Single-shock LTD by local dendritic spikes in pyramidal neurons of mouse visual cortex

The spike-timing-dependent plasticity of VIP interneurons in motor cortex

The plasticity of inhibitory interneurons (INs) plays an important role in the organization and maintenance of cortical microcircuits. Given the many different IN types, there is an even greater diversity in synapse-type-specific plasticity learning rules at excitatory to excitatory (E→I), I→E, and I→I synapses. I→I synapses play a key disinhibitory role in cortical circuits. Because they typically target other INs, vasoactive intestinal peptide (VIP) INs are often featured in I→I→E disinhibition, which upregulates activity in nearby excitatory neurons. VIP IN dysregulation may thus lead to neuropathologies such as epilepsy. In spite of the important activity regulatory role of VIP INs, their long-term plasticity has not been described. Therefore, we characterized the phenomenology of spike-timing-dependent plasticity (STDP) at inputs and outputs of genetically defined VIP INs. Using a combination of whole-cell recording, 2-photon microscopy, and optogenetics, we explored I→I STDP at layer 2/3 (L2/3) VIP IN outputs onto L5 Martinotti cells (MCs) and basket cells (BCs). We found that VIP IN→MC synapses underwent causal long-term depression (LTD) that was presynaptically expressed. VIP IN→BC connections, however, did not undergo any detectable plasticity. Conversely, using extracellular stimulation, we explored E→I STDP at inputs to VIP INs which revealed long-term potentiation (LTP) for both causal and acausal timings. Taken together, our results demonstrate that VIP INs possess synapse-type-specific learning rules at their inputs and outputs. This suggests the possibility of harnessing VIP IN long-term plasticity to control activity-related neuropathologies such as epilepsy.

Large conductance voltage-and calcium-activated K+ (BK) channel in health and disease

Large Conductance Voltage- and Calcium-activated K+ (BK) channels are transmembrane pore-forming proteins that regulate cell excitability and are also expressed in non-excitable cells. They play a role in regulating vascular tone, neuronal excitability, neurotransmitter release, and muscle contraction. Dysfunction of the BK channel can lead to arterial hypertension, hearing disorders, epilepsy, and ataxia. Here, we provide an overview of BK channel functioning and the implications of its abnormal functioning in various diseases. Understanding the function of BK channels is crucial for comprehending the mechanisms involved in regulating vital physiological processes, both in normal and pathological conditions, controlled by BK. This understanding may lead to the development of therapeutic interventions to address BK channelopathies.

Synaptic plasticity through a naturalistic lens

From the myriad of studies on neuronal plasticity, investigating its underlying molecular mechanisms up to its behavioral relevance, a very complex landscape has emerged. Recent efforts have been achieved toward more naturalistic investigations as an attempt to better capture the synaptic plasticity underpinning of learning and memory, which has been fostered by the development of in vivo electrophysiological and imaging tools. In this review, we examine these naturalistic investigations, by devoting a first part to synaptic plasticity rules issued from naturalistic in vivo-like activity patterns. We next give an overview of the novel tools, which enable an increased spatio-temporal specificity for detecting and manipulating plasticity expressed at individual spines up to neuronal circuit level during behavior. Finally, we put particular emphasis on works considering brain-body communication loops and macroscale contributors to synaptic plasticity, such as body internal states and brain energy metabolism.

The dendritic engram

Accumulating evidence from a wide range of studies, including behavioral, cellular, molecular and computational findings, support a key role of dendrites in the encoding and recall of new memories. Dendrites can integrate synaptic inputs in non-linear ways, provide the substrate for local protein synthesis and facilitate the orchestration of signaling pathways that regulate local synaptic plasticity. These capabilities allow them to act as a second layer of computation within the neuron and serve as the fundamental unit of plasticity. As such, dendrites are integral parts of the memory engram, namely the physical representation of memories in the brain and are increasingly studied during learning tasks. Here, we review experimental and computational studies that support a novel, dendritic view of the memory engram that is centered on non-linear dendritic branches as elementary memory units. We highlight the potential implications of dendritic engrams for the learning and memory field and discuss future research directions.

Spike timing-dependent plasticity and memory

Spike timing-dependent plasticity (STDP) is a bidirectional form of synaptic plasticity discovered about 30 years ago and based on the relative timing of pre- and post-synaptic spiking activity with a millisecond precision. STDP is thought to be involved in the formation of memory but the millisecond-precision spike-timing required for STDP is difficult to reconcile with the much slower timescales of behavioral learning. This review therefore aims to expose and discuss recent findings about i) the multiple STDP learning rules at both excitatory and inhibitory synapses in vitro, ii) the contribution of STDP-like synaptic plasticity in the formation of memory in vivo and iii) the implementation of STDP rules in artificial neural networks and memristive devices.

A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex

Pyramidal cells (PCs) form the backbone of the layered structure of the neocortex, and plasticity of their synapses is thought to underlie learning in the brain. However, such long-term synaptic changes have been experimentally characterized between only a few types of PCs, posing a significant barrier for studying neocortical learning mechanisms. Here we introduce a model of synaptic plasticity based on data-constrained postsynaptic calcium dynamics, and show in a neocortical microcircuit model that a single parameter set is sufficient to unify the available experimental findings on long-term potentiation (LTP) and long-term depression (LTD) of PC connections. In particular, we find that the diverse plasticity outcomes across the different PC types can be explained by cell-type-specific synaptic physiology, cell morphology and innervation patterns, without requiring type-specific plasticity. Generalizing the model to in vivo extracellular calcium concentrations, we predict qualitatively different plasticity dynamics from those observed in vitro. This work provides a first comprehensive null model for LTP/LTD between neocortical PC types in vivo, and an open framework for further developing models of cortical synaptic plasticity.

The guide to dendritic spikes of the mammalian cortex in vitro and in vivo

Half a century since their discovery by Llinás and colleagues, dendritic spikes have been observed in various neurons in different brain regions, from the neocortex and cerebellum to the basal ganglia. Dendrites exhibit a terrifically diverse but stereotypical repertoire of spikes, sometimes specific to subregions of the dendrite. Despite their prevalence, we only have a glimpse into their role in the behaving animal. This article aims to survey the full range of dendritic spikes found in excitatory and inhibitory neurons, compare them in vivo versus in vitro, and discuss new studies describing dendritic spikes in the human cortex. We focus on dendritic spikes in neocortical and hippocampal neurons and present a roadmap to identify and understand the broader role of dendritic spikes in single-cell computation.

Voltage compartmentalization in dendritic spines in vivo

[Figure: see text].

