Synonyms
Definition
The brain of humans and animals consists of a large number of interconnected neurons. Learning in biological neural systems is thought to take place by changes in the connections between these neurons. Since the contact points between two neurons are called synapses, the change in the connection strength is called synaptic plasticity. The mathematical description of synaptic plasticity is called a (biological) learning rule. Most of these biological learning rules can be categorized in the context of machine learning as unsupervised learning rules, and the remaining ones as reward-based or reinforcement learning. The Hebb rule is an example of an unsupervised correlation-based learning rule formulated on the level of neuronal firing rates. Spike-timing-dependent plasticity (STDP) is an unsupervised learning rule formulated on the level of spikes. Modulation of learning rates in a Hebb rule or STDP rule by a...
This is a preview of subscription content, log in via an institution to check access.
Recommended Reading
Bliss, T., & Gardner-Medwin, A. (1973). Long-lasting potentation of synaptic transmission in the dendate area of unanaesthetized rabbit following stimulation of the perforant path. The Journal of Physiology, 232, 357–374.
Bliss, T., Collingridge, G., & Morris, R. (2003). Long-term potentiation: Enhancing neuroscience for 30 years - introduction. Philosophical Transactions of the Royal Society of London. Series B : Biological Sciences, 358, 607–611.
Cooper, L., Intrator, N., Blais, B., & Shouval, H. Z. (2004). Theory of cortical plasticity. Singapore: World Scientific.
Dayan, P., & Abbott, L. F. (2001). Theoretical Neuroscience. Cambridge, MA: MIT Press.
Gerstner, W., & Kistler, W. K. (2002). Spiking neuron models. Cambridgess, UK: Cambridge University Press.
Gerstner, W., Kempter, R., van Hemmen, J. L., & Wagner, H. (1996). A neuronal learning rule for sub-millisecond temporal coding. Nature, 383, 76–78.
Hebb, D. O. (1949). The organization of behavior. New York: Wiley.
Lisman, J. (2003). Long-term potentiation: Outstanding questions and attempted synthesis. Philosophical Transactions of the Royal Society of London Series B, Biological Sciences, 358, 829–842.
Malenka, R. C., & Nicoll, R. A. (1999). Long-term potentiation–a decade of progress? Science, 285, 1870–1874.
Markram, H., Lübke, J., Frotscher, M., & Sakmann, B. (1997). Regulation of synaptic efficacy by coincidence of postysnaptic AP and EPSP. Science, 275, 213–215.
Schultz, W., Dayan, P., & Montague, R. (1997). A neural substrate for prediction and reward. Science, 275, 1593–1599.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media, LLC
About this entry
Cite this entry
Gerstner, W. (2011). Biological Learning: Synaptic Plasticity, Hebb Rule and Spike TimingDependent Plasticity. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_80
Download citation
DOI: https://doi.org/10.1007/978-0-387-30164-8_80
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-30768-8
Online ISBN: 978-0-387-30164-8
eBook Packages: Computer ScienceReference Module Computer Science and Engineering