About the Program
The Neuroscience Graduate Program at UC Berkeley is a unique, diverse PhD training program that offers intensive, integrated training in multiple areas of neuroscience research.
The program involves more than 55 faculty from different campus departments, with expertise ranging from molecular and cellular neuroscience to developmental neuroscience, systems and computational neuroscience, and human cognitive neuroscience.
We provide a highly interdisciplinary, intellectually dynamic training environment of coursework, research training, and mentoring, within a strong research program that produces fundamental advances in knowledge and cutting-edge techniques.
Admission to the University
Minimum Requirements for Admission
The following minimum requirements apply to all graduate programs and will be verified by the Graduate Division:
- A bachelor’s degree or recognized equivalent from an accredited institution;
- A grade point average of B or better (3.0);
- If the applicant comes from a country or political entity (e.g., Quebec) where English is not the official language, adequate proficiency in English to do graduate work, as evidenced by a TOEFL score of at least 90 on the iBT test, 570 on the paper-and-pencil test, or an IELTS Band score of at least 7 on a 9-point scale (note that individual programs may set higher levels for any of these); and
- Sufficient undergraduate training to do graduate work in the given field.
Applicants Who Already Hold a Graduate Degree
The Graduate Council views academic degrees not as vocational training certificates, but as evidence of broad training in research methods, independent study, and articulation of learning. Therefore, applicants who already have academic graduate degrees should be able to pursue new subject matter at an advanced level without need to enroll in a related or similar graduate program.
Programs may consider students for an additional academic master’s or professional master’s degree only if the additional degree is in a distinctly different field.
Applicants admitted to a doctoral program that requires a master’s degree to be earned at Berkeley as a prerequisite (even though the applicant already has a master’s degree from another institution in the same or a closely allied field of study) will be permitted to undertake the second master’s degree, despite the overlap in field.
The Graduate Division will admit students for a second doctoral degree only if they meet the following guidelines:
- Applicants with doctoral degrees may be admitted for an additional doctoral degree only if that degree program is in a general area of knowledge distinctly different from the field in which they earned their original degree. For example, a physics PhD could be admitted to a doctoral degree program in music or history; however, a student with a doctoral degree in mathematics would not be permitted to add a PhD in statistics.
- Applicants who hold the PhD degree may be admitted to a professional doctorate or professional master’s degree program if there is no duplication of training involved.
Applicants may apply only to one single degree program or one concurrent degree program per admission cycle.
Required Documents for Applications
- Transcripts: Applicants may upload unofficial transcripts with your application for the departmental initial review. If the applicant is admitted, then official transcripts of all college-level work will be required. Official transcripts must be in sealed envelopes as issued by the school(s) attended. If you have attended Berkeley, upload your unofficial transcript with your application for the departmental initial review. If you are admitted, an official transcript with evidence of degree conferral will not be required.
- Letters of recommendation: Applicants may request online letters of recommendation through the online application system. Hard copies of recommendation letters must be sent directly to the program, not the Graduate Division.
- Evidence of English language proficiency: All applicants from countries or political entities in which the official language is not English are required to submit official evidence of English language proficiency. This applies to applicants from Bangladesh, Burma, Nepal, India, Pakistan, Latin America, the Middle East, the People’s Republic of China, Taiwan, Japan, Korea, Southeast Asia, most European countries, and Quebec (Canada). However, applicants who, at the time of application, have already completed at least one year of full-time academic course work with grades of B or better at a US university may submit an official transcript from the US university to fulfill this requirement. The following courses will not fulfill this requirement:
- courses in English as a Second Language,
- courses conducted in a language other than English,
- courses that will be completed after the application is submitted, and
- courses of a non-academic nature.
If applicants have previously been denied admission to Berkeley on the basis of their English language proficiency, they must submit new test scores that meet the current minimum from one of the standardized tests. Official TOEFL score reports must be sent directly from Educational Test Services (ETS). The institution code for Berkeley is 4833. Official IELTS score reports must be mailed directly to our office from British Council. TOEFL and IELTS score reports are only valid for two years.
Where to Apply
Visit the Berkeley Graduate Division application page.
