Computational analysis of action potential initiation in mitral cell soma and dendrites based on dual patch recordings

Optimized Signal Flow through Photoreceptors Supports the High-Acuity Vision of Primates

The fovea is a neural specialization that endows humans and other primates with the sharpest vision among mammals. This performance originates in the foveal cones, which are extremely narrow and long to form a high-resolution pixel array. Puzzlingly, this form is predicted to impede electrical conduction to an extent that appears incompatible with vision. We observe the opposite: signal flow through even the longest cones (0.4-mm axons) is essentially lossless. Unlike in most neurons, amplification and impulse generation by voltage-gated channels are dispensable. Rather, sparse channel activity preserves intracellular current, which flows as if unobstructed by organelles. Despite these optimizations, signaling would degrade if cones were lengthier. Because cellular packing requires that cone elongation accompanies foveal expansion, this degradation helps explain why the fovea is a constant, miniscule size despite multiplicative changes in eye size through evolution. These observations reveal how biophysical mechanisms tailor form-function relationships for primate behavioral performance.

Predicting brain organization with a computational model: 50-year perspective on lateral inhibition and oscillatory gating by dendrodendritic synapses

The first compartmental computer models of brain neurons using the Rall method predicted novel and unexpected dendrodendritic interactions between mitral and granule cells in the olfactory bulb. We review the models from a 50-year perspective on the work that has challenged, supported, and extended the original proposal that these interactions mediate both lateral inhibition and oscillatory activity, essential steps in the neural basis of olfactory processing and perception. We highlight strategies behind the neurophysiological experiments and the Rall methods that enhance the ability of detailed compartmental modeling to give counterintuitive predictions that lead to deeper insights into neural organization at the synaptic and circuit level. The application of these methods to mechanisms of neurogenesis and plasticity are exciting challenges for the future.

Generative Biophysical Modeling of Dynamical Networks in the Olfactory System

Generative models are computational models designed to generate appropriate values for all of their embedded variables, thereby simulating the response properties of a complex system based on the coordinated interactions of a multitude of physical mechanisms. In systems neuroscience, generative models are generally biophysically based compartmental models of neurons and networks that are explicitly multiscale, being constrained by experimental data at multiple levels of organization from cellular membrane properties to large-scale network dynamics. As such, they are able to explain the origins of emergent properties in complex systems, and serve as tests of sufficiency and as quantitative instantiations of working hypotheses that may be too complex to simply intuit. Moreover, when adequately constrained, generative biophysical models are able to predict novel experimental outcomes, and consequently are powerful tools for experimental design. We here outline a general strategy for the iterative design and implementation of generative, multiscale biophysical models of neural systems. We illustrate this process using our ongoing, iteratively developing model of the mammalian olfactory bulb. Because the olfactory bulb exhibits diverse and interesting properties at multiple scales of organization, it is an attractive system in which to illustrate the value of generative modeling across scales.

Human Cortical Pyramidal Neurons: From Spines to Spikes via Models

We present detailed models of pyramidal cells from human neocortex, including models on their excitatory synapses, dendritic spines, dendritic NMDA- and somatic/axonal Na⁺ spikes that provided new insights into signal processing and computational capabilities of these principal cells. Six human layer 2 and layer 3 pyramidal cells (HL2/L3 PCs) were modeled, integrating detailed anatomical and physiological data from both fresh and postmortem tissues from human temporal cortex. The models predicted particularly large AMPA- and NMDA-conductances per synaptic contact (0.88 and 1.31 nS, respectively) and a steep dependence of the NMDA-conductance on voltage. These estimates were based on intracellular recordings from synaptically-connected HL2/L3 pairs, combined with extra-cellular current injections and use of synaptic blockers, and the assumption of five contacts per synaptic connection. A large dataset of high-resolution reconstructed HL2/L3 dendritic spines provided estimates for the EPSPs at the spine head (12.7 ± 4.6 mV), spine base (9.7 ± 5.0 mV), and soma (0.3 ± 0.1 mV), and for the spine neck resistance (50–80 MΩ). Matching the shape and firing pattern of experimental somatic Na⁺-spikes provided estimates for the density of the somatic/axonal excitable membrane ion channels, predicting that 134 ± 28 simultaneously activated HL2/L3-HL2/L3 synapses are required for generating (with 50% probability) a somatic Na⁺ spike. Dendritic NMDA spikes were triggered in the model when 20 ± 10 excitatory spinous synapses were simultaneously activated on individual dendritic branches. The particularly large number of basal dendrites in HL2/L3 PCs and the distinctive cable elongation of their terminals imply that ~25 NMDA-spikes could be generated independently and simultaneously in these cells, as compared to ~14 in L2/3 PCs from the rat somatosensory cortex. These multi-sites non-linear signals, together with the large (~30,000) excitatory synapses/cell, equip human L2/L3 PCs with enhanced computational capabilities. Our study provides the most comprehensive model of any human neuron to-date demonstrating the biophysical and computational distinctiveness of human cortical neurons.

Parallel odor processing by mitral and middle tufted cells in the olfactory bulb

The olfactory bulb (OB) transforms sensory input into spatially and temporally organized patterns of activity in principal mitral (MC) and middle tufted (mTC) cells. Thus far, the mechanisms underlying odor representations in the OB have been mainly investigated in MCs. However, experimental findings suggest that MC and mTC may encode parallel and complementary odor representations. We have analyzed the functional roles of these pathways by using a morphologically and physiologically realistic three-dimensional model to explore the MC and mTC microcircuits in the glomerular layer and deeper plexiform layer. The model makes several predictions. MCs and mTCs are controlled by similar computations in the glomerular layer but are differentially modulated in deeper layers. The intrinsic properties of mTCs promote their synchronization through a common granule cell input. Finally, the MC and mTC pathways can be coordinated through the deep short-axon cells in providing input to the olfactory cortex. The results suggest how these mechanisms can dynamically select the functional network connectivity to create the overall output of the OB and promote the dynamic synchronization of glomerular units for any given odor stimulus.

Biophysical constraints on lateral inhibition in the olfactory bulb

The mitral cells (MCs) of the mammalian olfactory bulb (OB) constitute one of two populations of principal neurons (along with middle/deep tufted cells) that integrate afferent olfactory information with top-down inputs and intrinsic learning and deliver output to downstream olfactory areas. MC activity is regulated in part by inhibition from granule cells, which form reciprocal synapses with MCs along the extents of their lateral dendrites. However, with MC lateral dendrites reaching over 1.5 mm in length in rats, the roles of distal inhibitory synapses pose a quandary. Here, we systematically vary the properties of a MC model to assess the capacity of inhibitory synaptic inputs on lateral dendrites to influence afferent information flow through MCs. Simulations using passivized models with varying dendritic morphologies and synaptic properties demonstrated that, even with unrealistically favorable parameters, passive propagation fails to convey effective inhibitory signals to the soma from distal sources. Additional simulations using an active model exhibiting action potentials, subthreshold oscillations, and a dendritic morphology closely matched to experimental values further confirmed that distal synaptic inputs along the lateral dendrite could not exert physiologically relevant effects on MC spike timing at the soma. Larger synaptic conductances representative of multiple simultaneous inputs were not sufficient to compensate for the decline in signal with distance. Reciprocal synapses on distal MC lateral dendrites may instead serve to maintain a common fast oscillatory clock across the OB by delaying spike propagation within the lateral dendrites themselves.

