The power analysis used F-tests with between-subjects factors (number of groups = 2), yet the actual design uses a within-subjects manipulation (all participants experienced both human and robot conditions). This is a fundamental mismatch. With only 25 participants after exclusions, the study appears critically underpowered for detecting the three-way interaction (agent type × willingness × expected value) that forms the core of the fMRI findings. How do you justify the statistical validity of the reported interaction effects given this design-power mismatch?
The paper reports that participants rated robot images as representative of humanoid robots, but there is no reported manipulation check confirming that participants actually perceived the high vs. low willingness manipulation as intended. Given that the entire reinforcement learning model depends on participants tracking this variable, how can we be confident that the manipulation was effective if no explicit check was conducted?
In each trial, participants chose between two images of the same type (two humans OR two robots) with different eye colors presumably indicating willingness. However, Figure 1A shows robots with different eye colors (black vs. yellow) while humans have no such distinguishing feature. This creates a potential confound: robots could be distinguished by a simple visual feature (eye color) while humans required more complex social inference. Could this explain the differential neural activation in the precentral gyrus (action/embodied cognition) versus putamen (reward), rather than partner type per se?