Activity-independent homeostasis in rhythmically active neurons

Animal-to-Animal Variability in Neuromodulation and Circuit Function

Each animal alive in the world is different from all other individuals, while sharing most attributes of form and function with others of the same species. Still other attributes are shared within a phylum, and still others are common to most eukaryotic organisms. All animals have mechanisms that modulate the strength of their synapses or alter the intrinsic excitability of component neurons. What animal-to-animal variability in behavior arises from differences in neuronal structure, ion channel expression, or connectivity, and what variability arises from neuromodulation of brain states? Conversely, can robust behavior be maintained despite variability in circuit components by the action of neuromodulatory inputs? These are fundamental issues relevant to all nervous systems that have been illuminated by many years of study of the small, rhythmic motor circuits found in the crustacean stomatogastric nervous system.

Tonic 5nM DA stabilizes neuronal output by enabling bidirectional activity-dependent regulation of the hyperpolarization activated current via PKA and calcineurin

Volume transmission results in phasic and tonic modulatory signals. The actions of tonic dopamine (DA) at type 1 DA receptors (D1Rs) are largely undefined. Here we show that tonic 5nM DA acts at D1Rs to stabilize neuronal output over minutes by enabling activity-dependent regulation of the hyperpolarization activated current (I _h). In the presence but not absence of 5nM DA, I _h maximal conductance (G _max) was adjusted according to changes in slow wave activity in order to maintain spike timing. Our study on the lateral pyloric neuron (LP), which undergoes rhythmic oscillations in membrane potential with depolarized plateaus, demonstrated that incremental, bi-directional changes in plateau duration produced corresponding alterations in LP I _hG _max when preparations were superfused with saline containing 5nM DA. However, when preparations were superfused with saline alone there was no linear correlation between LP I _hG_max and duty cycle. Thus, tonic nM DA modulated the capacity for activity to modulate LP I _h G _max; this exemplifies metamodulation (modulation of modulation). Pretreatment with the Ca2+-chelator, BAPTA, or the specific PKA inhibitor, PKI, prevented all changes in LP I _h in 5nM DA. Calcineurin inhibitors blocked activity-dependent changes enabled by DA and revealed a PKA-mediated, activity-independent enhancement of LP I _hG _max. These data suggested that tonic 5nM DA produced two simultaneous, PKA-dependent effects: a direct increase in LP I _h G _max and a priming event that permitted calcineurin regulation of LP I _h. The latter produced graded reductions in LP I _hG _max with increasing duty cycles. We also demonstrated that this metamodulation preserved the timing of LP’s first spike when network output was perturbed with bath-applied 4AP. In sum, 5nM DA permits slow wave activity to provide feedback that maintains spike timing, suggesting that one function of low-level, tonic modulation is to stabilize specific features of a dynamic output.

QUANTITATIVE REEVALUATION OF THE EFFECTS OF SHORT- AND LONG-TERM REMOVAL OF DESCENDING MODULATORY INPUTS ON THE PYLORIC RHYTHM OF THE CRAB, CANCER BOREALIS

Neuromodulatory inputs are known to strongly influence the intrinsic excitability of individual neurons and the networks in which the targets of modulation are found. It is therefore important to understand how nervous systems respond to altered neuromodulatory environments.

The crustacean stomatogastric ganglion (STG) receives descending neuromodulatory inputs from three anterior ganglia: the paired commissural ganglia (CoGs), and the single esophageal ganglion (OG). In this paper, we provide the first detailed and quantitative analyses of the short- and long-term effects of removal of these descending inputs (decentralization) on the pyloric rhythm of the STG. Thirty minutes after decentralization, the mean frequency of the pyloric rhythm dropped from 1.20 Hz in control to 0.52 Hz. Whereas the relative phase of pyloric neuron activity was approximately constant across frequency in the controls, after decentralization this changed markedly. Nine control preparations kept for 5–6 d in vitro maintained pyloric rhythm frequencies close to their initial values. Nineteen decentralized preparations kept for 5–6 d dropped slightly in frequency from those seen at 30 min following decentralization, but then displayed stable activity over 6 d. Bouts of higher frequency activity were intermittently seen in both control and decentralized preparations, but the bouts began earlier and were more frequent in the decentralized preparations. Although the bouts may indicate that the removal of the modulatory inputs triggered changes in neuronal excitability, these changes did not produce obvious long-lasting changes in the frequency of the decentralized preparations.