Sparse coding and lateral inhibition arising from balanced and unbalanced dendrodendritic excitation and inhibition

The precise mechanism by which synaptic excitation and inhibition interact with each other in odor coding through the unique dendrodendritic synaptic microcircuits present in olfactory bulb is unknown. Here a scaled-up model of the mitral-granule cell network in the rodent olfactory bulb is used to analyze dendrodendritic processing of experimentally determined odor patterns. We found that the interaction between excitation and inhibition is responsible for two fundamental computational mechanisms: (1) a balanced excitation/inhibition in strongly activated mitral cells, leading to a sparse representation of odorant input, and (2) an unbalanced excitation/inhibition (inhibition dominated) in surrounding weakly activated mitral cells, leading to lateral inhibition. These results suggest how both mechanisms can carry information about the input patterns, with optimal level of synaptic excitation and inhibition producing the highest level of sparseness and decorrelation in the network response. The results suggest how the learning process, through the emergent development of these mechanisms, can enhance odor representation of olfactory bulb.

Electrical responses of three classes of granule cells of the olfactory bulb to synaptic inputs in different dendritic locations

This work consists of a computational study of the electrical responses of three classes of granule cells of the olfactory bulb to synaptic activation in different dendritic locations. The constructed models were based on morphologically detailed compartmental reconstructions of three granule cell classes of the olfactory bulb with active dendrites described by Bhalla and Bower (1993, pp. 1948-1965) and dendritic spine distributions described by Woolf et al. (1991, pp. 1837-1854). The computational studies with the model neurons showed that different quantities of spines have to be activated in each dendritic region to induce an action potential, which always was originated in the active terminal dendrites, independently of the location of the stimuli, and the morphology of the dendritic tree. These model predictions might have important computational implications in the context of olfactory bulb circuits.

Functional neurology of a brain system: a 3D olfactory bulb model to process natural odorants

The network of interactions between mitral and granule cells in the olfactory bulb is a critical step in the processing of odor information underlying the neural basis of smell perception. We are building the first computational model in 3 dimensions of this network in order to analyze the rules for connectivity and function within it. The initial results indicate that this network can be modeled to simulate experimental results on the activation of the olfactory bulb by natural odorants, providing a much more powerful approach for 3D simulation of brain neurons and microcircuits.

A two-layer biophysical model of cholinergic neuromodulation in olfactory bulb

Cholinergic inputs from the basal forebrain regulate multiple olfactory bulb (OB) functions, including odor discrimination, perceptual learning, and short-term memory. Previous studies have shown that nicotinic cholinergic receptor activation sharpens mitral cell chemoreceptive fields, likely via intraglomerular circuitry. Muscarinic cholinergic activation is less well understood, though muscarinic receptors are implicated in olfactory learning and in the regulation of synchronized oscillatory dynamics in hippocampus and cortex. To understand the mechanisms underlying cholinergic neuromodulation in OB, we developed a biophysical model of the OB neuronal network including both glomerular layer and external plexiform layer (EPL) computations and incorporating both nicotinic and muscarinic neuromodulatory effects. Our simulations show how nicotinic activation within glomerular circuits sharpens mitral cell chemoreceptive fields, even in the absence of EPL circuitry, but does not facilitate intrinsic oscillations or spike synchronization. In contrast, muscarinic receptor activation increases mitral cell spike synchronization and field oscillatory power by potentiating granule cell excitability and lateral inhibitory interactions within the EPL, but it has little effect on mitral cell firing rates and hence does not sharpen olfactory representations under a rate metric. These results are consistent with the theory that EPL interactions regulate the timing, rather than the existence, of mitral cell action potentials and perform their computations with respect to a spike timing-based metric. This general model suggests that the roles of nicotinic and muscarinic receptors in olfactory bulb are both distinct and complementary to one another, together regulating the effects of ascending cholinergic inputs on olfactory bulb transformations.

The periglomerular cell of the olfactory bulb and its role in controlling mitral cell spiking: a computational model

Interneurons in the olfactory bulb are key elements of odor processing but their roles have not yet being fully understood. Two types of inhibitory interneurons, periglomerular and granule cells, act at two different levels within the olfactory bulb and may have different roles in coordinating the spiking of mitral cells, which are the principal output neurons of the olfactory bulb. In this work we introduce a reduced compartmental model of the periglomerular cell and use it to investigate its role on mitral cell spiking in a model of an elementary cell triad composed of these two cell types plus a granule cell. Our simulation results show that the periglomerular cell is more effective in inhibiting the mitral cell than the granule cell. Based on our results we predict that periglomerular and granule cells have different roles in the control of mitral cell spiking. The periglomerular cell would be the only one capable of completely inhibiting the mitral cell, and the activity decrease of the mitral cell through this inhibitory action would occur in a stepwise fashion depending on parameters of the periglomerular and granule cells as well as on the relative times of arrival of external stimuli to the three cells. The major role of the granule cell would be to facilitate the inhibitory action of the periglomerular cell by enlarging the range of parameters of the periglomerular cell which correspond to complete inhibition of the mitral cell. The combined action of the two interneurons would thus provide an efficient way of controling the instantaneous value of the firing rate of the mitral cell.

Burst firing versus synchrony in a gap junction connected olfactory bulb mitral cell network model

A key player in olfactory processing is the olfactory bulb (OB) mitral cell (MC). We have used dual whole-cell patch-clamp recordings from the apical dendrite and cell soma of MCs to develop a passive compartmental model based on detailed morphological reconstructions of the same cells. Matching the model to traces recorded in experiments we find: C_m = 1.91 ± 0.20 μF cm⁻², R_m = 3547 ± 1934 Ω cm² and R_i = 173 ± 99 Ω cm. We have constructed a six MC gap-junction (GJ) network model of morphologically accurate MCs. These passive parameters (PPs) were then incorporated into the model with Na⁺, Kdr, and KA conductances and GJs from Migliore et al. (2005). The GJs were placed in the apical dendrite tuft (ADT) and their conductance adjusted to give a coupling ratio between MCs consistent with experimental findings (~0.04). Firing at ~50 Hz was induced in all six MCs with continuous current injections (0.05–0.07 nA) at 20 locations to the ADT of two of the MCs. It was found that MCs in the network synchronized better when they shared identical PPs rather than using their own PPs for the fit suggesting that the OB may have populations of MCs tuned for synchrony. The addition of calcium-activated potassium channels (iKCa) and L-type calcium channels (iCa(L)) (Bhalla and Bower, 1993) to the model enabled MCs to generate burst firing. However, the GJ coupling was no longer sufficient to synchronize firing. When cells were stimulated by a continuous current injection there was an initial period of asynchronous burst firing followed after ~120 ms by synchronous repetitive firing. This occurred as intracellular calcium fell due to reduced iCa(L) activity. The kinetics of one of the iCa(L) gate variables, which had a long activation time constant (τ ~ range 18–150 ms), was responsible for this fall in iCa(L). The model makes predictions about the nature of the kinetics of the calcium current that will need experimental verification.

