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1.
Long-term modification of synaptic efficacy can depend on the timing of pre- and postsynaptic action potentials. In model studies, such spike timing-dependent plasticity (STDP) introduces the desirable features of competition among synapses and regulation of postsynaptic firing characteristics. STDP strengthens synapses that receive correlated input, which can lead to the formation of stimulus-selective columns and the development, refinement, and maintenance of selectivity maps in network models. The temporal asymmetry of STDP suppresses strong destabilizing self-excitatory loops and allows a group of neurons that become selective early in development to direct other neurons to become similarly selective. STDP, acting alone without further hypothetical global constraints or additional forms of plasticity, can also reproduce the remapping seen in adult cortex following afferent lesions. 相似文献
2.
Vassilis Cutsuridis 《Cognitive neurodynamics》2012,6(5):421-441
Spike timing dependent plasticity (STDP) is a synaptic learning rule where the relative timing between the presynaptic and postsynaptic action potentials determines the sign and strength of synaptic plasticity. In its basic form STDP has an asymmetric form which incorporates both persistent increases and persistent decreases in synaptic strength. The basic form of STDP, however, is not a fixed property and depends on the dendritic location. An asymmetric curve is observed in the distal dendrites, whereas a symmetrical one is observed in the proximal ones. A recent computational study has shown that the transition from the asymmetry to symmetry is due to inhibition under certain conditions. Synapses have also been observed to be unreliable at generating plasticity when excitatory postsynaptic potentials and single spikes are paired at low frequencies. Bursts of spikes, however, are reliably signaled because transmitter release is facilitated. This article presents a two-compartment model of the CA1 pyramidal cell. The model is neurophysiologically plausible with its dynamics resulting from the interplay of many ionic and synaptic currents. Plasticity is measured by a deterministic Ca2+ dynamics model which measures the instantaneous calcium level and its time course in the dendrite and change the strength of the synapse accordingly. The model is validated to match the asymmetrical form of STDP from the pairing of a presynaptic (dendritic) and postsynaptic (somatic) spikes as observed experimentally. With the parameter set unchanged the model investigates how pairing of bursts with single spikes and bursts in the presence or absence of inhibition shapes the STDP curve. The model predicts that inhibition strength and frequency are not the only factors of the asymmetry-to-symmetry switch of the STDP curve. Burst interspike interval is another factor. This study is an important first step towards understanding how STDP is affected under natural firing patterns in vivo. 相似文献
3.
Spike-timing dependent plasticity (STDP), a widespread synaptic modification mechanism, is sensitive to correlations between presynaptic spike trains and it generates competition among synapses. However, STDP has an inherent instability because strong synapses are more likely to be strengthened than weak ones, causing them to grow in strength until some biophysical limit is reached. Through simulations and analytic calculations, we show that a small temporal shift in the STDP window that causes synchronous, or nearly synchronous, pre- and postsynaptic action potentials to induce long-term depression can stabilize synaptic strengths. Shifted STDP also stabilizes the postsynaptic firing rate and can implement both Hebbian and anti-Hebbian forms of competitive synaptic plasticity. Interestingly, the overall level of inhibition determines whether plasticity is Hebbian or anti-Hebbian. Even a random symmetric jitter of a few milliseconds in the STDP window can stabilize synaptic strengths while retaining these features. The same results hold for a shifted version of the more recent "triplet" model of STDP. Our results indicate that the detailed shape of the STDP window function near the transition from depression to potentiation is of the utmost importance in determining the consequences of STDP, suggesting that this region warrants further experimental study. 相似文献
4.
In spike-timing-dependent plasticity (STDP) the synapses are potentiated or depressed depending on the temporal order and temporal difference of the pre- and post-synaptic signals. We present a biophysical model of STDP which assumes that not only the timing, but also the shapes of these signals influence the synaptic modifications. The model is based on a Hebbian learning rule which correlates the NMDA synaptic conductance with the post-synaptic signal at synaptic location as the pre- and post-synaptic quantities. As compared to a previous paper [Saudargiene, A., Porr, B., Worgotter, F., 2004. How the shape of pre- and post-synaptic signals can influence stdp: a biophysical model. Neural Comp.], here we show that this rule reproduces the generic STDP weight change curve by using real neuronal input signals and combinations of more than two (pre- and post-synaptic) spikes. We demonstrate that the shape of the STDP curve strongly depends on the shape of the depolarising membrane potentials, which induces learning. As these potentials vary at different locations of the dendritic tree, model predicts that synaptic changes are location dependent. The model is extended to account for the patterns of more than two spikes of the pre- and post-synaptic cells. The results show that STDP weight change curve is also activity dependent. 相似文献
5.
