Functional correlates of likelihood and prior representations in a virtual distance task

虚拟距离任务中可能性和先验表征的功能相关性

阅读:1

Abstract

Spatial navigation is an imperative cognitive function, in which individuals must interact with their environment in order to accurately reach a destination. Previous research has demonstrated that, when traveling a predetermined distance, humans must balance between noise in the measurement process and the prior history of traveled distances. This tradeoff has recently been formally described using Bayesian estimation; however, the neural correlates of Bayesian estimation during distance reproduction have yet to be investigated. Here, human subjects performed a virtual reality distance reproduction task during functional Magnetic Resonance Imaging (fMRI), in which they were required to reproduce various traveled distances in the absence of overt navigational cues. As previously demonstrated, subjects exhibited a central tendency effect, wherein reproduced distances gravitated to the mean of the stimulus set. fMRI activity during this task revealed distance-sensitive activity in a network of regions, including prefrontal and hippocampal regions. Using a computational index of central tendency, we found that activity in the retrosplenial cortex, a region highly implicated in spatial navigation, negatively covaried between subjects with the degree of central tendency observed; conversely, we found that activity in the anterior hippocampus/amygdala complex was positively correlated with the central tendency effect of gravitating to the average reproduced distance. These findings suggest dissociable roles for the retrosplenial cortex and hippocampal complex during distance reproduction, with both regions coordinating with the prefrontal cortex the influence of prior history of the environment with present experience. Hum Brain Mapp 37:3172-3187, 2016. © 2016 Wiley Periodicals, Inc.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。