Robustness, variability, phase dependence, and longevity of individual synaptic input effects on spike timing during fluctuating synaptic backgrounds: a modeling study of globus pallidus neuron phase response properties

A neuron's phase response curve (PRC) shows how inputs arriving at different times during the spike cycle differentially affect the timing of subsequent spikes. Using a full morphological model of a globus pallidus (GP) neuron, we previously demonstrated that dendritic conductances shape the PRC in a spike frequency-dependent manner, suggesting different functional roles of perisomatic and distal dendritic synapses in the control of patterned network activity. In the present study we extend this analysis to examine the impact of physiologically realistic high conductance states on somatic and dendritic PRCs and the time course of spike train perturbations. First, we found that average somatic and dendritic PRCs preserved their shapes and spike frequency dependence when the model was driven by spatially-distributed, stochastic conductance inputs rather than tonic somatic current. However, responses to inputs during specific synaptic backgrounds often deviated substantially from the average PRC. Therefore, we analyzed the interactions of PRC stimuli with transient fluctuations in the synaptic background on a trial-by-trial basis. We found that the variability in responses to PRC stimuli and the incidence of stimulus-evoked added or skipped spikes were stimulus-phase-dependent and reflected the profile of the average PRC, suggesting commonality in the underlying mechanisms. Clear differences in the relation between the phase of input and variability of spike response between dendritic and somatic inputs indicate that these regions generally represent distinct dynamical subsystems of synaptic integration with respect to influencing the stability of spike time attractors generated by the overall synaptic conductance.

Role of axonal sodium-channel band in neuronal excitability

Action potential initiation (API) is a crucial step in neural information integration and communication. A stable site of API is beneficial for neural coding. A specialized band with a high density of sodium channels in the axon initial segment has been proved as the primary site of API. In this paper we investigate the role of a dense sodium-channel band in the threshold and the location of API of a neuron with a multicompartment model. It is shown that the threshold of the injected current for API is enhanced by a farther distance between the stimulated site and the band and lowered by an increase of the sodium-channel density and the bandwidth. There exists an optimal location of the dense sodium-channel band, which enables the lowest threshold for API. In the case of an excitable dendrite, the site of API shifts from the band to the stimulated dendritic site with increasing stimuli strength. A larger bandwidth and higher sodium-channel density elevate the stability of the sodium-channel band as the site of API and an optimal band position enables the highest stability.

Dendritic sodium channels promote active decorrelation and reduce phase locking to parkinsonian input oscillations in model globus pallidus neurons

Correlated firing among populations of neurons is present throughout the brain and is often rhythmic in nature, observable as an oscillatory fluctuation in the local field potential. Although rhythmic population activity is believed to be critical for normal function in many brain areas, synchronized neural oscillations are associated with disease states in other cases. In the globus pallidus (GP in rodents, homolog of the primate GPe), pairs of neurons generally have uncorrelated firing in normal animals despite an anatomical organization suggesting that they should receive substantial common input. In contrast, correlated and rhythmic GP firing is observed in animal models of Parkinson's disease (PD). Based in part on these findings, it has been proposed that an important part of basal ganglia function is active decorrelation, whereby redundant information is compressed. Mechanisms that implement active decorrelation, and changes that cause it to fail in PD, are subjects of great interest. Rat GP neurons express fast, transient voltage-dependent sodium channels (NaF channels) in their dendrites, with the expression level being highest near asymmetric synapses. We recently showed that the dendritic NaF density strongly influences the responsiveness of model GP neurons to synchronous excitatory inputs. In the present study, we use rat GP neuron models to show that dendritic NaF channel expression is a potential cellular mechanism of active decorrelation. We further show that model neurons with lower dendritic NaF channel expression have a greater tendency to phase lock with oscillatory synaptic input patterns like those observed in PD.

Effective stimuli for constructing reliable neuron models

The rich dynamical nature of neurons poses major conceptual and technical challenges for unraveling their nonlinear membrane properties. Traditionally, various current waveforms have been injected at the soma to probe neuron dynamics, but the rationale for selecting specific stimuli has never been rigorously justified. The present experimental and theoretical study proposes a novel framework, inspired by learning theory, for objectively selecting the stimuli that best unravel the neuron's dynamics. The efficacy of stimuli is assessed in terms of their ability to constrain the parameter space of biophysically detailed conductance-based models that faithfully replicate the neuron's dynamics as attested by their ability to generalize well to the neuron's response to novel experimental stimuli. We used this framework to evaluate a variety of stimuli in different types of cortical neurons, ages and animals. Despite their simplicity, a set of stimuli consisting of step and ramp current pulses outperforms synaptic-like noisy stimuli in revealing the dynamics of these neurons. The general framework that we propose paves a new way for defining, evaluating and standardizing effective electrical probing of neurons and will thus lay the foundation for a much deeper understanding of the electrical nature of these highly sophisticated and non-linear devices and of the neuronal networks that they compose.

Models of neocortical layer 5b pyramidal cells capturing a wide range of dendritic and perisomatic active properties

The thick-tufted layer 5b pyramidal cell extends its dendritic tree to all six layers of the mammalian neocortex and serves as a major building block for the cortical column. L5b pyramidal cells have been the subject of extensive experimental and modeling studies, yet conductance-based models of these cells that faithfully reproduce both their perisomatic Na(+)-spiking behavior as well as key dendritic active properties, including Ca(2+) spikes and back-propagating action potentials, are still lacking. Based on a large body of experimental recordings from both the soma and dendrites of L5b pyramidal cells in adult rats, we characterized key features of the somatic and dendritic firing and quantified their statistics. We used these features to constrain the density of a set of ion channels over the soma and dendritic surface via multi-objective optimization with an evolutionary algorithm, thus generating a set of detailed conductance-based models that faithfully replicate the back-propagating action potential activated Ca(2+) spike firing and the perisomatic firing response to current steps, as well as the experimental variability of the properties. Furthermore, we show a useful way to analyze model parameters with our sets of models, which enabled us to identify some of the mechanisms responsible for the dynamic properties of L5b pyramidal cells as well as mechanisms that are sensitive to morphological changes. This automated framework can be used to develop a database of faithful models for other neuron types. The models we present provide several experimentally-testable predictions and can serve as a powerful tool for theoretical investigations of the contribution of single-cell dynamics to network activity and its computational capabilities.

