Oscillatory activity in the brain has been known for a long time, but its functional significance is still being debated. It has recently been proposed that neural oscillations play an important role in controlling how information flows in the brain and which ensembles of neurons are able to exchange information, allowing the brain to flexibly adjust to varying task demands. While this view has been supported by recordings of brain activity from particular subsystems, a rigorous test of the ideas requires manipulation of brain activity to establish a causal link between synchronized brain activity and neural communication. While experimental techniques for generally suppressing or enhancing neural activity are readily available, addressing this scientific question requires new technology for manipulating neural activity with a precise timing relationship relative to ongoing neural activity. The goal of this research project is to develop a closed-loop stimulation system that can analyze ongoing brain oscillations in real time and that uses the resulting information to trigger neural stimulation. This allows manipulating neural activity time-locked to ongoing activity at another location in the brain. Sharing this tool with the scientific community is expected to provide novel, fundamental insights into the functional significance of synchronized brain activity in a variety of neural systems, which cannot be obtained with currently available technology. The technique might also find application in neural prostheses and brain stimulation systems for the treatment of neurologic and psychiatric disorders.
The project involves: 1) Developing an algorithm that reliably extracts instantaneous frequency and phase of a dominant oscillatory component from a local field potential and accurately predicts the next occurrence of particular phase angles. 2) Implementing the algorithm(s) in a combination of software and hardware that is fast enough for real-time control of a stimulation device. 3) Validating the closed-loop stimulation technique in vivo and developing applications for studying cortico-cortical and thalamo-cortical communication. Successful development of such a system would remove a major obstacle for testing theories about the functional significance of the timing of neural signals, in particular synchronized rhythmic activity. It would allow going beyond correlational measures and exploring the behavioral (and neural) consequences of artificial manipulation of neural signals contingent on the timing of currently ongoing neural activity. With the help of this technology, a major advance in understanding the role of the timing of neural signals in coding and transmitting information between ensembles of neurons is expected.
