Ruff Douglas A, Markman Sol K, Kim Jason Z, Cohen Marlene R
Department of Neurobiology, University of Chicago, IL, USA.
Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, MA, USA.
bioRxiv. 2025 Jan 3:2025.01.03.631242. doi: 10.1101/2025.01.03.631242.
Animals capable of complex behaviors tend to have more distinct brain areas than simpler organisms, and artificial networks that perform many tasks tend to self-organize into modules (1-3). This suggests that different brain areas serve distinct functions supporting complex behavior. However, a common observation is that essentially anything that an animal senses, knows, or does can be decoded from neural activity in any brain area (4-6). If everything is everywhere, why have distinct areas? Here we show that the function of a brain area is more related to how different types of information are combined (formatted) in neural representations than merely whether that information is present. We compared two brain areas: the middle temporal area (MT), which is important for visual motion perception (7, 8), and the dorsolateral prefrontal cortex (dlPFC), which is linked to decision-making and reward expectation (9, 10)). When monkeys based decisions on a combination of motion and reward information, both types of information were present in both areas. However, they were formatted differently: in MT, they were encoded separably, while in dlPFC, they were represented jointly in ways that reflected the monkeys' decision-making. A recurrent neural network (RNN) model that mirrored the information formatting in MT and dlPFC predicted that manipulating activity in these areas would differently affect decision-making. Consistent with model predictions, electrically stimulating MT biased choices midway between the visual motion stimulus and the preferred direction of the stimulated units (11), while stimulating dlPFC produced 'winner-take-all' decisions that sometimes reflected the visual motion stimulus and sometimes reflected the preference of the stimulated units, but never in between. These results are consistent with the tantalizing possibility that a modular structure enables complex behavior by flexibly reformatting information to accomplish behavioral goals.
能够表现出复杂行为的动物往往比简单生物体拥有更多不同的脑区，而执行多种任务的人工网络往往会自组织成模块（1 - 3）。这表明不同的脑区具有支持复杂行为的不同功能。然而，一个常见的观察结果是，动物感知、知晓或做的任何事情基本上都可以从任何脑区的神经活动中解码出来（4 - 6）。如果一切信息都存在于各个脑区，那为什么还会有不同的脑区呢？在这里，我们表明脑区的功能与其说是与特定信息是否存在有关，不如说是与不同类型的信息在神经表征中如何组合（格式化）更为相关。我们比较了两个脑区：颞中区（MT），它对视觉运动感知很重要（7, 8），以及背外侧前额叶皮层（dlPFC），它与决策和奖励期望有关（9, 10）。当猴子基于运动和奖励信息的组合做出决策时，这两种信息在两个脑区都存在。然而，它们的格式化方式不同：在MT中，它们是分别编码的，而在dlPFC中，它们以反映猴子决策的方式共同呈现。一个反映MT和dlPFC中信息格式化的循环神经网络（RNN）模型预测，操纵这些脑区的活动会对决策产生不同的影响。与模型预测一致，电刺激MT会使选择偏向于视觉运动刺激和被刺激单元的偏好方向之间的中间位置（11），而刺激dlPFC则会产生“胜者全得”的决策，有时反映视觉运动刺激，有时反映被刺激单元的偏好，但绝不会处于两者之间。这些结果与一种诱人的可能性相一致，即模块化结构通过灵活地重新格式化信息以实现行为目标，从而使复杂行为成为可能。