Several formulations of correlation-based Hebbian learning are reviewed. On the presynaptic side, activity is described either
by a firing rate or by presynaptic spike arrival. The state of the postsynaptic neuron can be described by its membrane potential,
its firing rate, or the timing of backpropagating action potentials (BPAPs). It is shown that all of the above formulations
can be derived from the point of view of an expansion. In the absence of BPAPs, it is natural to correlate presynaptic spikes
with the postsynaptic membrane potential. Time windows of spike-time-dependent plasticity arise naturally if the timing of
postsynaptic spikes is available at the site of the synapse, as is the case in the presence of BPAPs. With an appropriate
choice of parameters, Hebbian synaptic plasticity has intrinsic normalization properties that stabilizes postsynaptic firing
rates and leads to subtractive weight normalization.
Received: 1 February 2002 / Accepted: 28 March 2002
Correspondence to: W. Gerstner (e-mail: wulfram.gerstner@epfl.ch, Tel.: +41-21-6936713, Fax: +41-21-6935263) 相似文献
6.
Spike timing dependent plasticity (STDP) likely plays an important role in forming and changing connectivity patterns between neurons in our brain. In a unidirectional synaptic connection between two neurons, it uses the causal relation between spiking activity of a presynaptic input neuron and a postsynaptic output neuron to change the strength of this connection. While the nature of STDP benefits unsupervised learning of correlated inputs, any incorporation of value into the learning process needs some form of reinforcement. Chemical neuromodulators such as Dopamine or Acetylcholine are thought to signal changes between external reward and internal expectation to many brain regions, including the basal ganglia. This effect is often modelled through a direct inclusion of the level of Dopamine as a third factor into the STDP rule. While this gives the benefit of direct control over synaptic modification, it does not account for observed instantaneous effects in neuronal activity on application of Dopamine agonists. Specifically, an instant facilitation of neuronal excitability in the striatum can not be explained by the only indirect effect that dopamine-modulated STDP has on a neuron’s firing pattern. We therefore propose a model for synaptic transmission where the level of neuromodulator does not directly influence synaptic plasticity, but instead alters the relative firing causality between pre- and postsynaptic neurons. Through the direct effect on postsynaptic activity, our rule allows indirect modulation of the learning outcome even with unmodulated, two-factor STDP. However, it also does not prohibit joint operation together with three-factor STDP rules. 相似文献
7.
DE Feldman 《Neuron》2012,75(4):556-571
In spike-timing-dependent plasticity (STDP), the order and precise temporal interval between presynaptic and postsynaptic spikes determine the sign and magnitude of long-term potentiation (LTP) or depression (LTD). STDP is widely utilized in models of circuit-level plasticity, development, and learning. However, spike timing is just one of several factors (including firing rate, synaptic cooperativity, and depolarization) that govern plasticity induction, and its relative importance varies across synapses and activity regimes. This review summarizes this broader view of plasticity, including the forms and cellular mechanisms for the spike-timing dependence of plasticity, and, the evidence that spike timing is an important determinant of plasticity in?vivo. 相似文献
8.
Palikhova TA 《Zhurnal vysshe? nervno? deiatelnosti imeni I P Pavlova》2000,50(5):775-790
The synaptic plasticity is a background for learning and memory. Identifiable synapses that are the synapses between individually identifiable neurons are a very convenient model for studying plasticity. Synapses between the interoceptive mechanosensory neurons and the command neurons of the withdrawal behavior were identified in the Helix lucorum brain. It was shown that synaptic plasticity estimated by the dynamics of the elementary postsynaptic potentials elicited by single presynaptic spikes differed from the synaptic plasticity estimated by the dynamics of compound synaptic responses of the same neurons to sensory stimulation. Habituation and heterosynaptic facilitation phenomena are discussed in terms of the dynamics of the elementary postsynaptic potentials. 相似文献
9.
