GSTDTAP

浏览/检索结果: 共3条,第1-3条 帮助

已选(0)清除 条数/页:   排序方式:
A distributional code for value in dopamine-based reinforcement learning 期刊论文
NATURE, 2020, 577 (7792) : 671-+
作者:  House, Robert A.;  Maitra, Urmimala;  Perez-Osorio, Miguel A.;  Lozano, Juan G.;  Jin, Liyu;  Somerville, James W.;  Duda, Laurent C.;  Nag, Abhishek;  Walters, Andrew;  Zhou, Ke-Jin;  Roberts, Matthew R.;  Bruce, Peter G.
收藏  |  浏览/下载:61/0  |  提交时间:2020/07/03

Since its introduction, the reward prediction error theory of dopamine has explained a wealth of empirical phenomena, providing a unifying framework for understanding the representation of reward and value in the brain(1-3). According to the now canonical theory, reward predictions are represented as a single scalar quantity, which supports learning about the expectation, or mean, of stochastic outcomes. Here we propose an account of dopamine-based reinforcement learning inspired by recent artificial intelligence research on distributional reinforcement learning(4-6). We hypothesized that the brain represents possible future rewards not as a single mean, but instead as a probability distribution, effectively representing multiple future outcomes simultaneously and in parallel. This idea implies a set of empirical predictions, which we tested using single-unit recordings from mouse ventral tegmental area. Our findings provide strong evidence for a neural realization of distributional reinforcement learning.


Analyses of single-cell recordings from mouse ventral tegmental area are consistent with a model of reinforcement learning in which the brain represents possible future rewards not as a single mean of stochastic outcomes, as in the canonical model, but instead as a probability distribution.


  
Hyperactivation of sympathetic nerves drives depletion of melanocyte stem cells 期刊论文
NATURE, 2020, 577 (7792) : 676-+
作者:  Zhao, Ruozhu;  Chen, Xin;  Ma, Weiwei;  Zhang, Jinyu;  Guo, Jie;  Zhong, Xiu;  Yao, Jiacheng;  Sun, Jiahui;  Rubinfien, Julian;  Zhou, Xuyu;  Wang, Jianbin;  Qi, Hai
收藏  |  浏览/下载:12/0  |  提交时间:2020/07/03

Empirical and anecdotal evidence has associated stress with accelerated hair greying (formation of unpigmented hairs)(1,2), but so far there has been little scientific validation of this link. Here we report that, in mice, acute stress leads to hair greying through the fast depletion of melanocyte stem cells. Using a combination of adrenalectomy, denervation, chemogenetics(3,4), cell ablation and knockout of the adrenergic receptor specifically in melanocyte stem cells, we find that the stress-induced loss of melanocyte stem cells is independent of immune attack or adrenal stress hormones. Instead, hair greying results from activation of the sympathetic nerves that innervate the melanocyte stem-cell niche. Under conditions of stress, the activation of these sympathetic nerves leads to burst release of the neurotransmitter noradrenaline (also known as norepinephrine). This causes quiescent melanocyte stem cells to proliferate rapidly, and is followed by their differentiation, migration and permanent depletion from the niche. Transient suppression of the proliferation of melanocyte stem cells prevents stress-induced hair greying. Our study demonstrates that neuronal activity that is induced by acute stress can drive a rapid and permanent loss of somatic stem cells, and illustrates an example in which the maintenance of somatic stem cells is directly influenced by the overall physiological state of the organism.


Stress induces hair greying in mice through depletion of melanocyte stem cells, which is mediated by the activation of sympathetic nerves rather than through immune attack or adrenal stress hormones.


  
The impact of the EU Emissions Trading System on low-carbon technological change: The empirical evidence 期刊论文
ECOLOGICAL ECONOMICS, 2019, 164
作者:  Teixido, Jordi;  Verde, Stefano F.;  Nicolli, Francesco
收藏  |  浏览/下载:8/0  |  提交时间:2019/11/27
EU ETS  Low-carbon technological change  Innovation incentives  Free allocation  Empirical evidence