Spike-timing-dependent plasticity

Spike-timing-dependent plasticity (STDP) is a biological process that adjusts the strength of synaptic connections between neurons based on the relative timing of their action potentials (or spikes). It is a temporally sensitive form of synaptic plasticity, meaning that the efficiency of synaptic transmission is modified by the timing of neural activity. When a presynaptic neuron consistently fires just before a postsynaptic neuron, the connection is typically strengthened—a process known as long-term potentiation (LTP). If the timing is reversed and the presynaptic neuron fires after the postsynaptic neuron, the connection is weakened through long-term depression (LTD).

STDP is considered a key mechanism in learning and memory formation and helps explain activity-dependent development of neural circuits. It has been observed in multiple brain regions, including the hippocampus, neocortex, and visual system, and has been widely implemented in computational models of biologically inspired learning algorithms and network dynamics.

STDP develops early in life, helping to refine sensory maps and establish functional connectivity during critical periods. The process depends on molecular mechanisms such as NMDA receptor-mediated calcium signaling and is influenced by synapse location and neuromodulators like dopamine and acetylcholine.

Variants of STDP have been found at inhibitory synapses and in response to complex spike patterns. The process also interacts with other forms of plasticity, including rate-based learning, homeostatic regulation, and structural remodeling. Disruptions in STDP have been linked to neurological and psychiatric conditions such as Alzheimer’s disease, Fragile X syndrome, epilepsy, and Parkinson’s disease.

Mechanism

Spike-timing-dependent plasticity (STDP) depends on the precise timing of action potentials (spikes) between presynaptic and postsynaptic neurons, hence the name: "spike-timing-dependent plasticity". If a presynaptic spike occurs shortly before a postsynaptic spike—typically within a window of 10 to 20 milliseconds—the synapse is strengthened, a process known as long-term potentiation (LTP). If the presynaptic spike follows the postsynaptic spike, the synapse is weakened, resulting in long-term depression (LTD). This timing-dependent adjustment of synaptic strength enables neurons to reinforce inputs that are likely to have contributed to their activation while weakening those that were not causally involved.

The effect of STDP is cumulative: repeated pairings of causally timed spikes strengthen the relevant synapses, while others weaken over time. Eventually, this leads to a subset of inputs being selectively retained, particularly those that tend to fire together within narrow temporal windows. As a result, the neuron becomes tuned to detect and respond preferentially to input patterns that consistently precede its own activation, which may reflect meaningful or predictive features of the environment.

Calcium influx through NMDA receptors activates CaMKII, which initiates signaling cascades involving Rho family GTPases, primarily RhoA and Cdc42. These pathways regulate actin-binding proteins such as cofilin and profilin. During the transient phase, LIMK1 phosphorylates ADF/cofilin, inhibiting actin depolymerization, expanding dendritic spine volume, and contributing to the induction of LTP.

At the molecular level, STDP is primarily mediated by N-methyl-D-aspartate receptors (NMDA receptors) located on the postsynaptic membrane. These receptors function as coincidence detectors: they require both the release of glutamate from the presynaptic terminal and sufficient depolarization of the postsynaptic membrane to become fully activated. When these conditions are met—such as when a back-propagating action potential follows synaptic input—the NMDA receptor channel opens, allowing calcium ions to enter the postsynaptic cell.

The amplitude and duration of calcium influx determine the direction of synaptic change. High-amplitude, rapid calcium transients typically trigger LTP via the activation of calcium-sensitive kinases, while lower, prolonged calcium levels are associated with LTD, in part due to the activation of phosphatases. The spike-timing rule is therefore shaped by intracellular signaling cascades that translate calcium signals into long-term structural or biochemical changes at the synapse.

Although the mechanisms of LTP are relatively well understood, the pathways underlying spike-timing-dependent LTD can vary. LTD may involve voltage-dependent calcium entry through other channels, activation of metabotropic glutamate receptors, or the release of retrograde messengers such as endocannabinoids. In some synapses, presynaptic NMDA receptors also contribute to LTD by modulating neurotransmitter release.

