Dendritic spikes and their inhibition in alligator Purkinje cells

Engram mechanisms of memory linking and identity

Memories are thought to be stored in neuronal ensembles referred to as engrams. Studies have suggested that when two memories occur in quick succession, a proportion of their engrams overlap and the memories become linked (in a process known as prospective linking) while maintaining their individual identities. In this Review, we summarize the key principles of memory linking through engram overlap, as revealed by experimental and modelling studies. We describe evidence of the involvement of synaptic memory substrates, spine clustering and non-linear neuronal capacities in prospective linking, and suggest a dynamic somato-synaptic model, in which memories are shared between neurons yet remain separable through distinct dendritic and synaptic allocation patterns. We also bring into focus retrospective linking, in which memories become associated after encoding via offline reactivation, and discuss key temporal and mechanistic differences between prospective and retrospective linking, as well as the potential differences in their cognitive outcomes.

A mechanism for differential control of axonal and dendritic spiking underlying learning in a cerebellum-like circuit

In addition to the action potentials used for axonal signaling, many neurons generate dendritic "spikes" associated with synaptic plasticity. However, in order to control both plasticity and signaling, synaptic inputs must be able to differentially modulate the firing of these two spike types. Here, we investigate this issue in the electrosensory lobe (ELL) of weakly electric mormyrid fish, where separate control over axonal and dendritic spikes is essential for the transmission of learned predictive signals from inhibitory interneurons to the output stage of the circuit. Through a combination of experimental and modeling studies, we uncover a novel mechanism by which sensory input selectively modulates the rate of dendritic spiking by adjusting the amplitude of backpropagating axonal action potentials. Interestingly, this mechanism does not require spatially segregated synaptic inputs or dendritic compartmentalization but relies instead on an electrotonically distant spike initiation site in the axon-a common biophysical feature of neurons.

Self-Adaptive Multicompartment: A Unified Self-Adaptive Multicompartmental Spiking Neuron Model for Learning With Working Memory

Working memory is a fundamental feature of biological brains for perception, cognition, and learning. In addition, learning with working memory, which has been show in conventional artificial intelligence systems through recurrent neural networks, is instrumental to advanced cognitive intelligence. However, it is hard to endow a simple neuron model with working memory, and to understand the biological mechanisms that have resulted in such a powerful ability at the neuronal level. This article presents a novel self-adaptive multicompartment spiking neuron model, referred to as SAM, for spike-based learning with working memory. SAM integrates four major biological principles including sparse coding, dendritic non-linearity, intrinsic self-adaptive dynamics, and spike-driven learning. We first describe SAM’s design and explore the impacts of critical parameters on its biological dynamics. We then use SAM to build spiking networks to accomplish several different tasks including supervised learning of the MNIST dataset using sequential spatiotemporal encoding, noisy spike pattern classification, sparse coding during pattern classification, spatiotemporal feature detection, meta-learning with working memory applied to a navigation task and the MNIST classification task, and working memory for spatiotemporal learning. Our experimental results highlight the energy efficiency and robustness of SAM in these wide range of challenging tasks. The effects of SAM model variations on its working memory are also explored, hoping to offer insight into the biological mechanisms underlying working memory in the brain. The SAM model is the first attempt to integrate the capabilities of spike-driven learning and working memory in a unified single neuron with multiple timescale dynamics. The competitive performance of SAM could potentially contribute to the development of efficient adaptive neuromorphic computing systems for various applications from robotics to edge computing.

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.

The Cellular Electrophysiological Properties Underlying Multiplexed Coding in Purkinje Cells

Neuronal firing patterns are crucial to underpin circuit level behaviors. In cerebellar Purkinje cells (PCs), both spike rates and pauses are used for behavioral coding, but the cellular mechanisms causing code transitions remain unknown. We use a well-validated PC model to explore the coding strategy that individual PCs use to process parallel fiber (PF) inputs. We find increasing input intensity shifts PCs from linear rate-coders to burst-pause timing-coders by triggering localized dendritic spikes. We validate dendritic spike properties with experimental data, elucidate spiking mechanisms, and predict spiking thresholds with and without inhibition. Both linear and burst-pause computations use individual branches as computational units, which challenges the traditional view of PCs as linear point neurons. Dendritic spike thresholds can be regulated by voltage state, compartmentalized channel modulation, between-branch interaction and synaptic inhibition to expand the dynamic range of linear computation or burst-pause computation. In addition, co-activated PF inputs between branches can modify somatic maximum spike rates and pause durations to make them carry analog signals. Our results provide new insights into the strategies used by individual neurons to expand their capacity of information processing.

SIGNIFICANCE STATEMENT Understanding how neurons process information is a fundamental question in neuroscience. Purkinje cells (PCs) were traditionally regarded as linear point neurons. We used computational modeling to unveil their electrophysiological properties underlying the multiplexed coding strategy that is observed during behaviors. We demonstrate that increasing input intensity triggers localized dendritic spikes, shifting PCs from linear rate-coders to burst-pause timing-coders. Both coding strategies work at the level of individual dendritic branches. Our work suggests that PCs have the ability to implement branch-specific multiplexed coding at the cellular level, thereby increasing the capacity of cerebellar coding and learning.

