Causal evidence of a line attractor encoding an affective state

吸引子 光遗传学 神经科学 编码 物理 拓扑(电路) 计算机科学 生物 数学 数学分析 遗传学 基因 组合数学
作者
Amit Vinograd,Aditya Nair,Joseph Kim,Scott W. Linderman,David J. Anderson
出处
期刊:Nature [Nature Portfolio]
被引量:1
标识
DOI:10.1038/s41586-024-07915-x
摘要

Line attractors are emergent population dynamics hypothesized to encode continuous variables such as head direction and internal states1-4. In mammals, direct evidence of neural implementation of a line attractor has been hindered by the challenge of targeting perturbations to specific neurons within contributing ensembles2,3. Linear dynamical systems modeling has revealed that neurons in the hypothalamus exhibit approximate line attractor dynamics in male mice during aggressive encounters5. We have previously hypothesized that these dynamics may encode the variable intensity of an aggressive internal motive state. Here, we report that these neurons also showed line attractor dynamics in head-fixed mice observing aggression6. We identified and perturbed line attractor-contributing neurons using 2-photon calcium imaging and holographic optogenetic perturbations. On-manifold perturbations yielded integration and persistent activity that drove the system along the line attractor, while transient off-manifold perturbations were followed by rapid relaxation back into the attractor. Furthermore, single-cell stimulation and imaging revealed selective functional connectivity among attractor-contributing neurons. Intriguingly, individual differences among mice in line attractor stability were correlated with the degree of functional connectivity among attractor neurons. Mechanistic RNN modelling indicated that dense subnetwork connectivity and slow neurotransmission7 best recapitulate our empirical findings. Our work bridges circuit and manifold levels3, providing causal evidence of continuous attractor dynamics encoding an affective internal state in the mammalian hypothalamus.

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
DaSheng发布了新的文献求助10
1秒前
SciGPT应助hajimi123采纳,获得10
1秒前
武老师贼帅完成签到,获得积分10
1秒前
洛洛洛完成签到,获得积分10
1秒前
2秒前
放青松完成签到 ,获得积分10
2秒前
心灵美的静芙完成签到,获得积分10
2秒前
4秒前
王昕钥完成签到,获得积分10
4秒前
小何医生发布了新的文献求助10
4秒前
5秒前
聪明的羊完成签到,获得积分10
5秒前
6秒前
笑点低的乐荷完成签到,获得积分10
6秒前
6秒前
王一博发布了新的文献求助10
6秒前
小龙仔123完成签到 ,获得积分10
9秒前
Kevin完成签到,获得积分10
10秒前
Mzuser发布了新的文献求助10
10秒前
10秒前
神烦狗发布了新的文献求助10
10秒前
超帅的蚂蚁完成签到,获得积分10
12秒前
冷静千柔完成签到 ,获得积分10
13秒前
今夕何夕完成签到,获得积分10
14秒前
wang@163.com完成签到,获得积分10
14秒前
Ava应助科研通管家采纳,获得10
14秒前
14秒前
14秒前
情怀应助科研通管家采纳,获得10
14秒前
李爱国应助科研通管家采纳,获得10
15秒前
FashionBoy应助科研通管家采纳,获得10
15秒前
CodeCraft应助科研通管家采纳,获得10
15秒前
研友_VZG7GZ应助科研通管家采纳,获得10
15秒前
jim_cheo应助科研通管家采纳,获得10
15秒前
15秒前
深情安青应助科研通管家采纳,获得10
15秒前
HH应助科研通管家采纳,获得10
15秒前
高大妖丽应助科研通管家采纳,获得10
15秒前
今后应助科研通管家采纳,获得10
15秒前
16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
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 2500
Roms fliessende Grenzen : Archäologische Landesausstellung Nordrhein-Westfalen 1000
Atlas of Aligner Treatment and Planning A Case-Based Approach 1000
Geist der Kunst und Kultur 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Soil mites of the family Rhagidiidae (Actinedida: Eupodoidea). Morphology, Systematics, Ecology 520
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7425689
求助须知:如何正确求助?哪些是违规求助? 9028744
关于积分的说明 19232774
捐赠科研通 7054320
什么是DOI,文献DOI怎么找? 3235704
关于科研通互助平台的介绍 2399149
邀请新用户注册赠送积分活动 2218285