Engrams of Fast Learning

Fast learning designates the behavioral and neuronal mechanisms underlying the acquisition of a long-term memory trace after a unique and brief experience. As such it is opposed to incremental, slower reinforcement or procedural learning requiring repetitive training. This learning process, found in most animal species, exists in a large spectrum of natural behaviors, such as one-shot associative, spatial, or perceptual learning, and is a core principle of human episodic memory. We review here the neuronal and synaptic long-term changes associated with fast learning in mammals and discuss some hypotheses related to their underlying mechanisms. We first describe the variety of behavioral paradigms used to test fast learning memories: those preferentially involve a single and brief (from few hundred milliseconds to few minutes) exposures to salient stimuli, sufficient to trigger a long-lasting memory trace and new adaptive responses. We then focus on neuronal activity patterns observed during fast learning and the emergence of long-term selective responses, before documenting the physiological correlates of fast learning. In the search for the engrams of fast learning, a growing body of evidence highlights long-term changes in gene expression, structural, intrinsic, and synaptic plasticities. Finally, we discuss the potential role of the sparse and bursting nature of neuronal activity observed during the fast learning, especially in the induction plasticity mechanisms leading to the rapid establishment of long-term synaptic modifications. We conclude with more theoretical perspectives on network dynamics that could enable fast learning, with an overview of some theoretical approaches in cognitive neuroscience and artificial intelligence.

Dendritic Voltage Recordings Explain Paradoxical Synaptic Plasticity: A Modeling Study

Experiments have shown that the same stimulation pattern that causes Long-Term Potentiation in proximal synapses, will induce Long-Term Depression in distal ones. In order to understand these, and other, surprising observations we use a phenomenological model of Hebbian plasticity at the location of the synapse. Our model describes the Hebbian condition of joint activity of pre- and postsynaptic neurons in a compact form as the interaction of the glutamate trace left by a presynaptic spike with the time course of the postsynaptic voltage. Instead of simulating the voltage, we test the model using experimentally recorded dendritic voltage traces in hippocampus and neocortex. We find that the time course of the voltage in the neighborhood of a stimulated synapse is a reliable predictor of whether a stimulated synapse undergoes potentiation, depression, or no change. Our computational model can explain the existence of different -at first glance seemingly paradoxical- outcomes of synaptic potentiation and depression experiments depending on the dendritic location of the synapse and the frequency or timing of the stimulation.

REM sleep promotes experience-dependent dendritic spine elimination in the mouse cortex

In many parts of the nervous system, experience-dependent refinement of neuronal circuits predominantly involves synapse elimination. The role of sleep in this process remains unknown. We investigated the role of sleep in experience-dependent dendritic spine elimination of layer 5 pyramidal neurons in the visual (V1) and frontal association cortex (FrA) of 1-month-old mice. We found that monocular deprivation (MD) or auditory-cued fear conditioning (FC) caused rapid spine elimination in V1 or FrA, respectively. MD- or FC-induced spine elimination was significantly reduced after total sleep or REM sleep deprivation. Total sleep or REM sleep deprivation also prevented MD- and FC-induced reduction of neuronal activity in response to visual or conditioned auditory stimuli. Furthermore, dendritic calcium spikes increased substantially during REM sleep, and the blockade of these calcium spikes prevented MD- and FC-induced spine elimination. These findings reveal an important role of REM sleep in experience-dependent synapse elimination and neuronal activity reduction.

Sleep plays an important role in learning and memory. Here the authors show that experience dependent elimination of spines is attenuated by REM sleep deprivation.

Emergence of Stable Synaptic Clusters on Dendrites Through Synaptic Rewiring

The connectivity structure of neuronal networks in cortex is highly dynamic. This ongoing cortical rewiring is assumed to serve important functions for learning and memory. We analyze in this article a model for the self-organization of synaptic inputs onto dendritic branches of pyramidal cells. The model combines a generic stochastic rewiring principle with a simple synaptic plasticity rule that depends on local dendritic activity. In computer simulations, we find that this synaptic rewiring model leads to synaptic clustering, that is, temporally correlated inputs become locally clustered on dendritic branches. This empirical finding is backed up by a theoretical analysis which shows that rewiring in our model favors network configurations with synaptic clustering. We propose that synaptic clustering plays an important role in the organization of computation and memory in cortical circuits: we find that synaptic clustering through the proposed rewiring mechanism can serve as a mechanism to protect memories from subsequent modifications on a medium time scale. Rewiring of synaptic connections onto specific dendritic branches may thus counteract the general problem of catastrophic forgetting in neural networks.

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.

Endocannabinoid-LTP Mediated by CB1 and TRPV1 Receptors Encodes for Limited Occurrences of Coincident Activity in Neocortex

Synaptic efficacy changes, long-term potentiation (LTP) and depression (LTD), underlie various forms of learning and memory. Synaptic plasticity is generally assessed under prolonged activation, whereas learning can emerge from few or even a single trial. Here, we investigated the existence of rapid responsiveness of synaptic plasticity in response to a few number of spikes, in neocortex in a synaptic Hebbian learning rule, the spike-timing-dependent plasticity (STDP). We investigated the effect of lowering the number of pairings from 100 to 50, and 10 on STDP expression, using whole-cell recordings from pyramidal cells in rodent somatosensory cortical brain slices. We found that a low number of paired stimulations induces LTP at neocortical layer 4–2/3 synapses. Besides the asymmetric Hebbian STDP reported in the neocortex induced by 100 pairings, we observed a symmetric anti-Hebbian LTD for 50 pairings and unveiled a unidirectional Hebbian spike-timing-dependent LTP (tLTP) induced by 10–15 pairings. This tLTP was not mediated by NMDA receptor activation but requires CB₁ receptors and transient receptor potential vanilloid type-1 (TRPV1) activated by endocannabinoids (eCBs). eCBs have been widely described as mediating short- and long-term synaptic depression. Here, the eCB-tLTP reported at neocortical synapses could constitute a substrate operating in the online learning of new associative memories or during the initial stages of learning. In addition, these findings should provide useful insight into the mechanisms underlying eCB-plasticity occurring during marijuana intoxication.