Dendrite P Systems Toolbox: Representation, Algorithms and Simulators

Dendrite P systems (DeP systems) are a recently introduced neural-like model of computation. They provide an alternative to the more classical spiking neural (SN) P systems. In this paper, we present the first software simulator for DeP systems, and we investigate the key features of the representation of the syntax and semantics of such systems. First, the conceptual design of a simulation algorithm is discussed. This is helpful in order to shade a light on the differences with simulators for SN P systems, and also to identify potential parallelizable parts. Second, a novel simulator implemented within the P-Lingua simulation framework is presented. Moreover, MeCoSim, a GUI tool for abstract representation of problems based on P system models has been extended to support this model. An experimental validation of this simulator is also covered.

Illuminating dendritic function with computational models

Dendrites have always fascinated researchers: from the artistic drawings by Ramon y Cajal to the beautiful recordings of today, neuroscientists have been striving to unravel the mysteries of these structures. Theoretical work in the 1960s predicted important dendritic effects on neuronal processing, establishing computational modelling as a powerful technique for their investigation. Since then, modelling of dendrites has been instrumental in driving neuroscience research in a targeted manner, providing experimentally testable predictions that range from the subcellular level to the systems level, and their relevance extends to fields beyond neuroscience, such as machine learning and artificial intelligence. Validation of modelling predictions often requires - and drives - new technological advances, thus closing the loop with theory-driven experimentation that moves the field forward. This Review features the most important, to our understanding, contributions of modelling of dendritic computations, including those pending experimental verification, and highlights studies of successful interactions between the modelling and experimental neuroscience communities.

Ca2+ transients in melanocyte dendrites and dendritic spine-like structures evoked by cell-to-cell signaling

Melanocytes are the neural crest-derived pigment-producing cells of the skin that possess dendrites. Yet little is known about how melanocyte dendrites receive and process information from neighboring cells. Here, using a co-culture system to interrogate the interaction between melanocyte dendrites and keratinocytes, we show that signals from neighboring keratinocytes trigger local compartmentalized Ca2+ transients within the melanocyte dendrites. The localized dendritic Ca2+ transients could be triggered by two keratinocyte-secreted factors, endothelin and acetylcholine, which acted via specific melanocyte receptors. Furthermore, compartmentalized Ca2+ transients were also generated on discrete dendritic spine-like structures on the melanocytes. These spines were also present in intact human skin. Our findings provide insights into how melanocyte dendrites communicate with neighboring cells and offer a new model system for studying compartmentalized signaling in dendritic structures.

Can NMDA Spikes Dictate Computations of Local Networks and Behavior?

Intelligence is the ability to learn appropriate responses to stimuli and the capacity to master new skills. Synaptic integration at the dendritic level is thought to be essential for this ability through linear and non-linear processing, by allowing neurons to be tuned to relevant information and to maximize adaptive behavior. Showing that dendrites are able to generate local computations that influence how animals perceive the world, form a new memory or learn a new skill was a break-through in neuroscience, since in the past they were seen as passive elements of the neurons, just funneling information to the soma. Here, we provide an overview of the role of dendritic integration in improving the neuronal network and behavioral performance. We focus on how NMDA spikes are generated and their role in neuronal computation for optimal behavioral output based on recent in vivo studies on rodents.

Dendritic sodium spikes endow neurons with inverse firing rate response to correlated synaptic activity

Many neurons possess dendrites enriched with sodium channels and are capable of generating action potentials. However, the role of dendritic sodium spikes remain unclear. Here, we study computational models of neurons to investigate the functional effects of dendritic spikes. In agreement with previous studies, we found that point neurons or neurons with passive dendrites increase their somatic firing rate in response to the correlation of synaptic bombardment for a wide range of input conditions, i.e. input firing rates, synaptic conductances, or refractory periods. However, neurons with active dendrites show the opposite behavior: for a wide range of conditions the firing rate decreases as a function of correlation. We found this property in three types of models of dendritic excitability: a Hodgkin-Huxley model of dendritic spikes, a model with integrate and fire dendrites, and a discrete-state dendritic model. We conclude that fast dendritic spikes confer much broader computational properties to neurons, sometimes opposite to that of point neurons.

Dendritic Spikes in Sensory Perception

What is the function of dendritic spikes? One might argue that they provide conditions for neuronal plasticity or that they are essential for neural computation. However, despite a long history of dendritic research, the physiological relevance of dendritic spikes in brain function remains unknown. This could stem from the fact that most studies on dendrites have been performed in vitro. Fortunately, the emergence of novel techniques such as improved two-photon microscopy, genetically encoded calcium indicators (GECIs), and optogenetic tools has provided the means for vital breakthroughs in in vivo dendritic research. These technologies enable the investigation of the functions of dendritic spikes in behaving animals, and thus, help uncover the causal relationship between dendritic spikes, and sensory information processing and synaptic plasticity. Understanding the roles of dendritic spikes in brain function would provide mechanistic insight into the relationship between the brain and the mind. In this review article, we summarize the results of studies on dendritic spikes from a historical perspective and discuss the recent advances in our understanding of the role of dendritic spikes in sensory perception.

