural Mechanisms
Understanding how the brain maintains and transitions between different internal states, with a focus on the computational principles underlying state dynamics.
Zebrafish Quiescence
Investigating the neural substrates of quiescence substates using whole-brain imaging and behavioral paradigms to map state-specific neural activity.
Biological Cybernetics
Exploring the intersection of biology and computational systems, applying control theory and systems biology approaches to understand neural circuits.
Current Work
My current research focuses on understanding the complex neural dynamics that govern behavioral states in zebrafish. Through advanced imaging techniques including two-photon calcium imaging and optogenetics, combined with computational modeling and machine learning approaches, I aim to uncover the fundamental principles that regulate internal state transitions.
This work has implications for understanding how the brain maintains homeostasis, how states are encoded in neural circuits, and how disruptions in state regulation might contribute to various neurological conditions.
Methodology
My research employs a multidisciplinary approach combining:
- Advanced live brain Imaging: Single and two-photon calcium imaging, tracking sysytem, light-sheet microscopy, and functional imaging
- Behavioral Analysis: Automated tracking, state classification, and behavioral phenotyping
- Computational Methods: Machine learning, deep learning, network analysis, and dynamical systems modeling
- Optogenetics: Targeted manipulation of neural circuits to understand causality