The specific shape of the STDP learning window—the curve that relates spike timing difference to synaptic change—differs across brain regions and cell types. Many synapses exhibit an asymmetric window favoring LTP for pre-before-post timing and LTD for post-before-pre. However, other synapses display symmetric, anti-Hebbian, or frequency-dependent patterns, particularly under different neuromodulatory conditions or in inhibitory circuits.

STDP in Inhibitory Synapses

Most early STDP research focused on excitatory (glutamatergic) synapses, but timing-dependent plasticity also occurs at inhibitory synapses. However, the rules of STDP at GABAergic synapses can differ significantly from their excitatory counterparts. In many cases, inhibitory STDP is anti-Hebbian or weight-dependent in the opposite manner. For example, in cortical circuits, fast-spiking parvalbumin-positive interneurons that synapse onto pyramidal cells exhibit timing-dependent changes in synaptic strength. When the interneuron fires slightly before the postsynaptic pyramidal neuron, providing feed-forward inhibition, the inhibitory synapse is weakened, a process known as inhibitory long-term depression. In contrast, if the interneuron fires after, or with a longer delay relative to the pyramidal neuron, the synapse is strengthened, resulting in inhibitory long-term potentiation .

This was first demonstrated in the rodent neocortex with paired recordings: near-synchronous firing produced inhibitory long-term potentiation, but if the inhibitory neuron consistently led the excitatory cell by a few milliseconds, the connection underwent lasting depression . Such timing rules for inhibitory STDP are essentially the mirror-image of classic excitatory STDP and serve to modulate circuit excitability. Strengthening an inhibitory synapse when it fires after the excitatory neuron can be interpreted as enhancing feedback inhibition, whereas weakening it when it fires before the excitatory neuron reduces feed-forward inhibition, potentially allowing the excitatory neuron to fire more easily in the future.

The physiological roles of inhibitory STDP are still being elucidated. One important function appears to be the fine-tuning of excitatory–inhibitory balance in neural networks. Timing-dependent changes at inhibitory synapses have been shown to contribute to sensory map plasticity. In the auditory cortex, for instance, plasticity of inhibitory synapses following specific spike-timing protocols has been linked to the remapping of neuronal frequency preference, implying that inhibitory STDP participates in experience-dependent reorganization of receptive fields.

Endocannabinoids released from the postsynaptic neuron modulate synaptic strength. In homosynaptic plasticity, these effects are confined to the active synapse, whereas in heterosynaptic plasticity, the signaling can influence neighboring, inactive synapses. (See section "Interaction with Other Forms of Plasticity" for more detail)

Moreover, distinct molecular mechanisms underlie STDP at inhibitory synapses. Unlike excitatory LTP/LTD (often NMDA receptor-dependent), inhibitory long-term plasticity can require retrograde signaling and neuromodulators. In hippocampal CA1 pyramidal cells, an STDP protocol that induces long-term depression of GABAergic synapses was found to depend on endocannabinoid release and the activation of presynaptic M2 muscarinic acetylcholine receptors. In this case, precisely timed postsynaptic spikes trigger the synthesis of endocannabinoids which act on CB1 receptors at the interneuron terminals, reducing GABA release, a mechanism quite different from NMDA-dependent excitatory STDP . Such requirements highlight that inhibitory STDP often engages metaplastic gating factors (e.g., cholinergic tone or cannabinoid signaling) to occur.

Overall, STDP in inhibitory synapses adds an important plasticity paradigm: it enables activity-dependent adjustment of inhibition in neural circuits, complementing excitatory plasticity and ensuring that the timing of inhibition relative to excitation can be optimized through experience.

Neuromodulation of STDP

Neuromodulators strongly influence STDP by modifying the timing rules that determine whether a synapse is strengthened or weakened. These changes depend on broader brain states, such as arousal, attention, or reward, allowing synaptic plasticity to be tuned to the behavioral context. Experimental studies have shown that the presence of neuromodulatory signals (such as dopamine, acetylcholine, noradrenaline, serotonin, etc.) can gate or alter the outcome of STDP. For example, in hippocampal and cortical slices, activation of β-adrenergic receptors can convert what would normally be an LTD-induced timing into a net LTP. One study demonstrated that applying isoproterenol (a β-adrenergic agonist) during an STDP induction protocol abolished the LTD that would occur when postsynaptic spikes followed presynaptic spikes (post–pre pairing), and instead resulted in potentiation for all spike-timing intervals tested . In essence, adrenergic neuromodulation extended the potentiation window and prevented LTD, overriding the usual temporal requirements. This finding aligns with a broader principle: neuromodulators that activate cAMP/PKA pathways (like norepinephrine via β receptors or dopamine via D1 receptors) tend to bias synaptic plasticity toward potentiation, whereas other signals can bias toward depression.

