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Developing whole-brain emulation (WBE) technology would provide immense benefits across neuroscience, biomedicine, artificial intelligence, and robotics. At this time, constructing a simulated human brain lacks feasibility due to limited experimental data and limited computational resources. However, I suggest that progress toward this goal might be accelerated by working toward an intermediate objective, namely insect brain emulation (IBE). More specifically, this would entail creating biologically realistic simulations of entire insect nervous systems along with more approximate simulations of non-neuronal insect physiology to make "virtual insects." I argue that this could be realistically achievable within the next 20 years. I propose that developing emulations of insect brains will galvanize the global community of scientists, businesspeople, and policymakers toward pursuing the loftier goal of emulating the human brain. By demonstrating that WBE is possible via IBE, simulating mammalian brains and eventually the human brain may no longer be viewed as too radically ambitious to deserve substantial funding and resources. Furthermore, IBE will facilitate dramatic advances in cognitive neuroscience, artificial intelligence, and robotics through studies performed using virtual insects.

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

Parkinson's disease (PD) is a common neurodegenerative disease. However, therapeutic methods of PD are still limited due to complex pathophysiology in PD. Here, optical measurements of individual neurons from in vitro PD model using optical diffraction tomography (ODT) are presented. By measuring 3D refractive index distribution of neurons, morphological and biophysical alterations in in-vitro PD model are quantitatively investigated. It was found that neurons show apoptotic features in early PD progression. The present approach will open up new opportunities for quantitative investigation of the pathophysiology of various neurodegenerative diseases. © 2017 International Society for Advancement of Cytometry., (© 2017 International Society for Advancement of Cytometry.)

Over the last several years, technological advances have enabled researchers to more readily observe single-cell membrane biophysics in awake, behaving animals. Studies utilizing these technologies have provided important insights into the mechanisms generating functional neural codes in both sensory and non-sensory cortical circuits. Crucial for a deeper understanding of how membrane biophysics control circuit dynamics however, is a continued effort to move toward large scale studies of membrane biophysics, in terms of the numbers of neurons and ion channels examined. Future work faces a number of theoretical and technical challenges on this front but recent technological developments hold great promise for a larger scale understanding of how membrane biophysics contribute to circuit coding and computation., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

We analyze the bifurcations occurring in the 3D Hindmarsh-Rose neuronal model with and without random signal. When under a sufficient stimulus, the neuron activity takes place; we observe various types of bifurcations that lead to chaotic transitions. Beside the equilibrium solutions and their stability, we also investigate the deterministic bifurcation. It appears that the neuronal activity consists of chaotic transitions between two periodic phases called bursting and spiking solutions. The stochastic bifurcation, defined as a sudden change in character of a stochastic attractor when the bifurcation parameter of the system passes through a critical value, or under certain condition as the collision of a stochastic attractor with a stochastic saddle, occurs when a random Gaussian signal is added. Our study reveals two kinds of stochastic bifurcation: the phenomenological bifurcation (P-bifurcations) and the dynamical bifurcation (D-bifurcations). The asymptotical method is used to analyze phenomenological bifurcation. We find that the neuronal activity of spiking and bursting chaos remains for finite values of the noise intensity.

We develop an approach to understanding long chaotic transients in networks of excitatory pulse-coupled oscillators. Our idea is to identify a class of attractors, sequentially active firing (SAF) attractors, in terms of the temporal event structure of firing and receipt of pulses. Then all attractors can be classified into two groups: SAF attractors and non-SAF attractors. We establish that long transients typically arise in the transitional region of the parameter space where the SAF attractors are collectively destabilized. Bifurcation behavior of the SAF attractors is analyzed to provide a detailed understanding of the long irregular transients. Although demonstrated using pulse-coupled oscillator networks, our general methodology may be useful in understanding the origin of transient chaos in other types of networked systems, an extremely challenging problem in nonlinear dynamics and complex systems.

The minimal integrate-and-fire-or-burst neuron model succinctly describes both tonic firing and postinhibitory rebound bursting of thalamocortical cells in the sensory relay. Networks of integrate-and-fire-or-burst (IFB) neurons with slow inhibitory synaptic interactions have been shown to support stable rhythmic states, including globally synchronous and cluster oscillations, in which network-mediated inhibition cyclically generates bursting in coherent subgroups of neurons. In this paper, we introduce a reduced IFB neuronal population model to study synchronization of inhibition-mediated oscillatory bursting states to periodic excitatory input. Using numeric methods, we demonstrate the existence and stability of 1:1 phase-locked bursting oscillations in the sinusoidally forced IFB neuronal population model. Phase locking is shown to arise when periodic excitation is sufficient to pace the onset of bursting in an IFB cluster without counteracting the inhibitory interactions necessary for burst generation. Phase-locked bursting states are thus found to destabilize when periodic excitation increases in strength or frequency. Further study of the IFB neuronal population model with pulse-like periodic excitatory input illustrates that this synchronization mechanism generalizes to a broad range of n:m phase-locked bursting states across both globally synchronous and clustered oscillatory regimes.

The Feller process is an one-dimensional diffusion process with linear drift and state-dependent diffusion coefficient vanishing at the origin. The process is positive definite and it is this property along with its linear character that have made Feller process a convenient candidate for the modeling of a number of phenomena ranging from single-neuron firing to volatility of financial assets. While general properties of the process have long been well known, less known are properties related to level crossing such as the first-passage and the escape problems. In this work we thoroughly address these questions.

Intracellular calcium dynamics is critical for many functions of cerebellar granule cells (GrCs) including membrane excitability, synaptic plasticity, apoptosis, and regulation of gene transcription. Recent measurements of calcium responses in GrCs to depolarization and synaptic stimulation reveal spatial compartmentalization and heterogeneity within dendrites of these cells. However, the main determinants of local calcium dynamics in GrCs are still poorly understood. One reason is that there have been few published studies of calcium dynamics in intact GrCs in their native environment. In the absence of complete information, biophysically realistic models are useful for testing whether specific Ca(2+) handling mechanisms may account for existing experimental observations. Simulation results can be used to identify critical measurements that would discriminate between different models. In this review, we briefly describe experimental studies and phenomenological models of Ca(2+) signaling in GrC, and then discuss a particular biophysical model, with a special emphasis on an approach for obtaining information regarding the distribution of Ca(2+) handling systems under conditions of incomplete experimental data. Use of this approach suggests that Ca(2+) channels and fixed endogenous Ca(2+) buffers are highly heterogeneously distributed in GrCs. Research avenues for investigating calcium dynamics in GrCs by a combination of experimental and modeling studies are proposed.