Calcium currents of olfactory bulb juxtaglomerular cells: profile and multiple conductance plateau potential simulation

The olfactory glomerulus is the locus of information transfer between olfactory sensory neurons and output neurons of the olfactory bulb. Juxtaglomerular cells (JGCs) may influence intraglomerular processing by firing plateau potentials that support multiple spikes. It is unclear what inward currents mediate this firing pattern. In previous work, we characterized potassium currents of JGCs. We focus here on the inward currents using whole cell current clamp and voltage recording in a rat in vitro slice preparation, as well as computer simulation. We first showed that sodium current was not required to mediate plateau potentials. Voltage clamp characterization of calcium current (I(Ca)) determined that I(Ca) consisted of a slow activating, rapidly inactivating (τ(10%-90% rise) 6-8 ms, τ(inactivation) 38-77 ms) component I(cat1), similar to T-type currents, and a sustained (τ(inactivation)>>500 ms) component I(cat2), likely composed of L-type and P/Q-type currents. We used computer simulation to test their roles in plateau potential firing. We robustly modeled I(cat1) and I(cat2) to Hodgkin-Huxley schemes (m(3)h and m(2), respectively) and simulated a JGC plateau potential with six conductances: calcium currents as above, potassium currents from our prior study (A-type I(kt1), D-type I(kt2), delayed rectifier I(kt3)), and a fast sodium current (I(Na)). We demonstrated that I(cat1) was required for mediating the plateau potential, unlike I(Na) and I(cat2), and its τ(inactivation) determined plateau duration. We also found that I(kt1) dictated plateau potential shape more than I(kt2) and I(kt3). The influence of these two transient and opposing conductances suggests a unique mechanism of plateau potential physiology.

Using computer simulations to determine the limitations of dynamic clamp stimuli applied at the soma in mimicking distributed conductance sources

In previous studies we used the technique of dynamic clamp to study how temporal modulation of inhibitory and excitatory inputs control the frequency and precise timing of spikes in neurons of the deep cerebellar nuclei (DCN). Although this technique is now widely used, it is limited to interpreting conductance inputs as being location independent; i.e., all inputs that are biologically distributed across the dendritic tree are applied to the soma. We used computer simulations of a morphologically realistic model of DCN neurons to compare the effects of purely somatic vs. distributed dendritic inputs in this cell type. We applied the same conductance stimuli used in our published experiments to the model. To simulate variability in neuronal responses to repeated stimuli, we added a somatic white current noise to reproduce subthreshold fluctuations in the membrane potential. We were able to replicate our dynamic clamp results with respect to spike rates and spike precision for different patterns of background synaptic activity. We found only minor differences in the spike pattern generation between focal or distributed input in this cell type even when strong inhibitory or excitatory bursts were applied. However, the location dependence of dynamic clamp stimuli is likely to be different for each cell type examined, and the simulation approach developed in the present study will allow a careful assessment of location dependence in all cell types.

Dendritic sodium channels regulate network integration in globus pallidus neurons: a modeling study

The globus pallidus (GP) predominantly contains GABAergic projection neurons that occupy a central position in the indirect pathway of the basal ganglia. They have long dendrites that can extend through one-half the diameter of the GP in rats, potentially enabling convergence and interaction between segregated basal ganglia circuits. Because of the length and fine diameter of GP dendrites, however, it is unclear how much influence distal synapses have on spiking activity. Dendritic expression of fast voltage-dependent Na(+) channels (NaF channels) can enhance the importance of distal excitatory synapses by allowing for dendritic spike initiation and by subthreshold boosting of EPSPs. Antibody labeling has demonstrated the presence of NaF channel proteins in GP dendrites, but the quantitative expression density of the channels remains unknown. We built a series of nine GP neuron models that differed only in their dendritic NaF channel expression level to assess the functional impact of this parameter. The models were all similar in their basic electrophysiological features; however, higher expression levels of dendritic NaF channels increased the relative effectiveness of distal inputs for both excitatory and inhibitory synapses, broadening the effective extent of the dendritic tree. Higher dendritic NaF channel expression also made the neurons more resistant to tonic inhibition and highly sensitive to clustered synchronous excitation. The dendritic NaF channel expression pattern may therefore be a critical determinant of convergence for both the striatopallidal and subthalamopallidal projections, while also dictating which spatiotemporal input patterns are most effective at driving GP neuron output.

Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells

Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus because Purkinje cell inhibition has to be turned into an excitatory output signal, and DCN neurons exhibit complex intrinsic properties. In particular, DCN neurons exhibit a range of rebound spiking properties following hyperpolarizing current injection, raising the question how this could contribute to signal processing in behaving animals. Computer modeling presents an ideal tool to investigate how intrinsic voltage-gated conductances in DCN neurons could generate the heterogeneous firing behavior observed, and what input conditions could result in rebound responses. To enable such an investigation we built a compartmental DCN neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than −70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum.

Odor information processing by the olfactory bulb analyzed in gene-targeted mice

In mammals, olfactory sensory neurons (OSNs) expressing a specific odorant receptor (OR) gene project with precise stereotypy onto mitral/tufted (M/T) cells in the main olfactory bulb (MOB). It remains challenging to understand how incoming olfactory signals are transformed into outputs of M/T cells. By recording from OSNs expressing mouse I7 receptor and their postsynaptic neurons in the bulb, we found that I7 OSNs and their corresponding M/T cells exhibit similarly selective tuning profiles at low concentrations. Increasing the concentration significantly reduces response selectivity for both OSNs and M/T cells, although the tuning curve of M/T cells remains comparatively narrow. By contrast, interneurons in the MOB are broadly tuned, and blocking GABAergic neurotransmission reduces selectivity of M/T cells at high odorant concentrations. Our results indicate that olfactory information carried by an OR is channeled to its corresponding M/T cells and support the role of lateral inhibition via interneurons in sharpening the tuning of M/T cells.

