Presynaptic Efficacy Directs Normalization of Synaptic Strength in Layer 2/3 Rat Neocortex After Paired Activity

Hardingham, Neil Robert; Hardingham, Giles E.; Fox, Kevin; Jack, J. J. B.

doi:10.1152/jn.01352.2006

Cited by 57 publications

(105 citation statements)

References 59 publications

(65 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar results at multiple synapses have also been observed using a variety of timingdependent learning rules (Debanne et al, 1999;Montgomery et al, 2001;Hardingham et al, 2007), and a number of explanations for this heterogeneity have been proposed. Timing-dependent Figure 7.…”

Section: Source Of Heterogeneous Plasticity and Metaplastic Model Of supporting

confidence: 72%

“…In the hippocampus and visual cortex, for example, the sign and magnitude of plasticity correlates with initial synaptic strength, with weaker synapses showing LTP and stronger synapses showing LTD (Bi and Poo, 1998;Montgomery et al, 2001;Hardingham et al, 2007). Accordingly, neural activity can dynamically gate the threshold for plasticity by regulating synaptic maturation.…”

Section: Source Of Heterogeneous Plasticity and Metaplastic Model Of mentioning

confidence: 99%

See 1 more Smart Citation

Retinocollicular Synapse Maturation and Plasticity Are Regulated by Correlated Retinal Waves

Shah¹,

Crair²

2008

J. Neurosci.

View full text Add to dashboard Cite

During development, spontaneous retinal waves are thought to provide an instructive signal for retinotopic map formation in the superior colliculus. In mice lacking the ␤2 subunit of nicotinic ACh receptors (␤2 Ϫ/Ϫ ), correlated retinal waves are absent during the first postnatal week, but return during the second postnatal week. In control retinocollicular synapses, in vitro analysis reveals that AMPA/ NMDA ratios and AMPA quantal amplitudes increase during the first postnatal week while the prevalence of silent synapses decreases. In age-matched ␤2 Ϫ/Ϫ mice, however, these parameters remain unchanged through the first postnatal week in the absence of retinal waves, but quickly mature to control levels by the end of the second week, suggesting that the delayed onset of correlated waves is able to drive synapse maturation. To examine whether such a mechanistic relationship exists, we applied a "burst-based" plasticity protocol that mimics coincident activity during retinal waves. We find that this pattern of activation is indeed capable of inducing synaptic strengthening [long-term potentiation (LTP)] on average across genotypes early in the first postnatal week [postnatal day 3 (P3) to P4] and, interestingly, that the capacity for LTP at the end of the first week (P6 -P7) is significantly greater in immature ␤2 Ϫ/Ϫ synapses than in mature control synapses. Together, our results suggest that retinal waves drive retinocollicular synapse maturation through a learning rule that is physiologically relevant to natural wave statistics and that these synaptic changes may serve an instructive role during retinotopic map refinement.

show abstract

Section: Source Of Heterogeneous Plasticity and Metaplastic Model Of supporting

confidence: 72%

Section: Source Of Heterogeneous Plasticity and Metaplastic Model Of mentioning

confidence: 99%

Retinocollicular Synapse Maturation and Plasticity Are Regulated by Correlated Retinal Waves

Shah¹,

Crair²

2008

J. Neurosci.

View full text Add to dashboard Cite

show abstract

“…8, d, e, and our data in h) clearly include cases of potentiation and depression, though the average is not significantly different from zero, probably because of balanced LTP and LTD. Notably, Hardingham and others (2007) found that potentiation and depression can be induced by the same protocol, whereby the direction of the EPSP amplitude change was correlated with initial release probability. The LTP and LTD data from this article represent cases selected by the direction of the change.…”

