Hebbian Theory

Hebbian theory is a neuroscientific theory claiming that an increase in synaptic efficacy arises from a presynaptic cell's repeated and persistent stimulation of a postsynaptic cell. Find the latest research on Hebbian theory here.

January 12, 2022
Preprint
Open Access

Hebbian activity-dependent plasticity in white matter

BioRxiv : the Preprint Server for Biology
Alberto LazariH. Johansen-Berg
December 10, 2021
Preprint

Where is Memory Information Stored in the Brain?

ArXiv
James Tee, Desmond P. Taylor
December 3, 2021

Unsupervised repetition enables rapid perceptual learning.

The Journal of the Acoustical Society of America
Vahid MontazeriPeter F Assmann
November 26, 2021
Open Access

Mapping Hebbian Learning Rules to Coupling Resistances for Oscillatory Neural Networks.

Frontiers in Neuroscience
Corentin Delacour, Aida Todri-Sanial
November 25, 2021

D1/D5 dopamine receptors and mGluR5 jointly enable non-Hebbian long-term potentiation at sensory synapses onto lamina I spinoparabrachial neurons.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
Jie LiMark L Baccei
November 11, 2021

Bridging the Functional and Wiring Properties of V1 Neurons Through Sparse Coding.

Neural Computation
Xiaolin Hu, Zhigang Zeng
November 1, 2021
Preprint

Deep neural networks as nested dynamical systems

ArXiv
David I. Spivak, Timothy Hosgood
October 30, 2021
Preprint
Open Access

Correcting the Hebbian Mistake: Toward a Fully Error-Driven Hippocampus

BioRxiv : the Preprint Server for Biology
Y. ZhengRandall C. O'Reilly
October 23, 2021
Open Access

Improved Visual Recognition Memory Model Based on Grid Cells for Face Recognition.

Frontiers in Neuroscience
Jie LiuXiao Zheng
October 11, 2021
Preprint

Can the brain use waves to solve planning problems?

ArXiv
Henry PowellHelmut Linde
September 11, 2021

Performance of biologically grounded models of the early visual system on standard object recognition tasks.

Neural Networks : the Official Journal of the International Neural Network Society
Michael TeichmannFred H Hamker
September 5, 2021
Preprint

Mechanisms for spontaneous symmetry breaking in developing visual cortex

ArXiv
Francesco FumarolaKenneth D. Miller
September 1, 2021
Open Access

Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions.

Evolutionary Computation
Anil YamanMykola Pechenizkiy
August 27, 2021

Hebbian semi-supervised learning in a sample efficiency setting.

Neural Networks : the Official Journal of the International Neural Network Society
Gabriele LaganiGiuseppe Amato
August 25, 2021
Preprint
Open Access

Stochastic Consolidation of Lifelong Memory

BioRxiv : the Preprint Server for Biology
N. ShahamHaim Sompolinsky
August 23, 2021
Open Access

Nonlinear Dendritic Coincidence Detection for Supervised Learning.

Frontiers in Computational Neuroscience
Fabian Schubert, Claudius Gros

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