Spinal cord recordings in rats during skilled reaching task

Functional connectivity among spikes in low dimensional space during working memory task in rat

Working memory (WM) is critically important in cognitive tasks. The functional connectivity has been a powerful tool for understanding the mechanism underlying the information processing during WM tasks. The aim of this study is to investigate how to effectively characterize the dynamic variations of the functional connectivity in low dimensional space among the principal components (PCs) which were extracted from the instantaneous firing rate series. Spikes were obtained from medial prefrontal cortex (mPFC) of rats with implanted microelectrode array and then transformed into continuous series via instantaneous firing rate method. Granger causality method is proposed to study the functional connectivity. Then three scalar metrics were applied to identify the changes of the reduced dimensionality functional network during working memory tasks: functional connectivity (GC), global efficiency (E) and casual density (CD). As a comparison, GC, E and CD were also calculated to describe the functional connectivity in the original space. The results showed that these network characteristics dynamically changed during the correct WM tasks. The measure values increased to maximum, and then decreased both in the original and in the reduced dimensionality. Besides, the feature values of the reduced dimensionality were significantly higher during the WM tasks than they were in the original space. These findings suggested that functional connectivity among the spikes varied dynamically during the WM tasks and could be described effectively in the low dimensional space.

Characterization of neural activity recorded from the descending tracts of the rat spinal cord

A multi-electrode array (MEA) was implanted in the dorsolateral funiculus of the cervical spinal cord to record descending information during behavior in freely moving rats. Neural signals were characterized in terms of frequency and information content. Frequency analysis revealed components both at the range of local field potentials and multi-unit activity. Coherence between channels decreased steadily with inter-contact distance and frequency suggesting greater spatial selectivity for multi-unit activity compared to local field potentials. Principal component analysis (PCA) extracted multiple channels of neural activity with patterns that correlated to the behavior, indicating multiple dimensionality of the signals. Two different behaviors involving the forelimbs, face cleaning and food reaching, generated neural signals through distinctly different combination of neural channels, which suggested that these two behaviors could readily be differentiated from recordings. This preliminary data demonstrated that descending spinal cord signals recorded with MEAs can be used to extract multiple channels of command control information and potentially be utilized as a means of communication in high level spinal cord injury subjects.