Acetylcholine and dopamine provide an example of sequential neuromodulation of STDP. Acetylcholine (acting largely through muscarinic receptors in the forebrain) can bias STDP toward depression, for instance, by lowering the threshold for LTD induction or narrowing the LTP window. This might occur during exploratory or attentive states when acetylcholine is high. If a reward or salient outcome then follows, dopamine is released and can invert the synaptic changes from depression to potentiation. In hippocampal experiments, an initial conditioning in the presence of acetylcholine resulted in synaptic weakening, but a subsequent application of dopamine converted that LTD into LTP. Moreover, dopamine can broaden the STDP time window for potentiation and can even rescue LTP if given shortly after the spike pairing, effectively imparting a reward timing signal to STDP. This modulatory sequence (ACh followed by dopamine) has been proposed as a cellular mechanism for associating sensory cues or actions with delayed reward, by first allowing synapses to depress and then reinforcing them if the outcome is positive.

In general, neuromodulators enable state-dependent plasticity: the brain can promote or prevent STDP under certain conditions. For instance, in the presence of cholinergic tone (e.g., during waking exploration), some cortical synapses may not potentiate with STDP unless dopaminergic or noradrenergic signals also indicate a behaviorally important event. Neuromodulation of STDP is not limited to the classic neurotransmitters; it potentially extends to neuropeptides, stress hormones, and other modulators that adjust neural plasticity. This dynamic regulation ensures that STDP in real neural circuits is context-sensitive. Synaptic changes occur not only based on spike timing but also in conjunction with the animal’s arousal, attention, and reward environment, thereby linking synaptic plasticity to learning and motivation processes.

History

The conceptual foundation for spike-timing-dependent plasticity (STDP) is rooted in the mid-20th century work of Canadian psychologist Donald Hebb. In his 1949 book, The Organization of Behavior, Hebb proposed that the repeated and persistent activation of a presynaptic neuron contributes to the firing of a postsynaptic neuron. This interaction strengthens the connection between them. This principle, now known as Hebbian theory, is often summarized as "cells that fire together, wire together". While Hebb's framework emphasized the co-occurrence of neural activity, it did not account for the precise temporal order of neuronal firing.

As early as 1973, M. M. Taylor proposed a theoretical learning rule in which synapses would be strengthened if a presynaptic spike reliably preceded a postsynaptic spike, and weakened if the timing was reversed. He suggested that such a temporally sensitive mechanism could support more efficient encoding of input patterns, although this idea did not receive widespread attention at the time.

Experimental studies in the 1980s and early 1990s began to probe the timing dependence of synaptic plasticity more directly. Notably, W. B. Levy and O. Steward (1983) demonstrated that the timing between pre- and postsynaptic activity could influence the direction of synaptic change. Subsequent work by Y. Dan and Mu-Ming Poo (1992) at neuromuscular synapses, and by D. Debanne, B. Gähwiler, and S. Thompson (1994) in the hippocampus, showed that asynchronous pairing of spikes could lead to long-term synaptic depression (LTD) .

The modern concept of STDP began to take clearer shape through work in the mid-1990s. Henry Markram, working in Bert Sakmann’s lab, used dual patch-clamp recordings to show that the order of spike firing between two connected neurons could bidirectionally modify synaptic strength. When the presynaptic neuron was activated approximately 10 milliseconds before the postsynaptic neuron, the connection was strengthened; reversing the order led to weakening. Although these findings were presented in abstracts and conference proceedings earlier, they were formally published in 1997.

Shortly after, in a seminal 1998 study, Guoqiang Bi and Mu-Ming Poo systematically mapped the time-dependent curve relating the order of pre- and postsynaptic spikes to the magnitude and direction of synaptic change in cultured hippocampal neurons. Their work demonstrated that small differences in spike timing—on the order of tens of milliseconds—could induce either long-term potentiation (LTP) or long-term depression (LTD) . This study became a foundational reference for what is now recognized as the canonical STDP “learning window.”

