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 includes 64 faculty from different campus departments, with expertise ranging from molecular and cellular neuroscience to systems and computational neuroscience to human cognitive neuroscience.
We provide a highly interdisciplinary, intellectually dynamic training environment of coursework, research training, professional development, and mentoring, within a strong research program that produces fundamental advances in knowledge and novel 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 has completed a basic degree 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 the 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. Unofficial transcripts must contain specific information including the name of the applicant, name of the school, all courses, grades, units, & degree conferral (if applicable).
- 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, by the recommender, not the Graduate Admissions.
Evidence of English language proficiency: All applicants who have completed a basic degree from a country or political entity in which the official language is not English are required to submit official evidence of English language proficiency. This applies to institutions 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.
Applicants who have previously applied to Berkeley must also submit new test scores that meet the current minimum requirement 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 for Graduate Organizations. Official IELTS score reports must be sent electronically from the testing center to University of California, Berkeley, Graduate Division, Sproul Hall, Rm 318 MC 5900, Berkeley, CA 94720. TOEFL and IELTS score reports are only valid for two years prior to beginning the graduate program at UC Berkeley. Note: score reports can not expire before the month of June.
Where to Apply
Visit the Berkeley Graduate Division application page.
Admission to the Program
Applicants to the program should have a bachelor's degree from a four-year college and at least one year of laboratory experience. The Graduate Record Examination (GRE) General Test is optional. For more information on our program requirements go to: https://neuroscience.berkeley.edu/phd-applications/.
Doctoral Degree Requirements
Normative Time Requirements
Normative Time to Advancement
Step I: Lab Rotations and Presentations, First Year Classes
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. Rotations also allow students to identify the laboratory in which their thesis research will be performed. Rotation research is graded and receives academic credit. This is accomplished by enrolling in NEUROSC 291A/B, a year-long course, during the rotation year. Also during the first-year students take NEUROSC 290A/B Methods & Career Skills Classes which introduce a broad range of modern neuroscience research methods in didactic lectures and provide advising in initial career skills. NEUROSC 290A (Fall) includes a survey of cutting-edge research methods, advising on how to choose a thesis mentor, training in scientific rigor and reproducibility, and an introduction to the use and misuse of statistics in neuroscience research. NEUROSC 290B (Spring) includes in-depth training on how to give a top-notch scientific talk, advising on how to write effective research papers, and on scientific project management. Finally, student also enroll in MCELLBI 293C during the spring of their first year to ensure that research trainees receive ample training in Responsible Conduct in Research, and to gain an understanding of federal, state, and UC Berkeley policies and resources available to further support their research endeavors.
Step II: Qualifying Exam
Students complete an oral qualifying exam during the spring semester of Year 2. The examination has three parts: Thesis Proposal, Related Research Areas, and Foundational Questions in Neuroscience. The thesis proposal is in the form of a written, NIH-style grant proposal, which is turned in to the committee, and then defended orally. Related Research Areas are identified cooperatively by the student and his/her committee prior to the exam, and are chosen to be complementary to the main thesis research subject. These areas are examined orally. The Foundational Questions in Neuroscience are designed to test broad knowledge in Neuroscience. These are a published list of questions, the same for all students, that are available upon entry to the program. These questions are designed to test basic common knowledge of neuroscience facts and principles, and a subset of them are examined orally during the qualifying exam. During the exam, students must demonstrate the ability to recognize fundamentally important research problems, propose relevant experimental approaches, and display comprehensive knowledge of appropriate disciplinary areas and related 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. During this time, students must meet at least annual with their thesis committee to discuss dissertation progress, review experimental results, set goals, and ensure students are adhering to appropriate timelines to completion. The students then write a dissertation based on the results of their research.
STEP IV: Dissertation Presentation/Formal Exit Seminar
There is no formal defense of the completed dissertation. However, Neuroscience students are required to publicly present a thesis seminar about their dissertation research in their final year. On completion of the research and approval of the dissertation by the committee, the students are awarded the doctorate.
