O'Doherty John P, Lee Sang Wan, Tadayonnejad Reza, Cockburn Jeff, Iigaya Kyo, Charpentier Caroline J
Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, 91125, USA; Computation and Neural Systems Program, California Institute of Technology, Pasadena, CA, 91125, USA.
Department of Bio and Brain Engineering and Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science Technology (KAIST), Daejeon, 34141, Republic of Korea.
Neurosci Biobehav Rev. 2021 Apr;123:14-23. doi: 10.1016/j.neubiorev.2020.10.022. Epub 2021 Jan 11.
It has long been suggested that human behavior reflects the contributions of multiple systems that cooperate or compete for behavioral control. Here we propose that the brain acts as a "Mixture of Experts" in which different expert systems propose strategies for action. It will be argued that the brain determines which experts should control behavior at any one moment in time by keeping track of the reliability of the predictions within each system, and by allocating control over behavior in a manner that depends on the relative reliabilities across experts. fMRI and neurostimulation studies suggest a specific contribution of the anterior prefrontal cortex in this process. Further, such a mechanism also takes into consideration the complexity of the expert, favoring simpler over more cognitively complex experts. Results from the study of different expert systems in both experiential and social learning domains hint at the possibility that this reliability-based control mechanism is domain general, exerting control over many different expert systems simultaneously in order to produce sophisticated behavior.
长期以来，人们一直认为人类行为反映了多个系统的作用，这些系统相互协作或竞争以控制行为。在此，我们提出大脑充当“专家混合体”，其中不同的专家系统提出行动策略。有人认为，大脑通过跟踪每个系统内预测的可靠性，并以依赖于各专家相对可靠性的方式分配对行为的控制，来决定在任何时刻应由哪些专家控制行为。功能磁共振成像（fMRI）和神经刺激研究表明前额叶前部皮质在此过程中具有特定作用。此外，这种机制还考虑了专家的复杂性，更倾向于选择较简单而非认知上更复杂的专家。在经验学习和社会学习领域对不同专家系统的研究结果暗示，这种基于可靠性的控制机制可能具有领域通用性，能够同时对许多不同的专家系统进行控制，从而产生复杂的行为。
