Table 3.
Neural data and model predictions | Onset |
Growth rate |
Baseline |
Threshold |
||||
---|---|---|---|---|---|---|---|---|
Easy | Hard | Easy | Hard | Easy | Hard | Easy | Hard | |
Neural data | ||||||||
Movement neurons | 0.53 (54.9) | 0.72 (68.9) | −0.22 (11.5) | −0.14 (9.8) | −0.11 (3.9) | −0.05 (1.6) | 0.12 (9.8) | 0.06 (13.1) |
Perfect integrator models | ||||||||
Race | 0.58 (60.6) | 0.67 (75.1) | −0.03 (4.3) | −0.02 (2.9) | −0.82 (98.6) | −0.82 (97.2) | 0.02 (3.0) | 0.01 (2.6) |
Diffusion | 0.46 (37.7) | 0.64 (67.6) | −0.10 (7.0) | −0.07 (6.5) | −0.68 (78.6) | −0.67 (73.5) | −0.02 (2.6) | −0.02 (1.9) |
Competitive | 0.60 (62.6) | 0.71 (81.5) | −0.05 (2.8) | −0.03 (2.8) | −0.78 (94.9) | −0.79 (96.6) | 0.03 (2.8) | 0.02 (3.0) |
Leaky models | ||||||||
Race | 0.72 (85.1) | 0.79 (92.4) | −0.13 (6.5) | −0.10 (3.8) | −0.36 (22.6) | −0.30 (18.2) | 0.06 (4.2) | 0.05 (3.8) |
Diffusion | 0.58 (57.2) | 0.76 (87.0) | −0.16 (6.6) | −0.11 (5.6) | −0.26 (21.6) | −0.26 (17.9) | 0.10 (5.8) | 0.09 (4.4) |
Competitive | 0.61 (66.4) | 0.72 (85.0) | −0.07 (3.9) | −0.06 (3.4) | −0.57 (59.0) | −0.56 (58.8) | 0.02 (3.6) | 0.01 (3.1) |
Gated models | ||||||||
Race | 0.67 (71.9) | 0.83 (96.0) | −0.22 (13.3) | −0.11 (7.0) | −0.04 (5.2) | −0.05 (5.4) | 0.10 (6.0) | 0.10 (4.4) |
Diffusion | 0.63 (68.1) | 0.84 (96.0) | −0.24 (9.2) | −0.16 (6.2) | −0.07 (6.4) | −0.09 (7.3) | 0.08 (4.5) | 0.10 (5.5) |
Competitive | 0.67 (70.8) | 0.83 (95.8) | −0.19 (11.3) | −0.10 (5.2) | −0.11 (6.9) | −0.06 (5.2) | 0.09 (5.4) | 0.09 (4.4) |
Note. Percentages of neurons/simulations with a significant correlation were calculated with α = .05. Observed data combine across animals. Predicted data are averaged across data sets. See Figures 11, 12, and 13 for plots of individual data sets. Data from Monkey Q are included in the hard condition. A subset of the neural data was previously published (Woodman, Kang, Thompson, & Schall, 2008).