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Mendeley readers
Attention Score in Context
| Title |
Homeostatic role of heterosynaptic plasticity: models and experiments
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, July 2015
|
| DOI | 10.3389/fncom.2015.00089 |
| Pubmed ID | |
| Authors |
Marina Chistiakova, Nicholas M. Bannon, Jen-Yung Chen, Maxim Bazhenov, Maxim Volgushev |
| Abstract |
Homosynaptic Hebbian-type plasticity provides a cellular mechanism of learning and refinement of connectivity during development in a variety of biological systems. In this review we argue that a complimentary form of plasticity-heterosynaptic plasticity-represents a necessary cellular component for homeostatic regulation of synaptic weights and neuronal activity. The required properties of a homeostatic mechanism which acutely constrains the runaway dynamics imposed by Hebbian associative plasticity have been well-articulated by theoretical and modeling studies. Such mechanism(s) should robustly support the stability of operation of neuronal networks and synaptic competition, include changes at non-active synapses, and operate on a similar time scale to Hebbian-type plasticity. The experimentally observed properties of heterosynaptic plasticity have introduced it as a strong candidate to fulfill this homeostatic role. Subsequent modeling studies which incorporate heterosynaptic plasticity into model neurons with Hebbian synapses (utilizing an STDP learning rule) have confirmed its ability to robustly provide stability and competition. In contrast, properties of homeostatic synaptic scaling, which is triggered by extreme and long lasting (hours and days) changes of neuronal activity, do not fit two crucial requirements for a hypothetical homeostatic mechanism needed to provide stability of operation in the face of on-going synaptic changes driven by Hebbian-type learning rules. Both the trigger and the time scale of homeostatic synaptic scaling are fundamentally different from those of the Hebbian-type plasticity. We conclude that heterosynaptic plasticity, which is triggered by the same episodes of strong postsynaptic activity and operates on the same time scale as Hebbian-type associative plasticity, is ideally suited to serve a homeostatic role during on-going synaptic plasticity. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 158 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 6 | 4% |
| Portugal | 2 | 1% |
| Chile | 1 | <1% |
| France | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 147 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 50 | 32% |
| Researcher | 31 | 20% |
| Student > Master | 25 | 16% |
| Student > Doctoral Student | 12 | 8% |
| Student > Bachelor | 9 | 6% |
| Other | 14 | 9% |
| Unknown | 17 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 54 | 34% |
| Agricultural and Biological Sciences | 38 | 24% |
| Computer Science | 11 | 7% |
| Engineering | 11 | 7% |
| Medicine and Dentistry | 7 | 4% |
| Other | 18 | 11% |
| Unknown | 19 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 29 July 2015.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from Frontiers in Computational Neuroscience
#919
of 1,463 outputs
Outputs of similar age
#164,721
of 276,107 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#36
of 47 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,463 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 276,107 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.