Beatriz Eymi Pimentel Mizusaki Sally Si Ying Li Rui Ponte Costa Per Jesper Sjstrm 《PLoS computational biology》2022,18(6)
A plethora of experimental studies have shown that long-term synaptic plasticity can be expressed pre- or postsynaptically depending on a range of factors such as developmental stage, synapse type, and activity patterns. The functional consequences of this diversity are not clear, although it is understood that whereas postsynaptic expression of plasticity predominantly affects synaptic response amplitude, presynaptic expression alters both synaptic response amplitude and short-term dynamics. In most models of neuronal learning, long-term synaptic plasticity is implemented as changes in connective weights. The consideration of long-term plasticity as a fixed change in amplitude corresponds more closely to post- than to presynaptic expression, which means theoretical outcomes based on this choice of implementation may have a postsynaptic bias. To explore the functional implications of the diversity of expression of long-term synaptic plasticity, we adapted a model of long-term plasticity, more specifically spike-timing-dependent plasticity (STDP), such that it was expressed either independently pre- or postsynaptically, or in a mixture of both ways. We compared pair-based standard STDP models and a biologically tuned triplet STDP model, and investigated the outcomes in a minimal setting, using two different learning schemes: in the first, inputs were triggered at different latencies, and in the second a subset of inputs were temporally correlated. We found that presynaptic changes adjusted the speed of learning, while postsynaptic expression was more efficient at regulating spike timing and frequency. When combining both expression loci, postsynaptic changes amplified the response range, while presynaptic plasticity allowed control over postsynaptic firing rates, potentially providing a form of activity homeostasis. Our findings highlight how the seemingly innocuous choice of implementing synaptic plasticity by single weight modification may unwittingly introduce a postsynaptic bias in modelling outcomes. We conclude that pre- and postsynaptically expressed plasticity are not interchangeable, but enable complimentary functions. 相似文献
10.
Suri RE 《Biological cybernetics》2004,90(6):400-409
Recent physiological findings have revealed that long-term adaptation of the synaptic strengths between cortical pyramidal neurons depends on the temporal order of presynaptic and postsynaptic spikes, which is called spike-timing-dependent plasticity (STDP) or temporally asymmetric Hebbian (TAH) learning. Here I prove by analytical means that a physiologically plausible variant of STDP adapts synaptic strengths such that the presynaptic spikes predict the postsynaptic spikes with minimal error. This prediction error model of STDP implies a mechanism for cortical memory: cortical tissue learns temporal spike patterns if these spike patterns are repeatedly elicited in a set of pyramidal neurons. The trained network finishes these patterns if their beginnings are presented, thereby recalling the memory. Implementations of the proposed algorithms may be useful for applications in voice recognition and computer vision. 相似文献
11.
Sandra J. Kuhlman Jiangteng Lu Matthew S. Lazarus Z. Josh Huang 《PLoS computational biology》2010,6(6)
Spike-timing-dependent plasticity (STDP), a form of Hebbian plasticity, is inherently stabilizing. Whether and how GABAergic inhibition influences STDP is not well understood. Using a model neuron driven by converging inputs modifiable by STDP, we determined that a sufficient level of inhibition was critical to ensure that temporal coherence (correlation among presynaptic spike times) of synaptic inputs, rather than initial strength or number of inputs within a pathway, controlled postsynaptic spike timing. Inhibition exerted this effect by preferentially reducing synaptic efficacy, the ability of inputs to evoke postsynaptic action potentials, of the less coherent inputs. In visual cortical slices, inhibition potently reduced synaptic efficacy at ages during but not before the critical period of ocular dominance (OD) plasticity. Whole-cell recordings revealed that the amplitude of unitary IPSCs from parvalbumin positive (Pv+) interneurons to pyramidal neurons increased during the critical period, while the synaptic decay time-constant decreased. In addition, intrinsic properties of Pv+ interneurons matured, resulting in an increase in instantaneous firing rate. Our results suggest that maturation of inhibition in visual cortex ensures that the temporally coherent inputs (e.g. those from the open eye during monocular deprivation) control postsynaptic spike times of binocular neurons, a prerequisite for Hebbian mechanisms to induce OD plasticity. 相似文献
12.
