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Modulation of Spike-Timing Dependent Plasticity: Towards the Inclusion of a Third Factor in Computational Models

Overview of attention for article published in Frontiers in Computational Neuroscience, July 2018
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

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Title
Modulation of Spike-Timing Dependent Plasticity: Towards the Inclusion of a Third Factor in Computational Models
Published in
Frontiers in Computational Neuroscience, July 2018
DOI 10.3389/fncom.2018.00049
Pubmed ID
Authors

Alexandre Foncelle, Alexandre Mendes, Joanna Jędrzejewska-Szmek, Silvana Valtcheva, Hugues Berry, Kim T. Blackwell, Laurent Venance

Abstract

In spike-timing dependent plasticity (STDP) change in synaptic strength depends on the timing of pre- vs. postsynaptic spiking activity. Since STDP is in compliance with Hebb's postulate, it is considered one of the major mechanisms of memory storage and recall. STDP comprises a system of two coincidence detectors with N-methyl-D-aspartate receptor (NMDAR) activation often posited as one of the main components. Numerous studies have unveiled a third component of this coincidence detection system, namely neuromodulation and glia activity shaping STDP. Even though dopaminergic control of STDP has most often been reported, acetylcholine, noradrenaline, nitric oxide (NO), brain-derived neurotrophic factor (BDNF) or gamma-aminobutyric acid (GABA) also has been shown to effectively modulate STDP. Furthermore, it has been demonstrated that astrocytes, via the release or uptake of glutamate, gate STDP expression. At the most fundamental level, the timing properties of STDP are expected to depend on the spatiotemporal dynamics of the underlying signaling pathways. However in most cases, due to technical limitations experiments grant only indirect access to these pathways. Computational models carefully constrained by experiments, allow for a better qualitative understanding of the molecular basis of STDP and its regulation by neuromodulators. Recently, computational models of calcium dynamics and signaling pathway molecules have started to explore STDP emergence in ex and in vivo-like conditions. These models are expected to reproduce better at least part of the complex modulation of STDP as an emergent property of the underlying molecular pathways. Elucidation of the mechanisms underlying STDP modulation and its consequences on network dynamics is of critical importance and will allow better understanding of the major mechanisms of memory storage and recall both in health and disease.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 117 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 20%
Researcher 23 20%
Student > Master 12 10%
Student > Bachelor 9 8%
Student > Doctoral Student 7 6%
Other 19 16%
Unknown 24 21%
Readers by discipline Count As %
Neuroscience 38 32%
Agricultural and Biological Sciences 14 12%
Engineering 10 9%
Computer Science 7 6%
Psychology 4 3%
Other 15 13%
Unknown 29 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 October 2023.
All research outputs
#13,957,880
of 24,689,476 outputs
Outputs from Frontiers in Computational Neuroscience
#483
of 1,422 outputs
Outputs of similar age
#160,668
of 333,158 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#17
of 33 outputs
Altmetric has tracked 24,689,476 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,422 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has gotten more attention than average, scoring higher than 64% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 333,158 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.