Robustness of STDP to spike timing jitter

In Hebbian plasticity, neural circuits adjust their synaptic weights depending on patterned firing. Spike-timing-dependent plasticity (STDP), a synaptic Hebbian learning rule, relies on the order and timing of the paired activities in pre- and postsynaptic neurons. Classically, in ex vivo experiments, STDP is assessed with deterministic (constant) spike timings and time intervals between successive pairings, thus exhibiting a regularity that differs from biological variability. Hence, STDP emergence from noisy inputs as occurring in in vivo-like firing remains unresolved. Here, we used noisy STDP pairings where the spike timing and/or interval between pairings were jittered. We explored with electrophysiology and mathematical modeling, the impact of jitter on three forms of STDP at corticostriatal synapses: NMDAR-LTP, endocannabinoid-LTD and endocannabinoid-LTP. We found that NMDAR-LTP was highly fragile to jitter, whereas endocannabinoid-plasticity appeared more resistant. When the frequency or number of pairings was increased, NMDAR-LTP became more robust and could be expressed despite strong jittering. Our results identify endocannabinoid-plasticity as a robust form of STDP, whereas the sensitivity to jitter of NMDAR-LTP varies with activity frequency. This provides new insights into the mechanisms at play during the different phases of learning and memory and the emergence of Hebbian plasticity in in vivo-like activity.

Abnormal dendritic calcium activity and synaptic depotentiation occur early in a mouse model of Alzheimer's disease

Background

Alzheimer’s disease (AD) is characterized by amyloid deposition, tangle formation as well as synapse loss. Synaptic abnormalities occur early in the pathogenesis of AD. Identifying early synaptic abnormalities and their underlying mechanisms is likely important for the prevention and treatment of AD.

Methods

We performed in vivo two-photon calcium imaging to examine the activities of somas, dendrites and dendritic spines of layer 2/3 pyramidal neurons in the primary motor cortex in the APPswe/PS1dE9 mouse model of AD and age-matched wild type control mice. We also performed calcium imaging to determine the effect of Aβ oligomers on dendritic calcium activity. In addition, structural and functional two-photon imaging were used to examine the link between abnormal dendritic calcium activity and changes in dendritic spine size in the AD mouse model.

Results

We found that somatic calcium activities of layer 2/3 neurons were significantly lower in the primary motor cortex of 3-month-old APPswe/PS1dE9 mice than in wild type mice during quiet resting, but not during running on a treadmill. Notably, a significantly larger fraction of apical dendrites of layer 2/3 pyramidal neurons showed calcium transients with abnormally long duration and high peak amplitudes during treadmill running in AD mice. Administration of Aβ oligomers into the brain of wild type mice also induced abnormal dendritic calcium transients during running. Furthermore, we found that the activity and size of dendritic spines were significantly reduced on dendritic branches with abnormally prolonged dendritic calcium transients in AD mice.

Conclusion

Our findings show that abnormal dendritic calcium transients and synaptic depotentiation occur before amyloid plaque formation in the motor cortex of the APPswe/PS1dE9 mouse model of AD. Dendritic calcium transients with abnormally long durations and high amplitudes could be induced by soluble Aβ oligomers and contribute to synaptic deficits in the early pathogenesis of AD.

Electronic supplementary material

The online version of this article (10.1186/s13024-017-0228-2) contains supplementary material, which is available to authorized users.

Modelling plasticity in dendrites: from single cells to networks

One of the key questions in neuroscience is how our brain self-organises to efficiently process information. To answer this question, we need to understand the underlying mechanisms of plasticity and their role in shaping synaptic connectivity. Theoretical neuroscience typically investigates plasticity on the level of neural networks. Neural network models often consist of point neurons, completely neglecting neuronal morphology for reasons of simplicity. However, during the past decades it became increasingly clear that inputs are locally processed in the dendrites before they reach the cell body. Dendritic properties enable local interactions between synapses and location-dependent modulations of inputs, rendering the position of synapses on dendrites highly important. These insights changed our view of neurons, such that we now think of them as small networks of nearly independent subunits instead of a simple point. Here, we propose that understanding how the brain processes information strongly requires that we consider the following properties: which plasticity mechanisms are present in the dendrites and how do they enable the self-organisation of synapses across the dendritic tree for efficient information processing? Ultimately, dendritic plasticity mechanisms can be studied in networks of neurons with dendrites, possibly uncovering unknown mechanisms that shape the connectivity in our brains.

Modulating STDP Balance Impacts the Dendritic Mosaic

The ability for cortical neurons to adapt their input/output characteristics and information processing capabilities ultimately relies on the interplay between synaptic plasticity, synapse location, and the nonlinear properties of the dendrite. Collectively, they shape both the strengths and spatial arrangements of convergent afferent inputs to neuronal dendrites. Recent experimental and theoretical studies support a clustered plasticity model, a view that synaptic plasticity promotes the formation of clusters or hotspots of synapses sharing similar properties. We have previously shown that spike timing-dependent plasticity (STDP) can lead to synaptic efficacies being arranged into spatially segregated clusters. This effectively partitions the dendritic tree into a tessellated imprint which we have called a dendritic mosaic. Here, using a biophysically detailed neuron model of a reconstructed layer 2/3 pyramidal cell and STDP learning, we investigated the impact of altered STDP balance on forming such a spatial organization. We show that cluster formation and extend depend on several factors, including the balance between potentiation and depression, the afferents' mean firing rate and crucially on the dendritic morphology. We find that STDP balance has an important role to play for this emergent mode of spatial organization since any imbalances lead to severe degradation- and in some case even destruction- of the mosaic. Our model suggests that, over a broad range of of STDP parameters, synaptic plasticity shapes the spatial arrangement of synapses, favoring the formation of clustered efficacy engrams.

Bidirectional Hebbian Plasticity Induced by Low-Frequency Stimulation in Basal Dendrites of Rat Barrel Cortex Layer 5 Pyramidal Neurons

According to Hebb's original hypothesis (Hebb, 1949), synapses are reinforced when presynaptic activity triggers postsynaptic firing, resulting in long-term potentiation (LTP) of synaptic efficacy. Long-term depression (LTD) is a use-dependent decrease in synaptic strength that is thought to be due to synaptic input causing a weak postsynaptic effect. Although the mechanisms that mediate long-term synaptic plasticity have been investigated for at least three decades not all question have as yet been answered. Therefore, we aimed at determining the mechanisms that generate LTP or LTD with the simplest possible protocol. Low-frequency stimulation of basal dendrite inputs in Layer 5 pyramidal neurons of the rat barrel cortex induces LTP. This stimulation triggered an EPSP, an action potential (AP) burst, and a Ca²⁺ spike. The same stimulation induced LTD following manipulations that reduced the Ca²⁺ spike and Ca²⁺ signal or the AP burst. Low-frequency whisker deflections induced similar bidirectional plasticity of action potential evoked responses in anesthetized rats. These results suggest that both in vitro and in vivo similar mechanisms regulate the balance between LTP and LTD. This simple induction form of bidirectional hebbian plasticity could be present in the natural conditions to regulate the detection, flow, and storage of sensorimotor information.