Principles of Synaptic Organization of GABAergic Interneurons in the Striatum

The striatum, the entry nucleus of the basal ganglia, lacks laminar or columnar organization of its principal cells; nevertheless, functional data suggest that it is spatially organized. Here we examine whether the connectivity and synaptic organization of striatal GABAergic interneurons contributes to such spatial organization. Focusing on the two main classes of striatal GABAergic interneurons (fast-spiking interneurons [FSIs] and low-threshold-spiking interneurons [LTSIs]), we apply a combination of optogenetics and viral tracing approaches to dissect striatal microcircuits in mice. Our results reveal fundamental differences between the synaptic organizations of both interneuron types. FSIs target exclusively striatal projection neurons (SPNs) within close proximity and form strong synapses on the proximal somatodendritic region. In contrast, LTSIs target both SPNs and cholinergic interneurons, and synaptic connections onto SPNs are made exclusively over long distances and onto distal dendrites. These results suggest fundamentally different functions of FSIs and LTSIs in shaping striatal output.

Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue

The cerebellar microcircuit has been the work bench for theoretical and computational modeling since the beginning of neuroscientific research. The regular neural architecture of the cerebellum inspired different solutions to the long-standing issue of how its circuitry could control motor learning and coordination. Originally, the cerebellar network was modeled using a statistical-topological approach that was later extended by considering the geometrical organization of local microcircuits. However, with the advancement in anatomical and physiological investigations, new discoveries have revealed an unexpected richness of connections, neuronal dynamics and plasticity, calling for a change in modeling strategies, so as to include the multitude of elementary aspects of the network into an integrated and easily updatable computational framework. Recently, biophysically accurate “realistic” models using a bottom-up strategy accounted for both detailed connectivity and neuronal non-linear membrane dynamics. In this perspective review, we will consider the state of the art and discuss how these initial efforts could be further improved. Moreover, we will consider how embodied neurorobotic models including spiking cerebellar networks could help explaining the role and interplay of distributed forms of plasticity. We envisage that realistic modeling, combined with closed-loop simulations, will help to capture the essence of cerebellar computations and could eventually be applied to neurological diseases and neurorobotic control systems.

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.

Dendritic integration: 60 years of progress

Understanding how individual neurons integrate the thousands of synaptic inputs they receive is critical to understanding how the brain works. Modeling studies in silico and experimental work in vitro, dating back more than half a century, have revealed that neurons can perform a variety of different passive and active forms of synaptic integration on their inputs. But how are synaptic inputs integrated in the intact brain? With the development of new techniques, this question has recently received substantial attention, with new findings suggesting that many of the forms of synaptic integration observed in vitro also occur in vivo, including in awake animals. Here we review six decades of progress, which collectively highlights the complex ways that single neurons integrate their inputs, emphasizing the critical role of dendrites in information processing in the brain.

The 40-year history of modeling active dendrites in cerebellar Purkinje cells: emergence of the first single cell "community model"

The subject of the effects of the active properties of the Purkinje cell dendrite on neuronal function has been an active subject of study for more than 40 years. Somewhat unusually, some of these investigations, from the outset have involved an interacting combination of experimental and model-based techniques. This article recounts that 40-year history, and the view of the functional significance of the active properties of the Purkinje cell dendrite that has emerged. It specifically considers the emergence from these efforts of what is arguably the first single cell "community" model in neuroscience. The article also considers the implications of the development of this model for future studies of the complex properties of neuronal dendrites.

Synaptic Conductance Estimates of the Connection Between Local Inhibitor Interneurons and Pyramidal Neurons in Layer 2/3 of a Cortical Column

Stimulation of a principal whisker yields sparse action potential (AP) spiking in layer 2/3 (L2/3) pyramidal neurons in a cortical column of rat barrel cortex. The low AP rates in pyramidal neurons could be explained by activation of interneurons in L2/3 providing inhibition onto L2/3 pyramidal neurons. L2/3 interneurons classified as local inhibitors based on their axonal projection in the same column were reported to receive strong excitatory input from spiny neurons in L4, which are also the main source of the excitatory input to L2/3 pyramidal neurons. Here, we investigated the remaining synaptic connection in this intracolumnar microcircuit. We found strong and reliable inhibitory synaptic transmission between intracolumnar L2/3 local-inhibitor-to-L2/3 pyramidal neuron pairs [inhibitory postsynaptic potential (IPSP) amplitude −0.88 ± 0.67 mV]. On average, 6.2 ± 2 synaptic contacts were made by L2/3 local inhibitors onto L2/3 pyramidal neurons at 107 ± 64 µm path distance from the pyramidal neuron soma, thus overlapping with the distribution of synaptic contacts from L4 spiny neurons onto L2/3 pyramidal neurons (67 ± 34 µm). Finally, using compartmental simulations, we determined the synaptic conductance per synaptic contact to be 0.77 ± 0.4 nS. We conclude that the synaptic circuit from L4 to L2/3 can provide efficient shunting inhibition that is temporally and spatially aligned with the excitatory input from L4 to L2/3.

