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后顶叶皮层中自身运动和目标的自适应整合。

Adaptive integration of self-motion and goals in posterior parietal cortex.

机构信息

Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA; Center for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Avenue, Boston, MA 02215, USA.

Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92093, USA.

出版信息

Cell Rep. 2022 Mar 8;38(10):110504. doi: 10.1016/j.celrep.2022.110504.

Abstract

Rats readily switch between foraging and more complex navigational behaviors such as pursuit of other rats or prey. These tasks require vastly different tracking of multiple behaviorally significant variables including self-motion state. To explore whether navigational context modulates self-motion tracking, we examined self-motion tuning in posterior parietal cortex neurons during foraging versus visual target pursuit. Animals performing the pursuit task demonstrate predictive processing of target trajectories by anticipating and intercepting them. Relative to foraging, pursuit yields multiplicative gain modulation of self-motion tuning and enhances self-motion state decoding. Self-motion sensitivity in parietal cortex neurons is, on average, history dependent regardless of behavioral context, but the temporal window of self-motion integration extends during target pursuit. Finally, many self-motion-sensitive neurons conjunctively track the visual target position relative to the animal. Thus, posterior parietal cortex functions to integrate the location of navigationally relevant target stimuli into an ongoing representation of past, present, and future locomotor trajectories.

摘要

老鼠很容易在觅食和更复杂的导航行为之间切换,例如追逐其他老鼠或猎物。这些任务需要对包括自身运动状态在内的多种具有重要行为意义的变量进行截然不同的跟踪。为了探索导航环境是否会调节自身运动跟踪,我们在觅食和视觉目标追逐期间检查了后顶叶皮层神经元的自身运动调节。执行追逐任务的动物通过预期和拦截目标轨迹来预测处理目标轨迹。与觅食相比,追逐会产生自身运动调节的乘法增益调制,并增强自身运动状态解码。无论行为环境如何,顶叶皮层神经元的自身运动敏感性平均都是依赖于历史的,但在目标追逐期间,自身运动整合的时间窗口会扩展。最后,许多对自身运动敏感的神经元共同跟踪相对于动物的视觉目标位置。因此,后顶叶皮层的功能是将与导航相关的目标刺激的位置整合到对过去、现在和未来运动轨迹的持续表示中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed0c/9026715/ae4346eb8be5/nihms-1787430-f0002.jpg

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