Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2019 Dec 3:13:520.
doi: 10.3389/fncel.2019.00520. eCollection 2019.

Mechanisms of Homeostatic Synaptic Plasticity in vivo

Hey-Kyoung Lee  1   2 , Alfredo Kirkwood  1
Affiliations
Review

Mechanisms of Homeostatic Synaptic Plasticity in vivo

Hey-Kyoung Lee et al. Front Cell Neurosci. .

Abstract

Synapses undergo rapid activity-dependent plasticity to store information, which when left uncompensated can lead to destabilization of neural function. It has been well documented that homeostatic changes, which operate at a slower time scale, are required to maintain stability of neural networks. While there are many mechanisms that can endow homeostatic control, sliding threshold and synaptic scaling are unique in that they operate by providing homeostatic control of synaptic strength. The former mechanism operates by adjusting the threshold for synaptic plasticity, while the latter mechanism directly alters the gain of synapses. Both modes of homeostatic synaptic plasticity have been studied across various preparations from reduced in vitro systems, such as neuronal cultures, to in vivo intact circuitry. While most of the cellular and molecular mechanisms of homeostatic synaptic plasticity have been worked out using reduced preparations, there are unique challenges present in intact circuitry in vivo, which deserve further consideration. For example, in an intact circuit, neurons receive distinct set of inputs across their dendritic tree which carry unique information. Homeostatic synaptic plasticity in vivo needs to operate without compromising processing of these distinct set of inputs to preserve information processing while maintaining network stability. In this mini review, we will summarize unique features of in vivo homeostatic synaptic plasticity, and discuss how sliding threshold and synaptic scaling may act across different activity regimes to provide homeostasis.

Keywords: BCM theory; cortical plasticity; hebbian plasticity; homeostasis; metaplasticity; sliding threshold; synaptic scaling.

PubMed Disclaimer

Figures

FIGURE 1
FIGURE 1
Different models of homeostatic synaptic plasticity comparison of sliding threshold model (A,B) and synaptic scaling (C). Sliding threshold model posits that the synaptic modification threshold (θM) changes as a function of past activity of a neuron. When integrated past activity is high θM slides up to a higher value (θM’) promoting LTD, while with lower overall activity θM slides down to a lower value (θM”) to preferential induce LTP. Expression of LTP or LTD as a consequence of sliding θM acts to provide homeostasis of the average neural activity. θM can slide via a horizontal shift (A), which is implemented by altering the induction mechanisms of LTP/LTD such as regulation of GluN2B-containing NMDARs. θM can also slide by a vertical shift (B), which is mediated by changes in the expression mechanisms of LTP/LTD such as alteration in AMPAR phosphorylation state. Synaptic scaling was initially reported to occur globally across all synapses. A key feature that allows preservation of information stored at individual synapses despite global adjustment of synaptic weights is via multiplicative scaling (C). Individual synaptic weights (a1…ax) are multiplied by a same scaling factor (f), which is greater than 1 for adapting to inactivity and less than 1 for adaptation to increased activity.
FIGURE 2
FIGURE 2
Input-specific homeostatic synaptic plasticity and distinct activity regime. There are specific considerations needed when implementing homeostatic regulation in intact circuits in vivo, such as a need to provide homeostasis in an input-specific manner. Sliding threshold model can easily accomplish input-specificity as depicted in panel (A). When overall activity of a neuron is reduced, such as due to loss of its major input, θM slides down. This causes previously weak Input 2 to cross the LTP threshold for synaptic potentiation, but leaves the less active input (Input 1) in the LTD range. Such input-specific adaptation allows the neuron to dynamically update its synaptic weights to process the most active input(s) in the context of its overall activity. We propose that sliding threshold and synaptic scaling operate across different activity regimes in vivo as shown in panel (B). Based on the advantage sliding threshold endows intact neural networks, such as always adapting to the most relevant inputs as shown in panel (A), we surmise that this is the dominant mode of homeostatic adaptation within most physiological range of activity. However, sliding threshold is less likely to be effect at providing homeostasis at extreme ranges of activity. For instance, when activity levels are too low, even if the θM slides, there will be insufficient activity to activate NMDARs to drive potentiation of synapses. We suggest that NMDAR-independent synaptic scaling will be more effective at providing homeostatic adaptation with inactivity. At the other extreme, synaptic scaling will be much more effective at dampening overactive circuits, because it can globally reduce the strength of synapses.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Barnes S. J., Franzoni E., Jacobsen R. I., Erdelyi F., Szabo G., Clopath C., et al. (2017). Deprivation-Induced homeostatic spine scaling in vivo is localized to dendritic branches that have undergone recent spine loss. Neuron 96 871–882.e5. 10.1016/j.neuron.2017.09.052 - DOI - PMC - PubMed
    1. Bear M. F., Cooper L. N., Ebner F. F. (1987). A physiological basis for a theory of synapse modification. Science 237 42–48. 10.1126/science.3037696 - DOI - PubMed
    1. Bender K. J., Allen C. B., Bender V. A., Feldman D. E. (2006). Synaptic basis for whisker deprivation-induced synaptic depression in rat somatosensory cortex. J. Neurosci. 26 4155–4165. 10.1523/jneurosci.0175-06.2006 - DOI - PMC - PubMed
    1. Bienenstock E. L., Cooper L. N., Munro P. W. (1982). Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex. J. Neurosci. 2 32–48. 10.1523/jneurosci.02-01-00032.1982 - DOI - PMC - PubMed
    1. Blais B. S., Frenkel M. Y., Kuindersma S. R., Muhammad R., Shouval H. Z., Cooper L. N., et al. (2008). Recovery from monocular deprivation using binocular deprivation. J. Neurophysiol. 100 2217–2224. 10.1152/jn.90411.2008 - DOI - PMC - PubMed