Since these early findings, STDP has been confirmed in a wide range of preparations, including brain slices and in vivo systems, across different species and brain regions. STDP-like mechanisms have been observed in the visual cortex, hippocampus, cerebellum, and neocortex, as well as in sensory-evoked responses in intact animals . It has also been demonstrated that the initially asymmetric timing window seen in early STDP studies can evolve over time; for example, one study showed that a more symmetric “LTP-only” profile may emerge several days after initial induction.

STDP is now widely regarded as a key biological mechanism supporting Hebbian learning, particularly during development, where it is thought to refine neural circuits based on experience.

From Hebbian rule to STDP

According to Hebb’s original postulate, synaptic strength increases when the presynaptic neuron persistently contributes to the firing of the postsynaptic neuron. Conversely, synapses weaken when the activity of the presynaptic neuron is consistently unrelated to postsynaptic firing. These principles are often simplified by the mnemonics: "cells that fire together, wire together," and "out of sync, lose their link" .

However, Hebb’s formulation did not explicitly address the directionality of firing. Two neurons firing at exactly the same time cannot satisfy a causal relationship. To contribute to the firing of a postsynaptic neuron, the presynaptic neuron must fire shortly before it. Experimental studies confirmed that this precise temporal relationship is critical for synaptic modification: when the presynaptic spike occurs just before the postsynaptic one, the synapse is potentiated; if it follows, the synapse is depressed .

Furthermore, STDP appears to depend not only on the timing between individual spikes, but also on the consistency with which presynaptic firing predicts postsynaptic activation. This mirrors the principle of contingency (learning theory), well known in classical conditioning: consistent predictive relationships, rather than mere co-occurrence, are necessary for robust learning.

Role in hippocampal learning

Spike-timing-dependent plasticity (STDP) operates over a narrow time window—typically on the order of tens of milliseconds—yet the hippocampus is capable of associating events that unfold over several seconds, as is required during episodic memory formation. This apparent mismatch in time scales is reconciled, in part, by the presence of theta waves (4–8 Hz), rhythmic electrical activity in the hippocampus that organizes neuronal firing during active exploration and learning.

As an animal experiences a sequence of events or traverses space, hippocampal place cells fire at progressively earlier phases of each theta cycle, a phenomenon known as phase precession. This effectively compresses temporally distributed spikes into a narrower window—aligning them within a single theta cycle (~100–150 ms)—allowing spikes from sequentially active neurons to fall within the STDP window .

In the recurrent networks of the CA3 region, this phase alignment enables the strengthening of synaptic connections between neurons representing adjacent elements of an experience. STDP can thus support the formation of ordered memory traces by selectively reinforcing connections where presynaptic activity consistently predicts postsynaptic firing . This mechanism provides a biological basis for linking discrete experiences into coherent episodes and may underlie the hippocampus’s role in encoding the temporal structure of memory .

Computational models and applications

Training spiking neural networks

The principles of STDP can be utilized in the training of artificial spiking neural networks. Using this approach the weight of a connection between two neurons is increased if the time at which a presynaptic spike ($t_{pre}$) occurs is shortly before the time of a post synaptic spike($t_{post}$), ie. $t=t_{post}-t_{pre}$ and $t>0$. The size of the weight increase is dependent on the value of $t$ and decreases exponentially as the value of $t$ increases given by the equation:

$A_{+}\exp {\left({\frac {-t}{\tau _{+}}}\right)}$

where $A_{+}$ is the maximum possible change and $\tau _{+}$ is the time constant.

If the opposite scenario occurs ie a post synaptic spike occurs before a presynaptic spike then the weight is instead reduced according to the equation:

$A_{-}\exp {\left({\frac {-t}{\tau _{-}}}\right)}$

Where $A_{-}$and $\tau _{-}$ serve the same function of defining the maximum possible change and time constant as before respectively.

The parameters that define the decay profile ($A_{+}$,$A_{-}$, etc.) do not necessarily have to be fixed across the entire network and different synapses may have different shapes associated with them.