The ionic mechanism underlying optimal stimulus shapes that induce a neuron to fire an action potential, or spike, is relevant to understanding optimal information transmission and therapeutic stimulation in the nervous system. Here we analyze for the first time the ionic basis for stimulus optimality in the Hodgkin and Huxley model and for eliciting a spike in squid giant axons, the preparation for which the model was devised. The experimentally determined stimulus is a smoothly varying biphasic current waveform having a relatively long and shallow hyperpolarizing phase followed by a depolarizing phase of briefer duration. The hyperpolarizing phase removes a small degree of the resting level of Na(+) channel inactivation. This result together with the subsequent depolarizing phase provides a signal that is energetically more efficient for eliciting spikes than rectangular current pulses. Sodium channel inactivation is the only variable that is changed during the stimulus waveform, other than the membrane potential, V. The activation variables for Na(+) and K(+) channels are unchanged throughout the stimulus. This result demonstrates how an optimal stimulus waveform relates to ionic dynamics and may have implications for energy efficiency of neural excitation in many systems including the mammalian brain.

Direct electrical recording of the neuronal transmembrane potential has been crucial to our understanding of the biophysical mechanisms subserving neuronal computation. Existing intracellular recording techniques, however, limit the accuracy and duration of such measurements by changing intracellular biochemistry and/or by damaging the plasma membrane. Here we demonstrate that nanoengineered electrodes can be used to record neuronal transmembrane potentials in brain tissue without causing these physiological perturbations. Using focused ion beam milling, we have fabricated Solid-Conductor Intracellular NanoElectrodes (SCINEs), from conventional tungsten microelectrodes. SCINEs have tips that are <300 nm in diameter for several micrometers, but can be easily handled and can be inserted into brain tissue. Performing simultaneous whole-cell patch recordings, we show that SCINEs can record action potentials (APs) as well as slower, subthreshold neuronal potentials without altering cellular properties. These results show a key role for nanotechnology in the development of new electrical recording techniques in neuroscience.

ATP-sensitive K(+) (K(ATP)) channels are composed of pore-forming subunits, typically Kir6.2 in neurons, and regulatory sulfonylurea receptor subunits. In dorsal striatum, activity-dependent H(2)O(2) produced from glutamate receptor activation inhibits dopamine release via K(ATP) channels. Sources of modulatory H(2)O(2) include striatal medium spiny neurons, but not dopaminergic axons. Using fast-scan cyclic voltammetry in guinea-pig striatal slices and immunohistochemistry, we determined the time window for H(2)O(2)/K(ATP)-channel-mediated inhibition and assessed whether modulatory K(ATP) channels are on dopaminergic axons. Comparison of paired-pulse suppression of dopamine release in the absence and presence of glibenclamide, a K(ATP)-channel blocker, or mercaptosuccinate, a glutathione peroxidase inhibitor that enhances endogenous H(2)O(2) levels, revealed a time window for inhibition of 500-1000 ms after stimulation. Immunohistochemistry demonstrated localization of Kir6.2 K(ATP)-channel subunits on dopaminergic axons. Consistent with the presence of functional K(ATP) channels on dopaminergic axons, K(ATP)-channel openers, diazoxide and cromakalim, suppressed single-pulse evoked dopamine release. Although cholinergic interneurons that tonically regulate dopamine release also express K(ATP) channels, diazoxide did not induce the enhanced frequency responsiveness of dopamine release seen with nicotinic-receptor blockade. Together, these studies reveal subsecond regulation of striatal dopamine release by endogenous H(2)O(2) acting at K(ATP) channels on dopaminergic axons, including a role in paired-pulse suppression., (© 2011 The Authors. Journal of Neurochemistry © 2011 International Society for Neurochemistry.)

The response of a neuronal population to afferent drive can be expected to be sensitive to both the distribution and dynamics of membrane voltages within the population. Voltage fluctuations can be driven by synaptic noise, neuromodulators, or cellular inhomogeneities: processes ranging from millisecond autocorrelation times to effectively static or "frozen" noise. Here we extend previous studies of filtered fluctuations to the experimentally verified exponential integrate-and-fire model. How fast or frozen fluctuations affect the steady-state rate and firing-rate response are both examined using perturbative solutions and limits of a 1 + 2 dimensional Fokker-Planck equation. The central finding is that, under conditions of a more-or-less constant population voltage variance, the firing-rate response is only weakly dependent on the fluctuation filter constant: The voltage distribution is the principal determinant of the population response. This result is unexpected given the nature of the systems underlying the extreme limits of fast and frozen fluctuations; the first limit represents a homogeneous population of neurons firing stochastically, whereas the second limit is equivalent to a heterogeneous population of neurons firing deterministically.

Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.

A model is constructed to study the phenomenon of bursting in cultured neuronal networks by considering the effects of glial release and the extrasynaptic receptors on neurons. In the frequently observed situations of synchronized bursting, the whole neuronal network can be described by a mean-field model. In this model, the dynamics of the synchronized network in the presence of glia is represented by an effective two-compartment neuron with stimulations on both the dendrite and soma. Numerical simulations of this model show that most of the experimental observations in bursting, in particular the high plateau and the slow repolarization, can be reproduced. Our findings suggest that the effects of glia release and extrasynaptic receptors, which are usually neglected in neuronal models, can become important in intense network activities. Furthermore, simulations of the model are also performed for the case of glia-suppressed cultures to compare with recent experimental results.