REM sleep selectively prunes and maintains new synapses in development and learning

The functions and underlying mechanisms of rapid eye movement (REM) sleep remain unclear. Here we show that REM sleep prunes newly formed postsynaptic dendritic spines of layer 5 pyramidal neurons in the mouse motor cortex during development and motor learning. This REM sleep-dependent elimination of new spines facilitates subsequent spine formation during development and when a new motor task is learned, indicating a role for REM sleep in pruning to balance the number of new spines formed over time. Moreover, REM sleep also strengthens and maintains newly formed spines, which are critical for neuronal circuit development and behavioral improvement after learning. We further show that dendritic calcium spikes arising during REM sleep are important for pruning and strengthening new spines. Together, these findings indicate that REM sleep has multifaceted functions in brain development, learning and memory consolidation by selectively eliminating and maintaining newly formed synapses via dendritic calcium spike-dependent mechanisms.

BK Channels in the Central Nervous System

Large conductance Ca(2+)- and voltage-activated K(+) (BK) channels are widely distributed in the postnatal central nervous system (CNS). BK channels play a pleiotropic role in regulating the activity of brain and spinal cord neural circuits by providing a negative feedback mechanism for local increases in intracellular Ca(2+) concentrations. In neurons, they regulate the timing and duration of K(+) influx such that they can either increase or decrease firing depending on the cellular context, and they can suppress neurotransmitter release from presynaptic terminals. In addition, BK channels located in astrocytes and arterial myocytes modulate cerebral blood flow. Not surprisingly, both loss and gain of BK channel function have been associated with CNS disorders such as epilepsy, ataxia, mental retardation, and chronic pain. On the other hand, the neuroprotective role played by BK channels in a number of pathological situations could potentially be leveraged to correct neurological dysfunction.

Loss of the calcium channel β4 subunit impairs parallel fibre volley and Purkinje cell firing in cerebellum of adult ataxic mice

The auxiliary voltage-gated calcium channel subunit β4 supports targeting of calcium channels to the cell membrane, modulates ionic currents and promotes synaptic release in the central nervous system. β4 is abundant in cerebellum and its loss causes ataxia. However, the type of calcium channels and cerebellar functions affected by the loss of β4 are currently unknown. We therefore studied the structure and function of Purkinje cells in acute cerebellar slices of the β4 (-/-) ataxic (lethargic) mouse, finding that loss of β4 affected Purkinje cell input, morphology and pacemaker activity. In adult lethargic cerebellum evoked postsynaptic currents from parallel fibres were depressed, while paired-pulse facilitation and spontaneous synaptic currents were unaffected. Because climbing fibre input was spared, the parallel fibre/climbing fibre input ratio was reduced. The dendritic arbor of adult lethargic Purkinje cells displayed fewer and shorter dendrites, but a normal spine density. Accordingly, the width of the molecular and granular layers was reduced. These defects recapitulate the impaired cerebellar maturation observed upon Cav 2.1 ataxic mutations. However, unlike Cav 2.1 mutations, lethargic Purkinje cells also displayed a striking decrease in pacemaker firing frequency, without loss of firing regularity. All these deficiencies appear in late development, indicating the importance of β4 for the normal differentiation and function of mature Purkinje cells networks. The observed reduction of the parallel fibre input, the altered parallel fibre/climbing fibre ratio and the reduced Purkinje cell output can contribute to the severe motor impairment caused by the loss of the calcium channel β4 subunit in lethargic mice.

Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites

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.

Error-backpropagation is a successful algorithm for supervised learning in neural networks. Whether and how this technical algorithm is implemented in cortical structures, however, remains elusive. Here we show that this algorithm may be implemented within a single neuron equipped with nonlinear dendritic processing. An error expressed as mismatch between somatic firing and membrane potential may be backpropagated to the active dendritic branches where it modulates synaptic plasticity. This changes the classical view that learning in the brain is realized by rewiring simple processing units as formalized by the neural network theory. Instead, these processing units can themselves learn to implement much more complex input-output functions as previously thought. While the original algorithm only considered firing rates, the biological implementation enables learning for both a firing rate and a spike-timing code. Moreover, when modulated by a reward signal, the synaptic plasticity rule maximizes the expected reward in a reinforcement learning framework.

Endocannabinoids mediate bidirectional striatal spike-timing-dependent plasticity

KEY POINTS

Although learning can arise from few or even a single trial, synaptic plasticity is commonly assessed under prolonged activation. Here, we explored the existence of rapid responsiveness of synaptic plasticity at corticostriatal synapses in a major synaptic learning rule, spike-timing-dependent plasticity (STDP). We found that spike-timing-dependent depression (tLTD) progressively disappears when the number of paired stimulations (below 50 pairings) is decreased whereas spike-timing-dependent potentiation (tLTP) displays a biphasic profile: tLTP is observed for 75-100 pairings, is absent for 25-50 pairings and re-emerges for 5-10 pairings. This tLTP induced by low numbers of pairings (5-10) depends on activation of the endocannabinoid system, type-1 cannabinoid receptor and the transient receptor potential vanilloid type-1. Endocannabinoid-tLTP may represent a physiological mechanism operating during the rapid learning of new associative memories and behavioural rules characterizing the flexible behaviour of mammals or during the initial stages of habit learning.

ABSTRACT

Synaptic plasticity, a main substrate for learning and memory, is commonly assessed with prolonged stimulations. Since learning can arise from few or even a single trial, synaptic strength is expected to adapt rapidly. However, whether synaptic plasticity occurs in response to limited event occurrences remains elusive. To answer this question, we investigated whether a low number of paired stimulations can induce plasticity in a major synaptic learning rule, spike-timing-dependent plasticity (STDP). It is known that 100 pairings induce bidirectional STDP, i.e. spike-timing-dependent potentiation (tLTP) and depression (tLTD) at most central synapses. In rodent striatum, we found that tLTD progressively disappears when the number of paired stimulations is decreased (below 50 pairings) whereas tLTP displays a biphasic profile: tLTP is observed for 75-100 pairings, absent for 25-50 pairings and re-emerges for 5-10 pairings. This tLTP, induced by very few pairings (∼5-10) depends on the endocannabinoid (eCB) system. This eCB-dependent tLTP (eCB-tLTP) involves postsynaptic endocannabinoid synthesis, requires paired activity (post- and presynaptic) and the activation of type-1 cannabinoid receptor (CB1R) and transient receptor potential vanilloid type-1 (TRPV1). eCB-tLTP occurs in both striatopallidal and striatonigral medium-sized spiny neurons (MSNs) and is dopamine dependent. Lastly, we show that eCB-LTP and eCB-LTD can be induced sequentially in the same neuron, depending on the cellular conditioning protocol. Thus, while endocannabinoids are usually thought simply to depress synaptic function, they also constitute a versatile system underlying bidirectional plasticity. Our results reveal a novel form of synaptic plasticity, eCB-tLTP, which may underlie rapid learning capabilities characterizing behavioural flexibility.

