Asymmetric spike-timing dependent plasticity of striatal nitric oxide-synthase interneurons

Enhancing reinforcement learning models by including direct and indirect pathways improves performance on striatal dependent tasks

A major advance in understanding learning behavior stems from experiments showing that reward learning requires dopamine inputs to striatal neurons and arises from synaptic plasticity of cortico-striatal synapses. Numerous reinforcement learning models mimic this dopamine-dependent synaptic plasticity by using the reward prediction error, which resembles dopamine neuron firing, to learn the best action in response to a set of cues. Though these models can explain many facets of behavior, reproducing some types of goal-directed behavior, such as renewal and reversal, require additional model components. Here we present a reinforcement learning model, TD2Q, which better corresponds to the basal ganglia with two Q matrices, one representing direct pathway neurons (G) and another representing indirect pathway neurons (N). Unlike previous two-Q architectures, a novel and critical aspect of TD2Q is to update the G and N matrices utilizing the temporal difference reward prediction error. A best action is selected for N and G using a softmax with a reward-dependent adaptive exploration parameter, and then differences are resolved using a second selection step applied to the two action probabilities. The model is tested on a range of multi-step tasks including extinction, renewal, discrimination; switching reward probability learning; and sequence learning. Simulations show that TD2Q produces behaviors similar to rodents in choice and sequence learning tasks, and that use of the temporal difference reward prediction error is required to learn multi-step tasks. Blocking the update rule on the N matrix blocks discrimination learning, as observed experimentally. Performance in the sequence learning task is dramatically improved with two matrices. These results suggest that including additional aspects of basal ganglia physiology can improve the performance of reinforcement learning models, better reproduce animal behaviors, and provide insight as to the role of direct- and indirect-pathway striatal neurons.

Sensory Reinforced Corticostriatal Plasticity

BACKGROUND

Regional changes in corticostriatal transmission induced by phasic dopaminergic signals are an essential feature of the neural network responsible for instrumental reinforcement during discovery of an action. However, the timing of signals that are thought to contribute to the induction of corticostriatal plasticity is difficult to reconcile within the framework of behavioural reinforcement learning, because the reinforcer is normally delayed relative to the selection and execution of causally-related actions.

OBJECTIVE

While recent studies have started to address the relevance of delayed reinforcement signals and their impact on corticostriatal processing, our objective was to establish a model in which a sensory reinforcer triggers appropriately delayed reinforcement signals relayed to the striatum via intact neuronal pathways and to investigate the effects on corticostriatal plasticity.

METHODS

We measured corticostriatal plasticity with electrophysiological recordings using a light flash as a natural sensory reinforcer, and pharmacological manipulations were applied in an in vivo anesthetized rat model preparation.

RESULTS

We demonstrate that the spiking of striatal neurons evoked by single-pulse stimulation of the motor cortex can be potentiated by a natural sensory reinforcer, operating through intact afferent pathways, with signal timing approximating that required for behavioural reinforcement. The pharmacological blockade of dopamine receptors attenuated the observed potentiation of corticostriatal neurotransmission.

CONCLUSION

This novel in vivo model of corticostriatal plasticity offers a behaviourally relevant framework to address the physiological, anatomical, cellular, and molecular bases of instrumental reinforcement learning.

Long-term follow-up of dynamic brain changes in patients recovered from COVID-19 without neurological manifestations

BACKGROUND

After the initial surge in COVID-19 cases, large numbers of patients were discharged from a hospital without assessment of recovery. Now, an increasing number of patients report postacute neurological sequelae, known as “long COVID” — even those without specific neurological manifestations in the acute phase.

METHODS

Dynamic brain changes are crucial for a better understanding and early prevention of “long COVID.” Here, we explored the cross-sectional and longitudinal consequences of COVID-19 on the brain in 34 discharged patients without neurological manifestations. Gray matter morphology, cerebral blood flow (CBF), and volumes of white matter tracts were investigated using advanced magnetic resonance imaging techniques to explore dynamic brain changes from 3 to 10 months after discharge.

RESULTS

Overall, the differences of cortical thickness were dynamic and finally returned to the baseline. For cortical CBF, hypoperfusion in severe cases observed at 3 months tended to recover at 10 months. Subcortical nuclei and white matter differences between groups and within subjects showed various trends, including recoverable and long-term unrecovered differences. After a 10-month recovery period, a reduced volume of nuclei in severe cases was still more extensive and profound than that in mild cases.

CONCLUSION

Our study provides objective neuroimaging evidence for the coexistence of recoverable and long-term unrecovered changes in 10-month effects of COVID-19 on the brain. The remaining potential abnormalities still deserve public attention, which is critically important for a better understanding of “long COVID” and early clinical guidance toward complete recovery.

