Dynamic prediction of goal location by coordinated representation of prefrontal-hippocampal theta sequences

海马结构 代表(政治) 海马体 神经科学 前额叶皮质 计算机科学 空间记忆 生物 人工智能 机器学习 工作记忆 认知 政治学 政治 法学
作者
Yimeng Wang,Xueling Wang,Ling Wang,Zheng Li,Shuang Meng,Nan Zhu,Xingwei An,Lei Wang,Jiajia Yang,Chenguang Zheng,Dong Ming
出处
期刊:Current Biology [Elsevier]
卷期号:34 (9): 1866-1879.e6 被引量:4
标识
DOI:10.1016/j.cub.2024.03.032
摘要

Prefrontal (PFC) and hippocampal (HPC) sequences of neuronal firing modulated by theta rhythms could represent upcoming choices during spatial memory-guided decision-making. How the PFC-HPC network dynamically coordinates theta sequences to predict specific goal locations and how it is interrupted in memory impairments induced by amyloid beta (Aβ) remain unclear. Here, we detected theta sequences of firing activities of PFC neurons and HPC place cells during goal-directed spatial memory tasks. We found that PFC ensembles exhibited predictive representation of the specific goal location since the starting phase of memory retrieval, earlier than the hippocampus. High predictive accuracy of PFC theta sequences existed during successful memory retrieval and positively correlated with memory performance. Coordinated PFC-HPC sequences showed PFC-dominant prediction of goal locations during successful memory retrieval. Furthermore, we found that theta sequences of both regions still existed under Aβ accumulation, whereas their predictive representation of goal locations was weakened with disrupted spatial representation of HPC place cells and PFC neurons. These findings highlight the essential role of coordinated PFC-HPC sequences in successful memory retrieval of a precise goal location.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
zzz完成签到,获得积分10
1秒前
倩Q发布了新的文献求助10
1秒前
樱桃完成签到,获得积分10
2秒前
xiang发布了新的文献求助10
2秒前
NexusExplorer应助原野采纳,获得10
4秒前
5秒前
池林完成签到,获得积分10
5秒前
6秒前
量子星尘发布了新的文献求助10
7秒前
8秒前
10秒前
上官若男应助zh1858f采纳,获得10
11秒前
xiaoxioayixi发布了新的文献求助10
12秒前
高天雨发布了新的文献求助10
12秒前
Ecokarster发布了新的文献求助10
14秒前
14秒前
isvv发布了新的文献求助20
17秒前
Jasper应助义气的羽毛采纳,获得10
18秒前
KY完成签到,获得积分10
18秒前
量子星尘发布了新的文献求助10
19秒前
天天完成签到,获得积分10
19秒前
原野发布了新的文献求助10
19秒前
海人完成签到 ,获得积分10
21秒前
量子星尘发布了新的文献求助10
21秒前
小马甲应助qqqqqq采纳,获得10
22秒前
22秒前
23秒前
Rain完成签到,获得积分10
23秒前
科目三应助liuying采纳,获得10
23秒前
www268完成签到,获得积分10
23秒前
Ecokarster完成签到,获得积分10
26秒前
26秒前
28秒前
共享精神应助Guo采纳,获得10
28秒前
英俊的铭应助诚心黑夜采纳,获得10
28秒前
29秒前
29秒前
billevans发布了新的文献求助30
29秒前
30秒前
大个应助fengjingjing采纳,获得10
30秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Quaternary Science Reference Third edition 6000
Encyclopedia of Forensic and Legal Medicine Third Edition 5000
Introduction to strong mixing conditions volume 1-3 5000
Aerospace Engineering Education During the First Century of Flight 3000
Agyptische Geschichte der 21.30. Dynastie 3000
Les Mantodea de guyane 2000
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5785240
求助须知:如何正确求助?哪些是违规求助? 5686798
关于积分的说明 15467120
捐赠科研通 4914318
什么是DOI,文献DOI怎么找? 2645181
邀请新用户注册赠送积分活动 1592988
关于科研通互助平台的介绍 1547323