Branch-specific dendritic Ca(2+) spikes cause persistent synaptic plasticity

The brain has an extraordinary capacity for memory storage, but how it stores new information without disrupting previously acquired memories remains unknown. Here we show that different motor learning tasks induce dendritic Ca(2+) spikes on different apical tuft branches of individual layer V pyramidal neurons in the mouse motor cortex. These task-related, branch-specific Ca(2+) spikes cause long-lasting potentiation of postsynaptic dendritic spines active at the time of spike generation. When somatostatin-expressing interneurons are inactivated, different motor tasks frequently induce Ca(2+) spikes on the same branches. On those branches, spines potentiated during one task are depotentiated when they are active seconds before Ca(2+) spikes induced by another task. Concomitantly, increased neuronal activity and performance improvement after learning one task are disrupted when another task is learned. These findings indicate that dendritic-branch-specific generation of Ca(2+) spikes is crucial for establishing long-lasting synaptic plasticity, thereby facilitating information storage associated with different learning experiences.

State-dependencies of learning across brain scales

Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous “spontaneous” shifts in states, which, amongst others, are characterized by rhythmic activity of various frequencies. Besides the most obvious distinct modes of waking and sleep, wake-associated brain states comprise modulations of vigilance and attention. Recent findings show that certain brain states, particularly during sleep, are essential for learning and memory consolidation. Oscillatory activity plays a crucial role on several spatial scales, for example in plasticity at a synaptic level or in communication across brain areas. However, the underlying mechanisms and computational rules linking brain states and rhythms to learning, though relevant for our understanding of brain function and therapeutic approaches in brain disease, have not yet been elucidated. Here we review known mechanisms of how brain states mediate and modulate learning by their characteristic rhythmic signatures. To understand the critical interplay between brain states, brain rhythms, and learning processes, a wide range of experimental and theoretical work in animal models and human subjects from the single synapse to the large-scale cortical level needs to be integrated. By discussing results from experiments and theoretical approaches, we illuminate new avenues for utilizing neuronal learning mechanisms in developing tools and therapies, e.g., for stroke patients and to devise memory enhancement strategies for the elderly.

Dendritic function in vivo

Dendrites are the predominant entry site for excitatory synaptic potentials in most types of central neurons. There is increasing evidence that dendrites are not just passive transmitting devices but play active roles in synaptic integration through linear and non-linear mechanisms. Frequently, excitatory synapses are formed on dendritic spines. In addition to relaying incoming electrical signals, spines can play important roles in modifying these signals through complex biochemical processes and, thereby, determine learning and memory formation. Here, we review recent advances in our understanding of the function of spines and dendrites in central mammalian neurons in vivo by focusing particularly on insights obtained from Ca(2+) imaging studies.

Spiny neurons of amygdala, striatum, and cortex use dendritic plateau potentials to detect network UP states

Spiny neurons of amygdala, striatum, and cerebral cortex share four interesting features: (1) they are the most abundant cell type within their respective brain area, (2) covered by thousands of thorny protrusions (dendritic spines), (3) possess high levels of dendritic NMDA conductances, and (4) experience sustained somatic depolarizations in vivo and in vitro (UP states). In all spiny neurons of the forebrain, adequate glutamatergic inputs generate dendritic plateau potentials (“dendritic UP states”) characterized by (i) fast rise, (ii) plateau phase lasting several hundred milliseconds, and (iii) abrupt decline at the end of the plateau phase. The dendritic plateau potential propagates toward the cell body decrementally to induce a long-lasting (longer than 100 ms, most often 200–800 ms) steady depolarization (∼20 mV amplitude), which resembles a neuronal UP state. Based on voltage-sensitive dye imaging, the plateau depolarization in the soma is precisely time-locked to the regenerative plateau potential taking place in the dendrite. The somatic plateau rises after the onset of the dendritic voltage transient and collapses with the breakdown of the dendritic plateau depolarization. We hypothesize that neuronal UP states in vivo reflect the occurrence of dendritic plateau potentials (dendritic UP states). We propose that the somatic voltage waveform during a neuronal UP state is determined by dendritic plateau potentials. A mammalian spiny neuron uses dendritic plateau potentials to detect and transform coherent network activity into a ubiquitous neuronal UP state. The biophysical properties of dendritic plateau potentials allow neurons to quickly attune to the ongoing network activity, as well as secure the stable amplitudes of successive UP states.

Ionotropic NMDA receptor signaling is required for the induction of long-term depression in the mouse hippocampal CA1 region

Previous studies have provided strong support for the notion that NMDAR-mediated increases in postsynaptic Ca(2+) have a crucial role in the induction of long-term depression (LTD). This view has recently been challenged, however, by findings suggesting that LTD induction is instead attributable to an ion channel-independent, metabotropic form of NMDAR signaling. Thus, to explore the role of ionotropic versus metabotropic NMDAR signaling in LTD, we examined the effects of varying extracellular Ca(2+) levels or blocking NMDAR channel ion fluxes with MK-801 on LTD and NMDAR signaling in the mouse hippocampal CA1 region. We find that the induction of LTD in the adult hippocampus is highly sensitive to extracellular Ca(2+) levels and that MK-801 blocks NMDAR-dependent LTD in the hippocampus of both adult and immature mice. Moreover, MK-801 inhibits NMDAR-mediated activation of p38-MAPK and dephosphorylation of AMPAR GluA1 subunits at sites implicated in LTD. Thus, our results indicate that the induction of LTD in the hippocampal CA1 region is dependent on ionotropic, rather than metabotropic, NMDAR signaling.

