Cited by 267Neural dynamics and brain functionNeuroscience and Neuropharmacology ResearchMemory and Neural Mechanisms

Coding of temporal information by activity-dependent synapses.

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Fuhrmann, Galit, Segev, Idan, Markram, Henry, Tsodyks, Misha·2002·Journal of Neurophysiology

Abstract

Synaptic transmission in the neocortex is dynamic, such that the magnitude of the postsynaptic response changes with the history of the presynaptic activity. Therefore each response carries information about the temporal structure of the preceding presynaptic input spike train. We quantitatively analyze the information about previous interspike intervals, contained in single responses of dynamic synapses, using methods from information theory applied to experimentally based deterministic and probabilistic phenomenological models of depressing and facilitating synapses. We show that for any given dynamic synapse, there exists an optimal frequency of presynaptic spike firing for which the information content is maximal; simple relations between this optimal frequency and the synaptic parameters are derived. Depressing neocortical synapses are optimized for coding temporal information at low firing rates of 0.5-5 Hz, typical to the spontaneous activity of cortical neurons, and carry significant information about the timing of up to four preceding presynaptic spikes. Facilitating synapses, however, are optimized to code information at higher presynaptic rates of 9-70 Hz and can represent the timing of over eight presynaptic spikes.

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Crossref · 10.1152/jn.00258.2001

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  • The role of synapses as processing units of the human brain is reinforced by the results of computational simulation, which indicate that the computational power of a network is increased using dynamic synapses.

    “The role of synapses as processing units of the human brain is reinforced by the results of computational simulation, which indicate that the computational power of a network is increased using dynamic synapses.”

    From Human Brain/Cloud Interface (2019) · cites this paper as Fuhrmann et al., 2002

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References 53 · Cited by 267

Authors
Fuhrmann, G., Segev, I., Markram, H., & Tsodyks, M.
Affiliations
  • Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100; and
  • Hebrew University of Jerusalem (IL)
  • Weizmann Institute of Science (IL)
Venue
Journal of Neurophysiology
Published
2002-01-01
Volume
87
Issue
1
Pages
140-148
ISSN
  • 0022-3077 (ISSN-L)
  • 1522-1598
OpenAlex
W1875306972
Cited by
267
References
53
Citations by year
2026: 5 · 2025: 12 · 2024: 13 · 2023: 5 · 2022: 16 · 2021: 10 · 2020: 4 · 2019: 19 · 2018: 12 · 2017: 11 · 2016: 13 · 2015: 10 · 2014: 13 · 2013: 12 · 2012: 10
FWCI
5.84
Type
journal article
Language
en
Open access
Locations
  • Journal of Neurophysiology (publishedVersion)
  • PubMed (publishedVersion)
  • Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
  • Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
Keywords
dynamic synapses, synaptic depression, synaptic facilitation, temporal coding, interspike intervals, spike timing, neocortex, information theory, spontaneous cortical activity
MeSH terms
Action Potentials, Animals, Computer Simulation, Information Theory, Models, Neurological, Synaptic Transmission, Synapses, Time Factors, Time Perception, Models, Statistical, Rats

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