Phase response curve analysis of a full morphological globus pallidus neuron model reveals distinct perisomatic and dendritic modes of synaptic integration

Synchronization of globus pallidus (GP) neurons and cortically entrained oscillations between GP and other basal ganglia nuclei are key features of the pathophysiology of Parkinson's disease. Phase response curves (PRCs), which tabulate the effects of phasic inputs within a neuron's spike cycle on output spike timing, are efficient tools for predicting the emergence of synchronization in neuronal networks and entrainment to periodic input. In this study we apply physiologically realistic synaptic conductance inputs to a full morphological GP neuron model to determine the phase response properties of the soma and different regions of the dendritic tree. We find that perisomatic excitatory inputs delivered throughout the interspike interval advance the phase of the spontaneous spike cycle yielding a type I PRC. In contrast, we demonstrate that distal dendritic excitatory inputs can either delay or advance the next spike depending on whether they occur early or late in the spike cycle. We find this latter pattern of responses, summarized by a biphasic (type II) PRC, was a consequence of dendritic activation of the small conductance calcium-activated potassium current, SK. We also evaluate the spike-frequency dependence of somatic and dendritic PRC shapes, and we demonstrate the robustness of our results to variations of conductance densities, distributions, and kinetic parameters. We conclude that the distal dendrite of GP neurons embodies a distinct dynamical subsystem that could promote synchronization of pallidal networks to excitatory inputs. These results highlight the need to consider different effects of perisomatic and dendritic inputs in the control of network behavior.

Axonal Na+ channels ensure fast spike activation and back-propagation in cerebellar granule cells

In most neurons, Na+ channels in the axon are complemented by others localized in the soma and dendrites to ensure spike back-propagation. However, cerebellar granule cells are neurons with simplified architecture in which the dendrites are short and unbranched and a single thin ascending axon travels toward the molecular layer before bifurcating into parallel fibers. Here we show that in cerebellar granule cells, Na+ channels are enriched in the axon, especially in the hillock, but almost absent from soma and dendrites. The impact of this channel distribution on neuronal electroresponsiveness was investigated by multi-compartmental modeling. Numerical simulations indicated that granule cells have a compact electrotonic structure allowing excitatory postsynaptic potentials to diffuse with little attenuation from dendrites to axon. The spike arose almost simultaneously along the whole axonal ascending branch and invaded the hillock the activation of which promoted spike back-propagation with marginal delay (<200 micros) and attenuation (<20 mV) into the somato-dendritic compartment. These properties allow granule cells to perform sub-millisecond coincidence detection of pre- and postsynaptic activity and to rapidly activate Purkinje cells contacted by the axonal ascending branch.

Channel density distributions explain spiking variability in the globus pallidus: a combined physiology and computer simulation database approach

Globus pallidus (GP) neurons recorded in brain slices show significant variability in intrinsic electrophysiological properties. To investigate how this variability arises, we manipulated the biophysical properties of GP neurons using computer simulations. Specifically, we created a GP neuron model database with 100,602 models that had varying densities of nine membrane conductances centered on a hand-tuned model that replicated typical physiological data. To test the hypothesis that the experimentally observed variability can be attributed to variations in conductance densities, we compared our model database results to a physiology database of 146 slice recordings. The electrophysiological properties of generated models and recordings were assessed with identical current injection protocols and analyzed with a uniform set of measures, allowing a systematic analysis of the effects of varying voltage-gated and calcium-gated conductance densities on the measured properties and a detailed comparison between models and recordings. Our results indicated that most of the experimental variability could be matched by varying conductance densities, which we confirmed with additional partial block experiments. Further analysis resulted in two key observations: (1) each voltage-gated conductance had effects on multiple measures such as action potential waveform and spontaneous or stimulated spike rates; and (2) the effect of each conductance was highly dependent on the background context of other conductances present. In some cases, such interactions could reverse the effect of the density of one conductance on important excitability measures. This context dependence of conductance density effects is important to understand drug and neuromodulator effects that work by affecting ion channels.

Functional structure of the mitral cell dendritic tuft in the rat olfactory bulb

The input-output transform performed by mitral cells, the principal projection neurons of the olfactory bulb, is one of the key factors in understanding olfaction. We used combined calcium and voltage imaging from the same neuron and computer modeling to investigate signal processing in the mitral cells, focusing on the glomerular dendritic tuft. The main finding was that the dendritic tuft functions as a single electrical compartment for subthreshold signals within the range of amplitudes detectable by voltage-sensitive dye recording. These evoked EPSPs had uniform characteristics throughout the glomerular tuft. The Ca(2+) transients associated with spatially uniform subthreshold synaptic potentials were comparable but not equal in amplitude in all regions. The average range of normalized amplitudes of the EPSP-driven Ca(2+) signals from different locations on dendritic branches in the glomerular tuft was relatively narrow and appeared to be independent of the dendritic surface-to-volume ratio. The computer simulations constrained by the imaging data indicated that a synchronized activation of approximately 100 synapses randomly distributed on tuft branches was sufficient to generate spatially homogenous EPSPs. This number of activated synapses is consistent with the data from anatomical studies. Furthermore, voltage attenuation of the EPSP along the primary dendrite at physiological temperature was weak compared with other cell types. In the model, weak attenuation of the EPSP along the primary dendrite could be accounted for by passive electrical properties of the mitral cell.

Neurofitter: a parameter tuning package for a wide range of electrophysiological neuron models

The increase in available computational power and the higher quality of experimental recordings have turned the tuning of neuron model parameters into a problem that can be solved by automatic global optimization algorithms. Neurofitter is a software tool that interfaces existing neural simulation software and sophisticated optimization algorithms with a new way to compute the error measure. This error measure represents how well a given parameter set is able to reproduce the experimental data. It is based on the phase-plane trajectory density method, which is insensitive to small phase differences between model and data. Neurofitter enables the effortless combination of many different time-dependent data traces into the error measure, allowing the neuroscientist to focus on what are the seminal properties of the model.We show results obtained by applying Neurofitter to a simple single compartmental model and a complex multi-compartmental Purkinje cell (PC) model. These examples show that the method is able to solve a variety of tuning problems and demonstrate details of its practical application.

A novel multiple objective optimization framework for constraining conductance-based neuron models by experimental data

We present a novel framework for automatically constraining parameters of compartmental models of neurons, given a large set of experimentally measured responses of these neurons. In experiments, intrinsic noise gives rise to a large variability (e.g., in firing pattern) in the voltage responses to repetitions of the exact same input. Thus, the common approach of fitting models by attempting to perfectly replicate, point by point, a single chosen trace out of the spectrum of variable responses does not seem to do justice to the data. In addition, finding a single error function that faithfully characterizes the distance between two spiking traces is not a trivial pursuit. To address these issues, one can adopt a multiple objective optimization approach that allows the use of several error functions jointly. When more than one error function is available, the comparison between experimental voltage traces and model response can be performed on the basis of individual features of interest (e.g., spike rate, spike width). Each feature can be compared between model and experimental mean, in units of its experimental variability, thereby incorporating into the fitting this variability. We demonstrate the success of this approach, when used in conjunction with genetic algorithm optimization, in generating an excellent fit between model behavior and the firing pattern of two distinct electrical classes of cortical interneurons, accommodating and fast-spiking. We argue that the multiple, diverse models generated by this method could serve as the building blocks for the realistic simulation of large neuronal networks.