Biological evidence suggests that this pairwise STDP approach cannot give a complete description of a biological neuron and more advanced approaches which look at symmetric triplets of spikes (pre-post-pre, post-pre-post) have been developed and these are believed to be more biologically plausible.

Developmental and Critical Period Plasticity

STDP is thought to play significant roles in neural development, particularly during critical periods when activity-dependent refinement of connections is highly pronounced. In early postnatal development, synaptic plasticity mechanisms are transiently enhanced to allow experience to shape neural circuits such as sensory maps. STDP provides an elegant rule for such refinement, and evidence suggests that STDP properties change over development to support different phases of circuit maturation. In the rodent barrel cortex (whisker somatosensory map), for example, synapses initially exhibit a unimodal timing rule, essentially all correlated activity results in potentiation in the first two postnatal weeks. During this stage, any pairing of pre- and postsynaptic spikes tends to strengthen the connection, consistent with a developmental period of synapse stabilization. Then, around the onset of the critical period (approximately 15 days postnatal), classical bidirectional Hebbian STDP emerges at these synapses . The appearance of Hebbian, bidirectional STDP coincides with the maturation of local inhibitory circuits, particularly parvalbumin-positive interneurons, which sharpen the timing of postsynaptic spikes and restrict the time window for plasticity.

This developmental switch from “all-to-potentiation” to “timing-sensitive” plasticity marks a transition from a phase of general connectivity strengthening to one of competitive refinement. It is essential for the onset of the critical period in barrel cortex, as the newly emerged STDP rule allows for the fine-scale weakening of less-active inputs and strengthening of well-timed inputs, sculpting the receptive fields of layer 2/3 neurons to better discriminate whisker-specific inputs .

More broadly, STDP is implicated in critical period plasticity across multiple brain regions. During critical periods in visual cortex, for instance, the timing of pre- and postsynaptic activity (driven by visual experience) likely contributes to synaptic competition underlying ocular dominance plasticity and orientation selectivity . The flexibility of STDP appears to be greater in juvenile brains, studies have found that younger animals can exhibit larger timing-dependent changes, whereas in mature circuits the same STDP protocols might produce smaller effects unless neuromodulatory conditions re-enable plasticity. One contributing factor is the prevalence of NR2B-containing NMDA receptors in early development, which extend the duration of synaptic currents and broaden the timing window for STDP induction. Other developmental changes, such as the strengthening of perisomatic inhibition and the formation of extracellular matrix structures (e.g., perineuronal nets), serve to tighten STDP time windows and limit plasticity, contributing to critical period closure .

Experimental manipulations confirm these roles: increasing inhibition prematurely can close a critical period and suppress STDP, while reducing inhibition or delaying circuit maturation can prolong a plastic, STDP-permissive state . STDP’s contribution to developmental plasticity is also supported by theoretical models, which demonstrate that timing-based rules are sufficient to refine topographic maps and receptive fields in early sensory systems. In summary, STDP works in concert with developmental regulatory processes to ensure that early in life, synaptic connections are broadly strengthened by correlated activity, and later, as inhibition matures, STDP becomes more selective, enabling critical period experiences to fine-tune synapses and solidify mature circuit properties.

Disease and Dysfunction

Given STDP’s central role in synaptic modification, it is perhaps not surprising that abnormalities in STDP have been linked to various neurological disorders. In several diseases, the balance of timing-dependent potentiation and depression is disrupted, leading to impaired learning at the synaptic level.

Alzheimer’s Disease (AD):

In Alzheimer’s disease, synaptic plasticity is known to be impaired. Research in transgenic AD model mice (such as APP/PS1 mice, which accumulate amyloid-beta plaques) indicates that spike-timing-dependent LTP is significantly attenuated near amyloid plaques. CA1 synapses located within a few hundred microns of Aβ plaques show little or no potentiation in response to STDP pairing protocols that reliably induce LTP in healthy neurons, whereas synapses farther from plaques can still undergo normal potentiation. This research suggests that soluble or plaque-associated amyloid-beta pathology interferes with the molecular induction of timing-dependent LTP, possibly by impairing NMDA receptor function or downstream signaling, while leaving basal synaptic transmission relatively intact. Such localized STDP deficits could contribute to the early learning and memory problems in AD by preventing the normal strengthening of synapses through activity. While these results provide important insights into possible mechanisms underlying synaptic dysfunction in Alzheimer’s disease, they are based on preclinical models and may not fully capture the complexity of the human condition. Nevertheless, such localized STDP deficits in these models are hypothesized to contribute to early learning and memory impairments by preventing the normal activity-dependent strengthening of synapses.