Admission to the Program
Applicants to the program should have a bachelor's degree in science from a four-year college and at least one year of laboratory experience. Applicants are required to submit Graduate Record Examination (GRE) General Test scores, and are strongly encouraged to submit one GRE Subject Test score (in biochemistry and cell biology, chemistry, psychology, biology, computer science, or physics).
Doctoral Degree Requirements
Normative Time Requirements
Normative Time to Advancement
Step I: Lab Rotations and Presentations
During the first year of graduate study, each neuroscience graduate student spends three 10-week periods performing research projects in different faculty laboratories. The goal is to expose students to different techniques and approaches in neuroscience and to provide training in experimental design, critical analysis of data, and presentation of research findings. Performance in rotations is evaluated and graded. Rotations also allow students to identify the laboratory in which their thesis research will be performed. During the spring semester, students formally present results from the laboratory rotations in a dedicated course, NEUROSC 290 (Neuroscience First Year Research), designed to train students in clear, effective presentation of scientific findings.
Step II: Qualifying Exam
Students complete an oral qualifying exam during the spring semester of Year 2. This exam is structured around two written proposals—one in the student’s proposed area of thesis research, and the other in an area of neuroscience outside the thesis topic. During the exam, a faculty committee tests the student’s knowledge of these areas and general neuroscience. Students must demonstrate the ability to recognize important research problems, propose relevant experimental approaches, and display comprehensive knowledge of relevant subjects. Students must pass the qualifying examination before advancing to doctoral candidacy.
Normative Time in Candidacy
Step III: Dissertation
Students undertake research for the PhD dissertation under a four-person committee in charge of their research and dissertation. Students do original research using a wide variety of cutting-edge neuroscience methods. The students then write the dissertation based on the results of this research. On completion of the research and approval of the dissertation by the committee, the students are awarded the doctorate.
Total Normative Time
Total normative time is 5.5 years.
Time to Advancement
One Graduate Course in Each of the Following Three Foundational Areas
Students can either take one graduate-level course from each category, or three graduate level courses from two area, plus a selected advanced undergraduate course from a third area. They are taken in years 1–2.
1. Cellular, Molecular and Developmental Neuroscience
|MCELLBI 231||Advanced Developmental and Stem Cell Biology||4|
|MCELLBI 236||Advanced Mammalian Physiology||5|
|MCELLBI 240||Advanced Genetic Analysis||4|
|NEUROSC C261||Cellular and Developmental Neurobiology||3|
2. Systems and Computational Neuroscience
|PSYCH 210B||Proseminar: Cognition, Brain, and Behavior||3|
|VIS SCI 265||Neural Computation||3|
|NEUROSC C262||Circuit and Systems Neurobiology||3|
3. Cognition, Brain and Behavior
|PSYCH 117||Human Neuropsychology||3|
|PSYCH C127||Cognitive Neuroscience||3|
|PSYCH 210A||Proseminar: Cognition, Brain, and Behavior||3|
|PSYCH 210D||Proseminar: Cognition, Brain, and Behavior||3|
|PSYCH 214||Functional MRI Methods||3|
|PSYCH 240A||Proseminar: Biological, Cognitive, and Language Development||3|
|PB HLTH C217D||Biological and Public Health Aspects of Alzheimer's Disease||3|
|VIS SCI 262||Visual Cognitive Neuroscience||3|
One Graduate Elective Seminar Course
Students must take one additional elective course. This can be either a graduate-level seminar or graduate-level lecture course, and can be 1 unit or more. This is typically taken in years three-four. You may also select a foundation course as an elective. Consult your thesis adviser and thesis committee to select the most appropriate course for you.
