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dc.contributor.authorKim, Jimok
dc.contributor.authorTsien, Richard W.
dc.contributor.authorAlger, Bradley E.
dc.date.accessioned2012-10-26T20:30:45Z
dc.date.available2012-10-26T20:30:45Z
dc.date.issued2012-05-17en_US
dc.identifier.citationPLoS One. 2012 May 17; 7(5):e37364en_US
dc.identifier.issn1932-6203en_US
dc.identifier.pmid22615990en_US
dc.identifier.doi10.1371/journal.pone.0037364en_US
dc.identifier.urihttp://hdl.handle.net/10675.2/791
dc.description.abstractHomeostatic scaling of synaptic strengths is essential for maintenance of network "gain", but also poses a risk of losing the distinctions among relative synaptic weights, which are possibly cellular correlates of memory storage. Multiplicative scaling of all synapses has been proposed as a mechanism that would preserve the relative weights among them, because they would all be proportionately adjusted. It is crucial for this hypothesis that all synapses be affected identically, but whether or not this actually occurs is difficult to determine directly. Mathematical tests for multiplicative synaptic scaling are presently carried out on distributions of miniature synaptic current amplitudes, but the accuracy of the test procedure has not been fully validated. We now show that the existence of an amplitude threshold for empirical detection of miniature synaptic currents limits the use of the most common method for detecting multiplicative changes. Our new method circumvents the problem by discarding the potentially distorting subthreshold values after computational scaling. This new method should be useful in assessing the underlying neurophysiological nature of a homeostatic synaptic scaling transformation, and therefore in evaluating its functional significance.
dc.rightsKim et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.subjectResearch Articleen_US
dc.subjectBiologyen_US
dc.subjectAnatomy and Physiologyen_US
dc.subjectNeurological Systemen_US
dc.subjectSynapsesen_US
dc.subjectNeuroscienceen_US
dc.subjectNeurophysiologyen_US
dc.subjectCentral Nervous Systemen_US
dc.subjectHomeostatic Mechanismsen_US
dc.subjectSynapsesen_US
dc.subjectNeural Networksen_US
dc.subjectMedicineen_US
dc.subjectAnatomy and Physiologyen_US
dc.subjectNeurological Systemen_US
dc.subjectSynapsesen_US
dc.titleAn Improved Test for Detecting Multiplicative Homeostatic Synaptic Scalingen_US
dc.typeArticleen_US
dc.identifier.pmcidPMC3355135en_US
dc.contributor.corporatenameInstitute of Molecular Medicine and Genetics
dc.contributor.corporatenameGraduate Program in Neuroscience
dc.contributor.corporatenameDepartment of Neurology
refterms.dateFOA2019-04-10T00:51:15Z
html.description.abstractHomeostatic scaling of synaptic strengths is essential for maintenance of network "gain", but also poses a risk of losing the distinctions among relative synaptic weights, which are possibly cellular correlates of memory storage. Multiplicative scaling of all synapses has been proposed as a mechanism that would preserve the relative weights among them, because they would all be proportionately adjusted. It is crucial for this hypothesis that all synapses be affected identically, but whether or not this actually occurs is difficult to determine directly. Mathematical tests for multiplicative synaptic scaling are presently carried out on distributions of miniature synaptic current amplitudes, but the accuracy of the test procedure has not been fully validated. We now show that the existence of an amplitude threshold for empirical detection of miniature synaptic currents limits the use of the most common method for detecting multiplicative changes. Our new method circumvents the problem by discarding the potentially distorting subthreshold values after computational scaling. This new method should be useful in assessing the underlying neurophysiological nature of a homeostatic synaptic scaling transformation, and therefore in evaluating its functional significance.


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