Title :
Corticospinal signals recorded with MEAs can predict the volitional forearm forces in rats
Author :
Yi Guo ; Mesut, Sahin ; Foulds, Richard A. ; Adamovich, S.V.
Author_Institution :
Dept. of Biomed. Eng., Inst. of Technol., Newark, NJ, USA
Abstract :
We set out to investigate if volitional components in the descending tracts of the spinal cord white matter can be accessed with multi-electrode array (MEA) recording technique. Rats were trained to press a lever connected to a haptic device with force feedback to receive sugar pellets. A flexible-substrate multi-electrode array was chronically implanted into the dorsal column of the cervical spinal cord. Field potentials and multi-unit activities were recorded from the descending axons of the corticospinal tract while the rat performed a lever pressing task. Forelimb forces, recorded with the sensor attached to the lever, were reconstructed using the hand position data and the neural signals through multiple trials over three weeks. The regression coefficients found from the trial set were cross-validated on the other trials recorded on same day. Approximately 30 trials of at least 2 seconds were required for accurate model estimation. The maximum correlation coefficient between the actual and predicted force was 0.7 in the test set. Positional information and its interaction with neural signals improved the correlation coefficient by 0.1 to 0.15. These results suggest that the volitional information contained in the corticospinal tract can be extracted with multi-channel neural recordings made with parenchymal electrodes.
Keywords :
bioelectric potentials; biomedical electrodes; correlation methods; feature extraction; haptic interfaces; medical signal processing; neurophysiology; patient diagnosis; prosthetics; regression analysis; signal reconstruction; MEA; cervical spinal cord; chronic implantation; corticospinal signal; corticospinal tract; descending axon; dorsal column; field potential; flexible-substrate multielectrode array; force feedback; hand position data; haptic device; lever pressing task; maximum correlation coefficient; model estimation; multichannel neural recording extraction; multielectrode array recording technique; multiunit activities; neural signal interaction; parenchymal electrode; positional information; regression coefficient; signal reconstruction; spinal cord white matter; sugar pellets; volitional forearm forces; volitional information; Arrays; Correlation coefficient; Estimation; Force; Haptic interfaces; Spinal cord; Transfer functions;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
DOI :
10.1109/EMBC.2013.6609918