FUNDING

National Natural Science Foundation of China.

Cholinergic modulation of striatal microcircuits

The purpose of this review is to bridge the gap between earlier literature on striatal cholinergic interneurons and mechanisms of microcircuit interaction demonstrated with the use of newly available tools. It is well known that the main source of the high level of acetylcholine in the striatum, compared to other brain regions, is the cholinergic interneurons. These interneurons provide an extensive local innervation that suggests they may be a key modulator of striatal microcircuits. Supporting this idea requires the consideration of functional properties of these interneurons, their influence on medium spiny neurons, other interneurons, and interactions with other synaptic regulators. Here, we underline the effects of intrastriatal and extrastriatal afferents onto cholinergic interneurons and discuss the activation of pre‐ and postsynaptic muscarinic and nicotinic receptors that participate in the modulation of intrastriatal neuronal interactions. We further address recent findings about corelease of other transmitters in cholinergic interneurons and actions of these interneurons in striosome and matrix compartments. In addition, we summarize recent evidence on acetylcholine‐mediated striatal synaptic plasticity and propose roles for cholinergic interneurons in normal striatal physiology. A short examination of their role in neurological disorders such as Parkinson's, Huntington's, and Tourette's pathologies and dystonia is also included.

Region-specific and state-dependent action of striatal GABAergic interneurons

Striatum processes a wide range of functions including goal-directed behavior and habit formation, respectively encoded by the dorsomedial striatum (DMS) and dorsolateral striatum (DLS). GABAergic feedforward inhibition is known to control the integration of cortical information by striatal projection neurons (SPNs). Here we questioned whether this control is specific between distinct striatal functional territories. Using opto-activation and opto-inhibition of identified GABAergic interneurons, we found that different circuits are engaged in DLS and DMS, both ex vivo and in vivo: while parvalbumin interneurons efficiently control SPNs in DLS, somatostatin interneurons control SPNs in DMS. Moreover, both parvalbumin and somatostatin interneurons use a dual hyperpolarizing/depolarizing effect to control cortical input integration depending on SPN activity state: GABAergic interneurons potently inhibit spiking SPNs while in resting SPNs, they favor cortical activity summation via a depolarizing effect. Our findings establish that striatal GABAergic interneurons exert efficient territory-specific and state-dependent control of SPN activity and functional output.

Interplay of multiple pathways and activity-dependent rules in STDP

Hebbian plasticity describes a basic mechanism for synaptic plasticity whereby synaptic weights evolve depending on the relative timing of paired activity of the pre- and postsynaptic neurons. Spike-timing-dependent plasticity (STDP) constitutes a central experimental and theoretical synaptic Hebbian learning rule. Various mechanisms, mostly calcium-based, account for the induction and maintenance of STDP. Classically STDP is assumed to gradually emerge in a monotonic way as the number of pairings increases. However, non-monotonic STDP accounting for fast associative learning led us to challenge this monotonicity hypothesis and explore how the existence of multiple plasticity pathways affects the dynamical establishment of plasticity. To account for distinct forms of STDP emerging from increasing numbers of pairings and the variety of signaling pathways involved, we developed a general class of simple mathematical models of plasticity based on calcium transients and accommodating various calcium-based plasticity mechanisms. These mechanisms can either compete or cooperate for the establishment of long-term potentiation (LTP) and depression (LTD), that emerge depending on past calcium activity. Our model reproduces accurately the striatal STDP that involves endocannabinoid and NMDAR signaling pathways. Moreover, we predict how stimulus frequency alters plasticity, and how triplet rules are affected by the number of pairings. We further investigate the general model with an arbitrary number of pathways and show that depending on those pathways and their properties, a variety of plasticities may emerge upon variation of the number and/or the frequency of pairings, even when the outcome after large numbers of pairings is identical. These findings, built upon a biologically realistic example and generalized to other applications, argue that in order to fully describe synaptic plasticity it is not sufficient to record STDP curves at fixed pairing numbers and frequencies. In fact, considering the whole spectrum of activity-dependent parameters could have a great impact on the description of plasticity, and a better understanding of the engram.

