Correlation-based Plasticity
Correlation-Based Plasticity is a theoretical framework within Hebbian plasticity that posits synaptic strength changes as a function of the statistical correlation between pre- and postsynaptic neural activities, distinguishing itself from other plasticity models by emphasizing covariance-driven learning rules over temporally precise spike-order dependence.
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4.3K
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162
Authors
101
Institutions
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2017–2026
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The Role of Constraints in Hebbian Learning
Kenneth D. Miller, David Mackay · Neural Computation · 1994 · 477 citations
Learning Input Correlations through Nonlinear Temporally Asymmetric Hebbian Plasticity
Robert Gütig, R. Aharonov, Stefan Rotter et al. · Journal of Neuroscience · 2003 · 414 citations · Full text
Tobias Bonhoeffer, V Staiger, Ad Aertsen · Proceedings of the National Academy of Sciences · 1989 · 220 citations · Full text
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Bernstein Center for Computational Neuroscience Göttingen
Göttingen, Germany
3 h-index
5 publications
110 citations

University of Freiburg
Freiburg im Breisgau, Germany
3 h-index
5 publications
973 citations

Brandeis University
Waltham, United States
3 h-index
5 publications
1.6K citations

The University of Melbourne
Melbourne, Australia
2 h-index
6 publications
364 citations
Bionics Institute
East Melbourne, Australia
2 h-index
6 publications
278 citations

University of Göttingen
Göttingen, Germany
2 h-index
4 publications
74 citations

SIB Swiss Institute of Bioinformatics
Lausanne, Switzerland
2 h-index
4 publications
246 citations

McGill University
Montreal, Canada
2 h-index
2 publications
33 citations
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6 publications · 700 citations
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4 publications · 196 citations
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3 publications · 109 citations
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3 publications · 1.2K citations
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3 publications · 68 citations
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