Dendritic spikes and activity-dependent synaptic plasticity

Whereas the regenerative nature of action potential conduction in axons has been known since the late 1940s, neuronal dendrites have been considered as passive cables transferring incoming synaptic activity to the soma. The relatively recent discovery that neuronal dendrites contain active conductances has revolutionized our view of information processing in neurons. In many neuronal cell types, sodium action potentials initiated at the axon initial segment can back-propagate actively into the dendrite thereby serving, for the dendrite, as an indicator of the output activity of the neuron. In addition, the dendrites themselves can initiate action-potential-like regenerative responses, so-called dendritic spikes, that are mediated either by the activation of sodium, calcium, and/or N-methyl-D-aspartate receptor channels. Here, we review the recent experimental and theoretical evidence for a role of regenerative dendritic activity in information processing within neurons and, especially, in activity-dependent synaptic plasticity.     

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.     

Effects of active conductance distribution over dendrites on the synaptic integration in an identified nonspiking interneuron

The synaptic integration in individual central neuron is critically affected by how active conductances are distributed over dendrites. It has been well known that the dendrites of central neurons are richly endowed with voltage- and ligand-regulated ion conductances. Nonspiking interneurons (NSIs), almost exclusively characteristic to arthropod central nervous systems, do not generate action potentials and hence lack voltage-regulated sodium channels, yet having a variety of voltage-regulated potassium conductances on their dendritic membrane including the one similar to the delayed-rectifier type potassium conductance. It remains unknown, however, how the active conductances are distributed over dendrites and how the synaptic integration is affected by those conductances in NSIs and other invertebrate neurons where the cell body is not included in the signal pathway from input synapses to output sites. In the present study, we quantitatively investigated the functional significance of active conductance distribution pattern in the spatio-temporal spread of synaptic potentials over dendrites of an identified NSI in the crayfish central nervous system by computer simulation. We systematically changed the distribution pattern of active conductances in the neuron's multicompartment model and examined how the synaptic potential waveform was affected by each distribution pattern. It was revealed that specific patterns of nonuniform distribution of potassium conductances were consistent, while other patterns were not, with the waveform of compound synaptic potentials recorded physiologically in the major input-output pathway of the cell, suggesting that the possibility of nonuniform distribution of potassium conductances over the dendrite cannot be excluded as well as the possibility of uniform distribution. Local synaptic circuits involving input and output synapses on the same branch or on the same side were found to be potentially affected under the condition of nonuniform distribution while operation of the major input-output pathway from the soma side to the one on the opposite side remained the same under both conditions of uniform and nonuniform distribution of potassium conductances over the NSI dendrite.     

Thin dendrites of cerebellar interneurons confer sublinear synaptic integration and a gradient of short-term plasticity

Interneurons are critical for neuronal circuit function, but how their dendritic morphologies and membrane properties influence information flow within neuronal circuits is largely unknown. We studied the spatiotemporal profile of synaptic integration and short-term plasticity in dendrites of mature cerebellar stellate cells by combining two-photon guided electrical stimulation, glutamate uncaging, electron microscopy, and modeling. Synaptic activation within thin (0.4?μm) dendrites produced somatic responses that became smaller and slower with increasing distance from the soma, sublinear subthreshold input-output relationships, and a somatodendritic gradient of short-term plasticity. Unlike most studies showing that neurons employ active dendritic mechanisms, we found that passive cable properties of thin dendrites determine the sublinear integration and plasticity gradient, which both result from large?dendritic depolarizations that reduce synaptic driving force. These integrative properties allow stellate cells to act as spatiotemporal filters of synaptic input patterns, thereby biasing their output in favor of sparse presynaptic activity.     