Reactivation of the same synapses during spontaneous up states and sensory stimuli

In the mammalian brain, calcium signals in dendritic spines are involved in many neuronal functions, particularly in the induction of synaptic plasticity. Recent studies have identified sensory stimulation-evoked spine calcium signals in cortical neurons in vivo. However, spine signaling during ongoing cortical activity in the absence of sensory input, which is essential for important functions like memory consolidation, is not well understood. Here, by using in vivo two-photon imaging of auditory cortical neurons, we demonstrate that subthreshold, NMDA-receptor-dependent spine calcium signals are abundant during up states, but almost absent during down states. In each neuron, about 500 nonclustered spines, which are widely dispersed throughout the dendritic field, are on average active during an up state. The same subset of spines is reliably active during both sensory stimulation and up states. Thus, spontaneously recurring up states evoke in these spines "patterned" calcium activity that may control consolidation of synaptic strength following epochs of sensory stimulation.

Extrasynaptic glutamate receptor activation as cellular bases for dynamic range compression in pyramidal neurons

Repetitive synaptic stimulation overcomes the ability of astrocytic processes to clear glutamate from the extracellular space, allowing some dendritic segments to become submerged in a pool of glutamate, for a brief period of time. This dynamic arrangement activates extrasynaptic NMDA receptors located on dendritic shafts. We used voltage-sensitive and calcium-sensitive dyes to probe dendritic function in this glutamate-rich location. An excess of glutamate in the extrasynaptic space was achieved either by repetitive synaptic stimulation or by glutamate iontophoresis onto the dendrites of pyramidal neurons. Two successive activations of synaptic inputs produced a typical NMDA spike, whereas five successive synaptic inputs produced characteristic plateau potentials, reminiscent of cortical UP states. While NMDA spikes were coupled with brief calcium transients highly restricted to the glutamate input site, the dendritic plateau potentials were accompanied by calcium influx along the entire dendritic branch. Once initiated, the glutamate-mediated dendritic plateau potentials could not be interrupted by negative voltage pulses. Activation of extrasynaptic NMDA receptors in cellular compartments void of spines is sufficient to initiate and support plateau potentials. The only requirement for sustained depolarizing events is a surplus of free glutamate near a group of extrasynaptic receptors. Highly non-linear dendritic spikes (plateau potentials) are summed in a highly sublinear fashion at the soma, revealing the cellular bases of signal compression in cortical circuits. Extrasynaptic NMDA receptors provide pyramidal neurons with a function analogous to a dynamic range compression in audio engineering. They limit or reduce the volume of “loud sounds” (i.e., strong glutamatergic inputs) and amplify “quiet sounds” (i.e., glutamatergic inputs that barely cross the dendritic threshold for local spike initiation). Our data also explain why consecutive cortical UP states have uniform amplitudes in a given neuron.

Cholinergic induction of input-specific late-phase LTP via localized Ca2+ release in the visual cortex

Acetylcholine facilitates long-term potentiation (LTP) and long-term depression (LTD), substrates of learning, memory, and sensory processing, in which acetylcholine also plays a crucial role. Ca(2+) ions serve as a canonical regulator of LTP/LTD but little is known about the effect of acetylcholine on intracellular Ca(2+) dynamics. Here, we investigated dendritic Ca(2+) dynamics evoked by synaptic stimulation and the resulting LTP/LTD in layer 2/3 pyramidal neurons of the rat visual cortex. Under muscarinic stimulation, single-shock electrical stimulation (SES) inducing ∼20 mV EPSP, applied via a glass electrode located ∼10 μm from the basal dendrite, evoked NMDA receptor-dependent fast Ca(2+) transients and the subsequent Ca(2+) release from the inositol 1,4,5-trisphosphate (IP(3))-sensitive stores. These secondary dendritic Ca(2+) transients were highly localized within 10 μm from the center (SD = 5.0 μm). The dendritic release of Ca(2+) was a prerequisite for input-specific muscarinic LTP (LTPm). Without the secondary Ca(2+) release, only muscarinic LTD (LTDm) was induced. D(-)-2-amino-5-phosphopentanoic acid and intracellular heparin blocked LTPm as well as dendritic Ca(2+) release. A single burst consisting of 3 EPSPs with weak stimulus intensities instead of the SES also induced secondary Ca(2+) release and LTPm. LTPm and LTDm were protein synthesis-dependent. Furthermore, LTPm was confined to specific dendritic compartments and not inducible in distal apical dendrites. Thus, cholinergic activation facilitated selectively compartment-specific induction of late-phase LTP through IP(3)-dependent Ca(2+) release.

Probing synaptic function in dendrites with calcium imaging

Calcium imaging has become a widely used technique to probe neuronal activity on the cellular and subcellular levels. In contrast to standard electrophysiological methods, calcium imaging resolves sub- and suprathreshold activation patterns in structures as small as fine dendritic branches and spines. This review highlights recent findings gained on the subcellular level using calcium imaging, with special emphasis on synaptic transmission and plasticity in individual spines. Since imaging allows monitoring activity across populations of synapses, it has recently been adopted to investigate how dendrites integrate information from many synapses. Future experiments, ideally carried out in vivo, will reveal how the dendritic tree integrates and computes afferent signals. For example, it is now possible to directly test the concept that dendritic inputs are clustered and that single dendrites or dendritic stretches act as independent computational units.

Glutamate spillover promotes the generation of NMDA spikes

NMDA spikes are prominent in the basal dendrites of cortical pyramidal neurons and greatly expand their ability to integrate synaptic inputs. Calcium (Ca) signals during these spikes are important for synaptic plasticity and fundamentally depend on activation of NMDA receptors. However, the factors that shape the activation of these receptors and the initiation of NMDA spikes remain unclear. Here we examine the properties of NMDA spikes in the basal dendrites of layer 5 pyramidal neurons in the mouse prefrontal cortex. Using two-photon imaging, we demonstrate that NMDA spikes evoke large Ca signals in both postsynaptic spines and nearby dendrites. We find that the dendrite Ca signals depend on NMDA and AMPA receptors but not sodium (Na) or Ca channels. Using voltage-clamp recordings, we show that activation of dendrite NMDA receptors is enhanced by concerted synaptic activity. Blocking glutamate reuptake further increases activation of these receptors and promotes the initiation of NMDA spikes. We conclude that glutamate spillover and recruitment of extrasynaptic receptors contribute to the initiation of NMDA spikes. These results have important implications for how synaptic activity generates both electrical and biochemical signals in dendrites and spines.

