Seminar: 6/17 - Eberhard Fetz
1:00 to 2:30 PM at:
Univ. of Washington
A variety of brain-computer interfaces [BCI] have been developed to transform neural activity into signals that control a computer cursor or other external devices. Effective BCI control depends significantly on the ability of the subject to modify neural activity appropriately. Volitional modulation of neural activity is evident in many conventional experimental paradigms, and the degree of neural control has been directly tested in biofeedback experiments and BCI applications. While the usual BCI paradigm involves brain control of external devices, a recurrent BCI [R-BCI] generates output that is fed back into the nervous system or muscles. We are investigating an implantable R-BCI consisting of autonomously operating electronic circuitry, including a computer chip that interacts continuously with the brain of a monkey. The so-called “Neurochip” can document the activity of motor cortex cells and arm muscles during free behavior and sleep, storing this activity for subsequent download via an infrared port. In a recurrent mode, the Neurochip can convert cell activity to electrical stimuli delivered back to the spinal cord or muscles, implementing neurally controlled functional electrical stimulation. When the R-BCI converted motor cortex cell activity into stimuli delivered at an adjacent cortical site continuous operation of such spike-triggered stimulation for a day generated long-lasting changes in connections between the synchronized sites. Looking ahead, two applications of the R-BCI have therapeutic potential for treating movement disorders or stroke. First, the artificial recurrent connection could bridge impaired biological connections and allow the subject to learn to generate the neural activity that is appropriate to compensate for the lost pathway. Second, by delivering stimuli synchronized with cell activity, continuous operation of the R-BCI can strengthen weak existing biological connections through Hebbian mechanisms. The R-BCI paradigm has numerous potential applications, depending on the input signals, the computed transform and the output targets.
"Volitional control of neural activity and recurrent brain-computer interfaces"