Role of active dendritic conductances in subthreshold input integration

Dendrites of many types of neurons contain voltage-dependent conductances that are active at subthreshold membrane potentials. To understand the computations neurons perform it is key to understand the role of active dendrites in the subthreshold processing of synaptic inputs. We examine systematically how active dendritic conductances affect the time course of postsynaptic potentials propagating along dendrites, and how they affect the interaction between such signals. Voltage-dependent currents can be classified into two types that have qualitatively different effects on subthreshold input responses: regenerative dendritic currents boost and broaden EPSPs, while restorative currents attenuate and narrow EPSPs. Importantly, the effects of active dendritic currents on EPSP shape increase as the EPSP travels along the dendrite. The effectiveness of active currents in modulating the EPSP shape is determined by their activation time constant: the faster it is, the stronger the effect on EPSP amplitude, while the largest effects on EPSP width occur when it is comparable to the membrane time constant. We finally demonstrate that the two current types can differentially improve precision and robustness of neural computations: restorative currents enhance coincidence detection of dendritic inputs, whereas direction selectivity to sequences of dendritic inputs is enhanced by regenerative dendritic currents.     

Active dendrites,potassium channels and synaptic plasticity

The dendrites of CA1 pyramidal neurons in the hippocampus express numerous types of voltage-gated ion channel, but the distributions or densities of many of these channels are very non-uniform. Sodium channels in the dendrites are responsible for action potential (AP) propagation from the axon into the dendrites (back-propagation); calcium channels are responsible for local changes in dendritic calcium concentrations following back-propagating APs and synaptic potentials; and potassium channels help regulate overall dendritic excitability. Several lines of evidence are presented here to suggest that back-propagating APs, when coincident with excitatory synaptic input, can lead to the induction of either long-term depression (LTD) or long-term potentiation (LTP). The induction of LTD or LTP is correlated with the magnitude of the rise in intracellular calcium. When brief bursts of synaptic potentials are paired with postsynaptic APs in a theta-burst pairing paradigm, the induction of LTP is dependent on the invasion of the AP into the dendritic tree. The amplitude of the AP in the dendrites is dependent, in part, on the activity of a transient, A-type potassium channel that is expressed at high density in the dendrites and correlates with the induction of the LTP. Furthermore, during the expression phase of the LTP, there are local changes in dendritic excitability that may result from modulation of the functioning of this transient potassium channel. The results support the view that the active properties of dendrites play important roles in synaptic integration and synaptic plasticity of these neurons.     

Linear summation of excitatory inputs by CA1 pyramidal neurons

A fundamental problem in neurobiology is understanding the arithmetic that dendrites use to integrate inputs. The impact of dendritic morphology and active conductances on input summation is still unknown. To study this, we use glutamate iontophoresis and synaptic stimulation to position pairs of excitatory inputs throughout the apical, oblique, and basal dendrites of CA1 pyramidal neurons in rat hippocampal slices. Under a variety of stimulation regimes, we find a linear summation of most input combinations that is implemented by a surprising balance of boosting and shunting mechanisms. Active conductances in dendrites paradoxically serve to make summation linear. This "active linearity" can reconcile predictions from cable theory with the observed linear summation in vivo and suggests that a simple arithmetic is used by apparently complex dendritic trees.     

Information processing by nonspiking interneurons: passive and active properties of dendritic membrane determine synaptic integration

Nonspiking interneurons control activities of postsynaptic cells without generating action potentials in the central nervous system of many invertebrates. Physiological characteristics of their dendritic membrane have been analyzed in previous studies using single electrode current- and voltage-clamp techniques. We constructed a single compartment model of an identified nonspiking interneuron of crayfish. Experimental results allowed us to simulate how the passive and active properties of the dendritic membrane influence the integrative processing of synaptic inputs. The results showed that not only the peak amplitude but also the time course of synaptic potentials were dependent on the membrane potential level at which the synaptic activity was evoked. When the synaptic input came sequentially, each individual input was still discernible at depolarized levels at which the membrane time constant was short due to depolarization-dependent membrane conductances. In contrast, synaptic potentials merged with each other to develop a sustained potential at hyperpolarized levels where the membrane behaved passively. Thus, synaptic integration in a single nonspiking interneuron depends on the value of membrane potential at which it occurs. This probably reflects the temporal resolution required for specific types of information processing.     

