CoChat
Sign Up
Cited by 1,757Neural dynamics and brain functionNeural Networks and ApplicationsMemory and Neural Mechanisms

The Computational Brain

Churchland, Patricia S., Sejnowski, Terrence J.·1992·The MIT Press eBooks
DOI 10.7551/mitpress/2010.001.0001
Open this paper in CoChat — free account

Abstract

Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. How do groups of neurons interact to enable the organism to see, decide, and move appropriately? What are the principles whereby networks of neurons represent and compute? These are the central questions probed by The Computational Brain. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework. Computer models constrained by neurobiological data can help reveal how—networks of neurons subserve perception and behavior—bow their physical interactions can yield global results in perception and behavior, and how their physical properties are used to code information and compute solutions. The Computational Brain focuses mainly on three domains: visual perception, learning and memory, and sensorimotor integration. Examples of recent computer models in these domains are discussed in detail, highlighting strengths and weaknesses, and extracting principles applicable to other domains. Churchland and Sejnowski show how both abstract models and neurobiologically realistic models can have useful roles in computational neuroscience, and they predict the coevolution of models and experiments at many levels of organization, from the neuron to the system. The Computational Brain addresses a broad audience: neuroscientists, computer scientists, cognitive scientists, and philosophers. It is written for both the expert and novice. A basic overview of neuroscience and computational theory is provided, followed by a study of some of the most recent and sophisticated modeling work in the context of relevant neurobiological research. Technical terms are clearly explained in the text, and definitions are provided in an extensive glossary. The appendix contains a précis of neurobiological techniques. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. Bradford Books imprint

Integrity signals

Registry

Crossref · 10.7551/mitpress/2010.001.0001

Cites

34 of 34 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • In response to incoming signals from a set of N pre-synaptic units, formal neurons exhibit sudden activation if the weighted sum of inputs surpasses a threshold.

    “In response to incoming signals from a set of N pre-synaptic units, formal neurons exhibit sudden activation if the weighted sum of inputs surpasses a threshold [253,254].”

    From Fundamental constraints to the logic of living systems (2024) · cites this paper as [253]

  • This kind of columnar organization is typical in biology.

    “This kind of columnar organization is typical in biology [38],[39].”

    From Towards a mathematical theory of cortical micro-circuits (2009) · cites this paper as [39]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Churchland, P. S., & Sejnowski, T. J.
Affiliations
University of California San Diego (US)
ORCID
Churchland, Patricia S.
Venue
The MIT Press eBooks
Publisher
The MIT Press
Published
1992-06-12
DOI
10.7551/mitpress/2010.001.0001
OpenAlex
W1589549454
Cited by
1,757
References
33
Citations by year
2026: 16 · 2025: 25 · 2024: 36 · 2023: 27 · 2022: 19 · 2021: 31 · 2020: 39 · 2019: 51 · 2018: 44 · 2017: 40 · 2016: 39 · 2015: 21 · 2014: 37 · 2013: 68 · 2012: 61
FWCI
12.21
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 › Cognitive Neuroscience › Memory and Neural Mechanisms
Keywords
population coding, neural population activity, artificial neural networks, computational neuroscience, neural coding, single-unit recording, brain function, neural network model

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review