Dendritic spines and distributed circuits

Dendritic spines receive most excitatory connections in pyramidal cells and many other principal neurons. But why do neurons use spines, when they could accommodate excitatory contacts directly on their dendritic shafts? One suggestion is that spines serve to connect with passing axons, thus increasing the connectivity of the dendrites. Another hypothesis is that spines are biochemical compartments that enable input-specific synaptic plasticity. A third possibility is that spines have an electrical role, filtering synaptic potentials and electrically isolating inputs from each other. In this review, I argue that, when viewed from the perspective of the circuit function, these three functions dovetail with one another to achieve a single overarching goal: to implement a distributed circuit with widespread connectivity. Spines would endow these circuits with nonsaturating, linear integration and input-specific learning rules, which would enable them to function as neural networks, with emergent encoding and processing of information.

The decade of the dendritic NMDA spike

In the field of cortical cellular physiology, much effort has been invested in understanding thick apical dendrites of pyramidal neurons and the regenerative sodium and calcium spikes that take place in the apical trunk. Here we focus on thin dendrites of pyramidal cells (basal, oblique, and tuft dendrites), and we discuss one relatively novel form of an electrical signal ("NMDA spike") that is specific for these branches. Basal, oblique, and apical tuft dendrites receive a high density of glutamatergic synaptic contacts. Synchronous activation of 10-50 neighboring glutamatergic synapses triggers a local dendritic regenerative potential, NMDA spike/plateau, which is characterized by significant local amplitude (40-50 mV) and an extraordinary duration (up to several hundred milliseconds). The NMDA plateau potential, when it is initiated in an apical tuft dendrite, is able to maintain a good portion of that tuft in a sustained depolarized state. However, if NMDA-dominated plateau potentials originate in proximal segments of basal dendrites, they regularly bring the neuronal cell body into a sustained depolarized state, which resembles a cortical Up state. At each dendritic initiation site (basal, oblique, and tuft) an NMDA spike creates favorable conditions for causal interactions of active synaptic inputs, including the spatial or temporal binding of information, as well as processes of short-term and long-term synaptic modifications (e.g., long-term potentiation or long-term depression). Because of their strong amplitudes and durations, local dendritic NMDA spikes make up the cellular substrate for multisite independent subunit computations that enrich the computational power and repertoire of cortical pyramidal cells. We propose that NMDA spikes are likely to play significant roles in cortical information processing in awake animals (spatiotemporal binding, working memory) and during slow-wave sleep (neuronal Up states, consolidation of memories).

Interregional synaptic competition in neurons with multiple STDP-inducing signals

Neocortical layer 5 (L5) pyramidal cells have at least two spike initiation zones: Na(+) spikes are generated near the soma, and Ca(2+) spikes at the apical dendritic tuft. These spikes interact with each other and serve as signals for synaptic plasticity. The present computational study explores the implications of having two spike-timing-dependent plasticity (STDP) signals in a neuron, each with its respective regional population of synaptic "pupils." In a detailed model of an L5 pyramidal neuron, competition emerges between synapses belonging to different regions, on top of the competition among synapses within each region, which characterizes the STDP mechanism. Interregional competition results in strengthening of one group of synapses, which ultimately dominates cell firing, at the expense of weakening synapses in other regions. This novel type of competition is inherent to dendrites with multiple regional signals for Hebbian plasticity. Surprisingly, such interregional competition exists even in a simplified model of two identical coupled compartments. We find that in a model of an L5 pyramidal cell, the different synaptic subpopulations "live in peace" when the induction of Ca(2+) spikes requires the back-propagating action potential (BPAP). Thus we suggest a new key role for the BPAP, to maintain the balance between synaptic efficacies throughout the dendritic tree, thereby sustaining the functional integrity of the entire neuron.

Spike timing-dependent plasticity as the origin of the formation of clustered synaptic efficacy engrams

Synapse location, dendritic active properties and synaptic plasticity are all known to play some role in shaping the different input streams impinging onto a neuron. It remains unclear however, how the magnitude and spatial distribution of synaptic efficacies emerge from this interplay. Here, we investigate this interplay using a biophysically detailed neuron model of a reconstructed layer 2/3 pyramidal cell and spike timing-dependent plasticity (STDP). Specifically, we focus on the issue of how the efficacy of synapses contributed by different input streams are spatially represented in dendrites after STDP learning. We construct a simple feed forward network where a detailed model neuron receives synaptic inputs independently from multiple yet equally sized groups of afferent fibers with correlated activity, mimicking the spike activity from different neuronal populations encoding, for example, different sensory modalities. Interestingly, ensuing STDP learning, we observe that for all afferent groups, STDP leads to synaptic efficacies arranged into spatially segregated clusters effectively partitioning the dendritic tree. These segregated clusters possess a characteristic global organization in space, where they form a tessellation in which each group dominates mutually exclusive regions of the dendrite. Put simply, the dendritic imprint from different input streams left after STDP learning effectively forms what we term a “dendritic efficacy mosaic.” Furthermore, we show how variations of the inputs and STDP rule affect such an organization. Our model suggests that STDP may be an important mechanism for creating a clustered plasticity engram, which shapes how different input streams are spatially represented in dendrite.

Dendritic organization of sensory input to cortical neurons in vivo

In sensory cortex regions, neurons are tuned to specific stimulus features. For example, in the visual cortex, many neurons fire predominantly in response to moving objects of a preferred orientation. However, the characteristics of the synaptic input that cortical neurons receive to generate their output firing pattern remain unclear. Here we report a novel approach for the visualization and functional mapping of sensory inputs to the dendrites of cortical neurons in vivo. By combining high-speed two-photon imaging with electrophysiological recordings, we identify local subthreshold calcium signals that correspond to orientation-specific synaptic inputs. We find that even inputs that share the same orientation preference are widely distributed throughout the dendritic tree. At the same time, inputs of different orientation preference are interspersed, so that adjacent dendritic segments are tuned to distinct orientations. Thus, orientation-tuned neurons can compute their characteristic firing pattern by integrating spatially distributed synaptic inputs coding for multiple stimulus orientations.

Rapid time course of action potentials in spines and remote dendrites of mouse visual cortex neurons

Axonally initiated action potentials back-propagate into spiny dendrites of central mammalian neurons and thereby regulate plasticity at excitatory synapses on individual spines as well as linear and supralinear integration of synaptic inputs along dendritic branches. Thus, the electrical behaviour of individual dendritic spines and terminal dendritic branches is critical for the integrative function of nerve cells. The actual dynamics of action potentials in spines and terminal branches, however, are not entirely clear, mostly because electrode recording from such small structures is not feasible. Additionally, the available membrane potential imaging techniques are limited in their sensitivity and require substantial signal averaging for the detection of electrical events at the spatial scale of individual spines. We made a critical improvement in the voltage-sensitive dye imaging technique to achieve multisite recordings of backpropagating action potentials from individual dendritic spines at a high frame rate. With this approach, we obtained direct evidence that in layer 5 pyramidal neurons from the visual cortex of juvenile mice, the rapid time course of somatic action potentials is preserved throughout all cellular compartments, including dendritic spines and terminal branches of basal and apical dendrites. The rapid time course of the action potential in spines may be a critical determinant for the precise regulation of spike timing-dependent synaptic plasticity within a narrow time window.

