Ionic current model of a hypoglossal motoneuron

The effects of membrane potential oscillations on the excitability of rat hypoglossal motoneurons

Oscillations in membrane potential induced by synaptic inputs and intrinsic ion channel activity play a role in regulating neuronal excitability, but the precise mechanisms underlying their contributions remain largely unknown. Here we used electrophysiological and modeling approaches to investigate the effects of Gaussian white noise injected currents on the membrane properties and discharge characteristics of hypoglossal (HG) motoneurons in P16-21 day old rats. We found that the noise-induced membrane potential oscillations facilitated spike initiation by hyperpolarizing the cells’ voltage threshold by 3.1 ± 1.0 mV and reducing the recruitment current for the tonic discharges by 0.26 ± 0.1 nA, on average (n = 59). Further analysis revealed that the noise reduced both recruitment and decruitment currents by 0.26 ± 0.13 and 0.33 ± 0.1 nA, respectively, and prolonged the repetitive firing. The noise also increased the slopes of frequency-current (F-I) relationships by 1.1 ± 0.2 Hz/nA. To investigate the potential mechanisms underlying these findings, we constructed a series of HG motoneuron models based on their electrophysiological properties. The models consisted of five compartments endowed with transient sodium (NaT), delayed-rectify potassium [K(DR)], persistent sodium (NaP), calcium-activated potassium [K(AHP)], L-type calcium (CaL) and H-current channels. In general, all our experimental results could be well fitted by the models, however, a modification of standard Hodgkin-Huxley kinetics was required to reproduce the changes in the F-I relationships and the prolonged discharge firing. This modification, corresponding to the noise generated by the stochastic flicker of voltage-gated ion channels (channel flicker, CF), was an adjustable sinusoidal function added to kinetics of the channels that increased their sensitivity to subthreshold membrane potential oscillations. Models with CF added to NaP and CaL channels mimicked the noise-induced alterations of membrane properties, whereas models with CF added to NaT and K(DR) were particularly effective in reproducing the noise-induced changes for repetitive firing observed in the real motoneurons. Further analysis indicated that the modified channel kinetics enhanced NaP- and CaL-mediated inward currents thus increasing the excitability and output of HG motoneurons, whereas they produced relatively small changes in NaT and K(DR), thus balancing these two currents and triggering variability of repetitive firing. This study provided insight into the types of membrane channel mechanisms that might underlie oscillation-induced alterations of neuronal excitability and motor output in rat HG motoneurons.

Effects of inflammation on the developing respiratory system: Focus on hypoglossal (XII) neuron morphology, brainstem neurochemistry, and control of breathing

Breathing is fundamental to life and any adverse change in respiratory function can endanger the health of an organism or even be fatal. Perinatal inflammation is known to adversely affect breathing in preterm babies, but lung infection/inflammation impacts all stages of life from birth to death. Little is known about the role of inflammation in respiratory control, neuronal morphology, or neural function during development. Animal models of inflammation can provide understanding and insight into respiratory development and how inflammatory processes alter developmental phenotype in addition to providing insight into new treatment modalities. In this review, we focus on recent work concerning the development of neurons, models of perinatal inflammation with an emphasis on two common LPS-based models, inflammation and its impact on development, and current and potential treatments for inflammation within the respiratory control circuitry of the mammalian brainstem. We have also discussed models of inflammation in adults and have specifically focused on hypoglossal motoneurons (XII) and neurons of the nucleus tractus solitarii (nTS) as these nuclei have been studied more extensively than other brainstem nuclei participating in breathing and airway control. Understanding the impact of inflammation on the developmental aspects of respiratory control and breathing pattern is critical to addressing problems of cardiorespiratory dysregulation in disease and this overview points out many gaps in our current knowledge.

