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Upward synaptic scaling is dependent on neurotransmission rather than spiking.

ABSTRACT: Homeostatic plasticity encompasses a set of mechanisms that are thought to stabilize firing rates in neural circuits. The most widely studied form of homeostatic plasticity is upward synaptic scaling (upscaling), characterized by a multiplicative increase in the strength of excitatory synaptic inputs to a neuron as a compensatory response to chronic reductions in firing rate. While reduced spiking is thought to trigger upscaling, an alternative possibility is that reduced glutamatergic transmission generates this plasticity directly. However, spiking and neurotransmission are tightly coupled, so it has been difficult to determine their independent roles in the scaling process. Here we combined chronic multielectrode recording, closed-loop optogenetic stimulation, and pharmacology to show that reduced glutamatergic transmission directly triggers cell-wide synaptic upscaling. This work highlights the importance of synaptic activity in initiating signalling cascades that mediate upscaling. Moreover, our findings challenge the prevailing view that upscaling functions to homeostatically stabilize firing rates.

SUBMITTER: Fong MF

PROVIDER: S-EPMC4355957 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Upward synaptic scaling is dependent on neurotransmission rather than spiking.

Fong Ming-fai MF Newman Jonathan P JP Potter Steve M SM Wenner Peter P

Nature communications 20150309

Homeostatic plasticity encompasses a set of mechanisms that are thought to stabilize firing rates in neural circuits. The most widely studied form of homeostatic plasticity is upward synaptic scaling (upscaling), characterized by a multiplicative increase in the strength of excitatory synaptic inputs to a neuron as a compensatory response to chronic reductions in firing rate. While reduced spiking is thought to trigger upscaling, an alternative possibility is that reduced glutamatergic transmiss ...[more]

PMID: 25751516

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Project description:Neuronal communication is tightly regulated in time and space. Following neuronal activation, an electrical signal triggers neurotransmitter (NT) release at the active zone. The process starts by the signal reaching the synapse followed by a fusion of the synaptic vesicle (SV) and diffusion of the released NT in the synaptic cleft. The NT then binds to the appropriate receptor and induces a membrane potential change at the target cell membrane. The entire process is controlled by a fairly small set of synaptic proteins, collectively called SYCONs. The biochemical features of SYCONs underlie the properties of NT release. SYCONs are characterized by their ability to detect and respond to changes in environmental signals. For example, consider synaptotagmin I (Syt1), a prototype of a protein family with over 20 gene and variants in mammals. Syt1 is a specific example of a multi-sensor device with a large repertoire of discrete states. Several of these states are stimulated by a local concentration of signaling molecules such as Ca2+. The ability of this protein to sense signaling molecules and to adopt multiple biochemical states is shared by other SYCONs such as the synapsins (Syns). Specific biochemical states of Syns determine the accessibility of SV for NT release. Each of these states is defined by a specific alternative spliced variant with a unique profile of phosphorylation modified sites. The plasticity of the synapse is a direct reflection of SYCON's multiple biochemical states. State transitions occurs in a wide range of time scales, and therefore these molecules need to cope with events that last milliseconds (i.e., exocytosis in fast responding synapses) and with events that can carry on for many minutes (i.e., organization of SV pools). We suggest that SYCONs are optimized throughout evolution as multi-sensor devices. A full repertoire of the switches leading to alternation of protein states and a detailed characterization of protein-protein network within the synapse is critical for the development of a dynamic model of synaptic transmission.

Dataset Information

Upward synaptic scaling is dependent on neurotransmission rather than spiking.

Publications

Upward synaptic scaling is dependent on neurotransmission rather than spiking.

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