An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing

Senn, Walter; Markram, Henry; Tsodyks, Misha (2001). An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing. Neural computation, 13(1), pp. 35-67. MIT Press 10.1162/089976601300014628

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The precise times of occurrence of individual pre- and postsynaptic action potentials are known to play a key role in the modification of synaptic efficacy. Based on stimulation protocols of two synaptically connected neurons, we infer an algorithm that reproduces the experimental data by modifying the probability of vesicle discharge as a function of the relative timing of spikes in the pre- and postsynaptic neurons. The primary feature of this algorithm is an asymmetry with respect to the direction of synaptic modification depending on whether the presynaptic spikes precede or follow the postsynaptic spike. Specifically, if the presynaptic spike occurs up to 50 ms before the postsynaptic spike, the probability of vesicle discharge is upregulated, while the probability of vesicle discharge is downregulated if the presynaptic spike occurs up to 50 ms after the postsynaptic spike. When neurons fire irregularly with Poisson spike trains at constant mean firing rates, the probability of vesicle discharge converges toward a characteristic value determined by the preand postsynaptic firing rates. On the other hand, if the mean rates of the Poisson spike trains slowly change with time, our algorithm predicts modifications in the probability of release that generalize Hebbian and Bienenstock-Cooper-Munro rules. We conclude that the proposed spike- based synaptic learning algorithm provides a general framework for regulating neurotransmitter release probability.

Item Type:	Journal Article (Original Article)
Division/Institute:	04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Physiology
UniBE Contributor:	Senn, Walter
Subjects:	600 Technology > 610 Medicine & health
ISSN:	0899-7667
Publisher:	MIT Press
Language:	English
Submitter:	Virginie Sabado
Date Deposited:	18 Jan 2023 15:29
Last Modified:	18 Jan 2023 23:28
Publisher DOI:	10.1162/089976601300014628
PubMed ID:	11177427
URI:	https://boris.unibe.ch/id/eprint/177231