The voltage-gated K(+) channel Kv1.3 has been reported to regulate transmitter release in select central and peripheral neurons. In this study, we evaluated its role at the synapse between visceral sensory afferents and secondary neurons in the nucleus of the solitary tract (NTS). We identified mRNA and protein for Kv1.3 in rat nodose ganglia using RT-PCR and Western blot analysis. In immunohistochemical experiments, anti-Kv1.3 immunoreactivity was very strong in internal organelles in the soma of nodose neurons with a weaker distribution near the plasma membrane. Anti-Kv1.3 was also identified in the axonal branches that project centrally, including their presynaptic terminals in the medial and commissural NTS. In current-clamp experiments, margatoxin (MgTx), a high-affinity blocker of Kv1.3, produced an increase in action potential duration in C-type but not A- or Ah-type neurons. To evaluate the role of Kv1.3 at the presynaptic terminal, we examined the effect of MgTx on tract evoked monosynaptic excitatory postsynaptic currents (EPSCs) in brain slices of the NTS. MgTx increased the amplitude of evoked EPSCs in a subset of neurons, with the major increase occurring during the first stimuli in a 20-Hz train. These data, together with the results from somal recordings, support the hypothesis that Kv1.3 regulates the duration of the action potential in the presynaptic terminal of C fibers, limiting transmitter release to the postsynaptic cell.

HCN1 channel subunits, which contribute to the hyperpolarization-activated cation current (Ih), are selectively targeted to distal apical dendrites of hippocampal CA1 pyramidal neurons. Here, we addressed the importance of the brain-specific auxiliary subunit of HCN1, TRIP8b, in regulating HCN1 expression and localization. More than ten N-terminal splice variants of TRIP8b exist in brain and exert distinct effects on HCN1 trafficking when overexpressed. We found that isoform-wide disruption of the TRIP8b/HCN1 interaction caused HCN1 to be mistargeted throughout CA1 somatodendritic compartments. In contrast, HCN1 was targeted normally to CA1 distal dendrites in a TRIP8b knockout mouse that selectively lacked exons 1b and 2. Of the two remaining hippocampal TRIP8b isoforms, TRIP8b(1a-4) promoted HCN1 surface expression in dendrites, whereas TRIP8b(1a) suppressed HCN1 misexpression in axons. Thus, proper subcellular localization of HCN1 depends on its differential additive and subtractive sculpting by two isoforms of a single auxiliary subunit., (Copyright © 2011 Elsevier Inc. All rights reserved.)

We study the effects of passive dendritic properties on the dynamics of neuronal oscillators. We find that the addition of a passive dendrite can sometimes have counterintuitive effects on firing frequency. Specifically, the addition of a hyperpolarized passive dendritic load can either increase, decrease, or have negligible effects on firing frequency. We use the theory of weak coupling to derive phase equations for "ball-and-stick" model neurons and two-compartment model neurons. We then develop a framework for understanding how the addition of passive dendrites modulates the frequency of neuronal oscillators. We show that the average value of the neuronal oscillator's phase response curves measures the sensitivity of the neuron's firing rate to the dendritic load, including whether the addition of the dendrite causes an increase or decrease in firing frequency. We interpret this finding in terms of to the slope of the neuronal oscillator's frequency-applied current curve. We also show that equivalent results exist for constant and noisy point-source input to the dendrite. We note that the results are not specific to neurons but are applicable to any oscillator subject to a passive load.

The generation of spikes by neurons is energetically a costly process and the evaluation of the metabolic energy required to maintain the signaling activity of neurons a challenge of practical interest. Neuron models are frequently used to represent the dynamics of real neurons but hardly ever to evaluate the electrochemical energy required to maintain that dynamics. This paper discusses the interpretation of a Hodgkin-Huxley circuit as an energy model for real biological neurons and uses it to evaluate the consumption of metabolic energy in the transmission of information between neurons coupled by electrical synapses, i.e., gap junctions. We show that for a single postsynaptic neuron maximum energy efficiency, measured in bits of mutual information per molecule of adenosine triphosphate (ATP) consumed, requires maximum energy consumption. For groups of parallel postsynaptic neurons we determine values of the synaptic conductance at which the energy efficiency of the transmission presents clear maxima at relatively very low values of metabolic energy consumption. Contrary to what could be expected, the best performance occurs at a low energy cost.

Schizophrenia may involve hypofunction of NMDA receptor (NMDAR)-mediated signaling, and alterations in parvalbumin-positive fast-spiking (FS) GABA neurons that may cause abnormal gamma oscillations. It was recently hypothesized that prefrontal cortex (PFC) FS neuron activity is highly dependent on NMDAR activation and that, consequently, FS neuron dysfunction in schizophrenia is secondary to NMDAR hypofunction. However, NMDARs are abundant in synapses onto PFC pyramidal neurons; thus, a key question is whether FS neuron or pyramidal cell activation is more dependent on NMDARs. We examined the AMPAR and NMDAR contribution to synaptic activation of FS neurons and pyramidal cells in the PFC of adult mice. In FS neurons, EPSCs had fast decay and weak NMDAR contribution, whereas in pyramidal cells, EPSCs were significantly prolonged by NMDAR-mediated currents. Moreover, the AMPAR/NMDAR EPSC ratio was higher in FS cells. NMDAR antagonists decreased EPSPs and EPSP-spike coupling more strongly in pyramidal cells than in FS neurons, showing that FS neuron activation is less NMDAR dependent than pyramidal cell excitation. The precise EPSP-spike coupling produced by fast-decaying EPSCs in FS cells may be important for network mechanisms of gamma oscillations based on feedback inhibition. To test this possibility, we used simulations in a computational network of reciprocally connected FS neurons and pyramidal cells and found that brief AMPAR-mediated FS neuron activation is crucial to synchronize, via feedback inhibition, pyramidal cells in the gamma frequency band. Our results raise interesting questions about the mechanisms that might link NMDAR hypofunction to alterations of FS neurons in schizophrenia.

