Figure 9. Brainstem neuromodulatory nuclei predict reduction of choice bias.

(A) Correlation between decision bias (criterion) and the combined neuromodulatory brainstem signal (linear combination of responses in LC, SN, VTA, BF-sept, and BF-subl maximizing the correlation to TPR; see Materials and methods; left), and the combined colliculi signal (linear combination of responses in SC and IC maximizing the correlation to TPR; right) (5 bins). Stats, permutation test. (B) As panel A but for the correlation to fraction of ‘yes’-choices. (C) Group-level posterior probability densities for means of parameters in the DDM regression model, through which we assessed the trial-by-trial, linear relationship between single-trial drift and the combined neuromodulatory response or the combined colliculi response (see Materials and methods; see Figure 9—figure supplement 1 for the remaining parameters ‘starting point’, ‘boundary separation’ and ‘non-decision time’). All panels: group average (N = 14); shading or error bars, s.e.m.

DOI: http://dx.doi.org/10.7554/eLife.23232.026

Figure 9—figure supplement 1. Brainstem responses are not associated to sensitivity.

(A) Correlation between perceptual sensitivity (d’) and the combined neuromodulatory brainstem response (linear combination of responses in LC, SN, VTA, BF-sept, and BF-subl maximizing the correlation to TPR; see Materials and methods), and the combined colliculi response (linear combination of responses in SC and IC maximizing the correlation to TPR) (5 bins). Stats, permutation test. (B) Group-level posterior probability densities for means of the remaining parameters in the DDM regression model, through which we assessed the linear relationship between the trial-by-trial drift and the trial-by-trial combined neuromodulatory response and the combined colliculi response (see Materials and methods). All panels: group average (N = 14); shading or error bars, s.e.m.

DOI: http://dx.doi.org/10.7554/eLife.23232.027