We can infer much about how a neural system functions by quantifying its output (behavior) in relation to its input (stimuli). But to completely understand a neural system, one must also have methods to measure its neural activity. Most such methods are invasive. However, invasive methods (1) alter the system that it sets out to measure, (2) often involve anesthesia that alters neural activity, (3) may inflict suffering on animals, and (4) usually can’t be used to study humans. Non-invasive functional neuro-imaging, although lagging behind invasive methods in spatial and temporal resolution, are mostly devoid of these drawbacks, and therefore are extremely valuable in the study of neural systems.
Members of the Biophysics Group are involved in all aspects of development and practice in this exciting field. Groups with expertise in physics and chemistry are developing the technological hardware and software for methods such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET). Others with expertise in computational modeling are developing methods of analysis for the large and complex data sets generated by neuro-imaging methods. Finally, we are applying these methods to study neural systems in sensory and cognitive processing in both animals and humans, and in both health and disease. In addition to imaging neural activity, these projects often entail efforts to develop new bioelectronics needed for measuring and modifying neural activity. One example is transmagnetic stimulation (TMS), being developed in several Berkeley labs. TMS may be used to generate neural activity de novo in humans, both to probe neural coding and as an option for treating neurological disease. This interdisciplinary combination of physical methods and biological goals puts this research squarely within the purview of the Biophysics Group.
Other research areas:
Structural Biophysics and Protein Dynamics
Molecular Microscopy and Optical Probes
Cell Signaling and Cellular Physiology
Computational Biology and Genomics