The olfactory glomerulus: a cortical module with specific functions

The axons of many olfactory receptor cells converge on an individual glomerulus in the olfactory bulb, where they make contacts with the distal dendrites of mitral and tufted cells. Each glomerulus is targeted by olfactory receptor neurons expressing a single type of olfactory receptor protein. The glomerulus provides a unique model in which the function of a cortical module can be unambiguously established. Here we review the increasing evidence that a key functional operation of the glomerulus is to act as a signal-to-noise enhancing device in the processing of sensory input and that this function is critical across vertebrate and invertebrate species for the ability to detect specific odor stimuli within "noisy" odor environments and to carry out discriminations between odor molecules that are structurally closely related.

Quantifying the magnitude of changes in synaptic level parameters with long-term potentiation

Experimental evidence supports a number of mechanisms for the synaptic change that occurs with long-term potentiation (LTP) including insertion of AMPA receptors, an increase in AMPA receptor single channel conductance, unmasking silent synapses, and increases in vesicle release probability. Here we combine experimental and modeling studies to quantify the magnitude of the change needed at the synaptic level to explain LTP with these proposed mechanisms. Whole cell patch recordings were used to measure excitatory postsynaptic potential (EPSP) amplitude in response to near minimal afferent stimulation before and after LTP induction in CA1 pyramidal cells. Detailed neuron and synapse level models were constructed to estimate quantitatively the changes needed to explain the experimental results. For cells in normal artificial cerebrospinal fluid (ACSF), we found a 60% average increase in EPSP amplitude with LTP. This was explained in the models by a 63% increase in the number of activated synapses, a 64% increase in the AMPA receptor single channel conductance, or a 73% increase in the number of AMPA receptors per potentiated synapse. When the percentage LTP was above the average, the required increases through the proposed mechanisms became nonlinear, particularly for increases in the number of receptors. Given constraints from other experimental studies, our quantification suggests that neither unmasking silent synapses nor increasing the numbers of AMPA receptors at synapses is sufficient to explain the magnitude of LTP we observed, but increasing AMPA single channel conductance or vesicle release probability can be sufficient. Our results are most compatible with a combination of mechanisms producing LTP.

Fitting experimental data to models that use morphological data from public databases

Ideally detailed neuron models should make use of morphological and electrophysiological data from the same cell. However, this rarely happens. Typically a modeler will choose a cell morphology from a public database, assign standard values for Ra, Cm, and other parameters and then do the modeling study. The assumption is that the model will produce results representative of what might be obtained experimentally. To test this assumption we developed models of CA1 hippocampal pyramidal neurons using 4 different morphologies obtained from 3 public databases. The multiple run fitter in NEURON was used to fit parameter values in each of the 4 morphological models to match experimental data recorded from 19 CA1 pyramidal cells. Fits with fixed standard parameter values produced results that were generally not representative of our experimental data. However, when parameter values were allowed to vary, excellent fits were obtained in almost all cases, but the fitted parameter values were very different among the 4 reconstructions and did not match standard values. The differences in fitted values can be explained by very different diameters, total lengths, membrane areas and volumes among the reconstructed cells, reflecting either cell heterogeneity or issues with the reconstruction data. The fitted values compensated for these differences to make the database cells and experimental cells more similar electrotonically. We conclude that models using fully reconstructed morphologies need to be calibrated with experimental data (even when morphological and electrophysiological data come from the same cell), model results should be generated with multiple reconstructions, morphological and experimental cells should come from the same strain of animal at the same age, and blind use of standard parameter values in models that use reconstruction data may not produce representative experimental results.

Tuft calcium spikes in accessory olfactory bulb mitral cells

The mammalian accessory olfactory system is critical for the detection and identification of pheromones and the representation of complex stimuli including sex, genetic relatedness, and individual identity. Mitral cells, the principal cells of the accessory olfactory bulb (AOB), receive monosynaptic input from the sensory periphery and already show highly specific response properties, firing selectively for combinations of genetic markers and gender-specific cues. Vomeronasal sensory neuron axons form synapses onto distal tuft-like branches of mitral cell primary dendrites. We have studied dendritic excitability and synaptic integration in AOB mitral cell dendrites, and we show that dendrites of accessory olfactory bulb mitral cells support action potential propagation and can fire regenerative spike-like events that are likely to contribute to the integration of inputs to these cells. These tuft spikes may be important for the specificity of AOB mitral cell responses.

Relation of apical dendritic spikes to output decision in CA1 pyramidal cells during synchronous activation: a computational study

Recent studies on the initiation and propagation of dendritic spikes have modified the classical view of postsynaptic integration. Earlier we reported that subthreshold currents and spikes recruited by synaptic currents play a critical role in defining outputs following synchronous activation. Experimental factors strongly condition these currents due to their nonlinear behaviour. Hence, we have performed a detailed parametric study in a CA1 pyramidal cell model to explore how different variables interact and initiate dendritic spiking, and how they influence cell output. The input pattern, the relative excitability of axon and dendrites, the presence/modulation of voltage-dependent channels, and inhibition were cross analysed. Subthreshold currents and spikes on synaptically excited branches fired spikes in other branches to jointly produce different modalities of apical shaft spiking with a variable impact on cell output. Synchronous activation initiated a varying number and temporal scatter of firing branches that produced in the apical shaft-soma axis nonpropagating spikes, pseudosaltatory or continuous forward conduction, or backpropagation. As few as 6-10 local spikes within a time window of 2 ms ensure cell output. However, the activation mode varied extremely when two or more variables were cross-analysed, becoming rather unpredictable when all the variables were considered. Spatially clustered inputs and upper modulation of dendritic Na(+) or Ca(2+) electrogenesis favour apical decision. In contrast, inhibition biased the output decision toward the axon and switched between dendritic firing modes. We propose that dendrites can discriminate input patterns and decide immediate cell output depending on the particular state of a variety of endogenous parameters.

Non-topographical contrast enhancement in the olfactory bulb

Background

Contrast enhancement within primary stimulus representations is a common feature of sensory systems that regulates the discrimination of similar stimuli. Whereas most sensory stimulus features can be mapped onto one or two dimensions of quality or location (e.g., frequency or retinotopy), the analogous similarities among odor stimuli are distributed high-dimensionally, necessarily yielding a chemotopically fragmented map upon the surface of the olfactory bulb. While olfactory contrast enhancement has been attributed to decremental lateral inhibitory processes among olfactory bulb projection neurons modeled after those in the retina, the two-dimensional topology of this mechanism is intrinsically incapable of mediating effective contrast enhancement on such fragmented maps. Consequently, current theories are unable to explain the existence of olfactory contrast enhancement.

