Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Dynamic representations and generative models of brain function.

K J Friston1, C J Price

  • 1The Wellcome Department of Cognitive Neurology, Institute of Neurology, London, United Kingdom.

Brain Research Bulletin
|April 5, 2001
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Generalised random tessellation stratified sampling over auxiliary spaces.

Journal of applied statistics·2025
Same author

Topographic Variation in Human Neurotransmitter Receptor Densities Explains Differences in Intracranial EEG Spectra.

Human brain mapping·2025
Same author

Canalization and plasticity in psychopathology.

Neuropharmacology·2022
Same author

REBUS and the Anarchic Brain: Toward a Unified Model of the Brain Action of Psychedelics.

Pharmacological reviews·2019
Same author

A validation of dynamic causal modelling for 7T fMRI.

Journal of neuroscience methods·2018
Same author

Neurophysiologically-informed markers of individual variability and pharmacological manipulation of human cortical gamma.

NeuroImage·2017
Same journal

Corrigendum to "Peripheral to central: Exploring the neural, endocrine, and immune pathways of the gut-brain axis in postoperative neurocognitive dysfunction" [Brain Res. Bull. 242 (2026) 111975].

Brain research bulletin·2026
Same journal

GLUT1-driven glycolytic reprogramming in microglia promotes neuroinflammation and cognitive deficits in sepsis-associated encephalopathy.

Brain research bulletin·2026
Same journal

Spinal astrocytes hardly proliferate following peripheral nerve injury: Evidence from adult Aldh1l1-GFP reporter mice.

Brain research bulletin·2026
Same journal

Shared Neural Mechanisms of Trait Mindfulness and Hypnotic Susceptibility: A Scoping Review Toward a Unifying Predictive Coding Framework.

Brain research bulletin·2026
Same journal

Cerebellar gray matter volume alterations and metabolic associations stratified by disease duration in patients with type 2 diabetes.

Brain research bulletin·2026
Same journal

Research progress of depression and pain comorbidity: Animal model, mechanism, treatment strategy.

Brain research bulletin·2026
See all related articles

Brain region function is not fixed but dynamically adapts based on context and interactions, particularly top-down connections. Generative models offer a more accurate framework for understanding neural specialization and representation construction in the brain.

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • Classical models of brain function often assume fixed specialization of neurons and cortical areas.
  • These models, including classical receptive fields and connectionism, may provide incomplete explanations of real brain architectures.

Purpose of the Study:

  • To propose that neuronal and cortical area function is dynamic and context-sensitive, challenging traditional views.
  • To introduce generative models as a more plausible framework for understanding brain function and neural representation.

Main Methods:

  • The study utilizes a theoretical approach based on generative models of functional brain architectures.
  • It emphasizes the role of functional integration, particularly top-down connections, in mediating adaptive specialization.

Related Experiment Videos

  • Explains how generative models resolve prediction errors between higher and lower brain systems.

    • Main Results:

    • Neuronal responses in any cortical area can represent different information depending on the context.
    • Specialization of a brain region is determined by both bottom-up inputs and top-down predictions, not intrinsic properties.
    • Top-down connections from higher-level areas modulate the selectivity of lower-level areas based on contextual information.

    Conclusions:

    • The dynamic and context-sensitive nature of neural specialization challenges classical models in neuroscience and cognitive science.
    • Generative models provide a more comprehensive framework for understanding how the brain constructs representations and achieves selective neurophysiological responses.
    • Functional specialization is a result of interactions and context, not an inherent property of brain regions.