Decoding based on the directionality of the individual cells predicts the directional percept.
A The directional percept (left) is predicted by the average over the cells activity (right), weighted by their directionality (right) and their distance to the stimulus (middle).
B Examples three directional cells based on the Shepard tones based spectrotemporal receptive fields (STRFs). Directionality was determined by the asymmetry of the 2nd column of the STRF (response to previous stimulus), centered at the maximum (BF) of the first column (response to current stimulus, see Methods for details). As usual, time on the abscissa runs into the past. The middle cell for example is a down-cell, since it responds more strongly to a stimulus sequence 10st => 7st, than 4st => 7st based on the STRF.
C The prediction of the decoding (ordinate) compared to the usually perceived direction for the two sequences (abscissa). Predictions depended on the length of the sequence (o = 5 tones, • = 10 tones) and the predicted tone (red = 1st tone, blue = 2nd tone). The dashed red line corresponds to a flat prediction.
D Predictive performance increased as a function of bias length and distance to the bias, reflected as 1st (red) or 2nd (blue) tone after the bias. Both dependencies are consistent with human performance and the build-up and recovery of adaptive processes.
E The basis for the directional decoding can be analyzed by considering the entire set of bias-induced differences in response, arranged by the directional preference of each cell (abscissa), and the location in BF relative to each stimulus in the Shepard pair (abscissa). Applying the analysis to the neural data, the obtained pattern of activity (top) is composed of two angled stripes of positive and negative differential activity. For cells with BFs close to the pitchclass of the test tones, the relative activities are significantly different (p=0.03, 1-way ANOVA) between ascending and descending preferring cells, thus predicting the percept of these tones. Grey boxes indicate combinations of directionality and relative location which did not exist in the cell population.
F Applied to a population of model neurons (as in Fig. 4, see Methods for details) subjected to the same stimulus as the real neurons, in the absence of adaptation (left) no significant pattern emerges. If no directional cells are present (middle), adaptation leads to a distinct pattern for different relative spectral locations, but the lack of directional cells prevents a directional judgement. Finally, with adaptation and directional cells a pattern of differential activation is obtained, similar to the pattern in the neural data. T Cells located close to the target tone (near 0 on the ordinate) show a differential activity, predictive of the percept, which was used in the direct decoding above (shown separately in the lower plots). While these activities exhibit no significant dependence in the absence of adaptation or directional cells, the dependence becomes significantly characteristic with adaptation (p<0.001, 1-way ANOVA, bottom right).
G The above results can be summarized as a symmetric imbalance in the activities of directional cells after the Bias around it (right), which when decoded predict steps consistent with the percept, i.e. both are judged in their relative position to the bias. Hence the percept of the frequency change direction is determined by the local activity, rather than by a global distance.