SOMMER, FRIEDRICH T Building analysis tools and a theory framework for inferring principles of neural computation from multi-scale organization in brain recordings EB026955
Title: Identifying correlates of behavior in multi-electrode LFP recordings
Oscillations in the local field potential (LFP) have historically been viewed as coarse-grained indicators of behavioral state. A challenge in understanding the LFP is that it is composed of responses of many thousands of cells and that it is dominated by spontaneous activity, not directly coupled to observable behavioral events or stimuli. Using multi-electrode LFP recordings from the hippocampus, we developed a method to extract precise behavioral information that is embedded within spatio-temporal oscillatory patterns. We have recently extended this approach to extract information from signals that are only weakly and intermittently oscillatory. Not only does our approach offer a robust alternative to spike-based brain-machine interfaces, it suggests how large-scale population codes are embedded within brain dynamics that could subserve inter-regional computation and communication.
Our LFP decoding tool would be most useful for groups interested in identifying the behavioral information embedded within a particular brain region of interest. The data would consist of simultaneous LFP recordings from at least a few dozen sites (the more sites the better), in addition to recordings of relevant behavioral variables (e.g. stimulus properties and behavior). The analysis pipeline offers both supervised and unsupervised modes for identifying dependencies between distributed LFP patterns and behavior. While we have applied this to data sampled in the hippocampus at 25 Hz over ~30 minutes, in principle our approach can be applied to recordings at any sampling rate, as long as there is at least some identifiable oscillatory activity within the signal.
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