Computational model of brain-stem circuit for state-dependent control of hypoglossal motoneurons

In patients with obstructive sleep apnea (OSA), the pharyngeal muscles become relaxed during sleep, which leads to a partial or complete closure of upper airway. Experimental studies suggest that withdrawal of noradrenergic and serotonergic drives importantly contributes to depression of hypoglossal motoneurons and, therefore, may contribute to OSA pathophysiology; however, specific cellular and synaptic mechanisms remain unknown. In this new study, we developed a biophysical network model to test the hypothesis that, to explain experimental observations, the neuronal network for monoaminergic control of excitability of hypoglossal motoneurons needs to include excitatory and inhibitory perihypoglossal interneurons that mediate noradrenergic and serotonergic drives to hypoglossal motoneurons. In the model, the state-dependent activation of the hypoglossal motoneurons was in qualitative agreement with in vivo data during simulated rapid eye movement (REM) and non-REM sleep. The model was applied to test the mechanisms of action of noradrenergic and serotonergic drugs during REM sleep as observed in vivo. We conclude that the proposed minimal neuronal circuit is sufficient to explain in vivo data and supports the hypothesis that perihypoglossal interneurons may mediate state-dependent monoaminergic drive to hypoglossal motoneurons. The population of the hypothesized perihypoglossal interneurons may serve as novel targets for pharmacological treatment of OSA. NEW & NOTEWORTHY In vivo studies suggest that during rapid eye movement sleep, withdrawal of noradrenergic and serotonergic drives critically contributes to depression of hypoglossal motoneurons (HMs), which innervate the tongue muscles. By means of a biophysical model, which is consistent with a broad range of empirical data, we demonstrate that the neuronal network controlling the excitability of HMs needs to include excitatory and inhibitory interneurons that mediate noradrenergic and serotonergic drives to HMs.

Novel description of the large conductance Ca2+-modulated K+ channel current, BK, during an action potential from suprachiasmatic nucleus neurons

The contribution of the large conductance, Ca²⁺‐modulated, voltage‐gated K⁺ channel current, I_BK, to the total current during an action potential (AP) from suprachiasmatic nucleus (SCN) neurons is described using a novel computational approach. An experimental recording of an SCN AP and the corresponding AP‐clamp recording of I_BK from the literature were both digitized. The AP data set was applied computationally to a kinetic model of I_BK that was based on results from a clone of the BK channel α subunit heterologolously expressed in Xenopus oocytes. The I_BK model result during an AP was compared with the AP‐clamp recording of I_BK. The comparison suggests that a change in the intracellular Ca²⁺ concentration does not have an immediate effect on BK channel kinetics. Rather, a delay of a few milliseconds may occur prior to the full effect of a change in Ca_i²⁺. As shown elsewhere, the β2 subunit of the BK channel in the SCN, which is present in the daytime along with the α subunit, shifts the BK channel activation curve leftward on the voltage axis relative to the activation curve of BK channels comprised of the α subunit alone. That shift may underlie the diurnal changes in electrical activity that occur in the SCN and it may also enhance the delay in the effect of a change in Ca_i²⁺ on BK kinetics reported here. The implication of these results for models of the AP for neurons in which BK channels are present is that an additional time dependent process may be required in the models, a process that describes the time dependence of the development of a change in the intracellular Ca²⁺ concentration on BK channel gating.

Respiratory rhythm generation: triple oscillator hypothesis

Breathing is vital for survival but also interesting from the perspective of rhythm generation. This rhythmic behavior is generated within the brainstem and is thought to emerge through the interaction between independent oscillatory neuronal networks. In mammals, breathing is composed of three phases - inspiration, post-inspiration, and active expiration - and this article discusses the concept that each phase is generated by anatomically distinct rhythm-generating networks: the preBötzinger complex (preBötC), the post-inspiratory complex (PiCo), and the lateral parafacial nucleus (pF L), respectively. The preBötC was first discovered 25 years ago and was shown to be both necessary and sufficient for the generation of inspiration. More recently, networks have been described that are responsible for post-inspiration and active expiration. Here, we attempt to collate the current knowledge and hypotheses regarding how respiratory rhythms are generated, the role that inhibition plays, and the interactions between the medullary networks. Our considerations may have implications for rhythm generation in general.

