| Since the original demonstration that electrical activity generated by ensemblesof cortical neurons can be employed directly to control a robotic manipulator, researchon brain-computer interfaces (BCIs) has experienced an impressive growth. And it hasbecome the focal interdisciplinary research of neuroscience and informationengineering technique.In this study, we synchronously collect local field potentials and spike activityfrom self-made multi-channel microelectrodes implanted in the forelimb region of theprimary motor cortex in rats. In order to study the relationship between neuralactivities and observed behaviors, we have developed a system that uses Muti-channelData Acquisition System (Cerebus system, Cyberkinetics, Inc.) to record neuralsignals and synchronized video of freely moving rat's behaviors with an open fieldsystem, which would be the basic research system for BCIs.The main tasks and results in this study are summarized as: 1. Software has beendeveloped by employing principal component analysis along with fuzzy c-meansclustering to classify spikes recorded by the same electrode. To find variousspace-time patterns in single units in different behaviors, methods including raster,firing rate, interspike interval histograms, cross/auto-correlation analysis have beenemployed. 2. We focused on analyzing the behavior of pressing the lever based onLFP (Local Field Potential) signals' gravity frequency, complexity measure andtime-frequency. 3. Spatio-temporal distribution of LFP's energy is calculated andanalyzed in order to identify different behaviors.Results indicate that: different behaviors appeared apparently distinctcharacteristic brain signals. All of these work imply that the method and system canbeen applied into BCI researches.
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