Recent indirect experimental evidence suggests that synaptic plasticity changes along the dendrites of a neuron. Here we present a synaptic plasticity rule which is controlled by the properties of the pre- and postsynaptic signals. Using recorded membrane traces of back-propagating and dendritic spikes we demonstrate that LTP and LTD will depend specifically on the shape of the postsynaptic depolarization at a given dendritic site. We find that asymmetrical spike-timing-dependent plasticity (STDP) can be replaced by temporally symmetrical plasticity within physiologically relevant time windows if the postsynaptic depolarization rises shallow. Presynaptically the rule depends on the NMDA channel characteristic, and the model predicts that an increase in Mg2+ will attenuate the STDP curve without changing its shape. Furthermore, the model suggests that the profile of LTD should be governed by the postsynaptic signal while that of LTP mainly depends on the presynaptic signal shape. 相似文献
13.
Although spike-timing-dependent plasticity (STDP) is well characterized when pre- and postsynaptic spikes are paired with a given time lag, how this generalizes for more complex spike-trains is unclear. Recent experiments demonstrate that contributions to synaptic plasticity from different spike pairs within a spike train do not add linearly. In the visual cortex conditioning with spike triplets shows that the effect of the first spike pair dominates over the second. Using a previously proposed calcium-dependent plasticity model, we show that short-term synaptic dynamics and interaction between successive back-propagating action potentials (BPAP) may jointly account for the nonlinearities observed. Paired-pulse depression and attenuation of BPAPs are incorporated into the model through the use-dependent depletion of pre- and postsynaptic resources, respectively. Simulations suggest that these processes may play critical roles in determining how STDP operates in the context of natural spike-trains. 相似文献
14.
Spike-timing dependent plasticity (STDP), a synaptic modification depending on a relative timing of presynaptic and postsynaptic spikes, has fascinated researchers in the fields of neurophysiology and computational neuroscience, because it is not only conceptually simple or biologically reasonable but is also versatile in neural network simulations. The STDP rule may be valid only under specific conditions, however. We propose herein a method that could find more natural and potent rules of synaptic plasticity. 相似文献
15.
In the last decade dendrites of cortical neurons have been shown to nonlinearly combine synaptic inputs by evoking local dendritic spikes. It has been suggested that these nonlinearities raise the computational power of a single neuron, making it comparable to a 2-layer network of point neurons. But how these nonlinearities can be incorporated into the synaptic plasticity to optimally support learning remains unclear. We present a theoretically derived synaptic plasticity rule for supervised and reinforcement learning that depends on the timing of the presynaptic, the dendritic and the postsynaptic spikes. For supervised learning, the rule can be seen as a biological version of the classical error-backpropagation algorithm applied to the dendritic case. When modulated by a delayed reward signal, the same plasticity is shown to maximize the expected reward in reinforcement learning for various coding scenarios. Our framework makes specific experimental predictions and highlights the unique advantage of active dendrites for implementing powerful synaptic plasticity rules that have access to downstream information via backpropagation of action potentials. 相似文献
16.
Spike-timing-dependent synaptic plasticity (STDP) is a simple and effective learning rule for sequence learning. However,
synapses being subject to STDP rules are readily influenced in noisy circumstances because synaptic conductances are modified
by pre- and postsynaptic spikes elicited within a few tens of milliseconds, regardless of whether those spikes convey information
or not. Noisy firing existing everywhere in the brain may induce irrelevant enhancement of synaptic connections through STDP
rules and would result in uncertain memory encoding and obscure memory patterns. We will here show that the LTD windows of
the STDP rules enable robust sequence learning amid background noise in cooperation with a large signal transmission delay
between neurons and a theta rhythm, using a network model of the entorhinal cortex layer II with entorhinal-hippocampal loop
connections. The important element of the present model for robust sequence learning amid background noise is the symmetric
STDP rule having LTD windows on both sides of the LTP window, in addition to the loop connections having a large signal transmission
delay and the theta rhythm pacing activities of stellate cells. Above all, the LTD window in the range of positive spike-timing
is important to prevent influences of noise with the progress of sequence learning. 相似文献
17.