Developmental changes in the morphology of mouse hypoglossal motor neurons

Hypoglossal motor neurons (XII MNs) innervate tongue muscles important in breathing, suckling and vocalization. Morphological properties of 103 XII MNs were studied using Neurobiotin™ filling in transverse brainstem slices from C57/Bl6 mice (n = 34) from embryonic day (E) 17 to postnatal day (P) 28. XII MNs from areas thought to innervate different tongue muscles showed similar morphology in most, but not all, features. Morphological properties of XII MNs were established prior to birth, not differing between E17-18 and P0. MN somatic volume gradually increased for the first 2 weeks post-birth. The complexity of dendritic branching and dendrite length of XII MNs increased throughout development (E17-P28). MNs in the ventromedial XII motor nucleus, likely to innervate the genioglossus, frequently (42 %) had dendrites crossing to the contralateral side at all ages, but their number declined with postnatal development. Unexpectedly, putative dendritic spines were found in all XII MNs at all ages, and were primarily localized to XII MN somata and primary dendrites at E18-P4, increased in distal dendrites by P5-P8, and were later predominantly found in distal dendrites. Dye-coupling between XII MNs was common from E18 to P7, but declined strongly with maturation after P7. Axon collaterals were found in 20 % (6 of 28) of XII MNs with filled axons; collaterals terminated widely outside and, in one case, within the XII motor nucleus. These results reveal new morphological features of mouse XII MNs, and suggest that dendritic projection patterns, spine density and distribution, and dye-coupling patterns show specific developmental changes in mice.

Distribution of transition times in a stochastic model of excitable cell: Insights into the cell-intrinsic mechanisms of randomness in neuronal interspike intervals

In this paper, we develop an analytical approach to studying random patterns of activity in excitable cells. Our analytical approach uses a two-state stochastic model of excitable system based on the electrophysiological properties of refractoriness and restitution, which characterize cell recovery after excitation. By applying the notion of probability density flux, we derive the distributions of transition times between states and the distribution of interspike interval (ISI) durations for a constant applied stimulus. The derived ISI distribution is unimodal and, provided that the time spent in the excited state is constant, can be approximated by a Rayleigh peak followed by an exponential tail. We then explore the role of the model parameters in determining the shape of the derived distributions and the ISI coefficient of variation. Finally, we use our analytical results to study simulation results from the stochastic Morris-Lecar neuron and from a three-state extension of the proposed stochastic model, which is capable of reproducing multimodal ISI histograms.

Novel description of ionic currents recorded with the action potential clamp technique: application to excitatory currents in suprachiasmatic nucleus neurons

The traditional method of recording ionic currents in neurons has been with voltage-clamp steps. Other waveforms such as action potentials (APs) can be used. The AP clamp method reveals contributions of ionic currents that underlie excitability during an AP (Bean BP. Nat Rev Neurosci 8: 451-465, 2007). A novel usage of the method is described in this report. An experimental recording of an AP from the literature is digitized and applied computationally to models of ionic currents. These results are compared with experimental AP-clamp recordings for model verification or, if need be, alterations to the model. The method is applied to the tetrodotoxin-sensitive sodium ion current, INa, and the calcium ion current, ICa, from suprachiasmatic nucleus (SCN) neurons (Jackson AC, Yao GL, Bean BP. J Neurosci 24: 7985-7998, 2004). The latter group reported voltage-step and AP-clamp results for both components. A model of INa is constructed from their voltage-step results. The AP clamp computational methodology applied to that model compares favorably with experiment, other than a modest discrepancy close to the peak of the AP that has not yet been resolved. A model of ICa was constructed from both voltage-step and AP-clamp results of this component. The model employs the Goldman-Hodgkin-Katz equation for the current-voltage relation rather than the traditional linear dependence of this aspect of the model on the Ca(2+) driving force. The long-term goal of this work is a mathematical model of the SCN AP. The method is general. It can be applied to any excitable cell.