The brain’s capacity to treat information, learn and store memory relies on synaptic connectivity patterns, which are altered through synaptic plasticity mechanisms. Experimentally, such plasticities were evidenced through protocols involving numerous repetitive stimulations of a given synapse, and were shown to be supported by multiple pathways. Using a simple biologically grounded mathematical model, we show how activation timescales and inactivation levels of each pathway interact and alter plasticity in an intricate manner as stimuli are presented. Building upon data from the synapse between cortex and striatum, we show that synaptic changes may revert or re-emerge as stimuli are presented, and predict specific responses to changes in stimulus frequency or to distinct simulation patterns. Our general model shows that a given plasticity profile emerging in response to a repetitive stimulation protocol can unfold into various scenarii upon variations of the number of stimulus presentations or patterns, which tightly depends on the underlying activated pathways. Altogether, these results argue that in order to better understand learning and memory, single plasticity responses obtained through intensive stimulations do not reveal the complexity of the responses for smaller number of presentations, which may have a strong impact in fast learning of stimuli with low numbers of presentations.

Modulation of Spike-Timing Dependent Plasticity: Towards the Inclusion of a Third Factor in Computational Models

In spike-timing dependent plasticity (STDP) change in synaptic strength depends on the timing of pre- vs. postsynaptic spiking activity. Since STDP is in compliance with Hebb's postulate, it is considered one of the major mechanisms of memory storage and recall. STDP comprises a system of two coincidence detectors with N-methyl-D-aspartate receptor (NMDAR) activation often posited as one of the main components. Numerous studies have unveiled a third component of this coincidence detection system, namely neuromodulation and glia activity shaping STDP. Even though dopaminergic control of STDP has most often been reported, acetylcholine, noradrenaline, nitric oxide (NO), brain-derived neurotrophic factor (BDNF) or gamma-aminobutyric acid (GABA) also has been shown to effectively modulate STDP. Furthermore, it has been demonstrated that astrocytes, via the release or uptake of glutamate, gate STDP expression. At the most fundamental level, the timing properties of STDP are expected to depend on the spatiotemporal dynamics of the underlying signaling pathways. However in most cases, due to technical limitations experiments grant only indirect access to these pathways. Computational models carefully constrained by experiments, allow for a better qualitative understanding of the molecular basis of STDP and its regulation by neuromodulators. Recently, computational models of calcium dynamics and signaling pathway molecules have started to explore STDP emergence in ex and in vivo-like conditions. These models are expected to reproduce better at least part of the complex modulation of STDP as an emergent property of the underlying molecular pathways. Elucidation of the mechanisms underlying STDP modulation and its consequences on network dynamics is of critical importance and will allow better understanding of the major mechanisms of memory storage and recall both in health and disease.

Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum

Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized computational entities, each contributing to the global activity, not in a simply linear fashion, but in a manner that is appropriate to achieve local and global stability of the neuron and the entire dendritic structure.

Symmetry of learning rate in synaptic plasticity modulates formation of flexible and stable memories

Spike-timing-dependent plasticity (STDP) is considered critical to learning and memory functions in the human brain. Across various types of synapse, STDP is observed as different profiles of Hebbian and anti-Hebbian learning rules. However, the specific roles of diverse STDP profiles in memory formation still remain elusive. Here, we show that the symmetry of the learning rate profile in STDP is crucial to determining the character of stored memory. Using computer simulations, we found that an asymmetric learning rate generates flexible memory that is volatile and easily overwritten by newly appended information. Moreover, a symmetric learning rate generates stable memory that can coexist with newly appended information. In addition, by combining these two conditions, we could realize a hybrid memory type that operates in a way intermediate between stable and flexible memory. Our results demonstrate that various attributes of memory functions may originate from differences in the synaptic stability.

GluA2-Lacking AMPA Receptors and Nitric Oxide Signaling Gate Spike-Timing-Dependent Potentiation of Glutamate Synapses in the Dorsal Raphe Nucleus

The dorsal raphe nucleus (DRn) receives glutamatergic inputs from numerous brain areas that control the function of DRn serotonin (5-HT) neurons. By integrating these synaptic inputs, 5-HT neurons modulate a plethora of behaviors and physiological functions. However, it remains unknown whether the excitatory inputs onto DRn 5-HT neurons can undergo activity-dependent change of strength, as well as the mechanisms that control their plasticity. Here, we describe a novel form of spike-timing–dependent long-term potentiation (tLTP) of glutamate synapses onto rat DRn 5-HT neurons. This form of synaptic plasticity is initiated by an increase in postsynaptic intracellular calcium but is maintained by a persistent increase in the probability of glutamate release. The tLTP of glutamate synapses onto DRn 5-HT is independent of NMDA receptors but requires the activation of calcium-permeable AMPA receptors and voltage-dependent calcium channels. The presynaptic expression of the tLTP is mediated by the retrograde messenger nitric oxide (NO) and activation of cGMP/PKG pathways. Collectively, these results indicate that glutamate synapses in the DRn undergo activity-dependent synaptic plasticity gated by NO signaling and unravel a previously unsuspected role of NO in controlling synaptic function and plasticity in the DRn.

