The Computational Neuroscience specialization is interdisciplinary and cross-departmental.
In principle, any faculty member at UCSD can serve as a thesis advisor or co-advisor,
subject to approval that the thesis project is sufficiently relevant to neuroscience.
The faculty listed below, and other potential advisors, are members of the
UCSD Neurosciences program; the
Salk Institute; the Departments of
Neurobiology (Division of Biological Sciences),
Neurosciences (School of Medicine),
Electrical and Computer Engineering,
Computer Science and Engineering,
the Institute for Neural Computation;
the The Scripps Research Institute;
and the Swartz Center for Computational Neuroscience.
The following faculty have advised Computational Neuroscience students.
Nonlinear dynamics, stability, and chaos in neural systems
Visual cortex, primate, neurophysiology, psychophysics, motion, form, color
Organization and function of neural circuits, visual cortex, genetic & viral methods
VLSI, neuromorphic systems engineering, implantable neural interfaces
Dissecting neural circuits regulating behavior in C.elegans and Zebrafish
Spatial attention, associative learning, cholinergic, amygdala
MRI functional and structural imaging
Virginia de Sa
Machine learning, perceptual illusions, classification
Cellular neurobiology, imaging, new instrument design
Plasticity, neurogenesis, genetics, genomics
Neuroethology of vocal communication and audition
Neural circuits and molecular mechanisms underlying action learning and selection
Active sensation, cortical bloodflow, neural patterns, whisking
Cortical microcircuits and behavior
Cognitive brain dynamics, Independent Component Analysis, EEG, ERP, fMRI
Central nervous system (CNS) morphology, protein localization, imaging of neurons and their processes, and neuroinformatics.
Neocortical mechanisms underlying natural behavior.
Computational modeling and analysis of large-scale data sets to understand complex biological networks of the brain
LGN, information theory, temporal coding, adaptation, natural scenes
Visual attention, cortex, psychophysics, neurophysiology, neural modeling
Neuronal modeling, temporal processing, population dynamics, imaging, ICA
Attention and perceptual decision making
Computational principles of natural sensory processing
Cellular neural engineering
Analysis of Complex Behavior Pheromones, Pheromone Identification, Molecular Biology of Pheromone Neurons
Representation of olfactory information in the nervous system of Drosophila
Attention, learning, decision-making, Bayesian modeling