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Principles of Neural Design
Abstract
Two distinguished neuroscientists distil general principles from more than a century of scientific study, “reverse engineering” the brain to understand its design. Neuroscience research has exploded, with more than fifty thousand neuroscientists applying increasingly advanced methods. A mountain of new facts and mechanisms has emerged. And yet a principled framework to organize this knowledge has been missing. In this book, Peter Sterling and Simon Laughlin, two leading neuroscientists, strive to fill this gap, outlining a set of organizing principles to explain the whys of neural design that allow the brain to compute so efficiently. Setting out to “reverse engineer” the brain—disassembling it to understand it—Sterling and Laughlin first consider why an animal should need a brain, tracing computational abilities from bacterium to protozoan to worm. They examine bigger brains and the advantages of “anticipatory regulation”; identify constraints on neural design and the need to “nanofy”; and demonstrate the routes to efficiency in an integrated molecular system, phototransduction. They show that the principles of neural design at finer scales and lower levels apply at larger scales and higher levels; describe neural wiring efficiency; and discuss learning as a principle of biological design that includes “save only what is needed.” Sterling and Laughlin avoid speculation about how the brain might work and endeavor to make sense of what is already known. Their distinctive contr…
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In the citing paper
“All animals run an internal model of their world for the purpose of allostasis”
From The theory of constructed emotion: an active inference account of interoception and categorization (2016) · cites this paper as Sterling and Laughlin, 2015
In the citing paper
“Allostasis is not a condition of the body, but a process for how the brain regulates the body according to costs and benefits”
From The theory of constructed emotion: an active inference account of interoception and categorization (2016) · cites this paper as Sterling and Laughlin, 2015
In the citing paper
“Even single-celled organisms that lack a brain learn, remember, make predictions, and forage in service to allostasis”
From The theory of constructed emotion: an active inference account of interoception and categorization (2016) · cites this paper as Sterling and Laughlin, 2015
In the citing paper
“All brains accomplish the same core task (Sterling and Laughlin, 2015): to efficiently ensure resources for physiological systems within an animal’s body (i.e. its internal milieu) so that an animal can grow, survive and reproduce.”
From The theory of constructed emotion: an active inference account of interoception and categorization (2016) · cites this paper as Sterling and Laughlin, 2015
In the citing paper
“‘efficiency’ requires the ability to anticipate the body’s needs and satisfy them before they arise”
From The theory of constructed emotion: an active inference account of interoception and categorization (2016) · cites this paper as Sterling and Laughlin, 2015
In the citing paper
“A brain can be thought of as running an internal model that controls central pattern generators in the service of allostasis (for more on pattern generators, see Burrows, 1996; Sterling and Laughlin, 2015; Swanson, 2000).”
From The theory of constructed emotion: an active inference account of interoception and categorization (2016) · cites this paper as Sterling and Laughlin, 2015
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Cited by
Sorted by citations
The theory of constructed emotion: an active inference account of interoception and categorization
Barrett, L. F. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw154 · Cited by 1,426
“All brains accomplish the same core task (Sterling and Laughlin, 2015): to efficiently ensure resources for physiological systems within an animal’s body (i.”
InfluentialA Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster
Zheng, Z., Lauritzen, J. S., Perlman, E., Robinson, C. G., Nichols, M., Milkie, D., Torrens, O., Price, J., Fisher, C. B., Sharifi, N., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.019 · Cited by 1,050
“Maps of connectivity inform and constrain all models of how neuronal circuits transform information and subserve behavior (Braitenberg and Schüz, 1998; Marr, 1969; Sterling and Laughlin, 2015).”
BackgroundThe theory of constructed emotion: an active inference account of interoception and categorization
Barrett, L. F. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx060 · Cited by 1,009
“All brains accomplish the same core task (Sterling and Laughlin, 2015): to efficiently ensure resources for physiological systems within an animal’s body (i.”
InfluentialLieder, F., & Griffiths, T. L. (2020) · Behavioral and Brain Sciences · doi:10.1017/s0140525x1900061x · Cited by 892
Evidence for a large-scale brain system supporting allostasis and interoception in humans
Kleckner, I. R., Zhang, J., Touroutoglou, A., Chanes, L., Xia, C., Simmons, W. K., Quigley, K. S., Dickerson, B. C., & Feldman Barrett, L. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0069 · Cited by 641
“This process is called allostasis 20–22 .”
Influential
Metadata
- Authors
- Sterling, P., & Laughlin, S.
- Affiliations
- Australian National University (AU)
- Venue
- The MIT Press eBooks
- Publisher
- The MIT Press
- Published
- 2015-05-22
- OpenAlex
- W4301042878
- Cited by
- 482
- References
- 630
- Citations by year
- 2026: 40 · 2025: 58 · 2024: 61 · 2023: 59 · 2022: 51 · 2021: 40 · 2020: 50 · 2019: 32 · 2018: 33 · 2017: 33 · 2016: 20 · 2015: 5
- FWCI
- 17.23
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- The MIT Press eBooks (publishedVersion)
- Project Muse (Johns Hopkins University) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- brain evolution, computational neuroscience, anticipatory regulation, phototransduction, neural efficiency
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