Extraction, processing, and analysis of multineuron data

Abstract

The work reported considers information coding by a population of neurons. Multineuron data were extracellularly recorded from the ventral nerve cord of the cockroach, Periplaneta americana. The nerve cord contains 14 giant interneurons which mediate the wind-evoked directed escape response. The activity of the giant interneurons was observed and tested to determine how directional information was encoded in these neurons.

It was found that action potential waveforms produced by the giant interneurons could be detected at a rate of 90% or more. Waveforms could be classified according to which subpopulation of giant interneurons produced them with at least 80% accuracy. These separation analyses allowed testing directional information contained in the neural activity observed on up to four physiologically meaningful groups of cells. The neural activity was interpreted in terms of the magnitude of each group's response, the latency to first action potential produced by each group, and the temporal patterning within each group.

The ability to classify wind direction using the recorded neural responses was assessed by computing the error rates resulting from making right versus left wind or front versus back wind decisions using binary hypothesis testing methods. It was found that the information within the nerve cord was best suited for coding right versus left winds and that good coding depended upon preserving the bilateral division inherent in the cord. The latency feature did not code direction nearly as well as did the response magnitude or temporal patterning features. The latter two features coded direction similarly well and at error rates of less than 10%, which is more accurate than the apparent behavioral discrimination.