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

Multiplicative contexts in associative memories

E Mizraji1, A Pomi, F Alvarez

  • 1Sección Biofisica, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay.

Bio Systems
|January 1, 1994
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

(R)-Mandelonitrile Lyase, a Homolog of Pru du 10, Is a Major Peach Allergen.

Journal of investigational allergology & clinical immunology·2025
Same author

Comparative Passivation of Si(100) by H<sub>2</sub> and D<sub>2</sub> Atmospheres under Simultaneous Xe<sup>+</sup> Bombardment: An X-ray Photoelectron Spectroscopy Analysis.

Langmuir : the ACS journal of surfaces and colloids·2024
Same author

Prelacrimal window approach to the maxillary sinus: a systematic review and meta-analysis of the literature.

Rhinology·2024
Same author

The effects of gestational age on neonatal cholestasis: A retrospective cohort study.

Journal of neonatal-perinatal medicine·2024
Same author

R-mandelonitrile-lyase, homolog to Pru d 10, is a major peach allergen in peach allergic Spanish population.

Journal of investigational allergology & clinical immunology·2024
Same author

Corrigendum to "Menstrual cycle and exogenous attention toward emotional expressions" [Horm. Behav. 146 (2022) 105259].

Hormones and behavior·2023
Same journal

Ruliological Resilience: Pattern Restoration and Robustness in Wolfram Patterns. A Basis for Regeneration, Not Just in Cone Shells?

Bio Systems·2026
Same journal

The Quantum-to-Classical Transducer: A Thermodynamic and Quantum Mechanical Framework for the Emergence of Bioenergetics.

Bio Systems·2026
Same journal

Forward-backward gene expression binarization for boolean state inference over a known regulatory network.

Bio Systems·2026
Same journal

Partial-label metric ceilings for evaluating gene regulatory networks inferred from single-cell foundation models.

Bio Systems·2026
Same journal

The impedance mismatch theory: A non-equilibrium thermodynamic framework for a shared energetic stress pathway in neurodegeneration.

Bio Systems·2026
Same journal

Immune signal-status misclassification: A theoretical framework for biological status assignment and failed status resolution.

Bio Systems·2026
See all related articles

This study shows that large-scale neural networks can tolerate significant connection loss while maintaining associative memory function. This resilience is crucial for understanding biological memory and developing robust artificial systems.

Area of Science:

  • Computational Neuroscience
  • Artificial Intelligence
  • Network Science

Background:

  • The brain's neural connections have local imprecision.
  • Multiplicative devices are explored as biological plausibility models.
  • Context-dependent associative memory systems are investigated.

Purpose of the Study:

  • To evaluate the performance of a context-dependent memory with incomplete connectivity in its multiplicative network.
  • To analyze the robustness of Kronecker product-based associative memory models.
  • To understand the relationship between network dimensionality, connectivity, and memory capacity.

Main Methods:

  • Simulating a two-net system: one for Kronecker product, one for correlation memory.
  • Analyzing memory performance under varying degrees of incomplete connectivity.

Related Experiment Videos

  • Establishing scaling relationships between incompleteness, memory capacity, and output tolerance.
  • Investigating network functions like novelty filtering and logical computation.

    • Main Results:

    • Large-dimensional systems exhibit considerable tolerance to incomplete connectivity.
    • A scaling relationship was found between incompleteness, memory capacity, and tolerance.
    • The network demonstrated versatility in performing various functions.

    Conclusions:

    • Context-dependent associative memory systems are robust to significant neural connection imprecision.
    • These models offer plausible biological mechanisms for memory and information processing.
    • The findings support the potential of multiplicative networks in artificial intelligence and neuroscience.