Energy homeostasis depends on behavior to predictively regulate metabolic states within narrow bounds. Here we review three theories of homeostatic control and ask how they provide insight into the circuitry underlying energy homeostasis. We offer two contributions. First, we detail how control theory and reinforcement learning are applied to homeostatic control. We show how these schemes rest on implausible assumptions; either via circular definitions, unprincipled drive functions, or by ignoring environmental volatility. We argue that active inference can elude these shortcomings while retaining important features of the model. Second, we review the neural basis of energetic control. We focus on a subset of arcuate subpopulations that project directly to, and are thus in a privileged position to opponently modulate dopaminergic cells as a function of energetic predictions over a spectrum of time horizons. We discuss how this can be interpreted under these theories, and how this can resolve paradoxes that have arisen. We propose this circuit constitutes a homeostatic-reward interface that underwrites the conjoint optimisation of physiological and behavioral homeostasis.
- Downloaded 1,779 times
- Download rankings, all-time:
- Site-wide: 12,344
- In neuroscience: 1,279
- Year to date:
- Site-wide: None
- Since beginning of last month:
- Site-wide: None
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!