Detection of movement-related potentials from the electro-encephalogram for possible use in a brain-computer interface.

Brain-computer interfaces are devices for enabling patients with severe motor disorders to communicate with the world. One method for operating such devices is to use movement-related potentials that are generated in the brain when the patient moves, or imagines a movement of, one of his limbs. An algorithm for detecting movement-related potentials using a small number of EEG channels was developed. This algorithm is a combination of the matched filter, a non-linear transformation previously developed as part of a similar detector, and a classifier. The algorithm was compared with previous designs of similar detectors by both theoretic analysis and off-line evaluation of performance on data recorded from five subjects. It is shown that the performance of the algorithm was superior to that of previous methods, improving the area under the receiver operating characteristic curve to 87.8%, an improvement of 25% compared with the best previously suggested detection method. Finally, the probable sources for false detections were identified, and possible ways to minimise them are proposed.

Movement-related potentials during the performance of a motor task II: cerebral areas activated during learning of the task.

Movement-related potentials (MRPs) recorded from the brain are thought to vary during learning of a motor task. However, since MRPs are recorded at a very low signal-to-noise ratio, it is difficult to measure these variations. In this study we attempt to remove most of the accompanying noise thus enabling the tracking of transient phenomena in MRPs recorded during learning of a motor task. Subjects performed a simple motor task which required learning. A modified version of the matching pursuit algorithm was used in order to remove a significant portion of the electroencephalographic noise overlapping the MRPs recorded in the experiment. Small groups of MRPs were then averaged according to experimental parameters. Our results show that the power of the MRPs does not decay uniformly during learning. Instead, there is a significant peak in their power after 4 or 5 repetitions of the task. This peak is noticeable especially in electrodes placed over the prefrontal region of the cortex at times subsequent to the actual movement. The observed pattern of activity may indicate problem solving related to comprehension of the force against which the user performed the task. It is possible that this problem solving occurs in the prefrontal cortex.

Movement-related potentials during the performance of a motor task I: the effect of learning and force.

Movement-related potentials (MRPs) recorded from the brain may be affected by several factors. These include the how well the subject knows the task and the load against which he performs it. The objective of this study is to determine how dominant these two factors are in influencing the shape and power of MRPs. MRPs were recorded during performance of a simple motor task that required learning of a force. A stochastic algorithm was used in order to partition a set of MRPs that are embedded in the surrounding electroencephalographic (EEG) activity into distinct classes according to the power of the underlying MRPs. Our results show that the most influential factor in the partition was the load against which the subject performed the task. Furthermore, it was found that learning has a smaller, though not insignificant, influence on the power of the MRPs.

Movement-related potentials in the human spinal cord preceding toe movement.

OBJECTIVES: A method by which potentials related to voluntary movement can be recorded noninvasively from the human spinal cord is presented. METHODS: A novel signal processing technique performed on signals recorded by surface electrodes placed over the spinal column was used to filter time-locked back muscle noise, so that the only remaining signals were the spinal movement-related potentials from the brain to the limbs and vice versa. RESULTS: The signals obtained from 7 subjects using this technique are shown and temporally compared with movement-related cortical potentials (MRCP) and muscle electromyogram. It is demonstrated that the spinal signal starts approximately 600 ms before the actual movement, and that some features of this signal correspond to changes in cortical potentials. CONCLUSIONS: These findings imply that the spinal cord is not a simple command-carrying medium from the brain to the limbs, and implies that some computational activities take place at the spinal cord level.

A model of induced coupled movements in the human body: a case study.

We present a case study of involuntary motion in one part of the body induced by a voluntary motion in another part. The case investigated was that of a steady-state motion of the fingers at various frequencies, which induced a similar kind of motion in the legs. These phenomena were observed in a subject practicing sphincter gymnastics, a physical therapy method in which repetitive motion of different muscles is exercised, and is known to induce motions in other muscles of the body. We show that a linear model, for which we give an experimental transfer function and demonstrate its validity, can describe the generation of the induced periodic motions by the voluntary motions. We compare the results of the transfer function with those of Von Holst's statistical analysis.