2026-11-10 京都大学

窃盗累犯では、仕事の報酬や刑罰等のフィードバックをもとに自身の行動を更新することが出来ず、窃盗行為を繰り返してしまうと考えられます。(作成者・後藤/図の作成に生成AI[Gemini 3.6 Flash]を使用)
<関連情報>
- https://www.kyoto-u.ac.jp/ja/research-news/2026-11-10
- https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2026.1997570/full
窃盗累犯者における探索・活⽤の意思決定に関わる強化学習の低下 Lower reward-based reinforcement learning underlying explore-exploit decision making in non-kleptomanic theft recidivists
Yukiori Goto,Satoshi Yoshino,Chikara Kita,Moojun Won,Young-A Lee
Frontiers in Psychology Published:09 November 2026
DOI:https://doi.org/10.3389/fpsyg.2026.1997570
Abstract
Introduction:
Larceny imposes profound societal and economic burdens; however, punitive judicial measures frequently fail to deter recidivism. The neurobehavioral mechanisms driving habitual offending, whether instrumental or kleptomanic, in theft recidivists remain poorly understood.
Methods:
In this study, we investigated explore-exploit decision-making and underlying reinforcement learning architectures in theft recidivists with a four-arm bandit task while prefrontal cortex (PFC) hemodynamics were continuously monitored using functional near-infrared spectroscopy (fNIRS).
Results:
Model-free behavioral analyses revealed that non-kleptomanic theft recidivists (NTR) accumulated significantly higher cumulative regret and made fewer optimal choices compared to control individuals without criminal records (CT), whereas results for the kleptomanic theft recidivists (KTR) remained inconclusive. Model-based analyses through Variational Bayesian Analysis identified Q-learning with decay model as the optimal computational fit. Parameter extraction using the model demonstrated that the NTR group exhibited a lower learning rate than CT and KTR groups, indicating a learning deficit in updating action values following environmental feedback. fNIRS tracking of trial-by-trial latent reinforcement variables revealed that while PFC activity was modulated by these variables, group differences were characterized by relative baseline hemodynamic shifts rather than rewirings of value-tracking neural circuits.
Discussion:
These findings suggest that non-kleptomanic recurrent thefts may be associated with impaired reinforcement learning mechanisms.