GABA-A receptor inhibition of local calcium signaling in spines and dendrites

Cortical interneurons activate GABA-A receptors to rapidly control electrical and biochemical signaling at pyramidal neurons. Different populations of interneurons are known to uniquely target the soma and dendrites of pyramidal neurons. However, the ability of these interneurons to inhibit Ca(2+) signaling at spines and dendrites is largely unexplored. Here we use whole-cell recordings, two-photon microscopy, GABA uncaging and optogenetics to study dendritic inhibition at layer 5 (L5) pyramidal neurons in slices of mouse PFC. We first show that GABA-A receptors strongly inhibit action potential (AP)-evoked Ca(2+) signals at both spines and dendrites. We find robust inhibition over tens of milliseconds that spreads along the dendritic branch. However, we observe no difference in the amount of inhibition at neighboring spines and dendrites. We then examine the influence of interneurons expressing parvalbumin (PV), somatostatin (SOM), or 5HT3a receptors. We determine that these populations of interneurons make unique contacts onto the apical and basal dendrites of L5 pyramidal neurons. We also show that SOM and 5HT3a but not PV interneurons potently inhibit AP Ca(2+) signals via GABA-A receptors at both spines and dendrites. These findings reveal how multiple interneurons regulate local Ca(2+) signaling in pyramidal neurons, with implications for cortical function and disease.

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.

Dendritic Na+ spikes enable cortical input to drive action potential output from hippocampal CA2 pyramidal neurons

Synaptic inputs from different brain areas are often targeted to distinct regions of neuronal dendritic arbors. Inputs to proximal dendrites usually produce large somatic EPSPs that efficiently trigger action potential (AP) output, whereas inputs to distal dendrites are greatly attenuated and may largely modulate AP output. In contrast to most other cortical and hippocampal neurons, hippocampal CA2 pyramidal neurons show unusually strong excitation by their distal dendritic inputs from entorhinal cortex (EC). In this study, we demonstrate that the ability of these EC inputs to drive CA2 AP output requires the firing of local dendritic Na⁺ spikes. Furthermore, we find that CA2 dendritic geometry contributes to the efficient coupling of dendritic Na⁺ spikes to AP output. These results provide a striking example of how dendritic spikes enable direct cortical inputs to overcome unfavorable distal synaptic locale to trigger axonal AP output and thereby enable efficient cortico-hippocampal information flow.

DOI:http://dx.doi.org/10.7554/eLife.04551.001

Cells called neurons carry information—in the form of electrical signals—around the brain. These cells connect to each other in complex networks and each neuron is able to form junctions, or synapses, with many neighbors. In a neuron, small electrical signals start from synapses at the tips of branched structures called dendrites. From there, these signals travel to the cell body of the neuron to activate a larger electrical signal—called an action potential—that travels along a long tail-like extension, called the axon, to reach synapses with other neurons.

In the dendrites, the small electrical signals can be amplified by rapid changes in the concentration of sodium ions, known as Na⁺ spikes. Although they were first recorded over 40 years ago, it is not clear how important the Na⁺ spikes are for triggering action potentials.

In this study, Sun et al. studied a type of neuron in the hippocampus called CA2 pyramidal neurons, which are involved in social memory and aggression. Unlike most other neurons in this region, CA2 neurons are strongly activated by signals from a neighboring region of the brain called the entorhinal cortex. The experiments show that Na⁺ spikes are able to travel from the dendrites to the cell body of these neurons, where they are required to trigger action potentials. However, this is not the case for other neurons in the hippocampus, where the Na⁺ spikes are very weak by the time they reach the cell body.

Sun et al. used a computational modeling technique to compare the different types of neurons in the hippocampus. The dendrites of these cells have different branching patterns and shapes, and the model suggests that this may explain the differences in how well the Na⁺ spikes travel to the cell body. The next major challenge is to understand the role of the Na⁺ spikes in social memory and other complex behaviors that are controlled by CA2 neurons.

DOI:http://dx.doi.org/10.7554/eLife.04551.002

Activity-dependent gating of calcium spikes by A-type K+ channels controls climbing fiber signaling in Purkinje cell dendrites

In cerebellar Purkinje cell dendrites, heterosynaptic calcium signaling induced by the proximal climbing fiber (CF) input controls plasticity at distal parallel fiber (PF) synapses. The substrate and regulation of this long-range dendritic calcium signaling are poorly understood. Using high-speed calcium imaging, we examine the role of active dendritic conductances. Under basal conditions, CF stimulation evokes T-type calcium signaling displaying sharp proximodistal decrement. Combined mGluR1 receptor activation and depolarization, two activity-dependent signals, unlock P/Q calcium spikes initiation and propagation, mediating efficient CF signaling at distal sites. These spikes are initiated in proximal smooth dendrites, independently from somatic sodium action potentials, and evoke high-frequency bursts of all-or-none fast-rising calcium transients in PF spines. Gradual calcium spike burst unlocking arises from increasing inactivation of mGluR1-modulated low-threshold A-type potassium channels located in distal dendrites. Evidence for graded activity-dependent CF calcium signaling at PF synapses refines current views on cerebellar supervised learning rules.