Calcium buffering in rodent olfactory bulb granule cells and mitral cells

In the mammalian olfactory bulb, axonless granule cells (GCs) mediate self- and lateral inhibitory interactions between mitral cells (MCs) via reciprocal dendrodendritic synapses. Calcium signals in the GC dendrites and reciprocal spines appear to decay unusually slowly, hence GC calcium handling might contribute to the known asynchronous release at this synapse. By recording fluorescence transients of different Ca(2+)-sensitive dyes at variable concentrations evoked by backpropagating action potentials (APs) and saturating AP trains we extrapolated Ca(2+) dynamics to conditions of zero added buffer for juvenile rat GC apical dendrites and spines and MC lateral dendrites. Resting [Ca(2+)] was at approximately 50 nM in both GC dendrites and spines. The average endogenous GC buffer capacities (kappa(E)) were within a range of 80-90 in the dendrites and 110-140 in the spines. The extrusion rate (gamma) was estimated as 570 s(-1) for dendrites and 870 s(-1) for spines and the decay time constant as approximately 200 ms for both. Single-current-evoked APs resulted in a [Ca(2+)] elevation of approximately 250 nM. Calcium handling in juvenile and adult mouse GCs appeared mostly similar. In MC lateral dendrites, we found AP-mediated [Ca(2+)] elevations of approximately 130 nM with a similar decay to that in GC dendrites, while kappa(E) and gamma were roughly 4-fold higher. In conclusion, the slow GC Ca(2+) dynamics are due mostly to sluggish Ca(2+) extrusion. Under physiological conditions this slow removal may well contribute to delayed release and also feed into other Ca(2+)-dependent mechanisms that foster asynchronous output from the reciprocal spine.

Activity-dependent control of neuronal output by local and global dendritic spike attenuation

Neurons possess elaborate dendritic arbors which receive and integrate excitatory synaptic signals. Individual dendritic subbranches exhibit local membrane potential supralinearities, termed dendritic spikes, which control transfer of local synaptic input to the soma. Here, we show that dendritic spikes in CA1 pyramidal cells are strongly regulated by specific types of prior input. While input in the linear range is without effect, supralinear input inhibits subsequent spikes, causing them to attenuate and ultimately fail due to dendritic Na(+) channel inactivation. This mechanism acts locally within the boundaries of the input branch. If an input is sufficiently strong to trigger axonal action potentials, their back-propagation into the dendritic tree causes a widespread global reduction in dendritic excitability which is prominent after firing patterns occurring in vivo. Together, these mechanisms control the capability of individual dendritic branches to trigger somatic action potential output. They are invoked at frequencies encountered during learning, and impose limits on the storage and retrieval rates of information encoded as branch excitability.

Synaptic clustering by dendritic signalling mechanisms

Dendritic signal integration is one of the fundamental building blocks of information processing in the brain. Dendrites are endowed with mechanisms of nonlinear summation of synaptic inputs leading to regenerative dendritic events including local sodium, NMDA and calcium spikes. The generation of these events requires distinct spatio-temporal activation patterns of synaptic inputs. We hypothesise that the recent findings on dendritic spikes and local synaptic plasticity rules suggest clustering of common inputs along a subregion of a dendritic branch. These clusters may enable dendrites to separately threshold groups of functionally similar inputs, thus allowing single neurons to act as a superposition of many separate integrate and fire units. Ultimately, these properties expand our understanding about the computational power of neuronal networks.

Plasticity of burst firing induced by synergistic activation of metabotropic glutamate and acetylcholine receptors

Subiculum, the primary efferent pathway of hippocampus, participates in memory for spatial tasks, relapse to drug abuse, and temporal lobe seizures. Subicular pyramidal neurons exhibit low-threshold burst firing driven by a spike afterdepolarization. Here we report that burst firing can be regulated by stimulation of afferent projections to subiculum. Unlike synaptic plasticity, burst plasticity did not require synaptic depolarization, activation of AMPA or NMDA receptors, or action potential firing. Rather, enhancement of burst firing required synergistic activation of group I, subtype 1 metabotropic glutamate receptors (mGluRs) and muscarinic acetylcholine receptors (mAChR). When either of these receptors was blocked, a suppression of bursting was revealed, which in turn was blocked by antagonists of group I, subtype 5 mGluRs. These results indicate that the output of subiculum can be strongly and bidirectionally regulated by activation of glutamatergic inputs within the hippocampus and cholinergic afferents from the medial septum.

Dendritic excitability and synaptic plasticity

Most synaptic inputs are made onto the dendritic tree. Recent work has shown that dendrites play an active role in transforming synaptic input into neuronal output and in defining the relationships between active synapses. In this review, we discuss how these dendritic properties influence the rules governing the induction of synaptic plasticity. We argue that the location of synapses in the dendritic tree, and the type of dendritic excitability associated with each synapse, play decisive roles in determining the plastic properties of that synapse. Furthermore, since the electrical properties of the dendritic tree are not static, but can be altered by neuromodulators and by synaptic activity itself, we discuss how learning rules may be dynamically shaped by tuning dendritic function. We conclude by describing how this reciprocal relationship between plasticity of dendritic excitability and synaptic plasticity has changed our view of information processing and memory storage in neuronal networks.

Active dendrites: colorful wings of the mysterious butterflies

Santiago Ramón y Cajal had referred to neurons as the 'mysterious butterflies of the soul.' Wings of these butterflies--their dendrites--were traditionally considered as passive integrators of synaptic information. Owing to a growing body of experimental evidence, it is now widely accepted that these wings are colorful, endowed with a plethora of active conductances, with each family of these butterflies made of distinct hues and shades. Furthermore, rapidly evolving recent literature also provides direct and indirect demonstrations for activity-dependent plasticity of these active conductances, pointing toward chameleonic adaptability in these hues. These experimental findings firmly establish the immense computational power of a single neuron, and thus constitute a turning point toward the understanding of various aspects of neuronal information processing. In this brief historical perspective, we track important milestones in the chameleonic transmogrification of these mysterious butterflies.