NMDA receptor-mediated dendritic spikes and coincident signal amplification

Dendrites of cortical neurons possess active conductances, which contribute to the nonlinear processing of synaptic information. Recently it has been shown that basal dendrites can generate highly localized spikes mediated by NMDA receptor channels. These spikes may serve as a powerful mechanism to detect and amplify synchronously activated spatially clustered excitatory synaptic inputs in individual dendritic segments, and may enable parallel processing in several integrative dendritic subunits.     

Plasticity of dendritic function

The various properties of neuronal dendrites--their morphology, active membrane and synaptic properties--all play important roles in determining the functional capabilities of central nervous system neurons. Because of their fundamental involvement in both synaptic integration and synaptic plasticity, the active dendritic properties are important for both neuronal information processing and storage. The active properties of dendrites are determined by the densities of voltage-gated ion channels located within the dendrites in addition to the biophysical characteristics of those channels. The real power of this system resides in the level of plasticity that is provided by the many forms of channel modulation known to exist in neurons. Indeed, voltage gated ion channel modulation shapes the active properties of neuronal dendrites to specific conditions, thus tailoring the functional role of the single neuron within its circuit.     

Dendritic integration of excitatory synaptic input

A fundamental function of nerve cells is the transformation of incoming synaptic information into specific patterns of action potential output. An important component of this transformation is synaptic integration--the combination of voltage deflections produced by a myriad of synaptic inputs into a singular change in membrane potential. There are three basic elements involved in integration: the amplitude of the unitary postsynaptic potential; the manner in which non-simultaneous unitary events add in time (temporal summation), and the addition of unitary events occurring simultaneously in separate regions of the dendritic arbor (spatial summation). This review discusses how passive and active dendritic properties, and the functional characteristics of the synapse, shape these three elements of synaptic integration.     

Active Dendrites Enhance Neuronal Dynamic Range

Since the first experimental evidences of active conductances in dendrites, most neurons have been shown to exhibit dendritic excitability through the expression of a variety of voltage-gated ion channels. However, despite experimental and theoretical efforts undertaken in the past decades, the role of this excitability for some kind of dendritic computation has remained elusive. Here we show that, owing to very general properties of excitable media, the average output of a model of an active dendritic tree is a highly non-linear function of its afferent rate, attaining extremely large dynamic ranges (above 50 dB). Moreover, the model yields double-sigmoid response functions as experimentally observed in retinal ganglion cells. We claim that enhancement of dynamic range is the primary functional role of active dendritic conductances. We predict that neurons with larger dendritic trees should have larger dynamic range and that blocking of active conductances should lead to a decrease in dynamic range.     

Transfer properties of neuronal dendrites with tonically activated conductances

The somatopetal current transfer was studied in the mathematical models of a reconstructed brainstem motoneuron with tonically activated excitatory synaptic inputs uniformly distributed over dendritic arborization. The soma and axon provided a constant passive leak. The extrasynaptic dendritic membrane was either passive or active (of a Hodgkin-Huxley type). The longitudinal membrane current density (per unit path length) was used as an estimate of the current transfer effectiveness of different dendritic paths. Introduction of a steady uniform voltage-independent conductance per unit membrane area simulated such a synaptic activation. This actions always produced a spatially inhomogeneous membrane depolarization decaying from the distal dendritic tips toward the soma. The reason for such an inhomogeneity was the preponderance of somatopetal over somatofugal input conductance at every site in the dendrites with sealed distal ends and a leaky somatic end. In active dendrites, partial voltage-dependent extrasynaptic conductances followed this depolarization according to their activation-inactivation kinetics. The greater the local depolarization, the greater the contribution of the non-inactivating potassium conductance to the total membrane conductance. The contribution of the inactivated sodium conductance was one order of magnitude smaller. Correspondingly, the effective equilibrium potential of the total transmembrane current became spatially inhomogeneous and shifted to the potassium equilibrium potential. In the passive dendrites, the equilibrium potential remained spatially homogeneous. Inhomogeneities of the dendritic geometry (abrupt change in the diameter and, especially, asymmetrical branching) caused characteristic perturbations in the voltage gradient, so that the path profiles of the voltage, conductances, and currents diverged. This indicated a geometry-induced separation of the dendritic paths in their transfer effectiveness. Active dendrites of the same geometry were less effective than passive ones due to the effect of the potassium conductance associated with the hyperpolarizing equilibrium potential.     