Section: Induction Of Input-specific and Heterosynaptic Plasticity: Smentioning

confidence: 94%

Heterosynaptic Plasticity

et al. 2014

View full text Add to dashboard Cite

Plasticity is a universal property of synapses. It is expressed in a variety of forms mediated by a multitude of mechanisms. Here we consider two broad kinds of plasticity that differ in their requirement for presynaptic activity during the induction. Homosynaptic plasticity occurs at synapses that were active during the induction. It is also called input specific or associative, and it is governed by Hebbian-type learning rules. Heterosynaptic plasticity can be induced by episodes of strong postsynaptic activity also at synapses that were not active during the induction, thus making any synapse at a cell a target to heterosynaptic changes. Both forms can be induced by typical protocols used for plasticity induction and operate on the same time scales but have differential computational properties and play different roles in learning systems. Homosynaptic plasticity mediates associative modifications of synaptic weights. Heterosynaptic plasticity counteracts runaway dynamics introduced by Hebbian-type rules and balances synaptic changes. It provides learning systems with stability and enhances synaptic competition. We conclude that homosynaptic and heterosynaptic plasticity represent complementary properties of modifiable synapses, and both are necessary for normal operation of neural systems with plastic synapses.

show abstract

“…In vitro studies have shown that STP has profound effects on temporal filtering [7], network stability [7], and working memory [8]. Moreover, there is bidirectional interaction between STP and long-term synaptic changes: STP can determine the magnitude of long-term plasticity [9][10][11][12], and long-term synaptic changes also modify STP [9][10][11][12][13]. This results in an interplay between STP and long-term plasticity on multiple timescales [13,14].…”

mentioning

confidence: 99%

Estimating short-term synaptic plasticity from pre- and postsynaptic spiking

Ghanbari

Malyshev

Volgushev

et al. 2017

Preprint

View full text Add to dashboard Cite

Short-term synaptic plasticity (STP) critically affects the processing of information in neuronal circuits by reversibly changing the effective strength of connections between neurons on time scales from milliseconds to a few seconds. STP is traditionally studied using intracellular recordings of postsynaptic potentials or currents evoked by presynaptic spikes. However, STP also affects the statistics of postsynaptic spikes. Here we present two model-based approaches for estimating synaptic weights and short-term plasticity from pre-and postsynaptic spike observations alone. We extend a generalized linear model (GLM) that predicts postsynaptic spiking as a function of the observed pre-and postsynaptic spikes and allow the connection strength (coupling term in the GLM) to vary as a function of time based on the history of presynaptic spikes. Our first model assumes that STP follows a TsodyksMarkram description of vesicle depletion and recovery. In a second model, we introduce a functional description of STP where we estimate the coupling term as a biophysically unrestrained function of the presynaptic inter-spike intervals. To validate the models, we test the accuracy of STP estimation using the spiking of pre-and postsynaptic neurons with known synaptic dynamics. We first test our models using the responses of layer 2/3 pyramidal neurons to simulated presynaptic input with different types of STP, and then use simulated spike trains to examine the effects of spike-frequency adaptation, stochastic vesicle release, spike sorting errors, and common input. We find that, using only spike observations, both model-based methods can accurately reconstruct the time-varying synaptic weights of presynaptic inputs for different types of STP. Our models also capture the differences in postsynaptic spike responses to presynaptic spikes following short vs long inter-spike intervals, similar to results reported for thalamocortical connections. These models may thus be useful tools for characterizing short-term plasticity from multi-electrode spike recordings in vivo. Author summaryInformation processing in the nervous system critically depends on dynamic changes in the strength of connections between neurons. Short-term synaptic plasticity (STP), changes that occur on timescales from milliseconds to a few seconds, is thought to play a role in tasks such as speech recognition, motion detection, and working memory. Although intracellular recordings in slices of neural tissue have identified synaptic mechanisms of STP and have demonstrated its potential role in information processing, studying STP in intact animals, especially during behavior, is experimentally difficult. Unlike intracellular recordings, extracellular spiking of hundreds of neurons simultaneously can be recorded even in behaving animals. Here we developed two models that allow estimation of STP from extracellular spike recordings. We validate these models using results from in vitro experiments which simulate a realistic synaptic input from a population of ...

show abstract

Presynaptic Efficacy Directs Normalization of Synaptic Strength in Layer 2/3 Rat Neocortex After Paired Activity

Cited by 57 publications

References 59 publications

Retinocollicular Synapse Maturation and Plasticity Are Regulated by Correlated Retinal Waves

Retinocollicular Synapse Maturation and Plasticity Are Regulated by Correlated Retinal Waves

Heterosynaptic Plasticity

Estimating short-term synaptic plasticity from pre- and postsynaptic spiking

Contact Info

Product

Resources

About