Differential effects of static and dynamic inputs on neuronal excitability

The intrinsic excitability of neurons is known to be dynamically regulated by activity-dependent plasticity and homeostatic mechanisms. Such processes are commonly analyzed in the context of input-output functions that describe how neurons fire in response to constant levels of current. However, it is not well understood how changes of excitability as observed under static inputs translate to the function of the same neurons in their natural synaptic environment. Here we performed a computational study and hybrid experiments on rat bed nucleus of stria terminalis neurons to compare the two scenarios. The inward rectifying Kir current (IKir) and the hyperpolarization-activated cation current (Ih) were found to be considerably more effective in regulating the firing under synaptic inputs than under static stimuli. This prediction was experimentally confirmed by dynamic-clamp insertion of a synthetic inwardly rectifying Kir current into the biological neurons. At the same time, ionic currents that activate with depolarization were more effective regulating the firing under static inputs. When two intrinsic currents are concurrently altered such as those under homeostatic regulation, the effects in firing responses under static vs. dynamic inputs can be even more contrasting. Our results show that plastic or homeostatic changes of intrinsic membrane currents can shape the current step responses of neurons and their firing under synaptic inputs in a differential manner.

High-conductance states and A-type K+ channels are potential regulators of the conductance-current balance triggered by HCN channels

An increase in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channel conductance reduces input resistance, whereas the consequent increase in the inward h current depolarizes the membrane. This results in a delicate and unique conductance-current balance triggered by the expression of HCN channels. In this study, we employ experimentally constrained, morphologically realistic, conductance-based models of hippocampal neurons to explore certain aspects of this conductance-current balance. First, we found that the inclusion of an experimentally determined gradient in A-type K+ conductance, but not in M-type K+ conductance, tilts the HCN conductance-current balance heavily in favor of conductance, thereby exerting an overall restorative influence on neural excitability. Next, motivated by the well-established modulation of neuronal excitability by synaptically driven high-conductance states observed under in vivo conditions, we inserted thousands of excitatory and inhibitory synapses with different somatodendritic distributions. We measured the efficacy of HCN channels, independently and in conjunction with other channels, in altering resting membrane potential (RMP) and input resistance ( Rin) when the neuron received randomized or rhythmic synaptic bombardments through variable numbers of synaptic inputs. We found that the impact of HCN channels on average RMP, Rin, firing frequency, and peak-to-peak voltage response was severely weakened under high-conductance states, with the impinging synaptic drive playing a dominant role in regulating these measurements. Our results suggest that the debate on the role of HCN channels in altering excitability should encompass physiological and pathophysiological neuronal states under in vivo conditions and the spatiotemporal interactions of HCN channels with other channels.

Neuronal plasticity: how do neurons know what to do?

A recent study confirms activity-dependent co-regulation of membrane conductances as a mechanism underlying homeostatic regulation of neuronal properties. How multiple cellular and synaptic homeostatic mechanisms interact in a neuronal circuit is best studied with a combination of experimentation and modeling.