Supervised learning with complex spikes and spike-timing-dependent plasticity

One distinctive feature of Purkinje cells is that they have two types of discharge: in addition to simple spikes they fire complex spikes in response to input from the climbing fibers. These complex spikes have an initial rapid burst of spikes and spikelets followed by a sustained depolarization; in some models of cerebellar function this climbing fiber input supervises learning in Purkinje cells. On the other hand, synaptic plasticity is often thought to rely on the timing of pre-synaptic and post-synaptic spikes. It is suggested here that the period of depolarization following a complex spike, combined with a simple spike-timing-dependent plasticity rule, gives a mechanism for the climbing fiber to supervise learning in the Purkinje cell. This proposal is illustrated using a simple simulation in which it is seen that the climbing fiber succeeds in supervising the learning.

Hidden synaptic differences in a neural circuit underlie differential behavioral susceptibility to a neural injury

Individuals vary in their responses to stroke and trauma, hampering predictions of outcomes. One reason might be that neural circuits contain hidden variability that becomes relevant only when those individuals are challenged by injury. We found that in the mollusc, Tritonia diomedea, subtle differences between animals within the neural circuit underlying swimming behavior had no behavioral relevance under normal conditions but caused differential vulnerability of the behavior to a particular brain lesion. The extent of motor impairment correlated with the site of spike initiation in a specific neuron in the neural circuit, which was determined by the strength of an inhibitory synapse onto this neuron. Artificially increasing or decreasing this inhibitory synaptic conductance with dynamic clamp correspondingly altered the extent of motor impairment by the lesion without affecting normal operation. The results suggest that neural circuit differences could serve as hidden phenotypes for predicting the behavioral outcome of neural damage.

Dendritic spikes enhance stimulus selectivity in cortical neurons in vivo

Neuronal dendrites are electrically excitable: they can generate regenerative events such as dendritic spikes in response to sufficiently strong synaptic input. Although such events have been observed in many neuronal types, it is not well understood how active dendrites contribute to the tuning of neuronal output in vivo. Here we show that dendritic spikes increase the selectivity of neuronal responses to the orientation of a visual stimulus (orientation tuning). We performed direct patch-clamp recordings from the dendrites of pyramidal neurons in the primary visual cortex of lightly anaesthetized and awake mice, during sensory processing. Visual stimulation triggered regenerative local dendritic spikes that were distinct from back-propagating action potentials. These events were orientation tuned and were suppressed by either hyperpolarization of membrane potential or intracellular blockade of NMDA (N-methyl-d-aspartate) receptors. Both of these manipulations also decreased the selectivity of subthreshold orientation tuning measured at the soma, thus linking dendritic regenerative events to somatic orientation tuning. Together, our results suggest that dendritic spikes that are triggered by visual input contribute to a fundamental cortical computation: enhancing orientation selectivity in the visual cortex. Thus, dendritic excitability is an essential component of behaviourally relevant computations in neurons.

Active processing of spatio-temporal input patterns in silicon dendrites

Capturing the functionality of active dendritic processing into abstract mathematical models will help us to understand the role of complex biophysical neurons in neuronal computation and to build future useful neuromorphic analog Very Large Scale Integrated (aVLSI) neuronal devices. Previous work based on an aVLSI multi-compartmental neuron model demonstrates that the compartmental response in the presence of either of two widely studied classes of active mechanisms, is a nonlinear sigmoidal function of the degree of either input temporal synchrony OR input clustering level. Using the same silicon model, this work expounds the interaction between both active mechanisms in a compartment receiving input patterns of varying temporal AND spatial clustering structure and demonstrates that this compartmental response can be captured by a combined sigmoid and radial-basis function over both input dimensions. This paper further shows that the response to input spatio-temporal patterns in a one-dimensional multi-compartmental dendrite, can be described by a radial-basis like function of the degree of temporal synchrony between the inter-compartmental inputs.

Principles governing the operation of synaptic inhibition in dendrites

Synaptic inhibition plays a key role in shaping the dynamics of neuronal networks and selecting cell assemblies. Typically, an inhibitory axon contacts a particular dendritic subdomain of its target neuron, where it often makes 10-20 synapses, sometimes on very distal branches. The functional implications of such a connectivity pattern are not well understood. Our experimentally based theoretical study highlights several new and counterintuitive principles for dendritic inhibition. We show that distal "off-path" rather than proximal "on-path" inhibition effectively dampens proximal excitable dendritic "hotspots," thus powerfully controlling the neuron's output. Additionally, with multiple synaptic contacts, inhibition operates globally, spreading centripetally hundreds of micrometers from the inhibitory synapses. Consequently, inhibition in regions lacking inhibitory synapses may exceed that at the synaptic sites themselves. These results offer new insights into the synergetic effect of dendritic inhibition in controlling dendritic excitability and plasticity and in dynamically molding functional dendritic subdomains and their output.

Dendritic calcium signaling in cerebellar Purkinje cell

The Purkinje cells in the cerebellum are unique neurons that generate local and global Ca(2+) signals in response to two types of excitatory inputs, parallel fiber and climbing fiber, respectively. The spatiotemporal distribution and interaction of these synaptic inputs produce complex patterns of Ca(2+) dynamics in the Purkinje cell dendrites. The Ca(2+) signals originate from Ca(2+) influx through voltage-gated Ca(2+) channels and Ca(2+) release from intracellular stores that are mediated by the metabotropic glutamate receptor signaling pathway. These Ca(2+) signals are essential for the induction of various forms of synaptic plasticity and for controlling the input-output relationship of Purkinje cells. In this article we review Ca(2+) signaling in Purkinje cell dendrites.

