小柯机器人

美国莱斯大学Valentin Dragoi和贝勒医学院Xaq Pitkow课题组合作取得一项新成果。经过不懈努力，他们的研究揭示了自由活动猕猴在觅食过程中策略变量的编码机制。相关论文发表在2024年3月5日出版的《自然-神经科学》杂志上。

研究人员让活动自由的猴子自由地与同时出现的奖励选项互动，同时利用无线装备记录背外侧前额叶皮层的群体活动。动物根据对奖励的预测是否实现来决定何时何地觅食。这种预测并不完全基于奖励交付的历史记录，还基于"等待时间越长，获得奖励的机会就越大"这一认识。

任务变量在高维群体活动的子空间中获得连续表示，这种压缩表示比真正的任务变量和原始神经活动更能预测动物随后的选择。该研究结果表明，猴子的觅食策略是基于动物自由探索环境时大脑皮层的奖励动态模型。

据介绍，迄今为止，研究自然环境中觅食行为的神经基础还很困难，因为以前的研究方法都是依靠受约束的动物来完成基于试验的觅食任务。

附：英文原文

Title: Population coding of strategic variables during foraging in freely moving macaques

Author: Shahidi, Neda, Franch, Melissa, Parajuli, Arun, Schrater, Paul, Wright, Anthony, Pitkow, Xaq, Dragoi, Valentin

Issue&Volume: 2024-03-05

Abstract: Until now, it has been difficult to examine the neural bases of foraging in naturalistic environments because previous approaches have relied on restrained animals performing trial-based foraging tasks. Here we allowed unrestrained monkeys to freely interact with concurrent reward options while we wirelessly recorded population activity in the dorsolateral prefrontal cortex. The animals decided when and where to forage based on whether their prediction of reward was fulfilled or violated. This prediction was not solely based on a history of reward delivery, but also on the understanding that waiting longer improves the chance of reward. The task variables were continuously represented in a subspace of the high-dimensional population activity, and this compressed representation predicted the animal’s subsequent choices better than the true task variables and as well as the raw neural activity. Our results indicate that monkeys’ foraging strategies are based on a cortical model of reward dynamics as animals freely explore their environment.

DOI: 10.1038/s41593-024-01575-w

Source: https://www.nature.com/articles/s41593-024-01575-w

Nature Neuroscience：《自然—神经科学》，创刊于1998年。隶属于施普林格·自然出版集团，最新IF：28.771
官方网址：https://www.nature.com/neuro/
投稿链接：https://mts-nn.nature.com/cgi-bin/main.plex