The anterior cingulate cortex (ACC) has been demonstrated to play an important role in the affective dimension of pain. Although much evidence has pointed to an increased excitatory synaptic transmission in the ACC in some of the pathological pain state, the inhibitory synaptic transmission in this process has not been well studied. Also, the overall changes of excitatory and inhibitory synaptic transmission have not been comparatively studied in an animal model displaying both long-term persistent nociception and hyperalgesia. Here we used patch clamp recordings in ACC brain slices to observe the changes in synaptic transmission in a pain model induced by peripheral bee venom injection. First, we show that, comparing with those of naive and saline controlled rats, there was a significant increase in spike frequency in ACC neurons harvested from rats after 2 h period of peripheral persistent painful stimuli. Second, it is further shown that the frequency, amplitude and half-width were all increased in spontaneous excitatory post-synaptic currents (sEPSCs), while the amplitude of spontaneous inhibitory post-synaptic currents (sIPSCs) was decreased. The recordings of miniature post-synaptic currents demonstrate an increase in frequency of miniature excitatory post-synaptic currents (mEPSCs) and a decrease in both frequency and amplitude of miniature inhibitory post-synaptic currents (mIPSCs) in rats' ACC slice of bee venom treatment. Taken together, the present results demonstrate an unparalleled change between excitatory and inhibitory synaptic transmission in the ACC under a state of peripheral persistent nociception that might be underlying mechanisms of the excessive excitability of the ACC neurons. We propose that the painful stimuli when lasts or becomes persistent may cause a disruption of the balance between excitatory and inhibitory synaptic transmission that can contribute to the functional change in the ACC., (Copyright © 2010 IBRO. Published by Elsevier Ltd. All rights reserved.)

Neurons react differently to incoming stimuli depending upon their previous history of stimulation. This property can be considered as a single-cell substrate for transient memory, or context-dependent information processing: depending upon the current context that the neuron "sees" through the subset of the network impinging on it in the immediate past, the same synaptic event can evoke a postsynaptic spike or just a subthreshold depolarization. We propose a formal definition of History-Dependent Excitability (HDE) as a measure of the propensity to firing in any moment in time, linking the subthreshold history-dependent dynamics with spike generation. This definition allows the quantitative assessment of the intrinsic memory for different single-neuron dynamics and input statistics. We illustrate the concept of HDE by considering two general dynamical mechanisms: the passive behavior of an Integrate and Fire (IF) neuron, and the inductive behavior of a Generalized Integrate and Fire (GIF) neuron with subthreshold damped oscillations. This framework allows us to characterize the sensitivity of different model neurons to the detailed temporal structure of incoming stimuli. While a neuron with intrinsic oscillations discriminates equally well between input trains with the same or different frequency, a passive neuron discriminates better between inputs with different frequencies. This suggests that passive neurons are better suited to rate-based computation, while neurons with subthreshold oscillations are advantageous in a temporal coding scheme. We also address the influence of intrinsic properties in single-cell processing as a function of input statistics, and show that intrinsic oscillations enhance discrimination sensitivity at high input rates. Finally, we discuss how the recognition of these cell-specific discrimination properties might further our understanding of neuronal network computations and their relationships to the distribution and functional connectivity of different neuronal types.

We study the effect that the heterogeneity present among the elements of an ensemble of coupled excitable neurons has on the collective response of the system to an external signal. We consider two different interaction scenarios, one in which the neurons are diffusively coupled and another in which the neurons interact via pulse-like signals. We find that the type of interaction between the neurons has a crucial role in determining the response of the system to the external modulation. We develop a mean-field theory based on an order parameter expansion that quantitatively reproduces the numerical results in the case of diffusive coupling.

The effects of Δ(9)-tetrahydrocannabinol (THC), the psychoactive component of cannabis, on the function of 5-HT type 3 (5-HT(3)) receptors were investigated using a two-electrode voltage clamp technique in Xenopus oocytes, and a whole-cell patch clamp technique in rat nodose ganglion neurons. In oocytes injected with 3 ng cRNA of 5-HT(3A) receptor, THC reversibly inhibited currents evoked with 5-HT (1 μM) in a concentration-dependent manner (IC(50)=1.2 μM). The extent of THC inhibition was inversely correlated with the amount of cRNA injected and the mean 5-HT(3A) receptor current densities. Pretreatment with actinomycin D, which inhibits transcription, decreased the mean 5-HT(3) receptor current density and increased the extent of THC inhibition on 5-HT(3) receptor-mediated currents. The IC(50) values for THC increased from 285 nM to 1.2 μM in oocytes injected with 1 and 3 ng of 5-HT(3A) cRNA, respectively. In radioligand binding studies on membrane preparations of oocytes expressing 5-HT(3A) receptors, THC did not alter the specific binding of a 5-HT(3A) receptor antagonist, [(3)H]GR65630. In the presence of 1 μM THC, the maximum 5-HT-induced response was also inhibited without a significant change in 5-HT potency, indicating that THC acts as a noncompetitive antagonist on 5-HT(3) receptors. In adult rat nodose ganglion neurons, application of 1 μM THC caused a significant inhibition of 5-HT(3) receptors, extent of which correlated with the density of 5-HT-induced currents, indicating that the observed THC effects occur in mammalian neurons. The inhibition of 5-HT(3) receptors by THC may contribute to its pharmacological actions in nociception and emesis., (Copyright © 2010. Published by Elsevier Ltd.)

Although examples of variation and diversity exist throughout the nervous system, their importance remains a source of debate. Even neurons of the same molecular type have notable intrinsic differences. Largely unknown, however, is the degree to which these differences impair or assist neural coding. We examined the outputs from a single type of neuron, the mitral cells of the mouse olfactory bulb, to identical stimuli and found that each cell's spiking response was dictated by its unique biophysical fingerprint. Using this intrinsic heterogeneity, diverse populations were able to code for twofold more information than their homogeneous counterparts. In addition, biophysical variability alone reduced pair-wise output spike correlations to low levels. Our results indicate that intrinsic neuronal diversity is important for neural coding and is not simply the result of biological imprecision.

Upon entry into the central nervous system (CNS), serum insulin-like growth factor-1 (IGF-I) modulates neuronal growth, survival, and excitability. Yet mechanisms that trigger IGF-I entry across the blood-brain barrier remain unclear. We show that neuronal activity elicited by electrical, sensory, or behavioral stimulation increases IGF-I input in activated regions. Entrance of serum IGF-I is triggered by diffusible messengers (i.e., ATP, arachidonic acid derivatives) released during neurovascular coupling. These messengers stimulate matrix metalloproteinase-9, leading to cleavage of the IGF binding protein-3 (IGFBP-3). Cleavage of IGFBP-3 allows the passage of serum IGF-I into the CNS through an interaction with the endothelial transporter lipoprotein related receptor 1. Activity-dependent entrance of serum IGF-I into the CNS may help to explain disparate observations such as proneurogenic effects of epilepsy, rehabilitatory effects of neural stimulation, and modulatory effects of blood flow on brain activity., (2010 Elsevier Inc. All rights reserved.)