|Neuro-Related Seminar Courses|
|EL ENG 290A||Advanced Topics in Electrical Engineering: Advanced Topics in Computer-Aided Design||1-3|
|EL ENG 290B||Advanced Topics in Electrical Engineering: Advanced Topics in Solid State Devices||1-3|
|EL ENG 290C||Advanced Topics in Electrical Engineering: Advanced Topics in Circuit Design||1-3|
|EL ENG 290D||Advanced Topics in Electrical Engineering: Advanced Topics in Semiconductor Technology||1-3|
|EL ENG 290F||Advanced Topics in Electrical Engineering: Advanced Topics in Photonics||1-3|
|EL ENG 290N||Advanced Topics in Electrical Engineering: Advanced Topics in System Theory||1-3|
|EL ENG 290O||Advanced Topics in Electrical Engineering: Advanced Topics in Control||1-3|
|EL ENG 290P||Advanced Topics in Electrical Engineering: Advanced Topics in Bioelectronics||1-3|
|EL ENG 290Q||Advanced Topics in Electrical Engineering: Advanced Topics in Communication Networks||1-3|
|EL ENG 290S||Advanced Topics in Electrical Engineering: Advanced Topics in Communications and Information Theory||1-3|
|EL ENG 290T||Advanced Topics in Electrical Engineering: Advanced Topics in Signal Processing||1-3|
|EL ENG 290Y||Advanced Topics in Electrical Engineering: Organic Materials in Electronics||3|
|LINGUIS 290A||Topics in Linguistic Theory: Syntax||3|
|LINGUIS 290B||Topics in Linguistic Theory: Semantics||3|
|LINGUIS 290D||Topics in Linguistic Theory: Pragmatics||3|
|LINGUIS 290E||Topics in Linguistic Theory: Phonology||3|
|LINGUIS 290F||Topics in Linguistic Theory: Diachronic Linguistics||3|
|LINGUIS 290H||Topics in Linguistic Theory: Linguistic Reconstruction||3|
|LINGUIS 290L||Additional Seminar on Special Topics to Be Announced||3|
|LINGUIS 290M||Topics in Linguistic Theory: Psycholinguistics||3|
|MCELLBI 290||Graduate Seminar||1|
|PSYCH 290B||Seminars: Biological||2|
|PSYCH 290E||Seminars: Perception||2|
|PSYCH 290H||Seminars: Developmental||2|
|PSYCH 290I||Seminars: Personality||2|
|PSYCH 290J||Seminars: Social||2|
|PSYCH 290K||Seminars: Clinical||2|
|PSYCH 290P||Seminars: Additional Seminars on Special Topics to Be Announced||2|
|PSYCH 290Q||Seminars: Cognition||2|
|VIS SCI 298||Group Studies, Seminars, or Group Research||1-6|
|PSYCH 102||Methods for Research in Psychological Sciences||3|
|PSYCH 205||Data Analysis||3|
|STAT 150||Stochastic Processes||3|
|STAT 151A||Linear Modelling: Theory and Applications||4|
|STAT 153||Introduction to Time Series||4|
|STAT 204||Probability for Applications||4|
|STAT C241A||Statistical Learning Theory||3|
|STAT C241B||Advanced Topics in Learning and Decision Making||3|
|STAT 248||Analysis of Time Series||4|
|MATH 118||Fourier Analysis, Wavelets, and Signal Processing||4|
|MATH 220||Introduction to Probabilistic Methods in Mathematics and the Sciences||4|
|Computer Science and Programming|
|COMPSCI C280||Computer Vision||3|
|EL ENG 120||Signals and Systems||4|
|EL ENG 123||Digital Signal Processing||4|
|EL ENG 126||Probability and Random Processes||4|
|EL ENG 221A||Linear System Theory||4|
|EL ENG 225A||Digital Signal Processing||3|
|EL ENG 225B||Digital Image Processing||3|
|EL ENG 226A||Random Processes in Systems||4|
|EL ENG 229A||Information Theory and Coding||3|
|BIO ENG C218||Stem Cells and Directed Organogenesis||3|
|BIO ENG C219||Protein Engineering||3|
|BIO ENG 231||Introduction to Computational Molecular and Cellular Biology||4|
|BIO ENG 243||Computational Methods in Biology||4|
|BIO ENG 263||Principles of Molecular and Cellular Biophotonics||4|
|BIO ENG C265||Principles of Magnetic Resonance Imaging||4|
|VIS SCI 212E||Color Vision and Visual Sensitivity||2|
|VIS SCI 212F||Spatial and Binocular Vision, Eye Movements, and Motion Perception||2|
|VIS SCI 212G||Molecular Genetics of Vertebrate Eye Development and Diseases||2|
Other Degree Requirements
|NEUROSC 290||Neuroscience First Year Research||2|
|NEUROSC 294||Neuroscience Graduate Student Presentation Seminar||1|
|Students must also complete a 1-semester course in Applied Statistics in Neuroscience, or an equivalent approved course in statistics or quantitative analysis methods.|
Time in Candidacy
Dissertation Presentation/Formal Exit Seminar
There is no formal defense of the completed dissertation. Neuroscience students are required to publicly present a thesis seminar about their dissertation research in their final year.