Results

We describe a novel neural circuit mechanism, non-topographical contrast enhancement (NTCE), which enables contrast enhancement among high-dimensional odor representations exhibiting unpredictable patterns of similarity. The NTCE algorithm relies solely on local intraglomerular computations and broad feedback inhibition, and is consistent with known properties of the olfactory bulb input layer. Unlike mechanisms based upon lateral projections, NTCE does not require a built-in foreknowledge of the similarities in molecular receptive ranges expressed by different olfactory bulb glomeruli, and is independent of the physical location of glomeruli within the olfactory bulb.

Conclusion

Non-topographical contrast enhancement demonstrates how intrinsically high-dimensional sensory data can be represented and processed within a physically two-dimensional neural cortex while retaining the capacity to represent stimulus similarity. In a biophysically constrained computational model of the olfactory bulb, NTCE successfully mediates contrast enhancement among odorant representations in the natural, high-dimensional similarity space defined by the olfactory receptor complement and underlies the concentration-independence of odor quality representations.

Computation in the olfactory system

Computational models are increasingly essential to systems neuroscience. Models serve as proofs of concept, tests of sufficiency, and as quantitative embodiments of working hypotheses and are important tools for understanding and interpreting complex data sets. In the olfactory system, models have played a particularly prominent role in framing contemporary theories and presenting novel hypotheses, a role that will only grow as the complexity and intricacy of experimental data continue to increase. This review will attempt to provide a comprehensive, functional overview of computational ideas in olfaction and outline a computational framework for olfactory processing based on the insights provided by these diverse models and their supporting data.

Action potential backpropagation and multiglomerular signaling in the rat vomeronasal system

In the accessory olfactory bulb (AOB), sensory neurons expressing a given vomeronasal receptor (VR) gene send divergent projections to many glomeruli, and second-order neurons (mitral cells) link to multiple glomeruli via branched primary dendrites. We used calcium imaging and paired somadendritic patch-clamp recording to track backpropagated action potentials (APs) in rat AOB primary dendrites. In cells loaded with 150 microm Calcium Orange, somatic spikes elicited fluorescence transients over the entire primary dendritic tree, and the relative fluorescence increment DeltaF/F(0) increased along all branches from soma to glomeruli. Backpropagation was reliant on Na+ channels: in 1 microm TTX, somatic AP commands evoked dendritic Ca2+ transients that declined steeply with distance. In paired soma- dendritic whole-cell recordings, backpropagated APs were unattenuated up to approximately 200 microm from the soma, whereas subthreshold voltage transients decayed markedly. Computational modeling indicated that the large distal Ca2+ transients are consistent with active, not passive, backpropagation. Genetic tracing in the AOB has suggested homotypic connectivity with individual mitral cell dendritic arbors projecting only to glomeruli targeted by sensory neurons expressing the same VR gene. Non-decremental, non-dichotomous backpropagation in AOB primary dendrites ensures fast, reliable communication between mitral cells and their homotypic glomeruli, binding them into functional modules in accordance with their VR-coded inputs.

Voltage imaging from dendrites of mitral cells: EPSP attenuation and spike trigger zones

To obtain a more complete description of individual neurons, it is necessary to complement the electrical patch pipette measurements with technologies that permit a massive parallel recording from many sites on neuronal processes. This can be achieved by using voltage imaging with intracellular dyes. With this approach, we investigated the functional structure of a mitral cell, the principal output neuron in the rat olfactory bulb. The most significant finding concerns the characteristics of EPSPs at the synaptic sites and surprisingly small attenuation along the trunk of the primary dendrite. Also, the experiments were performed to determine the number, location, and stability of spike trigger zones, the excitability of terminal dendritic branches, and the pattern and nature of spike initiation and propagation in the primary and secondary dendrites. The results show that optical data can be used to deduce the amplitude and shape of the EPSPs evoked by olfactory nerve stimulation at the site of origin (glomerular tuft) and to determine its attenuation along the entire length of the primary dendrite. This attenuation corresponds to an unusually large mean apparent "length constant" of the primary dendrite. Furthermore, the images of spike trigger zones showed that an action potential can be initiated in three different compartments of the mitral cell: the soma-axon region, the primary dendrite trunk, and the terminal dendritic tuft, which appears to be fully excitable. Finally, secondary dendrites clearly support the active propagation of action potentials.

Synaptically Recruited Apical Currents Are Required to Initiate Axonal and Apical Spikes in Hippocampal Pyramidal Cells: Modulation by Inhibition

Dendritic voltage-dependent currents and inhibition modulate the information flow between synaptic and decision areas. Subthreshold and spike currents are sequentially recruited by synaptic potentials in the apical shaft of pyramidal cells, which may also decide cell output. We studied the global role of proximal apical recruited currents on cell output in vitro and in the anesthetized rat after local blockade of Na+ currents in the axon initial segment (AIS) or the proximal apical shaft and their modulation by inhibition. Microejection of TTX, field potentials, and intrasomatic and intradendritic recordings were employed. Dendritic population spikes (PSs) were much smaller in vitro, but the gross relations between synaptic and active currents are similar to in vivo. Activation of Schaffer collaterals triggered PSs and action potentials (APs) in the apical shaft that fully propagated to the axon. However, the specific blockade of proximal Na+ currents avoided cell firing, although antidromic PSs and APs readily invaded somata. The somatic depolarization of subthreshold excitatory postsynaptic potentials (EPSPs) also decreased to about 50%. These results were not due to decreased excitatory input by TTX. However, when GABAA inhibition was locally removed, Schaffer synaptic currents skipped the proximal dendrite and fired somatic PSs, although initiated at the AIS. It is concluded that apical currents recruited en passant by Schaffer synaptic potentials in the apical shaft constitute a necessary amplifier for this input to cause output decision. Local inhibition decides when and where an AP will initiate, constituting an efficient mechanism to discriminate and weight different inputs.

Dendritic sodium spikelets and low-threshold calcium spikes in turtle olfactory bulb granule cells

Active dendritic membrane properties were investigated by whole cell recordings from adult turtle olfactory bulb granule cells. The laminar structure of the olfactory bulb allowed differential polarization of the distal apical dendrites versus the somatic part of the cells by an external electric field. Dendritic depolarization evoked small (approximately 10 mV) all-or-none depolarizing events of approximately 10-ms duration. These spikelets often occurred in bursts at high frequency (< or = 250 Hz); they were present despite the application of synaptic and gap junction antagonists, but were abolished by TTX and intracellularly applied QX314. The spikelets were interpreted as attenuated sodium spikes initiated in different branches of the granule cells dendrites. They occurred spontaneously, but could also be evoked by excitatory postsynaptic potentials (EPSPs) to the distal dendrites. Spikelets initiated by distal excitation could function as prepotentials for full sodium spikes, in part depending on the level of proximal depolarization. Somatic depolarization by the electric field evoked full sodium spikes as well as low-threshold calcium spikes (LTSs). Calcium imaging revealed that the electrophysiologically identified LTS evoked from the soma was associated with calcium transients in the proximal and the distal dendrites. Our data suggest that the LTS in the soma/proximal dendrites plays a major role in boosting excitability, thus contributing to the initiation of sodium spiking in this compartment. The results furthermore suggest that the LTS and the sodium spikes may act independently or cooperatively to regulate dendritic calcium influx.