Fragile X Syndrome (FXS):

Disorders of neurodevelopment and neuroplasticity also show alterations in STDP. In Fragile X syndrome, studies have observed that cortical synapses have an abnormally high threshold for timing-dependent LTP. Whereas in wild-type animals a modest number of pre-post pairings might suffice to induce potentiation, in Fragile X model mice many more pairings or higher firing rates are required. In effect, the synapses are biased toward LTD unless a strong coincident activity “pushes” them to potentiate. This has been attributed to changes in dendritic ion channel function and protein synthesis regulation caused by FMR1 gene mutation, which in turn affect the ability of a single back-propagating spike to produce a sufficient calcium signal for LTP. The result is a breakdown of normal STDP rules: timing-dependent strengthening is occluded or requires excessive activity, potentially contributing to the synaptic development anomalies and cognitive deficits in Fragile X and related autism spectrum disorders. Notably, experiments showed that providing extra postsynaptic depolarization or burst firing could overcome this raised threshold and rescue LTP in the Fragile X model, suggesting the core plasticity machinery is present but improperly regulated.

Parkinson’s Disease (PD):

STDP abnormalities are also implicated in circuit disorders like Parkinson’s disease. In PD, a clear link exists between dopamine loss and STDP disruption. Dopamine is required for normal STDP in the basal ganglia; specifically, corticostriatal synapses in the striatum typically need dopamine D1-receptor activation to undergo LTP with pre-post spike pairing. In PD models (and patients) with dopamine depletion, corticostriatal STDP tends to bias toward LTD or no change, essentially preventing the reinforcement of cortical inputs to the striatum. This shift in the plasticity regime, from a bidirectional one to predominantly depressive, is thought to contribute to the motor learning deficits and abnormal network oscillations in PD. Indeed, studies have noted that applying dopamine or mimicking its signaling can restore more normal STDP outcomes in dopamine-depleted circuits, highlighting STDP’s dependence on intact neuromodulatory systems.

Epilepsy:

In epilepsy, recurrent seizures and hyperexcitability might lead to maladaptive timing-dependent synaptic changes, such as uncontrolled LTP at excitatory synapses or LTD of inhibitory synapses. While research in this area is ongoing, alterations in STDP mechanisms are believed to contribute to the pathophysiology of epileptic networks .

Psychiatric and Mood Disorders:

Beyond PD, other psychiatric and mood disorders might involve STDP changes via neuromodulatory dysregulation. For example, chronic stress elevates corticosteroid levels, which can alter calcium dynamics and NMDA receptor function, potentially narrowing the STDP window or favoring LTD, a mechanism proposed to underlie stress-related cognitive impairments. Similarly, addiction and reward learning alterations have been linked to aberrant dopamine-modulated STDP in reward pathways.

Crucially, these insights suggest potential therapeutic angles. If a disease state biases synaptic timing rules (e.g., preventing LTP in AD or PD), treatments that re-balance STDP could ameliorate symptoms. For instance, drugs that reduce amyloid load or enhance NMDA receptor function might restore timing-dependent potentiation in early Alzheimer’s, and dopaminergic medications in PD not only alleviate symptoms but may also normalize synaptic plasticity in basal ganglia circuits. Research in neurological and psychiatric disorders increasingly points to STDP and related plasticity as sites where pathology and therapy intersect. Altered neuromodulation of STDP in disorders suggests that targeting neuromodulatory receptors (D1, muscarinic, adrenergic, etc.) might help correct abnormal learning rules .

In summary, a range of brain disorders involve measurable disruptions in the normal timing-dependent plasticity of synapses, linking the molecular pathology of disease to changes in how neural circuits adapt, or fail to adapt, to activity.

Interaction with Other Forms of Plasticity

Spike-timing-dependent plasticity (STDP) does not operate in isolation; it interacts with and is constrained by other plasticity mechanisms to ensure coherent learning and network stability.

