ABSTRACT
BACKGROUND: Brain Computer Interface (BCI) studies are performed in an increasing number of applications. Questions are raised about electrodes, data processing and effectors. Experiments are needed to solve these issues. OBJECTIVE: To develop a simple BCI set-up to easier studies for improving the mathematical tools to process the ECoG to control an effector. METHOD: We designed a simple BCI using transcranial electrodes (17 screws, three mechanically linked to create a common reference, 14 used as recording electrodes) to record Electro-Cortico-Graphic (ECoG) neuronal activities in rodents. The data processing is based on an online self-paced non-supervised (asynchronous) BCI paradigm. N-way partial least squares algorithm together with Continuous Wavelet Transformation of ECoG recordings detect signatures related to motor activities. Signature detection in freely moving rats may activate external effectors during a behavioral task, which involved pushing a lever to obtain a reward. RESULTS: After routine training, we showed that peak brain activity preceding a lever push (LP) to obtain food reward was located mostly in the cerebellar cortex with a higher correlation coefficient, suggesting a strong postural component and also in the occipital cerebral cortex. Analysis of brain activities provided a stable signature in the high gamma band (â¼180Hz) occurring within 1500 msec before the lever push approximately around -400 msec to -500 msec. Detection of the signature from a single cerebellar cortical electrode triggers the effector with high efficiency (68% Offline and 30% Online) and rare false positives per minute in sessions about 30 minutes and up to one hour (â¼2 online and offline). CONCLUSIONS: In summary, our results are original as compared to the rest of the literature, which involves rarely rodents, a simple BCI set-up has been developed in rats, the data show for the first time long-term, up to one year, unsupervised online control of an effector.