Accumbens nNOS Interneurons Regulate Cocaine Relapse

Relapse to drug use can be initiated by drug-associated cues. The intensity of cue-induced relapse is correlated with the induction of transient synaptic potentiation (t-SP) at glutamatergic synapses on medium spiny neurons (MSNs) in the nucleus accumbens core (NAcore) and requires spillover of glutamate from prefrontal cortical afferents. We used a rodent self-administration/reinstatement model of relapse to show that cue-induced t-SP and reinstated cocaine seeking result from glutamate spillover, initiating a metabotropic glutamate receptor 5 (mGluR5)-dependent increase in nitric oxide (NO) production. Pharmacological stimulation of mGluR5 in NAcore recapitulated cue-induced reinstatement in the absence of drug-associated cues. Using NO-sensitive electrodes, mGluR5 activation by glutamate was shown to stimulate NO production that depended on activation of neuronal nitric oxide synthase (nNOS). nNOS is expressed in ∼1% of NAcore neurons. Using a transgene strategy to express and stimulate designer receptors that mimicked mGluR5 signaling through Gq in nNOS interneurons, we recapitulated cue-induced reinstatement in the absence of cues. Conversely, using a transgenic caspase strategy, the intensity of cue-induced reinstatement was correlated with the extent of selective elimination of nNOS interneurons. The induction of t-SP during cued reinstatement depends on activating matrix metalloproteinases (MMPs) and selective chemogenetic stimulation of nNOS interneurons recapitulated MMP activation and t-SP induction (increase in AMPA currents in MSNs). These data demonstrate critical involvement of a sparse population of nNOS-expressing interneurons in cue-induced cocaine seeking, revealing a bottleneck in brain processing of drug-associated cues where therapeutic interventions could be effective in treating drug addiction.

SIGNIFICANCE STATEMENT

Relapse to cocaine use in a rat model is associated with transient increases in synaptic strength at prefrontal cortex synapses in the nucleus accumbens. We demonstrate the sequence of events that mediates synaptic potentiation and reinstated cocaine seeking induced by cocaine-conditioned cues. Activation of prefrontal inputs to the accumbens by cues initiates spillover of synaptic glutamate, which stimulates metabotropic glutamate receptor 5 (mGluR5) on a small population of interneurons (∼1%) expressing neuronal nitric oxide synthase. Stimulating these glutamate receptors increases nitric oxide (NO) production, which stimulates matrix metalloprotease-2 (MMP-2) and MMP-9 activity in the extracellular space. Manipulating the interaction between mGluR5, NO production, or MMP-2 and MMP-9 pharmacologically or genetically is sufficient to recapitulate transient synaptic potentiation and reinstate cocaine seeking.

Spike-timing-dependent plasticity enhanced synchronization transitions induced by autapses in adaptive Newman-Watts neuronal networks

In this paper, we numerically study the effect of spike-timing-dependent plasticity (STDP) on synchronization transitions induced by autaptic activity in adaptive Newman-Watts Hodgkin-Huxley neuron networks. It is found that synchronization transitions induced by autaptic delay vary with the adjusting rate A_p of STDP and become strongest at a certain A_p value, and the A_p value increases when network randomness or network size increases. It is also found that the synchronization transitions induced by autaptic delay become strongest at a certain network randomness and network size, and the values increase and related synchronization transitions are enhanced when A_p increases. These results show that there is optimal STDP that can enhance the synchronization transitions induced by autaptic delay in the adaptive neuronal networks. These findings provide a new insight into the roles of STDP and autapses for the information transmission in neural systems.

Synaptic Metaplasticity Realized in Oxide Memristive Devices

Metaplasticity, a higher order of synaptic plasticity, as well as a key issue in neuroscience, is realized with artificial synapses based on a WO3 thin film, and the activity-dependent metaplastic responses of the artificial synapses, such as spike-timing-dependent plasticity, are systematically investigated. This work has significant implications in neuromorphic computation.