Current- and Voltage-Clamp Recordings and Computer Simulations of Kenyon Cells in the Honeybee

The mushroom body of the insect brain is an important locus for olfactory information processing and associative learning. The present study investigated the biophysical properties of Kenyon cells, which form the mushroom body. Current- and voltage-clamp analyses were performed on cultured Kenyon cells from honeybees. Current-clamp analyses indicated that Kenyon cells did not spike spontaneously in vitro. However, spikes could be elicited by current injection in approximately 85% of the cells. Of the cells that produced spikes during a 1-s depolarizing current pulse, approximately 60% exhibited repetitive spiking, whereas the remaining approximately 40% fired a single spike. Cells that spiked repetitively showed little frequency adaptation. However, spikes consistently became broader and smaller during repetitive activity. Voltage-clamp analyses characterized a fast transient Na+current ( INa), a delayed rectifier K+current ( IK,V), and a fast transient K+current ( IK,A). Using the neurosimulator SNNAP, a Hodgkin–Huxley-type model was developed and used to investigate the roles of the different currents during spiking. The model led to the prediction of a slow transient outward current ( IK,ST) that was subsequently identified by reevaluating the voltage-clamp data. Simulations indicated that the primary currents that underlie spiking are INaand IK,V, whereas IK,Aand IK,STprimarily determined the responsiveness of the model to stimuli such as constant or oscillatory injections of current.

Electrical signaling in the olfactory bulb

The olfactory bulb employs lateral and feedback inhibitory pathways to distribute odor information across parallel assemblies of mitral and granule cells. The pathways involve dendritic action potentials that can interact with a variety of voltage-dependent conductances and synaptic transmission to produce complex and dynamic patterns of activity. Electrical coupling also helps to ensure proper coordination and synchronization of these patterns. These mechanisms provide numerous options for dynamic modulation and control of signaling in the olfactory bulb.

Theta oscillation coupled spike latencies yield computational vigour in a mammalian sensory system

Theoretical work carried out almost a decade ago proposed that subthreshold oscillations in membrane potential could be used to convert synaptic current strength into a code reliant on action potential (AP) latencies. Using whole-cell recordings we present experimental evidence for the occurrence of prominent network-driven subthreshold theta oscillations in mitral cells of the mouse olfactory bulb. Activity induced by both injected current and sensory input was accurately reflected in initial AP latency from the beginning of each oscillation cycle. In a network model we found that an AP latency code rather than AP number or instantaneous firing rate provided computational speed and high resolution, and was easily implemented. This coding strategy was also found to be invariant to the total input current as long as the relative input intensities to glomeruli remained constant. However, it was highly sensitive to changes in the ratios of the input currents and improved by lateral inhibitory mechanisms. Since the AP latency-based coding scheme was dependent on the subthreshold oscillation we conclude that the theta rhythm serves a functional role in temporally reformatting the strengths and patterns of synaptic input in this sensory system.

AMPA autoreceptors drive correlated spiking in olfactory bulb glomeruli

Information processing in the brain may rely on temporal correlations in spike activity between neurons. Within the olfactory bulb, correlated spiking in output mitral cells could affect the odor code by either binding or amplifying signals from individual odorant receptors. We examined the timing of spike trains in mitral cells of rat olfactory bulb slices. Depolarization of mitral cell pairs elicited spikes that were correlated on a rapid timescale (< or =10 ms) for cells whose primary dendrites projected to the same glomerulus. Correlated spiking was driven by a novel mechanism that depended on electrical coupling at mitral cell primary dendrites; the specific synchronizing signal was a coupled depolarization ( approximately 20 ms) that was mediated by dendritic AMPA autoreceptors. We suggest that glomerulus-specific correlated spiking in mitral cells helps to preserve the fidelity of odor signals that are delivered to the olfactory cortex.

Structural inhomogeneities differentially modulate action currents and population spikes initiated in the axon or dendrites

Action potentials (APs) in CA1 pyramidal cells propagate in different directions along the somatodendritic axis depending on the activation mode (synaptic or axonal). We studied how the geometrical inhomogeneities along the apical shaft, soma, and initial axon modulate the transmembrane current (I(m)) flow underlying APs, using model and experimental techniques. The computations obtained at the subcellular level during forward- and backpropagation were extrapolated to macroscopic level (field potentials) and compared with the basic in vivo features of the ortho- and antidromic population spike (PS) that reflects the sum total of all elementary currents from synchronously firing cells. The matching of theoretical and experimental results supports the following conclusions. Because the charge carried by axonal APs is almost entirely drained into dendrites, the soma invasion is preceded by little capacitive currents (I(cap)), the ionic currents (I(ion)) dominating I(m) and the depolarizing phase. The subsequent invasion of the tapering apical shaft is preceded, however, by significant I(cap), while I(ion) decayed gradually. A similar pattern occurred during backpropagation of spikes synaptically initiated in the axon. On the contrary, when the AP was apically initiated, the dendritic I(ion) was boosted by the apical flare, it was preceded by weak I(cap) and spread forwardly at a slower velocity. Soma invasion is reliable once the AP reached the main apical shaft but less so distal to the primary bifurcation, where it may be upheld by concurrent synaptic activity. The decreasing internal resistance of the apical shaft guided most axial current into the soma, causing its fast charging. There, I(ion) began later in the depolarizing phase of the AP and the reduced driving force made it smaller. This, in addition to a poor temporal overlapping of somatodendritic inward currents within individual cells, built a smaller extracellular sink, i.e., a smaller PS. In both experiment and model, the antidromic (axon-initiated) PS in the soma layer is approximately 30% larger than an orthodromic (apical shaft-initiated) PS contributed by the same number of firing cells. We conclude that the dominance of capacitive or ionic current components on I(m) is a distinguishing feature of forward and backward APs that is predictable from the geometric inhomogeneities between conducting subregions. Correspondingly, experimental and model APs have a faster rising slope during ortho than antidromic activation. The moderate flare of the apical shaft makes forward AP conduction quite safe. This alternative trigger zone enables two different processing modes for apical inputs.