DECODING ELECTRIC FIELDS OF THE NERVOUS SYSTEM: INVESTIGATIONS OF INFORMATION STORAGE AND TRANSFER IN THE CENTRAL AND PERIPHERAL NERVOUS SYSTEM

Electrical potentials are the fundamental currency of communication in the nervous system. The advanced executive functions of the prefrontal cortex and the motor commands delivered to the neuromuscular junction, though involved with very different aspects of behavior, both rely on time-varying electrical signals. It is possible to "listen to" the internal communications of the nervous system by measuring the electrical potentials in the extra-cellular space. However, this is only meaningful if there is some way to interpret these signals, which are incredibly complicated and information rich. This dissertation represents an attempt to decode some of these signals in order to reveal their significance for behavior and function. The first study is an investigation of the relationship between different elements of the local field potential in the prefrontal cortex and memory consolidation. It is shown that certain electrographic signatures of non-rapid eye movement sleep, namely K-complexes and low-voltage spindles, are correlated with neuronal replay of recent experiences. It is also shown that the global fluctuations of activity in the population of cells, known as up/down states, is correlated with neuronal replay. Finally, it is shown that high-voltage spindles are not correlated with memory replay, and are therefore functionally different from low-voltage spindles. The second study focuses on the relationship between movements of the upper limb and the coordinated neural control, as measured by the electromyogram (EMG), of the muscles generating that movement. We show that different probability-based models can be used to predict what the pattern of EMG in the different muscles will be for any given kinematic state of the hand. In the third study it is demonstrated that the kinematic output associated with a particular pattern of EMG can be reproduced with electrical stimulation. Thus, it is not only possible to understand the commands issued by the nervous system, it is also possible to issue commands by interfacing with the nervous system directly. Finally, the design for an experiment that would combine EMG prediction with translation of EMG into electrical stimulus patterns is presented. The objective of this study would be to use these methods to fully control the upper limb in a way that would be useful for a functional electrical stimulation-based neuroprosthetic for spinal cord injured patients