Acute restraint stress induces specific changes in nitric oxide production and inflammatory markers in the rat hippocampus and striatum

Chronic mild stress has been shown to cause hippocampal neuronal nitric oxide synthase (NOS) overexpression and the resultant nitric oxide (NO) production has been implicated in the etiology of depression. However, the extent of nitrosative changes including NOS enzymatic activity and the overall output of NO production in regions of the brain like the hippocampus and striatum following acute stress has not been characterized. In this study, outbred male Wistar rats aged 6-7 weeks were randomly allocated into 0 (control), 60, 120, or 240 min stress groups and neural regions were cryodissected for measurement of constitutive and inducible NOS enzymatic activity, nitrosative status, and relative gene expression of neuronal and inducible NOS. Hippocampal constitutive NOS activity increased initially but was superseded by the inducible isoform as stress duration was prolonged. Interestingly, hippocampal neuronal NOS and interleukin-1β mRNA expression was downregulated, while the inducible NOS isoform was upregulated in conjunction with other inflammatory markers. This pro-inflammatory phenotype within the hippocampus was further confirmed with an increase in the glucocorticoid-antagonizing macrophage migration inhibitory factor, Mif, and the glial surveillance marker, Ciita. This indicates that despite high levels of glucocorticoids, acute stress sensitizes a neuroinflammatory response within the hippocampus involving both pro-inflammatory cytokines and inducible NOS while concurrently modulating the immunophenotype of glia. Furthermore, there was a delayed increase in striatal inducible NOS expression while no change was found in other pro-inflammatory mediators. This suggests that short term stress induces a generalized increase in inducible NOS signaling that coincides with regionally specific increased markers of adaptive immunity and inflammation within the brain.

Mixed signal learning by spike correlation propagation in feedback inhibitory circuits

The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory.

Dopamine D1 and D5 receptors modulate spike timing-dependent plasticity at medial perforant path to dentate granule cell synapses

Although evidence suggests that DA modulates hippocampal function, the mechanisms underlying that dopaminergic modulation are largely unknown. Using perforated-patch electrophysiological techniques to maintain the intracellular milieu, we investigated how the activation of D1-type DA receptors regulates spike timing-dependent plasticity (STDP) of the medial perforant path (mPP) synapse onto dentate granule cells. When D1-type receptors were inhibited, a relatively mild STDP protocol induced LTP only within a very narrow timing window between presynaptic stimulation and postsynaptic response. The stimulus protocol produced timing-dependent LTP (tLTP) only when the presynaptic stimulation was followed 30 ms later by depolarization-induced postsynaptic action potentials. That is, the time between presynaptic stimulation and postsynaptic response was 30 ms (Δt = +30 ms). When D1-type receptors were activated, however, the same mild STDP protocol induced tLTP over a much broader timing window: tLTP was induced when -30 ms ≤ Δt ≤ +30 ms. The result indicated that D1-type receptor activation enabled synaptic potentiation even when postsynaptic activity preceded presynaptic stimulation within this Δt range. Results with null mice lacking the Kv4.2 potassium channel and with the potassium channel inhibitor, 4-aminopyridine, suggested that D1-type receptors enhanced tLTP induction by suppressing the transient IA-type K(+) current. Results obtained with antagonists and DA receptor knock-out mice indicated that endogenous activity of both D1 and D5 receptors modulated plasticity in the mPP. The DA D5 receptors appeared particularly important in regulating plasticity of the mPP onto the dentate granule cells.

Effects of spike-time-dependent plasticity on the stochastic resonance of small-world neuronal networks

The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.

Presynaptic long-term depression mediated by Gi/o-coupled receptors

Long-term depression (LTD) of the efficacy of synaptic transmission is now recognized as an important mechanism for the regulation of information storage and the control of actions, as well as for synapse, neuron, and circuit development. Studies of LTD mechanisms have focused mainly on postsynaptic AMPA-type glutamate receptor trafficking. However, the focus has now expanded to include presynaptically expressed plasticity, the predominant form being initiated by presynaptically expressed Gi/o-coupled metabotropic receptor (Gi/o-GPCR) activation. Several forms of LTD involving activation of different presynaptic Gi/o-GPCRs as a 'common pathway' are described. We review here the literature on presynaptic Gi/o-GPCR-mediated LTD, discuss known mechanisms, gaps in our knowledge, and evaluate whether all Gi/o-GPCRs are capable of inducing presynaptic LTD.

Excitatory and inhibitory STDP jointly tune feedforward neural circuits to selectively propagate correlated spiking activity

Spike-timing-dependent plasticity (STDP) has been well established between excitatory neurons and several computational functions have been proposed in various neural systems. Despite some recent efforts, however, there is a significant lack of functional understanding of inhibitory STDP (iSTDP) and its interplay with excitatory STDP (eSTDP). Here, we demonstrate by analytical and numerical methods that iSTDP contributes crucially to the balance of excitatory and inhibitory weights for the selection of a specific signaling pathway among other pathways in a feedforward circuit. This pathway selection is based on the high sensitivity of STDP to correlations in spike times, which complements a recent proposal for the role of iSTDP in firing-rate based selection. Our model predicts that asymmetric anti-Hebbian iSTDP exceeds asymmetric Hebbian iSTDP for supporting pathway-specific balance, which we show is useful for propagating transient neuronal responses. Furthermore, we demonstrate how STDPs at excitatory-excitatory, excitatory-inhibitory, and inhibitory-excitatory synapses cooperate to improve the pathway selection. We propose that iSTDP is crucial for shaping the network structure that achieves efficient processing of synchronous spikes.

