Improved best-stimulus classification of taste neurons

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Abstract
In taste neurophysiology, neurons are often classified according to their ‘best stimulus’, i.e., the stimulus substance thai elicits the largest maximum response. In practice, the stimulus is taken that elicits the largest response at ‘moderate’ stimulus intensity. This ‘mid-range concentration method’ is ambiguous, as the response still depends on the concentrations used. This paper proposes an improved classification scheme, the ‘slope method’. For a neuron following Beidler's taste equation, the slope of the response versus log-concentration curve is proportional to the maximum response. Two concentrations are sufficient to estimate this slope, which is less sensitive to the choice of concentrations than is response magnitude. The two methods were applied to recent experimental results from taste neurons in the nucleus of the tractus solitarius (NTS) in the rat. They produced different labels in a substantial number of cases. The methods were then compared using a Monte-Carlo computer simulation. The assumptions made, with respect to the equilibrium constant (i.e., the concentration eliciting the half-maximum response) and response variability, appear to be sufficiently realistic. For most conditions, the slope method was superior to the mid-range concentration method in identifying the best stimulus.

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