Inhibitory Regulation of Dendritic Activity in vivo

The spatiotemporal control of neuronal excitability is fundamental to the inhibitory process. We now have a wealth of information about the active dendritic properties of cortical neurons including axonally generated sodium action potentials as well as local sodium spikelets generated in the dendrites, calcium plateau spikes, and NMDA spikes. All of these events have been shown to be highly modified by the spatiotemporal pattern of nearby inhibitory input which can drastically change the output firing mode of the neuron. This means that particular populations of interneurons embedded in the neocortical microcircuitry can more precisely control pyramidal cell output than has previously been thought. Furthermore, the output of any given neuron tends to feed back onto inhibitory circuits making the resultant network activity further dependent on inhibition. Network activity is therefore ultimately governed by the subcellular microcircuitry of the cortex and it is impossible to ignore the subcompartmentalization of inhibitory influence at the neuronal level in order to understand its effects at the network level. In this article, we summarize the inhibitory circuits that have been shown so far to act on specific dendritic compartments in vivo.

The physiology of the axon initial segment

The action potential generally begins in the axon initial segment (AIS), a principle confirmed by 60 years of research; however, the most recent advances have shown that a very rich biology underlies this simple observation. The AIS has a remarkably complex molecular composition, with a wide variety of ion channels and attendant mechanisms for channel localization, and may feature membrane domains each with distinct roles in excitation. Its function may be regulated in the short term through the action of neurotransmitters, in the long term through activity- and Ca(2+)-dependent processes. Thus, the AIS is not merely the beginning of the axon, but rather a key site in the control of neuronal excitability.

Dendritic spikes mediate negative synaptic gain control in cerebellar Purkinje cells

Dendritic spikes appear to be a ubiquitous feature of dendritic excitability. In cortical pyramidal neurons, dendritic spikes increase the efficacy of distal synapses, providing additional inward current to enhance axonal action potential (AP) output, thus increasing synaptic gain. In cerebellar Purkinje cells, dendritic spikes can trigger synaptic plasticity, but their influence on axonal output is not well understood. We have used simultaneous somatic and dendritic patch-clamp recordings to directly assess the impact of dendritic calcium spikes on axonal AP output of Purkinje cells. Dendritic spikes evoked by parallel fiber input triggered brief bursts of somatic APs, followed by pauses in spiking, which cancelled out the extra spikes in the burst. As a result, average output firing rates during trains of input remained independent of the input strength, thus flattening synaptic gain. We demonstrate that this "clamping" of AP output by the pause following dendritic spikes is due to activation of high conductance calcium-dependent potassium channels by dendritic spikes. Dendritic spikes in Purkinje cells, in contrast to pyramidal cells, thus have differential effects on temporally coded and rate coded information: increasing the impact of transient parallel fiber input, while depressing synaptic gain for sustained parallel fiber inputs.

Multilayer processing of spatiotemporal spike patterns in a neuron with active dendrites

With the advent of new experimental evidence showing that dendrites play an active role in processing a neuron's inputs, we revisit the question of a suitable abstraction for the computing function of a neuron in processing spatiotemporal input patterns. Although the integrative role of a neuron in relation to the spatial clustering of synaptic inputs can be described by a two-layer neural network, no corresponding abstraction has yet been described for how a neuron processes temporal input patterns on the dendrites. We address this void using a real-time aVLSI (analog very-large-scale-integrated) dendritic compartmental model, which incorporates two widely studied classes of regenerative event mechanisms: one is mediated by voltage-gated ion channels and the other by transmitter-gated NMDA channels. From this model, we find that the response of a dendritic compartment can be described as a nonlinear sigmoidal function of both the degree of input temporal synchrony and the synaptic input spatial clustering. We propose that a neuron with active dendrites can be modeled as a multilayer network that selectively amplifies responses to relevant spatiotemporal input spike patterns.

Dendritic signals command firing dynamics in a mathematical model of cerebellar Purkinje cells

Dendrites of cerebellar Purkinje cells (PCs) respond to brief excitations from parallel fibers with lasting plateau depolarizations. It is unknown whether these plateaus are local events that boost the synaptic signals or they propagate to the soma and directly take part in setting the cell firing dynamics. To address this issue, we analyzed a likely mechanism underlying plateaus in three representations of a reconstructed PC with increasing complexity. Analysis in an infinite cable suggests that Ca plateaus triggered by direct excitatory inputs from parallel fibers and their mirror signals, valleys (putatively triggered by the local feed forward inhibitory network), cannot propagate. However, simulations of the model in electrotonic equivalent cables prove that Ca plateaus (resp. valleys) are conducted over the entire cell with velocities typical of passive events once they are triggered by threshold synaptic inputs that turn the membrane current inward (resp. outward) over the whole cell surface. Bifurcation analysis of the model in equivalent cables, and simulations in a fully reconstructed PC both indicate that dendritic Ca plateaus and valleys, respectively, command epochs of firing and silencing of PCs.