The rat prefrontostriatal system analyzed in 3D: evidence for multiple interacting functional units

Previous studies in monkeys disclosed a specific arrangement of corticostriatal projections. Prefrontal and premotor areas form dense projection fields surrounded by diffuse terminal areas extending outside the densely innervated region and overlapping with projections from other areas. In this study, the mode of prefrontostriatal innervation was analyzed in rats using a 3D approach. Following injections of tracers in defined cortical areas, 3D maps from individual cases were elaborated and combined into a global 3D map allowing us to define putative overlaps between projection territories. In addition to providing a detailed 3D mapping of the topographic representation of prefrontal cortical areas in the rat striatum, the results stress important similarities between the rodent and primate prefrontostriatal projections. They share the dual pattern of focal and diffuse corticostriatal projections. Moreover, besides segregated projections consistent with parallel processing, the interweaving of projection territories establishes specific patterns of overlaps spatially organized along the dorsoventral, mediolateral, and anteroposterior striatal axis. In particular, the extensive striatal projection fields from the prelimbic and anterior cingulate areas, which partly overlap the terminal fields from medial, orbital, and lateral prefrontal cortical areas, provide putative domains of convergence for integration between reward, cognitive, and motor processes.

The spike-timing dependence of plasticity

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.

Impact of environmental thermal stimulation on activation of hypothalamic neuronal nitric oxide synthase during the prenatal ontogenesis in Muscovy ducks

The aim of the study is to investigate the influence of prenatal temperature stimulation on neuronal NO synthase (nNOS) expression in the anterior hypothalamus of Muscovy duck embryos. Experiments were performed on embryonic day (E) E20, E23, E28, and E33 using histochemistry for identification of the nicotinamide adenine dinucleotide phosphate-diaphorase (NADPH-d) as marker of NOS-containing neurons. Until the experiments, all duck embryos were incubated under standard temperature conditions (37.5°C). During 3 hours before the start of the experiments, one group was incubated at 37.5°C (control group), the second was warm-experienced at 39°C, and the third was cold-experienced at 34°C. In normal and warm-incubated duck embryos, nNOS activity could be first detected on E23. Particularly, after cold stimulation, a significant increase in nNOS activity was found in all embryos investigated even on day 20. Warm stimulation obviously induces the opposite effect, but at later embryonic age (E33). It can be concluded that probably in late-term bird embryos NO acts as a mediator of the neuronal cold pathway in the anterior hypothalamus, which might be improved by prenatal cold stimulation.

Contribution of astrocytic glutamate and GABA uptake to corticostriatal information processing

The astrocytes, active elements of the tripartite synapse, remove most of the neurotransmitter that spills over the synaptic cleft. Neurotransmitter uptake operated by astrocytes contributes to the strength and timing of synaptic inputs. The striatum, the main input nucleus of basal ganglia, extracts pertinent cortical signals from the background noise and relays cortical information toward basal ganglia output structures. We investigated the role of striatal astrocytic uptake in the shaping of corticostriatal transmission.We performed dual patch-clamp recordings of striatal output neuron (the medium-sized spiny neurons, MSNs)–astrocyte pairs while stimulating the somatosensory cortex. Cortical activity evoked robust synaptically activated transporter-mediated currents (STCs) in 78% of the recorded astrocytes. STCs originated equally from the activities of glutamate transporters and GABA transporters (GATs). Astrocytic STCs reflected here a presynaptic release of neurotransmitters. STCs displayed a large magnitude associated with fast kinetics, denoting an efficient neurotransmitter clearance at the corticostriatal pathway. Inhibition of glutamate transporters type-1 (GLT-1) and GATs decreased the corticostriatal synaptic transmission, through, respectively, desensitization of AMPA receptors and activation of GABAA receptor. STCs displayed a bidirectional short-term plasticity (facilitation for paired-pulse intervals less than 100 ms and depression up to 1 s).We report a genuine facilitation of STCs for high-frequency cortical activity, which could strengthen the detection properties of cortical activity operated by MSNs. MSN EPSCs showed a triphasic short-term plasticity, which was modified by the blockade of GLT-1 or GATs. We show here that neurotransmitter uptake by astrocytes plays a key role in the corticostriatal information processing.