Using a computational model to analyze the effects of firing frequency on synchrony of a network of gap junction-coupled hypoglossal motoneurons

Hypoglossal motoneurons (HMs) are located in the brainstem and play an important role in the maintenance of upper airway patency. HMs are known to be coupled to one another via gap junctions and exhibit synchronous firing behavior when driven by premotor inputs. In the current study, we used a computational model to analyze the influence of firing frequency on synchronous firing behavior of a network of gap junction-coupled HMs. As there are many factors that can influence excitability and firing frequency of HMs, our simulations were focused on the effects of modulation of SK channel conductance and the magnitude of the input currents as a means of modifying firing frequency. Our simulations revealed that regardless of the mechanism by which firing frequency was modulated, increasing the firing frequency disrupted the synchrony in gap junction-coupled HM networks with low, medium, and high levels of gap junction coupling.

Context-dependent coding in single neurons

The linear-nonlinear cascade model (LN model) has proven very useful in representing a neural system's encoding properties, but has proven less successful in reproducing the firing patterns of individual neurons whose behavior is strongly dependent on prior firing history. While the cell's behavior can still usefully be considered as feature detection acting on a fluctuating input, some of the coding capacity of the cell is taken up by the increased firing rate due to a constant "driving" direct current (DC) stimulus. Furthermore, both the DC input and the post-spike refractory period generate regular firing, reducing the spike-timing entropy available for encoding time-varying fluctuations. In this paper, we address these issues, focusing on the example of motoneurons in which an afterhyperpolarization (AHP) current plays a dominant role regularizing firing behavior. We explore the accuracy and generalizability of several alternative models for single neurons under changes in DC and variance of the stimulus input. We use a motoneuron simulation to compare coding models in neurons with and without the AHP current. Finally, we quantify the tradeoff between instantaneously encoding information about fluctuations and about the DC.

Effects of calcium (Ca(2+)) extrusion mechanisms on electrophysiological properties in a hypoglossal motoneuron: insight from a mathematical model

Spike-frequency dynamics and spike shape can provide insight into the types of ion channels present in any given neuron and give a sense for the precise response any neuron may have to a given input stimulus. Motoneuron firing frequency over time is especially important due to its direct effect on motor output. Of particular interest is intracellular Ca(2+), which exerts a powerful influence on both firing properties over time and spike shape. In order to better understand the cellular mechanisms for the regulation of intracellular Ca(2+) and their effect on spiking behavior, we have modified a computational model of an HM to include a variety of Ca(2+) handling processes. For the current study, a series of HM models that include Ca(2+) pumps, Na(+)/Ca(2+) exchangers, and a generic exponential decay of excess Ca(2+) were generated. Simulations from these models indicate that although each extrusion mechanism exerts a similar effect on voltage, the firing properties change distinctly with the inclusion of additional Ca(2+)-related mechanisms: BK channels, Ca(2+) buffering, and diffusion of [Ca(2+)]i modeled via a linear diffusion partial differential equation. While an exponential decay of Ca(2+) seems to adequately capture short-term changes in firing frequency seen in biological data, internal diffusion of Ca(2+) appears to be necessary for capturing longer term frequency changes.

Interaction function of oscillating coupled neurons

Large scale simulations of electrically coupled neuronal oscillators often employ the phase coupled oscillator paradigm to understand and predict network behavior. We study the nature of the interaction between such coupled oscillators using weakly coupled oscillator theory. By employing piecewise linear approximations for phase response curves and voltage time courses and parametrizing their shapes, we compute the interaction function for all such possible shapes and express it in terms of discrete Fourier modes. We find that reasonably good approximation is achieved with four Fourier modes that comprise of both sine and cosine terms.

A novel analysis of excitatory currents during an action potential from suprachiasmatic nucleus neurons

A new application of the action potential (AP) voltage-clamp technique is described based on computational analysis. An experimentally recorded AP is digitized. The resulting Vi vs. ti data set is applied to mathematical models of the ionic conductances underlying excitability for the cell from which the AP was recorded to test model validity. The method is illustrated for APs from suprachiasmatic nucleus (SCN) neurons and the underlying tetrodotoxin-sensitive Na(+) current, INa, and the Ca(2+) current, ICa. Voltage-step recordings have been made for both components from SCN neurons (Jackson et al. 2004). The combination of voltage-step and AP clamp results provides richer constraints for mathematical models of voltage-gated ionic conductances than either set of results alone, in particular the voltage-step results. For SCN neurons the long-term goal of this work is a realistic mathematical model of the SCN AP in which the equations for I(Na) and I(Ca) obtained from this analysis will be a part. Moreover, the method described in this report is general. It can be applied to any excitable cell.