Target-dependent feedforward inhibition mediated by short-term synaptic plasticity in the cerebellum

Cerebellar feedforward inhibition (FFI) is mediated by two distinct pathways targeting different subcellular compartments of Purkinje cells (PCs). The axon of the granule cell, the parallel fiber, makes excitatory synapses not only onto PCs but also onto two types of interneurons, basket and stellate cells. Basket and stellate cells then send inhibitory signals to the soma and dendrites of Purkinje cells, respectively. Functional differences between somatic and dendritic FFI pathways, however, remain unknown. Here we address this question by examining how basket and stellate cells are recruited dynamically under high-frequency granule cell inputs at mice cerebellum. Short-term plasticity of various synapses within the FFI circuit has been explored. Unexpectedly, the parallel fiber synapse, which was considered to be facilitating during repetitive stimulation, shows depression, when the postsynaptic target is a basket cell. Other factors in the FFI circuit, such as firing properties of interneurons and dynamics of inhibitory synapses, are similar between somatic and dendritic pathways. The target-dependent parallel fiber synaptic plasticity has functional consequences for the two FFI pathways, because we observe that PCs receive transient somatic inhibition during 50 Hz stimulation of granule cells but persistent dendritic inhibition.

Dendritic Kv3.3 potassium channels in cerebellar purkinje cells regulate generation and spatial dynamics of dendritic Ca2+ spikes

Purkinje cell dendrites are excitable structures with intrinsic and synaptic conductances contributing to the generation and propagation of electrical activity. Voltage-gated potassium channel subunit Kv3.3 is expressed in the distal dendrites of Purkinje cells. However, the functional relevance of this dendritic distribution is not understood. Moreover, mutations in Kv3.3 cause movement disorders in mice and cerebellar atrophy and ataxia in humans, emphasizing the importance of understanding the role of these channels. In this study, we explore functional implications of this dendritic channel expression and compare Purkinje cell dendritic excitability in wild-type and Kv3.3 knockout mice. We demonstrate enhanced excitability of Purkinje cell dendrites in Kv3.3 knockout mice, despite normal resting membrane properties. Combined data from local application pharmacology, voltage clamp analysis of ionic currents, and assessment of dendritic Ca(2+) spike threshold in Purkinje cells suggest a role for Kv3.3 channels in opposing Ca(2+) spike initiation. To study the physiological relevance of altered dendritic excitability, we measured [Ca(2+)](i) changes throughout the dendritic tree in response to climbing fiber activation. Ca(2+) signals were specifically enhanced in distal dendrites of Kv3.3 knockout Purkinje cells, suggesting a role for dendritic Kv3.3 channels in regulating propagation of electrical activity and Ca(2+) influx in distal dendrites. These findings characterize unique roles of Kv3.3 channels in dendrites, with implications for synaptic integration, plasticity, and human disease.

Neocortical networks entrain neuronal circuits in cerebellar cortex

Activity in neocortex is often characterized by synchronized oscillations of neurons and networks, resulting in the generation of a local field potential (LFP) and electroencephalogram. Do the neuronal networks of the cerebellum also generate synchronized oscillations and are they under the influence of those in the neocortex? Here we show that, in the absence of any overt external stimulus, the cerebellar cortex generates a slow oscillation that is correlated with that of the neocortex. Disruption of the neocortical slow oscillation abolishes the cerebellar slow oscillation, whereas blocking cerebellar activity has no overt effect on the neocortex. We provide evidence that the cerebellar slow oscillation results in part from the activation of granule, Golgi, and Purkinje neurons. In particular, we show that granule and Golgi cells discharge trains of single spikes, and Purkinje cells generate complex spikes, during the "up" state of the slow oscillation. Purkinje cell simple spiking is weakly related to the cerebellar and neocortical slow oscillation in a minority of cells. Our results indicate that the cerebellum generates rhythmic network activity that can be recorded as an LFP in the anesthetized animal, which is driven by synchronized oscillations of the neocortex. Furthermore, we show that correlations between neocortical and cerebellar LFPs persist in the awake animal, indicating that neocortical circuits modulate cerebellar neurons in a similar manner in natural behavioral states. Thus, the projection neurons of the neocortex collectively exert a driving and modulatory influence on cerebellar network activity.

Topography and response timing of intact cerebellum stained with absorbance voltage-sensitive dye

Physiological activity of the turtle cerebellar cortex (Cb), maintained in vitro, was recorded during microstimulation of inferior olive (IO). Previous single-electrode responses to such stimulation showed similar latencies across a limited region of Cb, yet those recordings lacked spatial and temporal resolution and the recording depth was variable. The topography and timing of those responses were reexamined using photodiode optical recordings. Because turtle Cb is thin and unfoliated, its entire surface can be stained by a voltage-sensitive dye and transilluminated to measure changes in its local absorbance. Microstimulation of the IO evoked widespread depolarization from the rostral to the caudal edge of the contralateral Cb. The time course of responses measured at a single photodiode matched that of single-microelectrode responses in the corresponding Cb locus. The largest and most readily evoked response was a sagittal band centered about 0.7 mm from the midline. Focal white-matter (WM) microstimulation on the ventricular surface also activated sagittal bands, whereas stimulation of adjacent granule cells evoked a radial patch of activation. In contrast, molecular-layer (ML) microstimulation evoked transverse beams of activation, centered on the rostrocaudal stimulus position, which traveled bidirectionally across the midline to the lateral edges of the Cb. A timing analysis demonstrated that both IO and WM microstimulation evoked responses with a nearly simultaneous onset along a sagittal band, whereas ML microstimulation evoked a slowly propagating wave traveling about 25 cm/s. The response similarity to IO and WM microstimulation suggests that the responses to WM microstimulation are dominated by activation of its climbing fibers. The Cb's role in the generation of precise motor control may result from these temporal and topographic differences in orthogonally oriented pathways. Optical recordings of the turtle's thin flat Cb can provide insights into that role.