Required Professional Development
During their fourth year of study, students are required to make a presentation on the progress of their thesis work while enrolling in NEUROSC 294 (Neuroscience Graduate Student Presentation Seminar), a journal club, for a letter grade.
Neuroscience students are required to serve as graduate student instructors (GSIs) for two semesters. Whenever possible, GSI assignments are determined with an eye toward student research interests. Teaching occurs during fall semester of the second year and spring semester of the third. Teaching affords students supervised experience in a variety of educational situations, including labs, discussion sections, and demonstrations. GSIs also participate in record-keeping, grading, advising, and student consultations.
GSIs are evaluated by both supervising faculty and the students they teach. These evaluations become a permanent part of the student file. Deserving GSIs are nominated for the Outstanding Graduate Student Instructor Award.
Faculty and Instructors
+ Indicates this faculty member is the recipient of the Distinguished Teaching Award.
Hillel Adesnik, Assistant Professor.
Martin S. Banks, Professor. Stereopsis, virtual reality, optometry, multisensory interactions, self-motion perception, vision, depth perception, displays, picture perception, visual ergonomics.
Helen Bateup, Assistant Professor. Molecular and cellular neuroscience, neurodevelopmental disorders, autism, epilepsy.
Diana Bautista, Associate Professor. Ion channels, sensory physiology, chemosensation, touch, thermosensation, somatosensory system.
George Bentley, Associate Professor. Hormones and behavior, neuroendocrinology of reproduction.
Sonia Bishop, Assistant Professor.
Steve Brohawn, Assistant Professor.
Jose M. Carmena, Professor. Brain-machine interfaces, neural ensemble computation, neuroprosthetics, sensorimotor learning and control.
Christopher J. Chang, Professor. Chemistry, inorganic chemistry, neuroscience, bioinorganic chemistry, general physiology, organic chemistry, new chemical tools for biological imaging and proteomics, new metal complexes for energy catalysis and green chemistry, chemical biology.
Anne Collins, Assistant Professor. Human learning, decision-making and executive functions; Computational modeling at multiple levels (cognitive and neuroscience); Behavioral, EEG, drug and genes studies in healthy or patient populations.Human learning, decision-making and executive functions; Computational modeling at multiple levels (cognitive and neuroscience); Behavioral, EEG, drug and genes studies in healthy or patient populations.
Mark T. D'Esposito, Professor. Cognitive neuroscience, psychology, working memory, frontal lobe function, functional MRI, neurology, brain imaging, dopamine.
Yang Dan, Professor. Neuronal circuits, mammalian visual system, electrophysiological, psychophysical and computational techniques, visual cortical circuits, visual neurons.
Michael Deweese, Assistant Professor. Machine learning, computation, systems neuroscience, auditory cortex, neural coding.
Andrew Dillin, Professor.
+ Dan Feldman, Associate Professor. Neurobiology, learning, neurophysiology, sensory biology.
Marla B. Feller, Professor. Neurophysiology, developmental neuroscience.
John Gerard Flannery, Professor. Neurobiology, optometry, vision science, cell and molecular biology of the retina in normal and diseased states.
David Foster, Professor.
Darlene Francis, Associate Professor.
Jack L. Gallant, Professor. Vision science, form vision, attention, fMRI, computational neuroscience, natural scene perception, brain encoding, brain decoding.
Gian Garriga, Professor. Developmental neurobiology; molecular genetics, development of nervous systems, cell division, cell migration, axonal pathfinding, caenorhabditis elegans.
Tom Griffiths, Associate Professor. Machine learning, computational models of human cognition, Bayesian statistics, cultural evolution.
