Automated analyzer for on-line recognition of neural waveforms in extracellular recordings of multiple neurons

The progress of research in the neurophysiological foundations of brain functions such as sensory transformations, perception, learning, sensory-motor coordination and motor control depends on efforts for understanding the collective behavior of neurons. The physical constraints of the intracellular electrode dictate the use of extracellular electrodes for collecting simultaneous data from neuronal assemblies. However, the advantages of extracellular electrodes are accompanied by several challenges that have somewhat limited the efficient use of such electrodes: in extracellular recordings, the action potential waveforms of many neurons may be embedded in relatively high, colored noise and these waveforms need to be sorted in order to determine the activity of the individual neurons. Furthermore, when two neurons fire concurrently, their waveforms overlap; the severity of this problem increases with increased firing rates and contributes to the difficulty of neural waveform sorting. In most neuroscience experiments, the management of stimuli and recordings becomes more efficient and effective if the response of individual neurons is known to the scientist at the time of the recording rather than at a later time, off-line. Therefore on-line operation is highly desirable. Finally, in order to record the activity of a large number (e.g. 100) of neurons, multiple electrodes are needed. making full automation a prerequisite for on-line neural waveform sorting.