The origin of the complex spike in cerebellar Purkinje cells

Activation of the climbing fiber input powerfully excites cerebellar Purkinje cells via hundreds of widespread dendritic synapses, triggering dendritic spikes as well as a characteristic high-frequency burst of somatic spikes known as the complex spike. To investigate the relationship between dendritic spikes and the spikelets within the somatic complex spike, and to evaluate the importance of the dendritic distribution of climbing fiber synapses, we made simultaneous somatic and dendritic patch-clamp recordings from Purkinje cells in cerebellar slices. Injection of large climbing fiber-like synaptic conductances at the soma using dynamic clamp was sufficient to reproduce the complex spike, independently of dendritic spikes, indicating that neither a dendritic synaptic distribution nor dendritic spikes are required. Furthermore, we found that dendritic spikes are not directly linked to spikelets in the complex spike, and that each dendritic spike is associated with only 0.24 +/- 0.09 extra somatic spikelets. Rather, we demonstrate that dendritic spikes regulate the pause in firing that follows the complex spike. Finally, using dual somatic and axonal recording, we show that all spikelets in the complex spike are axonally generated. Thus, complex spike generation proceeds relatively independently of dendritic spikes, reflecting the dual functional role of climbing fiber input: triggering plasticity at dendritic synapses and generating a distinct output signal in the axon. The encoding of dendritic spiking by the post-complex spike pause provides a novel computational function for dendritic spikes, which could serve to link these two roles at the level of the target neurons in the deep cerebellar nuclei.

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.

The properties and implications of NMDA spikes in neocortical pyramidal cells

Integration of synaptic input in dendritic trees is a nonlinear process in which excitatory input may elicit spikes localized within the branch receiving input. In addition to membrane current-driven events, a type of dendritic spike has recently been described that instead depends on NMDA receptor current. These NMDA spikes enable superlinear integration among inputs targeted close together on a single branch. Here a compartment model of a layer 5 pyramidal cell was used to examine the mechanisms underlying NMDA spikes and to test properties not directly accessible experimentally. The results indicate the following: initiation of an NMDA spike in a tertiary dendrite in 1 mm [Mg2+] requires an NMDA conductance density equivalent to 6-8 nS within a 25-microm-long dendritic subsegment; dendritic membrane currents are not required for NMDA spike production; and targeted dendritic (but not somatic) inhibitory input is exquisitely suited to veto an NMDA spike if it arrives within a 30 ms window in time. Finally, an analysis of the spatial density of NMDA conductance required for NMDA spike production implies that, at least up to the age (postnatal day 35) that these events have been observed, most of the excitatory synaptic conductance arriving at pyramidal cells is NMDA mediated.

Dendritic calcium spikes are tunable triggers of cannabinoid release and short-term synaptic plasticity in cerebellar Purkinje neurons

Understanding the relationship between dendritic excitability and synaptic plasticity is vital for determining how dendrites regulate the input-output function of the neuron. Dendritic calcium spikes have been associated with the induction of long-term changes in synaptic efficacy. Here we use direct recordings from cerebellar Purkinje cell dendrites to show that synaptically activated local dendritic calcium spikes are potent triggers of cannabinoid release, producing a profound and short-term reduction in synaptic efficacy at parallel fiber synapses. Enhancing dendritic excitability by modulating dendritic large-conductance calcium-activated potassium (BK) channels improves the spread of dendritic calcium spikes and enhances cannabinoid release at the expense of spatial specificity. Our findings reveal that dendritic calcium spikes provide a local and tunable coincidence detection mechanism that readjusts synaptic gain when synchronous activity reaches a threshold, and they reveal a tight link between the regulation of dendritic excitability and the induction of synaptic plasticity.

Neuronal oscillations enhance stimulus discrimination by ensuring action potential precision

Although oscillations in membrane potential are a prominent feature of sensory, motor, and cognitive function, their precise role in signal processing remains elusive. Here we show, using a combination of in vivo, in vitro, and theoretical approaches, that both synaptically and intrinsically generated membrane potential oscillations dramatically improve action potential (AP) precision by removing the membrane potential variance associated with jitter-accumulating trains of APs. This increased AP precision occurred irrespective of cell type and--at oscillation frequencies ranging from 3 to 65 Hz--permitted accurate discernment of up to 1,000 different stimuli. At low oscillation frequencies, stimulus discrimination showed a clear phase dependence whereby inputs arriving during the trough and the early rising phase of an oscillation cycle were most robustly discriminated. Thus, by ensuring AP precision, membrane potential oscillations dramatically enhance the discriminatory capabilities of individual neurons and networks of cells and provide one attractive explanation for their abundance in neurophysiological systems.