Figure 17. Contribution of the logit transform to the predictions of the integrated stimulus-to-behavior generalized linear model (GLM).
(A) Comparison of the behavioral outputs of the GLM with and without logit transformation for the run-to-turn transitions elicited by a 8-s linear light ramp. In the absence of logit transformation, the GLM is based on a linear combination λ(t) = γ0 + γ1y(t). Negative values of the linear combination were rectified to be equal to 0. The parameters of the model were trained on the full set of ramps presented in Figure 5—figure supplement 1 (derived parameter set: γ0 = 0.3762, γ1 = −0.0198 Hz−1). The result of the GLM without logit transformation is represented by a dashed line. The GLM model that includes the logit transformation is represented by a plain line (parameter set listed in Table 3). The correlation coefficients (ρ) and coefficients of variation of the RMSE computed on the outputs of the GLM with and without logit transformation differ by 12% and 10%, respectively. (B) Same as panel A for a sigmoid light ramp. The correlation coefficients and coefficients of variation of the RMSE computed on the outputs of the GLM with and without logit transformation differ by 5% and 22%, respectively.