We examined the propagation pattern of neuronal excitation in slices from the central nucleus of the rat amygdala (CeA) using optical imaging with a voltage-sensitive dye. We analyzed the mechanisms for the long-term potentiation (LTP) of neuronal excitation induced by conditioning stimulation. High-frequency conditioning stimulation induced NMDA receptor-, cAMP-, and PKA-dependent LTP of neuronal excitation in the lateral part of the CeA. The bath application of forskolin also induced LTP that was PKA-dependent. These results suggest that the potentiation of neuronal excitation in the lateral part of the CeA is induced by the activation of intracellular cAMP/PKA signaling, which is triggered by the influx of Ca(2+) via NMDA receptors., (Copyright 2010 Elsevier B.V. All rights reserved.)

Cannabinoids, the primary active agent in drugs of abuse such as marijuana and hashish, tend to generate a distorted sense of time. Here we study the effect of cannabinoids on the brain's circadian clock, the suprachiasmatic nucleus (SCN), using patch clamp and cell-attached electrophysiological recordings, RT-PCR, immunocytochemistry, and behavioral analysis. The SCN showed strong expression of the cannabinoid receptor CB1R, as detected with RT-PCR. SCN neurons, including those using GABA as a transmitter, and axons within the SCN, expressed CB1R immunoreactivity. Behaviorally, cannabinoids did not alter the endogenous free-running circadian rhythm in the mouse brain, but did attenuate the ability of the circadian clock to entrain to light zeitgebers. In the absence of light, infusion of the CB1R antagonist AM251 caused a modest phase shift, suggesting endocannabinoid modulation of clock timing. Interestingly, cannabinoids had no effect on glutamate release from the retinohypothalamic projection, suggesting a direct action of cannabinoids on the retinohypothalamic tract was unlikely to explain the inhibition of the phase shift. Within the SCN, cannabinoids were excitatory by a mechanism based on presynaptic CB1R attenuation of axonal GABA release. These data raise the possibility that the time dissociation described by cannabinoid users may result in part from altered circadian clock function and/or entrainment to environmental time cues.

Recent theoretical and experimental work indicates that neurons tune themselves to maintain target levels of excitation by modulating ion channel expression and synaptic strengths. As a result, functionally equivalent circuits can produce similar activity despite disparate underlying network and cellular properties. To experimentally test the extent to which synaptic and intrinsic conductances can produce target activity in the presence of variability in neuronal intrinsic properties, we used the dynamic clamp to create hybrid two-cell circuits built from four types of stomatogastric neurons coupled to the same model Morris-Lecar neuron by reciprocal inhibition. We measured six intrinsic properties (input resistance, minimum membrane potential, firing rate in response to +1 nA of injected current, slope of the frequency-current curve, spike height, and spike voltage threshold) of dorsal gastric, gastric mill, lateral pyloric, and pyloric dilator neurons from male crabs of the species Cancer borealis. The intrinsic properties varied twofold to sevenfold in each cell type. We coupled each biological neuron to the Morris-Lecar model with seven different values of inhibitory synaptic conductance and also used the dynamic clamp to add seven different values of an artificial h-conductance, thus creating 49 different circuits for each biological neuron. Despite the variability in intrinsic excitability, networks formed from each neuron produced similar circuit performance at some values of synaptic and h-conductances. This work experimentally confirms results from previous modeling studies; tuning synaptic and intrinsic conductances can yield similar circuit outputs from neurons with variable intrinsic excitability.

Optimal function of neuronal networks requires interplay between rapid forms of Hebbian plasticity and homeostatic mechanisms that adjust the threshold for plasticity, termed metaplasticity. Numerous forms of rapid synapse plasticity have been examined in detail. However, the rules that govern synaptic metaplasticity are much less clear. Here, we demonstrate a local subunit-specific switch in NMDA receptors that alternately primes or prevents potentiation at single synapses. Prolonged suppression of neurotransmitter release enhances NMDA receptor currents, increases the number of functional NMDA receptors containing NR2B, and augments calcium transients at single dendritic spines. This local switch in NMDA receptors requires spontaneous glutamate release but is independent of action potentials. Moreover, single inactivated synapses exhibit a lower induction threshold for both long-term synaptic potentiation and plasticity-induced spine growth. Thus, spontaneous glutamate release adjusts plasticity threshold at single synapses by local regulation of NMDA receptors, providing a novel spatially delimited form of synaptic metaplasticity.

When neurons in layer 1 fire irregularly under stochastic noise, it is found synchronous firings can develop gradually in latter layers within a feed-forward multilayer neural network, which is consistent with experimental findings. The underlying mechanism of propagation of firing rate is explored, then rate encoding realized by synchronization is clarified. Furthermore, the effects of connection probability between nearest layers, stochastic noise, and ratio of inhibitory connections to total connection on (i) propagation of firing rate by synchronization and (ii) coherence of firing pattern are investigated, respectively. It is observed that (i) there is a threshold for connection probability, beyond which firing rate of each layer can propagate successfully through the whole network by synchronization. The dependence of firing rate on layer index is very different for different connection probability. In addition, larger the connection probability is, more rapidly the synchrony is built up. (ii) Increasing intensity of stochastic noise enhances firing rate in output layer. Stochastic noise plays a constructive role in improving synchrony by causing the synchronization more quickly. (iii) The inhibitory connection offsets excitatory input therefore reduces firing rate and synchrony. As layer index increases, coherence measure goes through a peak, i.e., the coherence of firing pattern is the worst at certain a layer. With increasing the ratio of inhibitory connections, the variability of firing train is enhanced, exhibiting destructive role of inhibitory connections on coherence of firing pattern.