Emerging methodologies for the study of hypothalamic gonadotropin-releasing-hormone (GnRH) neurons

Gonadotropin-releasing-hormone (GnRH) neurons form part of a central neural oscillator that controls sexual reproduction through intermittent release of the GnRH peptide. Activity of GnRH neurons, and by extension release of GnRH, has been proposed to reflect intrinsic properties and synaptic input of GnRH neurons. To study GnRH neurons, we used traditional electrophysiology and computational methods. These emerging methodologies enhance the elucidation of processing in GnRH neurons. We used dynamic current-clamping to understand how living GnRH somata process input from glutamate and GABA, two key neurotransmitters in the neuroendocrine hypothalamus. In order to study the impact of synaptic integration in dendrites and neuronal morphology, we have developed full-morphology models of GnRH neurons. Using dynamic clamping, we have demonstrated that small-amplitude glutamatergic currents can drive repetitive firing in GnRH neurons. Furthermore, application of simulated GABAergic synapses with a depolarized reversal potential have revealed two functional subpopulations of GnRH neurons: one population in which GABA chronically depolarizes membrane potential (without inducing action potentials) and a second population in which GABAergic excitation results in slow spiking. Finally, when AMPA-type and GABA-type simulated inputs are applied together, action potentials occur when the AMPA-type conductance occurs during the descending phase of GABAergic excitation and at the nadir of GABAergic inhibition. Compartmental computer models have shown that excitatory synapses at >300 microns from somtata are unable to drive spiking with purely passive dendrites. In models with active dendrites, distal synapses are more efficient at driving spiking than somatic inputs. We then used our models to extend the results from dynamic current clamping at GnRH somata to distribute synaptic inputs along the dendrite. We show that propagation delays for dendritic synapses alter synaptic integration in GnRH neurons by widening the temporal window of interaction for the generation of action potentials. Finally, we have shown that changes in dendrite morphology can modulate the output of GnRH neurons by altering the efficacy of action potential generation in response to after-depolarization potentials (ADPs). Taken together, the methodologies of dynamic current clamping and multi-compartmental modeling can make major contributions to the study of synaptic integration and structure-function relationships in hypothalamic GnRH neurons. Use of these methodological approaches will continue to provide keen insights leading to conceptual advances in our understanding of reproductive hormone secretion in normal and pathological physiology and open the door to understanding whether the mechanisms of pulsatile GnRH release are conserved across species.     

Effects of active versus passive dendritic membranes on the transfer properties of a simulated neuron

