Unraveling Mechanisms of Homeostatic Synaptic Plasticity

Pozo, Karine; Goda, Yukiko

doi:10.1016/j.neuron.2010.04.028

Cited by 489 publications

(461 citation statements)

References 176 publications

(279 reference statements)

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“…83,84 Long-term memory appears to involve a change in the brain at the level of the synapse called synaptic plasticity. [85][86][87][88][89] At the molecular level, several factors are known to contribute to synaptic plasticity, including changes in the quantity of neurotransmitters released into a synapse and the response of the postsynaptic neuron to those neurotransmitters. 87,[90][91][92][93] Long-term potentiation (LTP), one of several phenomena underlying synaptic plasticity, is widely considered to be one of the major cellular mechanisms involved in learning and memory.…”

Section: General Anesthetics and The Neural Substrates Of Memorymentioning

confidence: 99%

Inhibition of learning and memory by general anesthetics

Wang

Orser

2010

Can J Anesth/J Can Anesth

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Section: General Anesthetics and The Neural Substrates Of Memorymentioning

confidence: 99%

Inhibition of learning and memory by general anesthetics

Wang

Orser

2010

Can J Anesth/J Can Anesth

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“…synaptic scaling | synaptic plasticity | GRIP1 | AMPAR | GluA2 P roper development of neuronal circuits, as well as efficient information storage during learning and memory, are thought to depend upon the presence of homeostatic mechanisms that stabilize neuronal excitability (1)(2)(3). One such mechanism is synaptic scaling, which compensates for perturbations in average firing by scaling up or down the postsynaptic strength of all of a neuron's excitatory synapses (4).…”

mentioning

confidence: 99%

Activity-dependent synaptic GRIP1 accumulation drives synaptic scaling up in response to action potential blockade

Gainey

Tatavarty

Nahmani

et al. 2015

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

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Synaptic scaling is a form of homeostatic plasticity that stabilizes neuronal firing in response to changes in synapse number and strength. Scaling up in response to action-potential blockade is accomplished through increased synaptic accumulation of GluA2-containing AMPA receptors (AMPAR), but the receptor trafficking steps that drive this process remain largely obscure. Here, we show that the AMPAR-binding protein glutamate receptor-interacting protein-1 (GRIP1) is essential for regulated synaptic AMPAR accumulation during scaling up. Synaptic abundance of GRIP1 was enhanced by activity deprivation, directly increasing synaptic GRIP1 abundance through overexpression increased the amplitude of AMPA miniature excitatory postsynaptic currents (mEPSCs), and shRNA-mediated GRIP1 knockdown prevented scaling up of AMPA mEPSCs. Furthermore, knockdown and replace experiments targeting either GRIP1 or GluA2 revealed that scaling up requires the interaction between GRIP1 and GluA2. Finally, GRIP1 synaptic accumulation during scaling up did not require GluA2 binding. Taken together, our data support a model in which activity-dependent trafficking of GRIP1 to synaptic sites drives the forward trafficking and enhanced synaptic accumulation of GluA2-containing AMPAR during synaptic scaling up.P roper development of neuronal circuits, as well as efficient information storage during learning and memory, are thought to depend upon the presence of homeostatic mechanisms that stabilize neuronal excitability (1-3). One such mechanism is synaptic scaling, which compensates for perturbations in average firing by scaling up or down the postsynaptic strength of all of a neuron's excitatory synapses (4). Synaptic scaling is a cell-autonomous process in which neurons detect changes in their own firing through a set of calcium-dependent sensors that then regulate receptor trafficking to increase or decrease the accumulation of AMPA receptors (AMPAR) at synaptic sites and thus increase or decrease synaptic strength (4-6). Despite great recent interest, the AMPA receptor-trafficking events that underlie synaptic scaling remain largely obscure. Defects in synaptic scaling have been postulated to contribute to disorders as diverse as Alzheimer's disease (7) and epilepsy (8), so illuminating the underlying AMPAR trafficking steps could shed light into the genesis of a wide range of neurological disorders.Most neocortical AMPAR are heteromeric receptors composed of both GluA1 and GluA2 subunits, which have unique phosphorylation sites and interact with distinct trafficking proteins (9). During synaptic scaling up in response to action potential blockade, synaptic strength is increased through enhanced synaptic accumulation of GluA1 and GluA2-containing AMPAR (5, 10-13) and requires the C-terminal domain of the GluA2 subunit (12), but which subunit-specific interactions underlie synaptic scaling remain controversial (12,14). Several trafficking proteins are known to interact with the GluA2, but not the GluA1, C-tail, including glutamate recepto...

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“…Em outras palavras, independente da LTP ou LTD que tenham sofrido, neurônios devem ter um mecanismo de regulação global das sinapses, incrementando ou diminuindo sua excitabilidade como um todo, a fim de convergir para um ponto operacionalmente estável, o que ocorre numa escala de tempo de minutos ou horas [32], [34], [33].…”

Section: Plasticidade Celularunclassified

“…Há inúmeros trabalhos sobre mecanismos de plasticidade em geral, destacam-se aqui as revisões em [33], [39], [92] e [36]. O texto a seguir é baseado ainda nos trabalhos: [32], [34], [93], [94], [95], [96], [97].…”

Section: Plasticidade Celularunclassified

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Computação por assembleias neurais em redes neurais pulsadas.

Ribeiro¹

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Ribeiro, João Henrique RanhelComputação por assembléias neurais em redes neurais pulsadas / J.H.R. Ribeiro. therefore, here we simulate assembly computing using spiking neural networks. In this thesis it is presented basically a functional approach; thus, it presents a theoretical approach concerning the properties, principles, characteristics, and components that allow the computational operations in neural coalitions. It is presented in the thesis that: (i) as neurons form assemblies it is implicit that a kind of stochastic logic function occurs; (ii) assemblies may form groups that feedback each other, creating bistable groups; (iii) bistable groups internally represent the event that created them; (iv) assemblies may branch and dissolve other assemblies, what give rise to complex algorithms. This is an initial investigation about neural assembly computing and there is a lot to be done; however, in this thesis we present the basal concepts for this new approach. There are programs in the appendices that allow the reader to simulate assembly formation, branching, inhibition, reverberation, among other properties and components in our proposal.

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Unraveling Mechanisms of Homeostatic Synaptic Plasticity

Cited by 489 publications

References 176 publications

Inhibition of learning and memory by general anesthetics

Inhibition of learning and memory by general anesthetics

Activity-dependent synaptic GRIP1 accumulation drives synaptic scaling up in response to action potential blockade

Computação por assembleias neurais em redes neurais pulsadas.

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