Spike-timing dependent plasticity in striatal interneurons

Basal ganglia, an ensemble of interconnected subcortical nuclei, are involved in adaptive motor planning and procedural learning. Striatum, the primary input nucleus of basal ganglia, extracts the pertinent cortical and thalamic information from background noise in relation with the environmental stimuli and motivation. The striatum comprises different neuronal populations: the GABAergic striatal output neurons, three classes of GABAergic interneurons and the cholinergic cells. Striatal interneurons exert a powerful control of striatal output neuron excitability and therefore shape the cortico-basal ganglia information processing. Besides output neurons, striatal interneurons also receive directly cortical information and are able to adapt their behavior depending on the level of cortical and striatal activation. In this review, we focus on the corticostriatal long-term synaptic efficacy changes occurring in interneurons, and especially the spike-timing dependent plasticity (STDP), as a Hebbian synaptic learning rule. Combined with the striatal local interactions between interneurons and output neurons, we will consider the functional consequences of the interneuron plasticity on the striatal output. This article is part of a Special Issue entitled 'Synaptic Plasticity & Interneurons'.

Spike-timing-dependent plasticity in the intact brain: counteracting spurious spike coincidences

A computationally rich algorithm of synaptic plasticity has been proposed based on the experimental observation that the sign and amplitude of the change in synaptic weight is dictated by the temporal order and temporal contiguity between pre- and postsynaptic activities. For more than a decade, this spike-timing-dependent plasticity (STDP) has been studied mainly in brain slices of different brain structures and cultured neurons. Although not yet compelling, evidences for the STDP rule in the intact brain, including primary sensory cortices, have been provided lastly. From insects to mammals, the presentation of precisely timed sensory inputs drives synaptic and functional plasticity in the intact central nervous system, with similar timing requirements than the in vitro defined STDP rule. The convergent evolution of this plasticity rule in species belonging to so distant phylogenic groups points to the efficiency of STDP, as a mechanism for modifying synaptic weights, as the basis of activity-dependent development, learning and memory. In spite of the ubiquity of STDP phenomena, a number of significant variations of the rule are observed in different structures, neuronal types and even synapses on the same neuron, as well as between in vitro and in vivo conditions. In addition, the state of the neuronal network, its ongoing activity and the activation of ascending neuromodulatory systems in different behavioral conditions have dramatic consequences on the expression of spike-timing-dependent synaptic plasticity, and should be further explored.

Distinct coincidence detectors govern the corticostriatal spike timing-dependent plasticity

Corticostriatal projections constitute the main input to the basal ganglia, an ensemble of interconnected subcortical nuclei involved in procedural learning. Thus, long-term plasticity at corticostriatal synapses would provide a basic mechanism for the function of basal ganglia in learning and memory. We had previously reported the existence of a corticostriatal anti-Hebbian spike timing-dependent plasticity (STDP) at synapses onto striatal output neurons, the medium-sized spiny neurons. Here, we show that the blockade of GABAergic transmission reversed the time dependence of corticostriatal STDP. We explored the receptors and signalling mechanisms involved in the corticostriatal STDP. Although classical models for STDP propose NMDA receptors as the unique coincidence detector, the involvement of multiple coincidence detectors has also been demonstrated. Here, we show that corticostriatal STDP depends on distinct coincidence detectors. Specifically, long-term potentiation is dependent on NMDA receptor activation, while long-term depression requires distinct coincidence detectors: the phospholipase Cbeta (PLCbeta) and the inositol-trisphosphate receptor (IP3R)-gated calcium stores. Furthermore, we found that PLCbeta activation is controlled by group-I metabotropic glutamate receptors, type-1 muscarinic receptors and voltage-sensitive calcium channel activities. Activation of PLCbeta and IP3Rs leads to robust retrograde endocannabinoid signalling mediated by 2-arachidonoyl-glycerol and cannabinoid CB1 receptors. Interestingly, the same coincidence detectors govern the corticostriatal anti-Hebbian STDP and the Hebbian STDP reported at cortical synapses. Therefore, LTP and LTD induced by STDP at corticostriatal synapses are mediated by independent signalling mechanisms, each one being controlled by distinct coincidence detectors.