Ming Hsu, Assistant Professor. Cognitive neuroscience, experimental economics, behavioral economics, neuroeconomics.
Ehud Y. Isacoff, Professor. Ion channel function, synaptic plasticity, neural excitability, synaptic transmission, the synapse.
Rich Ivry, Professor. Cognitive neuroscience, behavior, cognition, brain, attention, coordination, psychology, motor and perceptual processes in normal and neurologically impaired populations, temporal processing, executive control.
Lucia F. Jacobs, Professor. Cognitive and brain evolution, adaptive patterns in spatial memory, spatial navigation, cognitive sex differences and decision making.
William J. Jagust, Professor. Neuroscience, cognition, brain aging, dementia, imaging, Alzheimerandamp;#039;s disease.
Na Ji, Associate Professor. Biophysics.
Daniela Kaufer, Associate Professor. Neuroscience, stress, neural stem cells, epilepsy, traumatic brain injury, blood brain barrier, prosocial behavior.
Stanley A. Klein, Professor. Optometry, vision science, spatial vision modeling, psychophysical methods and vision test design, corneal topography and contact lens design, source localization of evoked potentials, fMRI, amblyopia.
Robert Thomas Knight, Professor. Cognitive neuroscience, language, physiology, memory, attention, psychology, working memory, neuropsychology, human prefrontal cortex, neural mechanisms of cognitive processing, sensory gating, sustained attention, ad novelty detection.
Richard H. Kramer, Professor. Cells, synaptic transmission, chemical signaling between neurons, ion channels, electrical signals, chemical reagents, synapses.
Lance Kriegsfeld, Associate Professor. NeuroendocrinologyCircadian Biology, Neuroimmunology, cancer biology, animal behavior.
Stephan Lammel, Assistant Professor. Neuroscience, Optogenetics, dopamine, addiction, depression.
Dennis M. Levi, Professor. Optometry, vision science, pattern vision, abnormal visual development.
Chunlei Liu, Professor.
Evan W. Miller, Assistant Professor.
John Ngai, Professor. Nervous system, molecular and cellular mechanisms of olfaction, detection of odors, odorant receptors, olfactory neurons, DNA microarray technologies, genome-wide patterns of gene expression.
Bruno Olshausen, Professor. Visual perception, computational neuroscience, computational vision.
Mu-Ming Poo, Professor. Neurobiology, cellular and molecular mechanisms, axon guidance, synapse formation, activity-dependent refinement of neural circuits.
Teresa Puthussery, Assistant Professor. Retinal Neurobiology and Neurophysiology.
David Schaffer, Professor. Neuroscience, biomolecular engineering, bioengineering, stem cell biology, gene therapy.
Kristin Scott, Professor. Nerve cell connectivity in developing nervous systems, taste perception in the fruit fly, taste neural circuits, sensory maps in the brain.
Arthur P. Shimamura, Professor. Cognitive neuroscience, behavior, cognition, brain, psychology, frontal lobe function, basic memory research.
Michael Silver, Associate Professor. Cognitive neuroscience, pharmacology, learning, attention, visual perception, neuroimaging.
Fritz SOMMER, Adjunct Professor. Bayesian methods, information theory, memory, sensory processing, visual system.
Mark A. Tanouye, Professor. Genetics, neuroanatomy, electrophysiology, mechanisms of nervous system structure and function, drosophila mutants.
W. Rowland Taylor, Professor. Retinal circuit function, neural architecture, immunohisochemical studies.
Frederic Theunissen, Professor. Behavior, cognition, brain, psychology, birdsong, vocal learning, audition, neurophysiology, speech perception, computational neuroscience, theoretical neuroscience.
Jonathan David Wallis, Professor. Prefrontal cortex, neurophysiology, executive control, decision making.
David Whitney, Professor. Cognitive neuroscience, cognition, attention, visual perception, vision, visually guided action.
Linda Wilbrecht, Assistant Professor. Neuroscience, addiction, early life adversity, adolescence.
Michael Yartsev, Assistant Professor. Neuroscience, engineering.
Neuroscience Graduate Group
444 Li Ka Shing Center