Emergent central pattern generator behavior in gap-junction-coupled Hodgkin-Huxley style neuron model

Most models of central pattern generators (CPGs) involve two distinct nuclei mutually inhibiting one another via synapses. Here, we present a single-nucleus model of biologically realistic Hodgkin-Huxley neurons with random gap junction coupling. Despite no explicit division of neurons into two groups, we observe a spontaneous division of neurons into two distinct firing groups. In addition, we also demonstrate this phenomenon in a simplified version of the model, highlighting the importance of afterhyperpolarization currents (I(AHP)) to CPGs utilizing gap junction coupling. The properties of these CPGs also appear sensitive to gap junction conductance, probability of gap junction coupling between cells, topology of gap junction coupling, and, to a lesser extent, input current into our simulated nucleus.

Analyzing the effects of gap junction blockade on neural synchrony via a motoneuron network computational model

In specific regions of the central nervous system (CNS), gap junctions have been shown to participate in neuronal synchrony. Amongst the CNS regions identified, some populations of brainstem motoneurons are known to be coupled by gap junctions. The application of various gap junction blockers to these motoneuron populations, however, has led to mixed results regarding their synchronous firing behavior, with some studies reporting a decrease in synchrony while others surprisingly find an increase in synchrony. To address this discrepancy, we employ a neuronal network model of Hodgkin-Huxley-style motoneurons connected by gap junctions. Using this model, we implement a series of simulations and rigorously analyze their outcome, including the calculation of a measure of neuronal synchrony. Our simulations demonstrate that under specific conditions, uncoupling of gap junctions is capable of producing either a decrease or an increase in neuronal synchrony. Subsequently, these simulations provide mechanistic insight into these different outcomes.

Cycle-by-cycle assembly of respiratory network activity is dynamic and stochastic

Rhythmically active networks are typically composed of neurons that can be classified as silent, tonic spiking, or rhythmic bursting based on their intrinsic activity patterns. Within these networks, neurons are thought to discharge in distinct phase relationships with their overall network output, and it has been hypothesized that bursting pacemaker neurons may lead and potentially trigger cycle onsets. We used multielectrode recording from 72 experiments to test these ideas in rhythmically active slices containing the pre-Bötzinger complex, a region critical for breathing. Following synaptic blockade, respiratory neurons exhibited a gradient of intrinsic spiking to rhythmic bursting activities and thus defied an easy classification into bursting pacemaker and nonbursting categories. Features of their firing activity within the functional network were analyzed for correlation with subsequent rhythmic bursting in synaptic isolation. Higher firing rates through all phases of fictive respiration statistically predicted bursting pacemaker behavior. However, a cycle-by-cycle analysis indicated that respiratory neurons were stochastically activated with each burst. Intrinsically bursting pacemakers led some population bursts and followed others. This variability was not reproduced in traditional fully interconnected computational models, while sparsely connected network models reproduced these results both qualitatively and quantitatively. We hypothesize that pacemaker neurons do not act as clock-like drivers of the respiratory rhythm but rather play a flexible and dynamic role in the initiation and stabilization of each burst. Thus, at the behavioral level, each breath can be thought of as de novo assembly of a stochastic collaboration of network topology and intrinsic properties.

Drive latencies in hypoglossal motoneurons indicate developmental change in the brainstem respiratory network

The respiratory rhythm originates and diverges from the brainstem to drive thousands of motoneurons that are responsible for control of the diaphragm, intercostals and upper airway. These motoneurons are known to have a wide range of phase relationships, even within a single motoneuron pool. The proposed source of this rhythm, the preBötzinger complex (preBötC), responds to an array of developmental changes in the first days post-birth, specifically at postnatal day 3 (P3). We hypothesize that such developmental changes in the preBötC have a direct effect on motoneuron phase relationships and should be detectable around age P3. To test our hypothesis, we obtained single- and dual-voltage-clamp recordings of hypoglossal motoneurons in an in vitro slice preparation. We introduce a novel approach to analyzing the phase relationships between motoneurons by using cross-correlation analysis to determine the drive latencies. This analysis reveals that the distribution of drive latencies undergoes a significant change at or before age P3. We use a computational model of the in vitro slice to demonstrate the observed phase differences and hypothesize that network heterogeneity alone may not be sufficient to explain them. Through simulations, we show the effects on the preBötC of different network characteristics such as clustering and common inputs.

