Multiple Forms of Short-Term Plasticity at Excitatory Synapses in Rat Medial Prefrontal Cortex

Hempel, Chris M.; Hartman, Kenichi H.; Wang, X.-J.; Turrigiano, Gina G.; Nelson, Sacha B.

doi:10.1152/jn.2000.83.5.3031

Cited by 202 publications

(172 citation statements)

References 48 publications

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“…Both short-and long-term synaptic plasticity can be induced in PFC networks in acute slices (19)(20)(21)(22)(23) and likely play an important role in PFC function. We first determined whether shortterm synaptic plasticity was impaired in the mPFC of the Dgcr8 +/− mice (WT: N = 7; n = 17; Dgcr8 +/− : N = 7; n = 17).…”

Section: Resultsmentioning

confidence: 99%

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Deficiency of Dgcr8 , a gene disrupted by the 22q11.2 microdeletion, results in altered short-term plasticity in the prefrontal cortex

Fénelon

Mukai

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

184

136

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Individuals with 22q11.2 microdeletions have cognitive and behavioral impairments and the highest known genetic risk for developing schizophrenia. One gene disrupted by the 22q11.2 microdeletion is DGCR8, a component of the "microprocessor" complex that is essential for microRNA production, resulting in abnormal processing of specific brain miRNAs and working memory deficits. Here, we determine the effect of Dgcr8 deficiency on the structure and function of cortical circuits by assessing their laminar organization, as well as the neuronal morphology, and intrinsic and synaptic properties of layer 5 pyramidal neurons in the prefrontal cortex of Dgcr8 +/− mutant mice. We found that heterozygous Dgcr8 mutant mice have slightly fewer cortical layer 2/4 neurons and that the basal dendrites of layer 5 pyramidal neurons have slightly smaller spines. In addition to the modest structural changes, field potential and whole-cell electrophysiological recordings performed in layer 5 of the prefrontal cortex revealed greater short-term synaptic depression during brief stimulation trains applied at 50 Hz to superficial cortical layers. This finding was accompanied by a decrease in the initial phase of synaptic potentiation. Our results identify altered short-term plasticity as a neural substrate underlying the cognitive dysfunction and the increased risk for schizophrenia associated with the 22q11.2 microdeletions.

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Section: Resultsmentioning

confidence: 99%

“…In L5 of the mPFC of rodents, trains of pulses at 50 Hz have previously been used to induce synaptic potentiation (19)(20)(21). Thus, we used field recordings to compare the level of potentiation induced by high-frequency stimulation in both mutant and WT mice (WT: N = 8, n = 12; Dgcr8 +/− : N = 7, n = 14).…”

Section: Resultsmentioning

confidence: 99%

Deficiency of Dgcr8 , a gene disrupted by the 22q11.2 microdeletion, results in altered short-term plasticity in the prefrontal cortex

Fénelon

Mukai

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

184

136

View full text Add to dashboard Cite

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“…This contradicts the statement 'it is unlikely that there exist mechanisms that support widespread structural changes and growth of new links within' hundreds of ms (Shastri and Aijanagadde 1993). There is biological evidence of STP based on short bursts of spikes that persist for seconds to minutes (Hempel et al 2000).…”

Section: Cr Huyckmentioning

confidence: 95%

“…However there is another type of learning, STP, and there is extensive evidence that STP occurs in biological neural systems (Buonomano 1999;Hempel, Hartman, Wang, Turrigiano, and Nelson 2000). It is still a type of Hebbian learning, based on the firing behaviour of the neurons a synapse connects, so that co-firing increases the synaptic weight.…”