The Kv1.3 voltage-dependent potassium channel is expressed at high levels in mitral cells of the olfactory bulb (OB). Deletion of the Kv1.3 potassium channel gene (Kv1.3-/-) in mice lowers the threshold for detection of odors, increases the ability to discriminate between odors, and alters the firing pattern of mitral cells. We have now found that loss of Kv1.3 produces a compensatory increase in Na(+)-activated K(+) currents (K(Na)) in mitral cells. Levels of the K(Na) channel subunit Slack-B determined by Western blotting are substantially increased in the OB from Kv1.3-/- animals compared with those of wildtype animals. In voltage-clamp recordings of OB slices, elevation of intracellular sodium from 0 to 60 mM increased mean outward currents by 15% in mitral cells from wildtype animals and by 40% in cells from Kv1.3-/- animals. In Kv1.3-/- cells, K(Na) current could even be detected with 0 mM Na(+) internal solutions, provided extracellular Na(+) was present, and this current could be abolished by TTX and ZD7288, blockers of Na(+) influx through voltage-dependent Na(+) channels and H-channels, respectively. The role of enhanced expression of Slack subunits in the increase of K(Na) current in Kv1.3-/- cells was also confirmed using an RNA interference (RNA(i)) approach to suppress Slack expression in primary cultures of olfactory neurons. In Kv1.3-/- neurons, treatment with Slack-specific RNA(i) inhibited approximately 75% of the net outward current, whereas in wildtype cells, the same treatment suppressed only about 25% of the total current. Scrambled and mismatched RNA(i) oligonucleotides failed to suppress currents. Our findings raise the possibility that the olfactory phenotype of Kv1.3-/- animals results in part from an enhancement of K(Na) currents.

We propose a stochastic dynamical model of noisy neural networks with complex architectures and discuss activation of neural networks by a stimulus, pacemakers, and spontaneous activity. This model has a complex phase diagram with self-organized active neural states, hybrid phase transitions, and a rich array of behaviors. We show that if spontaneous activity (noise) reaches a threshold level then global neural oscillations emerge. Stochastic resonance is a precursor of this dynamical phase transition. These oscillations are an intrinsic property of even small groups of 50 neurons.

The infinitesimal phase response curve (PRC) of a neural oscillator to a weak input is a powerful predictor of network dynamics; however, many networks have strong coupling and require direct measurement of the PRC for strong inputs under the assumption of pulsatile coupling. We incorporate measured noise levels in firing time maps constructed from PRCs to predict phase-locked modes of activity, phase difference, and locking strength in 78 heterogeneous hybrid networks of 2 neurons constructed using the dynamic clamp. We show that noise may either destroy or stabilize a phase-locked mode of activity.

Midbrain dopamine neurons release dopamine from both axons and dendrites. The mechanism underlying release at these different sites has been proposed to differ. This study used electrochemical and electrophysiological methods to compare the time course and calcium dependence of somatodendritic dopamine release in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) to that of axonal dopamine release in the dorsal striatum. The amount of dopamine released in the striatum was approximately 20-fold greater than in cell body regions of the VTA or SNc. However, the calcium dependence and time to peak of the dopamine transients were similar. These results illustrate an unexpected overall similarity in the mechanisms of dopamine release in the striatum and cell body regions. To examine how diffusion regulates the time course of dopamine following release, dextran was added to the extracellular solution to slow diffusion. In the VTA, dextran slowed the rate of rise and fall of the extracellular dopamine transient as measured by fast-scan cyclic voltammetry yet did not alter the kinetics of the dopamine-dependent IPSC. Dextran failed to significantly alter the time course of the rise and fall of the dopamine transient in the striatum, suggesting a more influential role for reuptake in the striatum. The conclusion is that the time course of dopamine within the extracellular space of the VTA is dependent on both diffusion and reuptake, whereas the activation of D(2) receptors on dopamine neurons is primarily limited by reuptake.

We studied how lateral connections affect the accuracy of a population code by using a model of orientation selectivity in the primary visual cortex. Investigating the effects of lateral connections on population coding is a complex problem because these connections simultaneously change the shape of tuning curves and correlations between neurons. Both of these changes caused by lateral connections have to be taken into consideration to correctly evaluate their effects. We propose a theoretical framework for analytically computing the Fisher information, which measures the accuracy of a population code, in stochastic spiking neuron models with refractory periods. Within our framework, we accurately evaluated both the changes in tuning curves and correlations caused by lateral connections and their effects on the Fisher information. We found that their effects conflicted with each other and the answer to whether or not the lateral connections increased the Fisher information strongly depended on the intrinsic properties of the model neuron. By systematically changing the coupling strengths of excitations and inhibitions, we found the parameter regions of lateral connectivities where sharpening of tuning curves through Mexican-hat connectivities led to an increase in information, which is in contrast to some previous findings.

We study the optimality conditions of information transfer in systems with memory in the low signal-to-noise ratio regime of vanishing input amplitude. We find that the optimal mutual information is represented by a maximum variance of the signal time course, with correlation structure determined by the Fisher information matrix. We provide illustration of the method on a simple biologically inspired model of electrosensory neuron. Our general results apply also to the study of information transfer in single neurons subject to weak stimulation, with implications to the problem of coding efficiency in biological systems.

We analyze the effects of noise correlations in the input to, or among, Bienenstock-Cooper-Munro neurons using the Wigner semicircular law to construct random, positive-definite symmetric correlation matrices and compute their eigenvalue distributions. In the finite dimensional case, we compare our analytic results with numerical simulations and show the effects of correlations on the lifetimes of synaptic strengths in various visual environments. These correlations can be due either to correlations in the noise from the input lateral geniculate nucleus neurons, or correlations in the variability of lateral connections in a network of neurons. In particular, we find that for fixed dimensionality, a large noise variance can give rise to long lifetimes of synaptic strengths. This may be of physiological significance.

Most neurons possess a single, nonmotile cilium that projects out from the cell surface. These microtubule-based organelles are important in brain development and neurogenesis; however, their function in mature neurons is unknown. Cilia express a complement of proteins distinct from other neuronal compartments, one of which is the somatostatin receptor subtype SST(3). We show here that SST(3) is critical for object recognition memory in mice. sst3 knock-out mice are severely impaired in discriminating novel objects, whereas they retain normal memory for object location. Further, systemic injection of an SST(3) antagonist (ACQ090) disrupts recall of familiar objects in wild-type mice. To examine mechanisms of SST(3), we tested synaptic plasticity in CA1 hippocampus. Electrically evoked long-term potentiation (LTP) was normal in sst3 knock-out mice, while adenylyl cyclase/cAMP-mediated LTP was impaired. The SST(3) antagonist also disrupted cAMP-mediated LTP. Basal cAMP levels in hippocampal lysate were reduced in sst3 knock-out mice compared with wild-type mice, while the forskolin-induced increase in cAMP levels was normal. The SST(3) antagonist inhibited forskolin-stimulated cAMP increases, whereas the SST(3) agonist L-796,778 increased basal cAMP levels in hippocampal slices but not hippocampal lysate. Our results show that somatostatin signaling in neuronal cilia is critical for recognition memory and suggest that the cAMP pathway is a conserved signaling motif in cilia. Neuronal cilia therefore represent a novel nonsynaptic compartment crucial for signaling involved in a specific form of synaptic plasticity and in novelty detection.