Associating changes in output behavior with changes in parameter values in spiking and bursting neuron models

Several recent studies have demonstrated that neuronal models allow multiple parameter value solutions for a given output. In the face of this variability of parameter values, what can be learned about neural function through parameter value differences? Here, in two different models, we examine this question by attempting to reconstruct the source of model output changes based on simple statistical analyses of parameter distributions generated by automated searches. We conclude that changes to parameter values or their associated distributions do not reliably reflect the specific mechanisms responsible for a given change in output.

Contribution of motoneuron intrinsic properties to fictive motor pattern generation

Previously, we reported a canonical ensemble model of the heart motoneurons that underlie heartbeat in the medicinal leech. The model motoneurons contained a minimal set of electrical intrinsic properties and received a synaptic input pattern based on measurements performed in the living system. Although the model captured the synchronous and peristaltic motor patterns observed in the living system, it did not match quantitatively the motor output observed. Because the model motoneurons had minimal intrinsic electrical properties, the mismatch between model and living system suggests a role for additional intrinsic properties in generating the motor pattern. We used the dynamic clamp to test this hypothesis. We introduced the same segmental input pattern used in the model to motoneurons isolated pharmacologically from their endogenous input in the living system. We show that, although the segmental input pattern determines the segmental phasing differences observed in motoneurons, the intrinsic properties of the motoneurons play an important role in determining their phasing, particularly when receiving the synchronous input pattern. We then used trapezoidal input waveforms to show that the intrinsic properties present in the living system promote phase advances compared with our model motoneurons. Electrical coupling between heart motoneurons also plays a role in shaping motoneuron output by synchronizing the activity of the motoneurons within a segment. These experiments provide a direct assessment of how motoneuron intrinsic properties interact with their premotor pattern of synaptic drive to produce rhythmic 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.

Modeling the spontaneous activity in suprachiasmatic nucleus neurons: role of cation single channels

A population of interconnected neurons of the mammalian suprachiasmatic nuclei (SCN) controls circadian rhythms in physiological functions. In turn, a circadian rhythm of individual neurons is driven by intracellular processes, which via activation of specific membrane channels, produce circadian modulation of electrical firing rate. Yet the membrane target(s) of the cellular clock have remained enigmatic. Previously, subthreshold voltage-dependent cation (SVC) channels have been proposed as the membrane target of the cellular clock responsible for circadian modulation of the firing rate in SCN neurons. We tested this hypothesis with computational modeling based on experimental results from on-cell recording of SVC channel openings in acutely isolated SCN neurons and long-term continuous recording of activity from dispersed SCN neurons in a multielectrode array dish (MED). The model reproduced the circadian behavior if the number of SVC channels or their kinetics were modulated in accordance with protein concentration in a model of the intracellular clock (Scheper et al., 1999. J. Neurosci. 19, 40-47). Such modulation changed the average firing rate of the model neuron from zero ("subjective-night" silence) up to 18 Hz ("subjective-day" peak). Furthermore, the variability of interspike intervals (ISI) and the circadian pattern of firing rate (i.e. silence-to-activity ratio and shape of circadian peaks) are in reasonable agreement with experimental data obtained in dispersed SCN neurons in MED. These results suggest that the variability of ISI in intact SCN neurons is mostly due to stochastic single-channel openings, and that the circadian pattern of the firing rate is specified by threshold properties of dependence of the spontaneous firing rate on the number of single channels (R-N relationship). This plausible mathematical modeling supports the hypothesis that SVC channels could be a critical element in circadian modulation of firing rate in SCN neurons.