Total Normative Time
Normative time to advancement is 2 years. Total normative time is 5.7 years.
Pedagogy, Rotations, Ethics, & Seminar Courses
Student must take all of the following courses. Pedagogy, Rotations, and Ethics courses are taken in year 1. Brain Lunch Seminar is taken in Years 1, 2, and 4.
|NEUROSC 290A||Neuroscience Research Design and Analysis||1|
|NEUROSC 290B||Neuroscience Career Skills||1|
|NEUROSC 291A||Neuroscience Introduction to Research||4-12|
|NEUROSC 291B||Neuroscience Introduction to Research||4-12|
|Ethics in Research|
|MCELLBI 293C||Responsible Conduct in Research||1|
|Brain Lunch Seminar|
|NEUROSC 294||Neuroscience Graduate Student Presentation Seminar (Brain Lunch)||1|
|All students are required to enroll in the Brain Lunch seminar for 1 semester in each of Years 1 and 2, and again in Year 4 (see "Presentations" under "Required Professional Development" below)|
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 areas, plus a selected advanced undergraduate course from a third area. They are taken in years 1–2. Courses offered will vary depending on the semester. The courses below are samples of courses that fulfill the area requirements.
1. Cellular, Molecular and Developmental Neuroscience
|MCELLBI 160||Cellular and Molecular Neurobiology||4|
|MCELLBI 166||Biophysical Neurobiology||3|
|MCELLBI 230||Advanced Cell and Developmental Biology||4|
|MCELLBI 231||Advanced Developmental and Stem Cell Biology||4|
|MCELLBI 240||Advanced Genetic Analysis||4|
|NEUROSC/MCELLBI C261||Cellular and Developmental Neurobiology||3|
2. Systems and Computational Neuroscience
|INTEGBI 139||The Neurobiology of Stress||4|
|MCELLBI 236||Advanced Mammalian Physiology||5|
|NEUROSC/MCELLBI C262||Circuit and Systems Neurobiology||3|
|PSYCH 210B||Proseminar: Cognition, Brain, and Behavior||3|
|VIS SCI 260C||Introduction to Visual Neuroscience||3|
|VIS SCI 265||Neural Computation||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 240A||Proseminar: Biological, Cognitive, and Language Development||3|
|PB HLTH C217D||Biological and Public Health Aspects of Alzheimer's Disease||3|
|PB HLTH 290||Health Issues Seminars (Neuroepidemiology)||1-4|
|VIS SCI 262||Visual Cognitive Neuroscience||3|
One course on statistical analysis or quantitative methods
Students must complete a 1-semester course in Applied Statistics in Neuroscience, or an equivalent approved course in statistics or quantitative analysis methods. This can be completed at any time prior to the semester of graduation. Students with prior appropriate coursework or whose thesis research uses substantial quantitative methods can use that prior experience to fulfill this requirement, subject to approval by the Head Graduate Adviser.
|NEUROSC 299||Seminars (Applied Statistics for Neuroscience)||1-3|
One Graduate Elective 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.
|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 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 111||Human Neuroanatomy||3|
|PSYCH 115||Introduction to Brain Imaging Analysis Methods||3|
|PSYCH 125||The Developing Brain||3|
|PSYCH 205||Data Analysis||3|
|PSYCH 208||Methods in Computational Modeling for Cognitive Science||3|
|STAT 150||Stochastic Processes||3|
|STAT 151A||Linear Modelling: Theory and Applications||4|
|STAT 153||Introduction to Time Series||4|
|STAT 158||Experimental Design||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|
|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 226A||Random Processes in Systems||4|
|EL ENG C227C||Convex Optimization and Approximation||3|
|EL ENG 229A||Information Theory and Coding||3|
|BIO ENG 231||Introduction to Computational Molecular and Cellular Biology||4|
|BIO ENG C265/EL ENG C225E||Principles of Magnetic Resonance Imaging||4|
|VIS SCI 260A||Optical and Neural Limits to Vision||3|
|VIS SCI 260D||Seeing in Time, Space and Color||3|
|PB HLTH 245||Introduction to Multivariate Statistics||4|
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, also known as "Brain Lunch"), 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
Hillel Adesnik, Associate Professor. Neural basis of sensation, perception, and action.