Extracellular recordings of single neurons in primary and secondary somatosensory cortices of monkeys in vivo have shown that their firing rate can increase, decrease, or remain constant in different cells, as the external stimulus frequency increases. We observed similar intrinsic firing patterns (increasing, decreasing or constant) in rat somatosensory cortex in vitro, when stimulated with oscillatory input using conductance injection (dynamic clamp). The underlying mechanism of this observation is not obvious, and presents a challenge for mathematical modelling. We propose a simple principle for describing this phenomenon using a leaky integrate-and-fire model with sinusoidal input, an intrinsic oscillation and Poisson noise. Additional enhancement of the gain of encoding could be achieved by local network connections amongst diverse intrinsic response patterns. Our work sheds light on the possible cellular and network mechanisms underlying these opposing neuronal responses, which serve to enhance signal detection.

Striatal medium-sized spiny neurons (MSNs) contain the highest levels of soluble guanylyl cyclase (sGC) in the brain. Striatal sGC signaling is activated by nitric oxide (NO) and other neuromodulators. MSNs also express cGMP-dependent protein kinase and other components of the cGMP signaling system which are critically involved in integrating corticostriatal transmission and regulating synaptic plasticity in striatal networks. However, the influence of tonic and phasic activation of this signaling pathway on striatal MSN activity is poorly understood. The present study examined the impact of systemic administration of the selective sGC inhibitor [1H-[1,2,4]oxadiazolo-[4,3-a]quinoxalin-1-one] (ODQ) on spike activity evoked using low and high frequency electrical stimulation of the frontal cortex. MSN activity was monitored using single-unit extracellular recordings in urethane-anesthetized rats. ODQ administration significantly decreased spike activity evoked by low frequency cortical stimulation in a stimulus intensity- and time-dependent manner. Additionally, ODQ administered along with the neuronal NO synthase inhibitor 7-nitroindazole (7-NI) potently decreased the incidence of excitatory responses observed during high-frequency train stimulation of the contralateral frontal cortex. The short-term depression of cortically-evoked spike activity induced by train stimulation was enhanced following pretreatment with ODQ in MSNs exhibiting an excitatory response during cortical train stimulation. Unexpectedly, this effect of ODQ was reversed in animals receiving co-administration of ODQ and 7-NI. 7-NI/ODQ co-administration also reversed measures of short-term depression observed in MSNs exhibiting an inhibitory response during cortical train stimulation. These observations extend previous studies showing that tonic and phasic NO-sGC signaling modulates the responsiveness of MSNs to corticostriatal input. Moreover, phasic activation of NO signaling is likely to regulate short-term changes in corticostriatal synaptic plasticity via complex mechanisms involving both sGC-cGMP-dependent and independent pathways., (Copyright 2009 Elsevier Ltd. All rights reserved.)

In this paper different topologies of populations of FitzHugh-Nagumo neurons have been introduce to investigate the effect of high-frequency driving on the response of neuron populations to a subthreshold low-frequency signal. We show that optimal amplitude of high-frequency driving enhances the response of neuron populations to a subthreshold low-frequency input and the optimal amplitude dependences on the connection among the neurons. By analyzing several kinds of topology (i.e., random and small world) different behaviors have been observed. Several topologies behave in an optimal way with respect to the range of low-frequency amplitude leading to an improvement in the stimulus response coherence, while others with respect to the maximum values of the performance index. However, the best results in terms of both the suitable amplitude of high-frequency driving and high stimulus response coherence have been obtained when the neurons have been connected in a small-world topology.

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.

In the cochlea, spiral ganglion neurons play a critical role in hearing as they form the relay between mechanosensory hair cells in the inner ear and cochlear nuclei in the brainstem. The proneural basic helix-loop-helix transcription factors Neurogenin1 (Neurog1) and NeuroD1 have been shown to be essential for the development of otocyst-derived inner ear sensory neurons. Here, we show neural competence of nonsensory epithelial cells in the cochlea, as ectopic expression of either Neurog1 or NeuroD1 results in the formation of neuronal cells. Since the high-mobility-group type transcription factor Sox2, which is also known to play a role in neurogenesis, is expressed in otocyst-derived neural precursor cells and later in the spiral ganglion neurons along with Neurog1 and NeuroD1, we used both gain- and loss-of-function experiments to examine the role of Sox2 in spiral ganglion neuron formation. We demonstrate that overexpression of Sox2 results in the production of neurons, suggesting that Sox2 is sufficient for the induction of neuronal fate in nonsensory epithelial cells. Furthermore, spiral ganglion neurons are absent in cochleae from Sox2(Lcc/Lcc) mice, indicating that Sox2 is also required for neuronal formation in the cochlea. Our results indicate that Sox2, along with Neurog1 and NeuroD1, are sufficient to induce a neuronal fate in nonsensory regions of the cochlea. Finally, we demonstrate that nonsensory cells within the cochlea retain neural competence through at least the early postnatal period.

Brivaracetam (ucb 34714; BRV), a new antiepileptic drug (AED) candidate, is a pyrrolidone derivative displaying a markedly higher affinity than levetiracetam (LEV; Keppra) to the synaptic vesicle protein SV2A, shown to be the brain-specific binding site of LEV. The higher affinity for SV2A correlates significant antiepileptic activity in animal epilepsy models in vitro and in vivo. Since many AEDs act upon inhibiting neuronal Na(+) currents, this study explored putative activity of BRV on the properties of these currents. Voltage-activated Na(+) currents were recorded by whole-cell patch-clamp on neuronal somas of rat neocortical neurons, grown in dissociated cell culture for up to 12 days. BRV, dissolved at the desired final concentration (between 0.2microM and 1mM) was applied by a multi-barrel pipette system near the soma of the recorded neuron. BRV produced a concentration-dependent inhibition of voltage-dependent Na(+) currents with IC(50) values of 41microM at the holding potential of -100mV, and of 6.5microM at the holding potential of -60mV. The voltage-dependence of activation and the kinetics of fast inactivation were not modified in the presence of BRV (30microM). Conversely, the recovery from fast inactivation was significantly slower and the voltage of half-maximal inactivation was shifted toward hyperpolarized value after BRV perfusion in a concentration-dependent manner. Furthermore, BRV (30microM) induced a significant use-dependent block at 50Hz stimulation frequency. These results indicate that BRV is able to modulate the voltage-activated Na(+) inflow in cortical neurons, which conceivably might contribute to the antiepileptic activity of this drug., (2009 Elsevier B.V. All rights reserved.)

