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Computational Neuroscience

The Computational Neuroscience specialization is a facet of the broader Neuroscience Graduate Program at UC San Diego. The goal of the specialization is to train the next generation of neuroscientists with the analytical and computational skills that are essential to understand the organization and function of neural systems. The specialization is open to all students and may be of particular interest to students with backgrounds in physics, computer science, engineering, and mathematics.

The specialization allows Neuroscience students to concentrate on a program of rigorous course work on fundamental aspects of computational neuroscience. Students are encouraged to pursue thesis projects that include both an experimental and a computational component, possibly arranged as a collaboration between two research groups. Upon achievement of degree requirements, students will receive a diploma indicating both their successful completion of the broader Neuroscience Program as well as their specialization in Computational Neuroscience.

The program is focused on these major themes relevant for computational neuroscience research:

  • Cellular and Synaptic Dynamics - Anatomy, physiology, and electrical and chemical dynamics of individual neurons. Neuromorphic models.
  • Biophysical Basis of Neuronal Computation - Collective properties and dynamics of neuronal systems, with emphasis on feedforward networks, associative networks, and networks of coupled oscillators.
  • Algorithms for the Analysis of Neural Data - Characterization of spiking and continuous processes (ECoG, LFP, MEG, fMRI). Statistical aspects of genomics and neuroanatomy.
The program includes optional courses in advanced topics, including advanced experimental techniques, e.g.:
  • Advanced Optical Tools in Quantitative Biology.
  • Workshop in Electron Microscopy.
  • Magnetic Resonance Imaging.

The program is currently led by David Kleinfeld (Physics and Neurobiology) and the primary teaching faculty also include Henry Abarbanel (Physics and Scripps Institution of Oceanography), Gert Cauwenberghs (Bioengineering), Eran Mukamel (Cognitive Science), Terrence Sejnowski (Salk Institute for Biological Studies and Neurobiology), Tatyana Sharpee (Salk Institute for Biological Studies and Physics) and Gabriel Silva (Ophthalmology and Bioengineering).


All students admitted to the Neurosciences Graduate Program are eligible to pursue the CNS. Additionally, Ph.D. candidates in Physics and Bioengineering are also eligible to apply to the CNS. Upon completion of the CNS required coursework, a Neuroscience, Physics or Bioengineering student can apply for the specialization by completing the form below. After a preliminary review, our team will request a copy of their C.V., undergraduate transcripts, graduate transcripts, and a short description of their research interests. This application will be approved by the Computation Neuroscience Committee Chair, Dr. David Kleinfeld at

Upon achievement of degree requirements, students will receive a diploma indicating both their successful completion of their Ph.D. program as well as their specialization in Computational Neuroscience.

Thesis Research

All CNS students are expected to complete a Ph.D. dissertation connected with an issue in contemporary computational neuroscience. Either the student's primary advisor or close co-advisor (approved by the Computational Neuroscience Committee) must be a member of the Neuroscience Graduate Program faculty