Interaction with Rate-Based Plasticity (BCM Theory):

One important interaction is with rate-based plasticity as described by the Bienenstock–Cooper–Munro (BCM) theory. Classical experiments showed that high-frequency presynaptic stimulation tends to induce long-term potentiation (LTP), while low-frequency stimulation induces long-term depression (LTD), independent of precise spike timing. STDP can be viewed as a timing-refined extension of these principles, and studies have found that spike timing rules are modulated by overall firing rate. For example, at neocortical synapses, if pre/post pairs are repeated at low frequencies (around 0.1–1 Hz), LTD dominates even for pre-before-post ordering, whereas at higher pairing frequencies (around 20–40 Hz), LTP can be obtained even for normally LTD timing. In one series of experiments, Sjöström et al. (2001) observed that when layer-2/3 synapses were stimulated at 0.1 Hz, post-leading-pre spiking reliably produced LTD, but if the same pairing was done at 10 Hz, the outcome shifted toward LTP regardless of order. Thus, the neuron's recent firing rate or burst activity can set a permissive range for STDP. At intermediate firing rates, the traditional STDP time dependence is seen, but outside that range, the timing rule "saturates" into the conventional frequency-dependent rule (with high-frequency favoring potentiation and very low-frequency favoring depression). This synergy shows that STDP and rate-based plasticity utilize common intracellular pathways. Mechanistically, higher repetition rates produce greater temporal summation of postsynaptic depolarization and calcium, satisfying the LTP requirements even for unfavorable timing, whereas very sparse activity may not sufficiently depolarize the postsynaptic neuron to permit LTP at all. In effect, the BCM sliding threshold concept, where the threshold between LTD and LTP moves based on average activity, can be partly understood as a modulation of STDP criteria by firing rate.

Interaction with Homeostatic Plasticity:

Another critical interaction is between STDP and homeostatic plasticity mechanisms that maintain overall neuronal stability. If each synapse modified itself purely according to STDP, a neuron that receives correlated bursts might potentiate many inputs and become hyperactive, while a neuron with uncorrelated inputs might depress them all and fall silent. Homeostatic plasticity prevents such extremes by adjusting synaptic strengths and intrinsic excitability in a compensatory manner . For instance, neurons can implement synaptic scaling: if overall firing drops below a set point, all excitatory synapses are up-regulated in gain, whereas if firing is too high, synapses are uniformly down-scaled. This process interacts with STDP by globally dampening or enhancing the magnitude of changes but preserving relative differences learned through timing. Additionally, homeostatic mechanisms can modulate the ability of synapses to undergo STDP based on their history (a form of metaplasticity). Experiments have shown that after a neuron undergoes long-term potentiation at many synapses, the requirements for further LTP become more stringent (the modification threshold slides upward), a phenomenon predicted by BCM theory and observed empirically as well . This ensures that synapses have a refractory period or a limit to potentiation, preventing runaway positive feedback. Conversely, if a neuron has been largely inactive, synapses may become more plastic or sensitive, lowering thresholds to allow learning to occur once activity resumes. Such metaplastic adjustment is crucial during development and learning; it may involve changes in NMDA receptor subunit composition or in the levels of plasticity-related proteins.

Interaction with Short-Term and Structural Plasticity:

STDP also intersects with other forms of synaptic plasticity like short-term plasticity and structural plasticity. Short-term synaptic changes (facilitation and depression on the scale of milliseconds to seconds) can influence STDP by affecting the effective spike pattern seen at the synapse. For example, if a presynaptic neuron fires two spikes in rapid succession, short-term facilitation may increase the second spike's excitatory postsynaptic potential (EPSP) amplitude, thereby giving that spike pair a greater chance to induce LTP if appropriately timed with a postsynaptic spike. In this way, short-term dynamics gate the induction of long-term changes. Moreover, STDP induction itself can alter release probability and short-term plasticity at synapses as part of its expression (e.g., timing-dependent LTD often involves reduced release probability, which will manifest as increased paired-pulse facilitation). There is also evidence for heterosynaptic plasticity accompanying STDP: when some synapses undergo potent Hebbian LTP, neighboring unstimulated synapses sometimes weaken to compensate (providing additional homeostatic balance). This heterosynaptic LTD can ensure the neuron's total synaptic weight does not increase uncontrollably as a result of STDP at a subset of inputs. On longer timescales, STDP can drive structural changes such as the growth of new dendritic spines or the enlargement of existing spines that were potentiated. Such structural plasticity solidifies the functional changes induced by STDP and can create opportunities for new synaptic contacts (which themselves will be subject to activity-driven refinement). Conversely, spine shrinkage and elimination have been observed after long-term depression, which may be initiated by anti-correlated spike timing. These structural outcomes feed back into the circuit, as the gain or loss of synapses will alter the connectivity landscape on which STDP operates.