Section: Binding Via Stpmentioning

confidence: 99%

Variable binding by synaptic strength change

Huyck

2009

Connection Science

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Copyright and moral rights to this thesis/research project are retained by the author and/or other copyright owners. The work is supplied on the understanding that any use for commercial gain is strictly forbidden. A copy may be downloaded for personal, non-commercial, research or study without prior permission and without charge. Any use of the thesis/research project for private study or research must be properly acknowledged with reference to the work's full bibliographic details.This thesis/research project may not be reproduced in any format or medium, or extensive quotations taken from it, or its content changed in any way, without first obtaining permission in writing from the copyright holder(s).If you believe that any material held in the repository infringes copyright law, please contact the Repository Team at Middlesex University via the following email address:eprints@mdx.ac.ukThe item will be removed from the repository while any claim is being investigated. Journal …Connection ScienceArticle ID … CCOS395590 Variable binding is a difficult problem for neural networks. Two new mechanisms for binding by synaptic change are presented, and in both, bindings are erased and can be reused. The first is based on the commonly used learning mechanism of permanent change of synaptic weight, and the second on synaptic change which decays. Both are biologically motivated models. Simulations of binding on a paired association task are shown with the first mechanism succeeding with a 97.5% F-Score, and the second performing perfectly.Further simulations show that binding by decaying synaptic change copes with cross talk, and can be used for compositional semantics. It can be inferred that binding by permanent change accounts for these, but it faces the stability plasticity dilemma. Two other existing binding mechanisms, synchrony and active links, are compatible with these new mechanisms. All four mechanisms are compared and integrated in a Cell Assembly theory.

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“…We adopted a model which describes STD as a presynaptic calcium dependent dynamic, in which the available vesicles decrease following each presynaptic spike and exponentially return to the baseline with a long time constant (Hempel et al 2000;Varela et al 1997;Abbott et al 1997). Specifically, the STD variable D is given by:…”

Section: Short-term Plasticitymentioning

confidence: 99%

A single-cell level and connectome-derived computational model of the Drosophila brain

Huang

Wang

et al. 2018

Preprint

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Computer simulations play an important role in testing hypotheses, integrating knowledge, and providing predictions of neural circuit functions. While considerable effort has been dedicated into simulating primate or rodent brains, the fruit fly (Drosophila melanogaster) is becoming a promising model animal in computational neuroscience for its small brain size, complex cognitive behavior, and abundancy of data available from genes to circuits.Moreover, several Drosophila connectome projects have generated a large number of neuronal images that account for a significant portion of the brain, making a systematic investigation of the whole brain circuit possible. Supported by FlyCircuit (http://www.flycircuit.tw), one of the largest Drosophila neuron image databases, we began a long-term project with the goal to construct a whole-brain spiking network model of the Drosophila brain. In this paper, we report the outcome of the first phase of the project. We developed the Flysim platform, which 1) identifies the polarity of each neuron arbor, 2) predicts connections between neurons, 3) translates morphology data from the database into physiology parameters for computational modeling, 4) reconstructs a brain-wide network model, which consists of 20,089 neurons and 1,044,020 synapses, and 5) performs computer simulations of the resting state. We compared the reconstructed brain network with a randomized brain network by shuffling the connections of each neuron. We found that the reconstructed brain can be easily stabilized by implementing synaptic short-term depression, while the randomized one exhibited seizure-like firing activity under the same treatment.Furthermore, the reconstructed Drosophila brain was structurally and dynamically more diverse than the randomized one and exhibited both Poisson-like and patterned firing activities. Despite being at its early stage of development, this single-cell level brain model allows us to study some of the fundamental properties of neural networks including network balance, critical behavior, long-term stability, and plasticity.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

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Multiple Forms of Short-Term Plasticity at Excitatory Synapses in Rat Medial Prefrontal Cortex

Cited by 202 publications

References 48 publications

Deficiency of Dgcr8 , a gene disrupted by the 22q11.2 microdeletion, results in altered short-term plasticity in the prefrontal cortex

Deficiency of Dgcr8 , a gene disrupted by the 22q11.2 microdeletion, results in altered short-term plasticity in the prefrontal cortex

Variable binding by synaptic strength change

A single-cell level and connectome-derived computational model of the Drosophila brain

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