Helen Bateup, Associate Professor. Molecular basis of synapse and circuit changes associated with epilepsy and autism.
Diana Bautista, Professor. Molecular mechanisms underlying the sensations of itch, touch, and pain.
Eric Betzig, Professor. Development of new tools for imaging and image analysis to enable biological discovery.
Sonia Bishop, Associate Professor. Neural basis of attention, emotion, and anxiety. Individual differences in cognitive control and emotional responsivity.
Kristofer Bouchard, Adjunct Assistant Professor. Functional organization and dynamic coordination of sensorimotor networks underlying learned, skilled behaviors.
Steve Brohawn, Assistant Professor. Molecular basis of sensory transduction and electrical signaling, especially mechanosensation.
Silvia Bunge, Professor. Neural mechanisms, development, and plasticity of higher cognitive functions in humans.
Jose M. Carmena, Adjunct Professor. Neural basis of motor skill learning. Application to neural prostheses and development of neural dust technology.
Christopher J. Chang, Professor. Chemical tools for imaging and optogenetics in neurobiology.
Anne Collins, Associate Professor. Computational modeling of human learning, decision-making, and executive functions.
Emily Cooper, Assistant Professor. Computational modeling of visual perception.
Mark T. D'Esposito, Professor. Neural basis of high-level cognitive processes such as working memory and executive control.
Yang Dan, Professor. Neural circuits controlling sleep; mechanisms of executive control. .
Michael Deweese, Associate Professor. Neural mechanisms underlying auditory processing and selective attention in the cerebral cortex and artificial neural networks.
Andrew Dillin, Professor. Genetic and molecular mechanisms regulating aging and aging-related disease.
* Dan Feldman, Professor. Sensory processing and plasticity in the somatosensory cortex.
* Marla B. Feller, Professor. Functional development and organization of neural circuits in the retina.
Yvette Fisher, Assistant Professor. Flexibility of neural circuits for spatial navigation.
John Gerard Flannery, Professor. Gene therapies for inherited retinal degenerations.
David Foster, Associate Professor. Encoding of spatial memory and navigation toward rewards by neural ensembles in the hippocampus.
Jack L. Gallant, Professor. Identifying cortical maps to discover how the brain represents information about the world and its own mental states.
Andrea Gomez, Assistant Professor. Instructive cues for neural form and function.
Ming Hsu, Associate Professor. Neural basis of economic and consumer decision-making.
Ehud Y. Isacoff, Professor. Mechanisms of ion channel function, synapse development, plasticity, and neural circuit function.
Richard Ivry, Professor. Cognition and action, with an emphasis on how people select actions, learn skills, and produce coordinated .
William J. Jagust, Professor. Anatomic, biochemical, and neurochemical bases of brain aging and dementia.
Na Ji, Associate Professor. Novel imaging methods to understand the brain.
Daniela Kaufer, Acting Associate Dean and Professor. Molecular mechanisms of brain plasticity in response to stress and neurological insults.
Robert Thomas Knight, Professor. Novel chemical reagents for non-invasive optical sensing and manipulation of ion channels and synapses.
Richard H. Kramer, Professor. Novel chemical reagents for non-invasive optical sensing and manipulation of ion channels and synapses.
+ Lance Kriegsfeld, Professor . Brain and endocrine regulation of circadian rhythms.
Stephan Lammel, Associate Professor. Midbrain dopamine circuits in reward-based behaviors and pathological changes in addiction, depression and schizophrenia.
Markita Landry, Assistant Professor. Exploiting nanomaterials to probe and characterize complex biological systems at the nano-scale; nanosensors for brain chemistry.