In the auditory system voltage-activated currents mediated by potassium channels Kv1.1 and Kv3.1b and their interaction with sodium inward currents play a crucial role for computational function. However, it is unresolved how these potassium channels are developmentally regulated. We have therefore combined a biochemical investigation of Kv1.1 and Kv3.1b protein expression with electrophysiological recordings of membrane currents to characterize neuronal differentiation in the auditory brain stem of the chick. Differentiation in vitro was compared with cells prepared from corresponding embryonic stages in vivo. Using a computer model based on the empirical data we were then able to predict physiological properties of developing auditory brain stem neurons. In vivo Kv3.1b expression increased strongly between E10 and E14, a time of functional synaptogenesis in the auditory brainstem. We also found this increase of expression in vitro, again coinciding with synaptogenesis in the cultures. Whole-cell patch recordings revealed a corresponding increase of the (Kv3.1-like) high threshold potassium current. In contrast, Kv1.1 protein expression failed to increase in vitro, and changes in (Kv1.1-like) low threshold potassium current with time in culture were not significant. Electrophysiological recordings revealed that sodium inward currents increased with cultivation time. Thus, our data suggest that Kv3.1b expression occurs with the onset of functional synaptogenesis, while a different signal, absent from cultures of dissociated auditory brain stem, is needed for Kv1.1 expression. A biophysical model constructed with parameters from our recordings was used to investigate the functional impact of the currents mediated by these channels. We found that during development both high and low threshold potassium currents need to be increased in a concerted manner with the sodium conductance for the neurons to exhibit fast and phasic action potential firing and a narrow time window of coincidence detection.

Considering the fact that signal transmission time delays between different pairs of synaptically coupled neurons in the brain are different, we study the effects of distributed time delays on phase synchronization of bursting neurons. We consider the case of inhibitory coupled bursting Hindmarsh-Rose neurons and find that distributed time delays in chemical coupling can induce a variety of phase-coherent dynamic behaviors. The critical mean time delay for the emergence of coherent behaviors is inversely proportional to both the coupling strength and the average degree. This phenomenon is robust to nonidentical external inputs and is independent of network topology. A physical theory is formulated to explain the emergence of coherent neuronal activity.

Inward rectifying potassium (K(IR)) currents in medium spiny (MS) neurons of nucleus accumbens inactivate significantly in approximately 40% of the neurons but not in the rest, which may lead to differences in input processing by these two groups. Using a 189-compartment computational model of the MS neuron, we investigate the influence of this property using injected current as well as spatiotemporally distributed synaptic inputs. Our study demonstrates that K(IR) current inactivation facilitates depolarization, firing frequency and firing onset in these neurons. These effects may be attributed to the higher input resistance of the cell as well as a more depolarized resting/down-state potential induced by the inactivation of this current. In view of the reports that dendritic intracellular calcium levels depend closely on burst strength and spike onset time, our findings suggest that inactivation of K(IR) currents may offer a means of modulating both excitability and synaptic plasticity in MS neurons.

N-type and L-type channels have significant gating differences, and we wondered whether some of these differences are linked to the relationship between charge movement and channel opening. The time constants for N-channel closing (tau(Deact)) and Off-gating charge movement (tauQ(Off)) were compared over a range of voltages. tauQ(Off) was significantly larger than tau(Deact) at voltages < -10 mV, and the voltage dependence of the tauQ(Off) was less steep than that for tau(Deact), which suggests that gating charge relaxation does not limit channel closing. Roscovitine, a drug that slows N-channel closing by holding the channel in a high open-probability state, was found to slow both tauQ(Off) and tau(Deact), and thus the time courses of channel closing and gating charge relaxation were similar. Our gating current results were reproduced with the addition of a voltage-independent, closed-closed transition to our previously published two-open-state N-channel model. This work suggests that, like L-type channels, there is a voltage-independent transition along the N-channel activation/deactivation pathway, but this transition occurs between closed states instead of the closed-open states of the L-channel. Also unlike L-type channels, the gating charge appears to be locked into the activated position by the N-channel open state.

Many synapses contain both AMPA receptors (AMPAR) and N-methyl-d-aspartate receptors (NMDAR), but their different roles in synaptic computation are not clear. We address this issue at the auditory nerve fiber synapse (called the endbulb of Held), which is formed on bushy cells of the cochlear nucleus. The endbulb refines and relays precise temporal information to nuclei responsible for sound localization. The endbulb has a number of specializations that aid precise timing, including AMPAR-mediated excitatory postsynaptic currents (EPSCs) with fast kinetics. Voltage-clamp experiments in mouse brain slices revealed that slow NMDAR EPSCs are maintained at mature endbulbs, contributing a peak conductance of around 10% of the AMPAR-mediated EPSC. During repetitive synaptic activity, AMPAR EPSCs depressed and NMDAR EPSCs summated, thereby increasing the relative importance of NMDARs. This could impact temporal precision of bushy cells because of the slow kinetics of NMDARs. We tested this by blocking NMDARs and quantifying bushy cell spike timing in current clamp when single endbulbs were activated. These experiments showed that NMDARs contribute to an increased probability of firing, shorter latency, and reduced jitter. Dynamic-clamp experiments confirmed this effect and showed it was dose-dependent. Bushy cells can receive inputs from multiple endbulbs. When we applied multiple synaptic inputs in dynamic clamp, NMDARs had less impact on spike timing. NMDAR conductances much higher than mature levels could disrupt spiking, which may explain its downregulation during development. Thus mature NMDAR expression can support the conveying of precise temporal information at the endbulb, depending on the stimulus conditions.