Dendrites determine the contribution of after depolarization potentials (ADPs) to generation of repetitive action potentials in hypothalamic gonadotropin releasing-hormone (GnRH) neurons

The impact of structure in modulating synaptic signals originating in dendrites is widely recognized. In this study, we focused on the impact of dendrite morphology on a local spike generating mechanism which has been implicated in hormone secretion, the after depolarization potential (ADP). Using multi-compartmental models of hypothalamic GnRH neurons, we systematically truncated dendrite length and determined the consequence on ADP amplitude and repetitive firing. Decreasing the length of the dendrite significantly increased the amplitude of the ADP and increased repetitive firing. These effects were observed in dendrites both with and without active conductances suggesting they largely reflect passive characteristics of the dendrite. In order to test the findings of the model, we performed whole-cell recordings in GnRH neurons and elicited ADPs using current injection. During recordings, neurons were filled with biocytin so that we could determine dendritic and total projection (dendrite plus axon) length. Neurons exhibited ADPs and increasing ADP amplitude was associated with decreasing dendrite length, in keeping with the predictions of the models. Thus, despite the relatively simple morphology of the GnRH neuron's dendrite, it can still exert a substantial impact on the final neuronal output.

Functional imaging, spatial reconstruction, and biophysical analysis of a respiratory motor circuit isolated in vitro

We combined real-time calcium-based neural activity imaging with whole-cell patch-clamp recording techniques to map the spatial organization and analyze electrophysiological properties of respiratory neurons forming the circuit transmitting rhythmic drive from the pre-Bötzinger complex (pre-BötC) through premotoneurons to hypoglossal (XII) motoneurons. Inspiratory pre-BötC neurons, XII premotoneurons (preMNs), and XII motoneurons (MNs) were retrogradely labeled with Ca(2+)-sensitive dye in neonatal rat in vitro brainstem slices. PreMN cell bodies were arrayed dorsomedially to pre-BötC neurons with little spatial overlap; axonal projections to MNs were ipsilateral. Inspiratory MNs were distributed in dorsal and ventral subnuclei of XII. Voltage-clamp recordings revealed that two currents, persistent sodium current (NaP) and K(+)-dominated leak current (Leak), primarily contribute to preMN/MN subthreshold current-voltage relationships. NaP or Leak conductance densities in preMNs and MNs were not significantly different. We quantified preMN and MN action potential time course and spike frequency-current (f-I) relationships and found no significant differences in repetitive spiking dynamics, steady-state f-I gains, and afterpolarizing potentials. Rhythmic synaptic drive current densities were similar in preMNs and MNs. Our results indicate that, despite topographic and morphological differences, preMNs and MNs have some common intrinsic membrane, synaptic integration, and spiking properties that we postulate ensure fidelity of inspiratory drive transmission and conversion of synaptic drive into (pre)motor output. There also appears to be a common architectonic organization for some respiratory drive transmission circuits whereby many preMNs are spatially segregated from pre-BötC rhythm-generating neurons, which we hypothesize may facilitate downstream integration of convergent inputs for premotor pattern formation.

STDP in a bistable synapse model based on CaMKII and associated signaling pathways

The calcium/calmodulin-dependent protein kinase II (CaMKII) plays a key role in the induction of long-term postsynaptic modifications following calcium entry. Experiments suggest that these long-term synaptic changes are all-or-none switch-like events between discrete states. The biochemical network involving CaMKII and its regulating protein signaling cascade has been hypothesized to durably maintain the evoked synaptic state in the form of a bistable switch. However, it is still unclear whether experimental LTP/LTD protocols lead to corresponding transitions between the two states in realistic models of such a network. We present a detailed biochemical model of the CaMKII autophosphorylation and the protein signaling cascade governing the CaMKII dephosphorylation. As previously shown, two stable states of the CaMKII phosphorylation level exist at resting intracellular calcium concentration, and high calcium transients can switch the system from the weakly phosphorylated (DOWN) to the highly phosphorylated (UP) state of the CaMKII (similar to a LTP event). We show here that increased CaMKII dephosphorylation activity at intermediate Ca(2+) concentrations can lead to switching from the UP to the DOWN state (similar to a LTD event). This can be achieved if protein phosphatase activity promoting CaMKII dephosphorylation activates at lower Ca(2+) levels than kinase activity. Finally, it is shown that the CaMKII system can qualitatively reproduce results of plasticity outcomes in response to spike-timing dependent plasticity (STDP) and presynaptic stimulation protocols. This shows that the CaMKII protein network can account for both induction, through LTP/LTD-like transitions, and storage, due to its bistability, of synaptic changes.