To summarize, STDP is one component of a multifaceted plasticity framework. It coexists and cooperates with mechanisms like rate-dependent plasticity, synaptic scaling, and metaplasticity. The interactions are such that STDP provides specificity and competition at the level of individual synapses, while homeostatic plasticity provides stability and global regulation. Together, they resolve the challenge of learning in a dynamic environment: Hebbian STDP finds and reinforces temporal patterns, and homeostatic/heterosynaptic processes prevent those changes from destabilizing the neuron. This balance allows neural circuits to retain the flexibility conferred by STDP's timing-based learning rules without sacrificing the overall equilibrium required for consistent function.

See also

• Synaptic plasticity
• Didactic organisation

Further reading

• Rumsey CC, Abbott LF (May 2004). "Equalization of synaptic efficacy by activity- and timing-dependent synaptic plasticity". Journal of Neurophysiology. 91 (5): 2273–80. CiteSeerX 10.1.1.323.8776. doi:10.1152/jn.00900.2003. PMID 14681332.
• Debanne D, Gähwiler BH, Thompson SM (February 1994). "Asynchronous pre- and postsynaptic activity induces associative long-term depression in area CA1 of the rat hippocampus in vitro". Proceedings of the National Academy of Sciences of the United States of America. 91 (3): 1148–52. Bibcode:1994PNAS...91.1148D. doi:10.1073/pnas.91.3.1148. PMC 521471. PMID 7905631.
• Sjöström PJ, Turrigiano GG, Nelson SB (December 2001). "Rate, timing, and cooperativity jointly determine cortical synaptic plasticity". Neuron. 32 (6): 1149–64. doi:10.1016/S0896-6273(01)00542-6. PMID 11754844. S2CID 14092591.
• Senn W, Markram H, Tsodyks M (January 2001). "An algorithm for modifying neurotransmitter release probability based on pre- and postsynaptic spike timing". Neural Computation. 13 (1): 35–67. doi:10.1162/089976601300014628. PMID 11177427. S2CID 9091640.
• Roberts PD, Bell CC (December 2002). "Spike timing dependent synaptic plasticity in biological systems". Biological Cybernetics. 87 (5–6): 392–403. doi:10.1007/s00422-002-0361-y. PMID 12461629. S2CID 8202648.
• Chechik G (July 2003). "Spike-timing-dependent plasticity and relevant mutual information maximization". Neural Computation. 15 (7): 1481–510. CiteSeerX 10.1.1.118.4572. doi:10.1162/089976603321891774. PMID 12816563. S2CID 10483746.
• Lisman J, Spruston N (July 2005). "Postsynaptic depolarization requirements for LTP and LTD: a critique of spike timing-dependent plasticity". Nature Neuroscience. 8 (7): 839–41. doi:10.1038/nn0705-839. PMID 16136666. S2CID 35555400.
• Sjöström, Jesper; Wulfram Gerstner (2010). "Spike-timing dependent plasticity". Scholarpedia. 5 (2): 1362. Bibcode:2010SchpJ...5.1362S. doi:10.4249/scholarpedia.1362. ISSN 1941-6016.
• Caporale, Natalia; Yang Dan (2008). "Spike Timing–Dependent Plasticity: A Hebbian Learning Rule". Annual Review of Neuroscience. 31 (1): 25–46. doi:10.1146/annurev.neuro.31.060407.125639. ISSN 0147-006X. PMID 18275283.
• Oertner, Thomas G. (2009). "How do synapses measure milliseconds?". Frontiers in Computational Neuroscience. 3: 7. doi:10.3389/neuro.10.007.2009. PMC 2692454. PMID 19564894.

External links

• Spike-timing dependent plasticity - Scholarpedia