Human decision-making in fast movements is not always optimal, especially when facing high risk of financial loss. Researchers compared human performance in reaching tasks with different incentive values to ideal and alternative models. They found that participants' movements align more with a simple heuristic model rather than optimal or loss-averse models, especially when facing potential losses. This challenges the idea that human perception-motor decision-making is always optimal.