Membrane Properties and Firing Patterns of Inferior Colliculus Neurons: An In Vivo Patch-Clamp Study in Rodents

The inferior colliculus (IC) is a large auditory nucleus in the midbrain, which is a nearly obligatory relay center for ascending auditory projections. We made in vivo whole cell patch-clamp recordings of IC cells in young-adult anesthetized C57/Bl6 mice and Wistar rats to characterize their membrane properties and spontaneous inputs. We observed spikelets in both rat (18%) and mouse (13%) IC neurons, suggesting that IC neurons may be connected by electrical synapses. In many cells, spontaneous postsynaptic potentials were sufficiently large to contribute to spike irregularity. Cells differed considerably in the number of simultaneous spontaneous postsynaptic potentials that would be needed to trigger an action potential. Depolarizing and hyperpolarizing current injections showed six different types of firing patterns: buildup, accelerating, burst-onset, burst-sustained, sustained, and accommodating. Their relative frequencies were similar in both species. In mice, about half of the cells showed a clear depolarizing sag, suggesting that they have the hyperpolarization-activated current Ih. This sag was observed more often in burst and in accommodating cells than in buildup, accelerating, or sustained neurons. Cells with Ih had a significantly more depolarized resting membrane potential. They were more likely to fire rebound spikes and generally showed long-lasting afterhyperpolarizations following long depolarizations. We therefore suggest a separate functional role for Ih.

Apamin-sensitive calcium-activated potassium currents (SK) are activated by persistent calcium currents in rat motoneurons

Low voltage-activated persistent inward calcium currents (Ca PICs) occur in rat motoneurons and are mediated by Cav1.3 L-type calcium channels (L-Ca current). The objectives of this paper were to determine whether this L-Ca current activates a sustained calcium-activated potassium current (SK current) and examine how such SK currents change with spinal injury. For comparison, the SK current that produces the postspike afterhyperpolarization (mAHP) was also quantified. Intracellular recordings were made from motoneurons of adult acute and chronic spinal rats while the whole sacrocaudal spinal cord was maintained in vitro. Spikes/AHPs were evoked with current injection or ventral root stimulation. Application of the SK channel blocker apamin completely eliminated the mAHP, which was not significantly different in chronic and acute spinal rats. The Ca PICs were measured with slow voltage ramps (or steps) with TTX to block sodium currents. In chronic spinal rats, the PICs were activated at -58.6 +/- 6.0 mV and were 2.2 +/- 1.2 nA in amplitude, significantly larger than in acute spinal rats. Apamin significantly increased the PIC, indicating that there was an SK current activated by L-Ca currents (SK(L) current), which ultimately reduced the net PIC. This SK(L) current was not different in acute and chronic spinal rats. The SK(AHP) and the SK(L) currents were activated by different calcium currents because the mAHP/SK(AHP) was blocked by the N, P-type calcium channel blocker omega-conotoxin MVIIC and was resistant to the L-type calcium channel blocker nimodipine, whereas the L-Ca and SK(L) currents were blocked by nimodipine. Furthermore, the SK(AHP) current activated within 10 ms of the spike, whereas the SK(L) current was delayed approximately 100 ms after the onset of the L-Ca current, suggesting that the SK(L) currents were not as spatially close to the L-Ca currents. Finally, the SK(L) and the L-Ca currents were poorly space clamped, with oscillations at their onset and hysteresis in their activation and deactivation voltages, consistent with currents of dendritic origin. The impact of these dendritic currents was especially pronounced in 15% of motoneurons, where apamin led to uncontrollable L-Ca currents that could not be deactivated, even with large hyperpolarizations of the soma. Thus, although the SK(L) currents are fairly small, they play a critical role in terminating the dendritic L-Ca currents.