PhD Program Admissions

Molecular and cellular neuroscientists at Berkeley study neuronal cell biology, cellular physiology, and molecular and genetic basis of neuron, synapse, and glial function. Specific topics include sensory transduction, cellular-level neuronal development, synaptic transmission and plasticity, ion channel physiology, neurodegenerative disease, and neurodevelopmental disorders. Many faculty develop novel molecular genetic tools to more precisely measure cellular physiology or to develop new therapeutical approaches to disease. Methods from molecular biology, computational biology (bioinformatics), and cellular physiology are often used in this research.

Circuit, systems and behavioral neuroscientists at UC Berkeley study how neural circuits, ensembles, and large-scale neural systems process information in order to interpret the sensory world, make and recall memories, and produce specific behaviors. Our faculty study neural systems for sensory processing (vision, audition, touch), innate behaviors, memory, navigation, motivated behaviors, sleep, circadian rhythms, social behaviors, decision making, and more. This research often involves neurophysiology, imaging, and optogenetics experiments, usually in behaving animals. Computational models of neural circuits, and sophisticated data analysis involving modeling and machine learning, are often used in this research.

Cognitive neuroscience at UC Berkeley focuses on human cognition and its brain correlates. Our faculty study the human cognitive abilities and neural mechanisms underlying learning and memory, decision making, perception, reasoning, attention, sleep, motor control, etc. Berkeley human cognition labs employ a broad range of experimental techniques, including functional and structural neuroimaging, electrophysiology, brain stimulation, pharmacology, computational modeling, and quantitative behavioral analyses.

Although quantitative methods are used in all sub areas of neuroscience for analyzing complex data sets, the focus of Computational Neuroscience is to model the brain or brain function: computational models can attempt to model experimental data obtained in neurophysiological experiments (biophysically plausible models) or model functions achieved by the brain such as object recognition, language comprehension, symbolic manipulations, etc. A strong mathematical and programming background is required for research in Computational Neuroscience.