Roberts PD 《Journal of computational neuroscience》2007,22(3):283-296
Dynamics of spike-timing dependent synaptic plasticity are analyzed for excitatory and inhibitory synapses onto cerebellar
Purkinje cells. The purpose of this study is to place theoretical constraints on candidate synaptic learning rules that determine
the changes in synaptic efficacy due to pairing complex spikes with presynaptic spikes in parallel fibers and inhibitory interneurons.
Constraints are derived for the timing between complex spikes and presynaptic spikes, constraints that result from the stability
of the learning dynamics of the learning rule. Potential instabilities in the parallel fiber synaptic learning rule are found
to be stabilized by synaptic plasticity at inhibitory synapses if the inhibitory learning rules are stable, and conditions
for stability of inhibitory plasticity are given. Combining excitatory with inhibitory plasticity provides a mechanism for
minimizing the overall synaptic input. Stable learning rules are shown to be able to sculpt simple-spike patterns by regulating
the excitability of neurons in the inferior olive that give rise to climbing fibers. 相似文献
18.
Finding the rules underlying how axons of cortical neurons form neural circuits and modify their corresponding synaptic strength is the still subject of intense research. Experiments have shown that internal calcium concentration, and both the precise timing and temporal order of pre and postsynaptic action potentials, are important constituents governing whether the strength of a synapse located on the dendrite is increased or decreased. In particular, previous investigations focusing on spike timing-dependent plasticity (STDP) have typically observed an asymmetric temporal window governing changes in synaptic efficacy. Such a temporal window emphasizes that if a presynaptic spike, arriving at the synaptic terminal, precedes the generation of a postsynaptic action potential, then the synapse is potentiated; however if the temporal order is reversed, then depression occurs. Furthermore, recent experimental studies have now demonstrated that the temporal window also depends on the dendritic location of the synapse. Specifically, it was shown that in distal regions of the apical dendrite, the magnitude of potentiation was smaller and the window for depression was broader, when compared to observations from the proximal region of the dendrite. To date, the underlying mechanism(s) for such a distance-dependent effect is (are) currently unknown. Here, using the ionic cable theory framework in conjunction with the standard calcium based plasticity model, we show for the first time that such distance-dependent inhomogeneities in the temporal learning window for STDP can be largely explained by both the spatial and active properties of the dendrite. 相似文献
19.
Synapses may undergo long-term increases or decreases in synaptic strength dependent on critical differences in the timing between pre-and postsynaptic activity. Such spike-timing-dependent plasticity (STDP) follows rules that govern how patterns of neural activity induce changes in synaptic strength. Synaptic plasticity in the dorsal cochlear nucleus (DCN) follows Hebbian and anti-Hebbian patterns in a cell-specific manner. Here we show that these opposing responses to synaptic activity result from differential expression of two signaling pathways. Ca2+/calmodulin-dependent protein kinase II (CaMKII) signaling underlies Hebbian postsynaptic LTP in principal cells. By contrast, in interneurons, a temporally precise anti-Hebbian synaptic spike-timing rule results from the combined effects of postsynaptic CaMKII-dependent LTP and endocannabinoid-dependent presynaptic LTD. Cell specificity in the circuit arises from selective targeting of presynaptic CB1 receptors in different axonal terminals. Hence, pre- and postsynaptic sites of expression determine both the sign and timing requirements of long-term plasticity in interneurons. 相似文献
20.
Plasticity at central synapses depends critically on the timing of presynaptic and postsynaptic action potentials. Key initial steps in synaptic plasticity involve the back-propagation of action potentials into the dendritic tree and calcium influx that depends nonlinearly on the action potential and synaptic input. These initial steps are now better understood. In addition, recent studies of processes as diverse as gene expression and channel inactivation suggest that responses to calcium transients depend not only their amplitude, but on their time course and on the location of their origin. 相似文献