Dynamical Neuroscience

Dynamical Neuroscience at the University of California offers an innovative interdisciplinary program designed to explore the complex functions and mechanisms of the brain through the lens of dynamical systems. This program integrates knowledge from neuroscience, physics, mathematics, engineering, and computer science to understand how neural circuits generate behavior, cognition, and perception. Students will engage in rigorous coursework that covers neural dynamics, computational modeling, sensory processing, learning and memory, and neural data analysis. The curriculum emphasizes both theoretical foundations and practical applications, preparing graduates to pursue research or careers in academia, industry, or healthcare.

Throughout the program, students will have the opportunity to collaborate with leading experts in the field and access state-of-the-art facilities for neural recording, data analysis, and modeling. They will learn to develop and apply mathematical models to simulate neural activity, analyze real neural data sets, and interpret experimental results within a dynamical systems framework. The program also emphasizes the importance of quantitative skills, including advanced mathematics, programming, and statistical methods, to address the challenges of understanding brain function at multiple scales.

Students are encouraged to participate in research projects that investigate neural circuitry, brain disorders, or neurotechnologies, fostering an environment of innovation and discovery. The program aims to produce graduates equipped with a deep understanding of how neural systems operate dynamically over time and how this knowledge can be applied to develop therapies for neurological disorders or to create brain-inspired artificial intelligence systems. With access to UC’s extensive academic resources and collaborations across departments, students will be well-prepared to contribute to the advancing field of neuroscience, making meaningful impacts on science and society.

Core Courses (16 units):

The required Dynamical Neuroscience core series consists of four 200-level, 4-unit courses, one each in engineering and mathematics, and two in psychological and brain sciences, plus the 1- unit Dynamical Neuroscience graduate seminar. The core courses are:

1. ECE 230A/ME 243A. Linear Systems I
2. MATH 214A. Ordinary Differential Equations
3. PSY 265. Computational Neuroscience
4. PSY 269. Neuroanatomy or MCDB 251. Neurobiology I
5. DYNS 592. Graduate Seminar Dynamical Neuroscience (1 unit per quarter)

Four Elective Courses (16 units):

Four additional courses will be required to be taken during years two and three of the program. These courses will be individually selected from the following list by the student under advice and consent by his/her mentor and approved by the steering committee.

• CMPSC 225/ECE 205A – Information Theory
• CMPSC 234 – Randomized Algorithms
• CMPSC 265 – Advanced Topics in Machine Intelligence
• CMPSC 281B/ECE 281B – Advanced Topics in Computer Vision
• ECE 230B/ME 243B – Linear Systems II
• ECE 235 – Stochastic Processes in Engineering
• ECE 236 – Nonlinear Control Systems
• MATH 214B – Chaotic Dynamics and Bifurcation Theory
• ME 215A – Applied Dynamical Systems I
• ME 215B – Applied Dynamical Systems II
• PHYS 219 – Statistical Mechanics
• PHYS 223C – Concepts and Phenomena of Condensed Matter Physics
• PSTAT 207A-B-C – Statistical Theory
• PSTAT 213A-B-C – Introduction to Probability Theory and Stochastic Processes
• PSY 221E – Statistical Analysis of fMRI Data
• PSY 228 – Perception
• PSY 231 – Cognitive Neuroscience
• PSY 232 – Neuroimaging

Students who enter the program with a Master's, or other, degrees for which they took graduate-level courses that are similar to those required for the Ph.D. in Dynamical Neuroscience may petition to receive subject credit for previously taken courses if the student received a grade of B or higher.

Research Requirements:

Dynamical Neuroscience students will be assigned to a faculty supervisor prior to matriculation, and they will conduct research under faculty supervision throughout the tenures of their graduate program.

Requirements

• Online application: https://www.graddiv.ucsb.edu/eapp
• Statement of Purpose, Personal Achievements/Contributions, and Resume or CV (submitted in the online application)
• Three Letters of Recommendation (submitted online)
• Official transcripts from all post-secondary institutions attended (submitted online)
• Recommended: Unofficial transcripts from all post-secondary institutions attended, uploaded as a single PDF document in the online application.
• GRE General test scores
• TOEFL scores 550 Paper-Based Test (PBT), 80 Internet-Based Test (IBT) or IELTS (International English Language Testing System) Overall Band score of 7 or higher (if applicable)
• Final/Official transcripts will be required for all applicants who are admitted and have indicated their intent to enroll at UC Santa Barbara by submitting a Statement of Intent to Register (SIR). UC Santa Barbara reserves the right to require official transcripts at any time during the admissions process, and rescind any offer of admission made if discrepancies between uploaded and official transcript(s) are found.

Scholarships

All students in the Interdepartmental Graduate Program in Dynamical Neuroscience who are in good academic standing and making satisfactory progress toward the degree can expect financial support while at UCSB. We offer financial packages that are competitive with other major institutions, in the form of a combination of fellowships, graduate student researcher and teaching assistantships. After the first year of study, students typically are supported through their faculty mentor's research grants as Graduate Student Researchers with a stipend plus payment of fees, tuition and health insurance. Continuing graduate students are eligible to apply for campus-based fellowships as well as off-campus fellowships to supplement their teaching or research assistantship income.

The University of California offers a specialized program in Dynamical Neuroscience that provides students with an in-depth understanding of the complex mechanisms underlying neural systems and their dynamic behaviors. This interdisciplinary field combines principles from neuroscience, physics, mathematics, and engineering to explore how neural circuits process, transmit, and store information over time. The program aims to equip students with the theoretical knowledge and practical skills necessary to analyze neural data, develop computational models, and conduct experimental research in brain dynamics.

Graduate students enrolled in this program typically engage in coursework that covers advanced topics such as neural coding, network dynamics, neurophysiology, electrophysiology, and computational modeling. The curriculum emphasizes quantitative methods, including statistical analysis, signal processing, and simulation techniques, enabling students to interpret complex neural signals accurately. Through rigorous training, students learn how to design, implement, and analyze experiments that investigate the temporal aspects of neural activity, contributing to a better understanding of brain function in health and disease.

Research components are integral to the program, with students working closely with faculty on cutting-edge projects in areas such as neural oscillations, sensory processing, motor control, and cognitive functions. The program fosters collaborations across departments, including the Department of Neurobiology, Behavior, and Coding, as well as computer science and engineering, providing a comprehensive environment for interdisciplinary research. Students have access to state-of-the-art laboratories equipped with advanced electrophysiological recording tools, imaging systems, and computational resources.

Graduates of the Dynamical Neuroscience program are well-prepared for careers in academia, industry, and healthcare, including roles in biomedical research, neurotechnology development, data analysis, and neural engineering. They often pursue doctoral studies or postdoctoral research to further specialize in neural dynamics, computational neuroscience, or related fields. The program also emphasizes the importance of scientific communication, encouraging students to publish their findings and present at national and international conferences.

Overall, the University of California's Dynamical Neuroscience program provides a comprehensive, research-intensive education that prepares students to tackle fundamental questions about how brain systems operate dynamically. Its multidisciplinary approach fosters innovation and advances our understanding of neural processes, ultimately contributing to developments in treating neurological disorders and developing brain-machine interfaces.