In a simulated neuron with a dendritic tree, the relative effects of active and passive dendritic membranes on transfer properties were studied. The simulations were performed by means of a digital computer. The computations calculated the changes in transmembrane voltages of many compartments over time as a function of other biophysical variables. These variables were synaptic input intensity, critical firing threshold, rate of leakage of current across the membrane, and rate of longitudinal current spread between compartments. For both passive and active dendrites, the transfer properties of the soma studied for different rates of longitudinal current spread. With low rates of current spread, graded changes in firing threshold produced correspondingly graded changes in output discharge. With high rates of current spread, the neuron became a bistable operator where spiking was enhanced if the threshold was below a certain level and suppressed if the threshold was above that level. Since alterations in firing threshold were shown to have the same effect on firing rate as alterations in synaptic input intensity, the neuron can be said to change from graded to contrast-enhancing in its response to stimuli of different intensities. The presence or absence of dendritic spiking was found to have a significant effect on the integrative properties of the simulated neuron. In particular, contrast enhancement was considerably more pronounced in neurons with passive than with active dendrites in that somatic spike rates reached a higher maximum when dendrites were passive. With active dendrites, a less intense input was needed to initiate somatic spiking than with passive dendrites because a distal dendritic spike could easily propagate by means of longitudinal current spread to the soma. Once somatic spiking was initiated, though, spike rates tended to be lower with active than with passive dendrites because the soma recovered more slowly from its post-spike refractory period if it was also influenced by refractory periods in the dendrites. The experiment of comparing neurons with active and passive dendrites was repeated at a different, higher value of synaptic input. The same differences in transfer properties between the active and passive cases emerged as before. Spiking patterns in neurons with active dendrites were also affected by the time distribution of synaptic inputs. In a previous study, inputs had been random over both space and time, varying about a predetermined mean, whereas in the present study, inputs were random over space but uniform over time. When inputs were made uniform over time, spiking became more difficult to initiate and the transition from graded to bistable response became less sharp.     

Computational simulation of the input-output relationship in hippocampal pyramidal cells

The precise mapping of how complex patterns of synaptic inputs are integrated into specific patterns of spiking output is an essential step in the characterization of the cellular basis of network dynamics and function. Relative to other principal neurons of the hippocampus, the electrophysiology of CA1 pyramidal cells has been extensively investigated. Yet, the precise input-output relationship is to date unknown even for this neuronal class. CA1 pyramidal neurons receive laminated excitatory inputs from three distinct pathways: recurrent CA1 collaterals on basal dendrites, CA3 Schaffer collaterals, mostly on oblique and proximal apical dendrites, and entorhinal perforant pathway on distal apical dendrites. We implemented detailed computer simulations of pyramidal cell electrophysiology based on three-dimensional anatomical reconstructions and compartmental models of available biophysical properties from the experimental literature. To investigate the effect of synaptic input on axosomatic firing, we stochastically distributed a realistic number of excitatory synapses in each of the three dendritic layers. We then recorded the spiking response to different stimulation patterns. For all dendritic layers, synchronous stimuli resulted in trains of spiking output and a linear relationship between input and output firing frequencies. In contrast, asynchronous stimuli evoked non-bursting spike patterns and the corresponding firing frequency input-output function was logarithmic. The regular/irregular nature of the input synaptic intervals was only reflected in the regularity of output inter-burst intervals in response to synchronous stimulation, and never affected firing frequency. Synaptic stimulations in the basal and proximal apical trees across individual neuronal morphologies yielded remarkably similar input-output relationships. Results were also robust with respect to the detailed distributions of dendritic and synaptic conductances within a plausible range constrained by experimental evidence. In contrast, the input-output relationship in response to distal apical stimuli showed dramatic differences from the other dendritic locations as well as among neurons, and was more sensible to the exact channel densities. Action Editor: Alain Destexhe     

Unique roles of SK and Kv4.2 potassium channels in dendritic integration

Focal activation of glutamate receptors in distal dendrites of hippocampal pyramidal cells triggers voltage-dependent Ca(2+) channel-mediated plateau potentials that are confined to the stimulated dendrite. We examined the role of dendritic K(+) conductances in determining the amplitude, duration, and spatial compartmentalization of plateau potentials. Manipulations that blocked SK-type Ca(2+)-activated K(+) channels, including apamin and BAPTA dialysis, increased the duration of plateau potentials without affecting their amplitude or compartmentalization. Manipulations that blocked Kv4.2 A-type K(+) channels, including a dominant-negative Kv4.2 construct and 4-aminopyridine, increased the amplitude of plateau potentials by allowing them to recruit neighboring dendrites. Prolongation of plateau potentials or block of Kv4.2 channels at branch points facilitated the ability of dendritic excitation to trigger fast action potentials. SK channels thus underlie repolarization of dendritic plateau potentials, whereas Kv4.2 channels confine these potentials to single dendritic branches, and both act in concert to regulate synaptic integration.     

