The physiological control of eating: signals, neurons, and networks

神经科学 背景(考古学) 后脑 能量稳态 前脑 生物神经网络 生物 中枢神经系统 肥胖 内分泌学 古生物学
作者
Alan G. Watts,Scott E. Kanoski,Graciela Sanchez‐Watts,Wolfgang Langhans
出处
期刊:Physiological Reviews [American Physiological Society]
卷期号:102 (2): 689-813 被引量:107
标识
DOI:10.1152/physrev.00028.2020
摘要

During the past 30 yr, investigating the physiology of eating behaviors has generated a truly vast literature. This is fueled in part by a dramatic increase in obesity and its comorbidities that has coincided with an ever increasing sophistication of genetically based manipulations. These techniques have produced results with a remarkable degree of cell specificity, particularly at the cell signaling level, and have played a lead role in advancing the field. However, putting these findings into a brain-wide context that connects physiological signals and neurons to behavior and somatic physiology requires a thorough consideration of neuronal connections: a field that has also seen an extraordinary technological revolution. Our goal is to present a comprehensive and balanced assessment of how physiological signals associated with energy homeostasis interact at many brain levels to control eating behaviors. A major theme is that these signals engage sets of interacting neural networks throughout the brain that are defined by specific neural connections. We begin by discussing some fundamental concepts, including ones that still engender vigorous debate, that provide the necessary frameworks for understanding how the brain controls meal initiation and termination. These include key word definitions, ATP availability as the pivotal regulated variable in energy homeostasis, neuropeptide signaling, homeostatic and hedonic eating, and meal structure. Within this context, we discuss network models of how key regions in the endbrain (or telencephalon), hypothalamus, hindbrain, medulla, vagus nerve, and spinal cord work together with the gastrointestinal tract to enable the complex motor events that permit animals to eat in diverse situations.
最长约 10秒,即可获得该文献文件

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
刚刚
千雪发布了新的文献求助10
刚刚
刚刚
1秒前
胡可完成签到 ,获得积分0
1秒前
我会发财完成签到 ,获得积分10
2秒前
2秒前
失眠呆呆鱼完成签到 ,获得积分10
2秒前
2秒前
3秒前
Zhang发布了新的文献求助10
3秒前
hjygzv发布了新的文献求助10
4秒前
科研渣渣发布了新的文献求助10
6秒前
愉快乐瑶发布了新的文献求助10
6秒前
翰林发布了新的文献求助10
6秒前
7秒前
怠惰的香香酱关注了科研通微信公众号
7秒前
8秒前
10秒前
研友_VZG7GZ应助Zhang采纳,获得10
10秒前
Orange应助默默的无敌采纳,获得10
11秒前
gyh举报复杂的问玉求助涉嫌违规
12秒前
12秒前
俊逸半烟完成签到,获得积分10
12秒前
12秒前
zsf发布了新的文献求助10
13秒前
13秒前
14秒前
LiuHX发布了新的文献求助10
15秒前
duoya完成签到,获得积分10
15秒前
15秒前
17秒前
17秒前
007完成签到,获得积分10
17秒前
高高发布了新的文献求助10
18秒前
英吉利25发布了新的文献求助10
19秒前
星辰大海应助LiuHX采纳,获得10
20秒前
叶远望发布了新的文献求助10
20秒前
Jack完成签到,获得积分10
20秒前
21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
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Social Cognition: Understanding People and Events 1000
Polymorphism and polytypism in crystals 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6030069
求助须知:如何正确求助?哪些是违规求助? 7704294
关于积分的说明 16191919
捐赠科研通 5177053
什么是DOI,文献DOI怎么找? 2770426
邀请新用户注册赠送积分活动 1753848
关于科研通互助平台的介绍 1639365