Computational Neuroscience
Math that learns how we learn. We develop computational frameworks to explain multi-scale and non-stationary dynamics of the neural signaling underlying adaptive behavior. We use methods such as deep learning, reinforement learning, and linear dynamical systems.
Experimental Neuroengineering
Is it mind control? Yep, it is. We engineering methods for neuromodulation of neural signals across different modalities, model systems, and neural circuits. Our lab leverags both endogenous neuromodulation, achieved through neurofeedback, and exogenous neuromodulation, achieved through direct interventions.
Neurotechnology
Flexing new tech 24/7. We use nano- and microfabrication methods to design neural interfaces of the future, which an emphasis on material innovation. We focus on material compliancy, interfacial engineering, and optimization for chronic in vivo applications.
Welcome.
The Santacruz Lab pioneers integrative neurotechnologies that interface with and modulate living neural systems, from organoids to brain circuits, to reveal fundamental principles of neural function and enable novel therapeutic strategies for psychiatric and movement disorders.
Understanding, predicting, and ultimately controlling how the brain adapts, learns, and malfunctions remains one of the most complex challenges in science and engineering. Our research program integrates experimental neuroengineering, computational neuroscience, and technology development to create a closed-loop cycle between tool building, data analysis, and theory. We engineer neurotechnologies across multiple modalities to measure and modulate neural activity with precision spanning single cells to large-scale circuits, enabling causal tests of how brain dynamics support motivation, learning, and decision-making.
In parallel, we develop advanced computational models that explain neural dynamics, predict how engineered tools influence circuit function, and define desired capabilities for next-generation devices. By bridging biological and artificial systems, my work uncovers general principles of neural adaptation and dysfunction while laying the technological and conceptual groundwork for future therapies. This research is driven by the belief that innovation in how we sense, model, and interact with the brain can reveal new mechanisms of brain function and accelerate translational impact to psychiatric and movement disorders.