Lexin Li, Professor. Statistical neuroimaging analysis, brain connectivity analysis, imaging causal inference, multimodal and longitudinal imaging analysis, and imaging tensor regression.
Chunlei Liu, Associate Professor. MRI technology development for the study of neural circuits and modulation.
Ellen Lumpkin, Professor. To elucidate force transduction mechanisms that initiate the senses of touch and pain.
Michel Maharbiz, Adjunct Professor. Building micro- and nano- scale machine interfaces to cells and organisms, including development of neural dust technology.
Evan W. Miller, Associate Professor. Development and application of molecular tools for studying neuroscience.
Bruno Olshausen, Professor. Computational models of sensory coding and visual perception.
Steven Piantadosi, Assistant Professor. Understanding what computational processes support language acquisition, math learning, and general cognition.
Teresa Puthussery, Assistant Professor. Processing of visual signals in the healthy and diseased retina.
Michael Rape, Professor. Molecular Mechanisms of Cell Fate Decisions in Development and Disease.
Austin Roorda, Professor. Vision Science and Optometry, development of adaptive optics to track, measure, and correct the eye's imperfection.
Kaoru Saijo, Assistant Professor. Microglial cell maintenance of homeostasis in the brain and sex dimorphism in diseases.
David Schaffer, Professor. Engineering stem cell and gene therapeutics.
Randy Schekman, Professor. Membrane assembly, vesicular transport, and membrane fusion among organelles of the secretory pathway.
Kristin Scott, Professor. Taste detection, processing, and behaviors.
Karthik Shekhar, Assistant Professor. Single-cell genomics and statistical inference.
Michael Silver, Professor. Neurophysiological and neurochemical substrates of human visual perception, attention, and learning.
Friedrich Sommer, Adjunct Professor. Theoretical principles of learning and perception.
Rowland Taylor, Professor. Structure and function of neural circuits in the retina.
Frederic Theunissen, Professor. Perception of complex sounds.
Doris Tsao, Professor. The Tsao lab seeks to understand how the brain builds a model of the visual world.
Matthew P. Walker, Professor. The impact of sleep on human health and disease.
Joni Wallis, Professor. Neuronal mechanisms underlying high-level cognitive and behavioral processes.
Kevin Weiner, Associate Professor. Models to explain how brain structure and function contribute to measurable behaviors (e.g. face perception).
David Whitney, Professor. Visual perception and attention.
Linda Wilbrecht, Associate Professor. Experience dependent plasticity and the development of circuits involved in value based decision making.
Ke Xu, Associate Professor. Super-resolution fluorescence microscopy to interrogate cellular processes at the nanoscale.
Michael Yartsev, Associate Professor. Neural basis of complex spatial and acoustic behaviors.
Martin S. Banks, Professor Emeritus. Visual space perception and sensory combination.
John Clarke, Professor of the Graduate School of Physics. Superconducting Quantum Interference Devices such as ultralow-frequency MRI.
Howard Fields, Adjunct Emeritus Professor. Mesolimbic circuits involved in goal directed behaviors, opioid regulation of synaptic function.
Ralph D. Freeman, Professor Emeritus. Central Visual Pathways: Systems and Computational Neuroscience.
John Ngai, Professor Emeritus. Understanding the molecular and cellular mechanisms underlying the function, development and regeneration of the vertebrate olfactory system.
Geoff Owen, Professor Emeritus. Comprehensive theory of retinal image processing.
Mu-Ming Poo, Professor Emeritus. Formation and plasticity of synapses, and activity-dependent modification of neural circuits.
Gerald Westheimer, Professor of the Graduate School Division of Neurobiology. Perceptual learning in spatial visual tasks.
Bob Zucker, Professor of the Graduate School Division of Neurobiology. Mechanisms underlying regulation of synaptic transmission.
Neuroscience Graduate Group
444 Li Ka Shing Center