Spike-timing dependent plasticity in inhibitory circuits

Inhibitory circuits in the brain rely on GABA-releasing interneurons. For long, inhibitory circuits were considered weakly plastic in the face of patterns of neuronal activity that trigger long-term changes in the synapses between excitatory principal cells. Recent studies however have shown that GABAergic circuits undergo various forms of long-term plasticity. For the purpose of this review, we identify three major long-term plasticity expression sites. The first locus is the glutamatergic synapses that excite GABAergic inhibitory cells and drive their activity. Such synapses, on many but not all inhibitory interneurons, exhibit long-term potentiation (LTP) and depression (LTD). Second, GABAergic synapses themselves can undergo changes in GABA release probability or postsynaptic GABA receptors. The third site of plasticity is in the postsynaptic anion gradient of GABAergic synapses; coincident firing of GABAergic axons and postsynaptic neurons can cause a long-lasting change in the reversal potential of GABA_A receptors mediating fast inhibitory postsynaptic potentials. We review the recent literature on these forms of plasticity by asking how they may be triggered by specific patterns of pre- and postsynaptic action potentials, although very few studies have directly examined spike-timing dependent plasticity (STDP) protocols in inhibitory circuits. Plasticity of interneuron recruitment and of GABAergic signaling provides for a rich flexibility in inhibition that may be central to many aspects of brain function. We do not consider plasticity at glutamatergic synapses on Purkinje cells and other GABAergic principal cells.

Spike-timing dependent plasticity in the striatum

The striatum is the major input nucleus of basal ganglia, an ensemble of interconnected sub-cortical nuclei associated with fundamental processes of action-selection and procedural learning and memory. The striatum receives afferents from the cerebral cortex and the thalamus. In turn, it relays the integrated information towards the basal ganglia output nuclei through which it operates a selected activation of behavioral effectors. The striatal output neurons, the GABAergic medium-sized spiny neurons (MSNs), are in charge of the detection and integration of behaviorally relevant information. This property confers to the striatum the ability to extract relevant information from the background noise and select cognitive-motor sequences adapted to environmental stimuli. As long-term synaptic efficacy changes are believed to underlie learning and memory, the corticostriatal long-term plasticity provides a fundamental mechanism for the function of the basal ganglia in procedural learning. Here, we reviewed the different forms of spike-timing dependent plasticity (STDP) occurring at corticostriatal synapses. Most of the studies have focused on MSNs and their ability to develop long-term plasticity. Nevertheless, the striatal interneurons (the fast-spiking GABAergic, NO-synthase and cholinergic interneurons) also receive monosynaptic afferents from the cortex and tightly regulated corticostriatal information processing. Therefore, it is important to take into account the variety of striatal neurons to fully understand the ability of striatum to develop long-term plasticity. Corticostriatal STDP with various spike-timing dependence have been observed depending on the neuronal sub-populations and experimental conditions. This complexity highlights the extraordinary potentiality in term of plasticity of the corticostriatal pathway.

Brief subthreshold events can act as Hebbian signals for long-term plasticity

BACKGROUND

Action potentials are thought to be determinant for the induction of long-term synaptic plasticity, the cellular basis of learning and memory. However, neuronal activity does not lead systematically to an action potential but also, in many cases, to synaptic depolarizing subthreshold events. This is particularly exemplified in corticostriatal information processing. Indeed, the striatum integrates information from the whole cerebral cortex and, due to the membrane properties of striatal medium spiny neurons, cortical inputs do not systematically trigger an action potential but a wide range of subthreshold postsynaptic depolarizations. Accordingly, we have addressed the following question: does a brief subthreshold event act as a Hebbian signal and induce long-term synaptic efficacy changes?

METHODOLOGY/PRINCIPAL FINDINGS

Here, using perforated patch-clamp recordings on rat brain corticostriatal slices, we demonstrate, that brief (30 ms) subthreshold depolarizing events in quasi-coincidence with presynaptic activity can act as Hebbian signals and are sufficient to induce long-term synaptic plasticity at corticostriatal synapses. This "subthreshold-depolarization dependent plasticity" (SDDP) induces strong, significant and bidirectional long-term synaptic efficacy changes at a very high occurrence (81%) for time intervals between pre- and postsynaptic stimulations (Deltat) of -110<Deltat<+110 ms. Such subthreshold depolarizations are able to induce robust long-term depression (cannabinoid type-1 receptor-activation dependent) as well as long-term potentiation (NMDA receptor-activation dependent).

CONCLUSION/SIGNIFICANCE

Our data show the existence of a robust, reliable and timing-dependent bidirectional long-term plasticity induced by brief subthreshold events paired with presynaptic activity. The existence of a subthreshold-depolarization dependent plasticity extends considerably, beyond the action potential, the neuron's capabilities to express long-term synaptic efficacy changes.