Initiation of Sodium Spikelets in Basal Dendrites of Neocortical Pyramidal Neurons

Cortical information processing relies critically on the processing of electrical signals in pyramidal neurons. Electrical transients mainly arise when excitatory synaptic inputs impinge upon distal dendritic regions. To study the dendritic aspect of synaptic integration one must record electrical signals in distal dendrites. Since thin dendritic branches, such as oblique and basal dendrites, do not support routine glass electrode measurements, we turned our effort towards voltage-sensitive dye recordings. Using the optical imaging approach we found and reported previously that basal dendrites of neocortical pyramidal neurons show an elaborate repertoire of electrical signals, including backpropagating action potentials and glutamate-evoked plateau potentials. Here we report a novel form of electrical signal, qualitatively and quantitatively different from backpropagating action potentials and dendritic plateau potentials. Strong glutamatergic stimulation of an individual basal dendrite is capable of triggering a fast spike, which precedes the dendritic plateau potential. The amplitude of the fast initial spikelet was actually smaller that the amplitude of the backpropagating action potential in the same dendritic segment. Therefore, the fast initial spike was dubbed “spikelet”. Both the basal spikelet and plateau potential propagate decrementally towards the cell body, where they are reflected in the somatic whole-cell recordings. The low incidence of basal spikelets in the somatic intracellular recordings and the impact of basal spikelets on soma-axon action potential initiation are discussed.     

Geometry-induced features of current transfer in neuronal dendrites with tonically activated conductances

The impact of dendritic geometry on somatopetal transfer of the current generated by steady uniform activation of excitatory synaptic conductance distributed over passive, or active (Hodgkin-Huxley type), dendrites was studied in simulated neurons. Such tonic activation was delivered to the uniform dendrite and to the dendrites with symmetric or asymmetric branching with various ratios of branch diameters. Transfer effectiveness of the dendrites with distributed sources was estimated by the core current increment directly related to the total membrane current per unit path length. The effectiveness decreased with increasing path distance from the soma along uniform branches. The primary reason for this was the asymmetry of somatopetal vs somatofugal input core conductance met by synaptic current due to a greater leak conductance at the proximal end of the dendrite. Under these conditions, an increasing somatopetal core current and a corresponding drop of the depolarization membrane potential occurred. The voltage-dependent extrasynaptic conductances, if present, followed this depolarization. Consequently, the driving potential and membrane current densities decreased with increasing path distance from the soma. All path profiles were perturbed at bifurcations, being identical in symmetrical branches and diverging in asymmetrical ones. These perturbations were caused by voltage gradient breaks (abrupt change in the profile slope) occurring at the branching node due to coincident inhomogeneity of the dendritic core cross-section area and its conductance. The gradient was greater on the side of the smaller effective cross-section. Correspondingly, the path profiles of the somatopetal current transfer effectiveness were broken and/or diverged. The dendrites, their paths, and sites which were more effective in the current transfer from distributed sources were also more effective in the transfer from single-site inputs. The effectiveness of the active dendrite depended on the activation-inactivation kinetics of its voltage-gated conductances. In particular, dendrites with the same geometry were less effective with the Hodgkin-Huxley membrane than with the passive membrane, because of the effect of the noninactivating K⁺-conductance associated with the hyperpolarization equilibrium potential. Such electrogeometrical coupling may form a basis for path-dependent input-output conversion in the dendritic neurons, as the output discharge rate is defined by the net current delivered to the soma. Received: 18 December 1997 / Accepted in revised form: 12 June 1998