Dynamical Neuroscience

Dynamical Neuroscience is an interdisciplinary field that is focused on the study of how the nervous system generates perception, behavior, and cognition. It is a computational approach that goes beyond traditional structure/function correlations.

Its subdisciplines include such areas as molecular and cellular biology, genetics, computer science, artificial intelligence, nonlinear systems, statistical processes, physics, and aspects of psychology.

The UCSB campus has superb standing faculty in all of these academic disciplines. We have 14 core faculty spanning seven departments who conduct research and provide education in dynamical neuroscience. This program incorporates the individual strengths of existing faculty and builds upon the significant intellectual activity in quantitative approaches to biological phenomena at UCSB.

Participating Departments

  • Psychological & Brain Sciences
  • Physics
  • Molecular, Cellular & Developmental Biology
  • Chemical Engineering
  • Computer Science
  • Electrical & Computer Engineering
  • Mechanical Engineering

Research Subfields

Computational Neuroscience

Builds biophysically detailed models of single neurons

Computational Cognitive Neuroscience

Models large-scale neural networks to formally test cognitive neuroscience theories of behavior

Network and Complexity Analyses

Use results from graph theory, complexity theory, and nonlinear dynamics to uncover fundamental principles of the brain organ

Signal Processing and Machine Learning

Use sophisticated algorithms from engineering and computer science to extract signal from noisy neuroscience data

Computational Vision

Understand and duplicate (e.g., in robots) human vision using methods from geometry, physics, statistical theory, and machine learning

Brain-Computer Interface

Engineering techniques to interface directly with the human brain (e.g., neuroprosthetics)