Activity-dependent feedback regulates correlated ion channel mRNA levels in single identified motor neurons

Neurons generate cell-specific outputs via interactions of conductances carried by ion channel proteins that are homeostatically regulated to maintain key quantitative relationships among subsets of conductances. Given the challenges of both normal channel protein turnover and short-term plasticity, how is the balance of membrane conductances maintained over long-term timescales to ensure stable electrophysiological phenotype? One possible mechanism is to dynamically regulate production of channel protein via feedback that constrains relationships at the channel mRNA level. Recent modeling work has postulated that such mRNA relationships could emerge as a result of activity-dependent homeostatic tuning rules that ensure an appropriate ratio of mRNA for key ion channels is maintained to preserve robust cellular output. Yet, this has never been demonstrated in biological neurons. In this study, we quantified multiple ion channel mRNAs from single identified motor neurons of the stomatogastric ganglion to determine whether correlations among channel mRNAs are actively maintained, and, if so, by what form of feedback. In these neurons, we identified correlations among mRNAs for voltage-gated calcium and potassium channels. By performing experiments that decoupled activity, synaptic connectivity, and neuromodulatory state, we determined that correlated channel mRNAs are maintained by an activity-dependent process. This is the first study to demonstrate that distinct relationships across channel mRNAs are dynamically maintained in an activity-dependent manner. This feedback from cellular activity to coordinated transcriptome-level interactions represents a novel aspect of regulation of neuronal output with implications for long-term stability of neuron function.

Ionic Current Variability and Functional Stability in the Nervous System

Identified neurons in different animals express ionic currents at highly variable levels (population variability). If neuronal identity is associated with stereotypical function, as is the case in genetically identical neurons or in unambiguously identified individual neurons, this variability poses a conundrum: How is activity the same if the components that generate it-ionic current levels-are different? In some cases, ionic current variability across similar neurons generates an output gradient. However, many neurons produce very similar output activity, despite substantial variability in ionic conductances. It appears that, in many such cells, conductance levels of one ionic current vary in proportion to the conductance levels of another current. As a result, in a population of neurons, these conductances appear to be correlated. Here, I review theoretical and experimental work that suggests that neuronal ionic current correlation can reduce the global ionic current variability and can contribute to functional stability.

Kv7 channels regulate pairwise spiking covariability in health and disease

Low-threshold M currents are mediated by the Kv7 family of potassium channels. Kv7 channels are important regulators of spiking activity, having a direct influence on the firing rate, spike time variability, and filter properties of neurons. How Kv7 channels affect the joint spiking activity of populations of neurons is an important and open area of study. Using a combination of computational simulations and analytic calculations, we show that the activation of Kv7 conductances reduces the covariability between spike trains of pairs of neurons driven by common inputs. This reduction is beyond that explained by the lowering of firing rates and involves an active cancellation of common fluctuations in the membrane potentials of the cell pair. Our theory shows that the excess covariance reduction is due to a Kv7-induced shift from low-pass to band-pass filtering of the single neuron spike train response. Dysfunction of Kv7 conductances is related to a number of neurological diseases characterized by both elevated firing rates and increased network-wide correlations. We show how changes in the activation or strength of Kv7 conductances give rise to excess correlations that cannot be compensated for by synaptic scaling or homeostatic modulation of passive membrane properties. In contrast, modulation of Kv7 activation parameters consistent with pharmacological treatments for certain hyperactivity disorders can restore normal firing rates and spiking correlations. Our results provide key insights into how regulation of a ubiquitous potassium channel class can control the coordination of population spiking activity.

Homeostasis of functional maps in active dendrites emerges in the absence of individual channelostasis

The maintenance of ion channel homeostasis, or channelostasis, is a complex puzzle in neurons with extensive dendritic arborization, encompassing a combinatorial diversity of proteins that encode these channels and their auxiliary subunits, their localization profiles, and associated signaling machinery. Despite this, neurons exhibit amazingly stereotypic, topographically continuous maps of several functional properties along their active dendritic arbor. Here, we asked whether the membrane composition of neurons, at the level of individual ion channels, is constrained by this structural requirement of sustaining several functional maps along the same topograph. We performed global sensitivity analysis on morphologically realistic conductance-based models of hippocampal pyramidal neurons that coexpressed six well-characterized functional maps along their trunk. We generated randomized models by varying 32 underlying parameters and constrained these models with quantitative experimental measurements from the soma and dendrites of hippocampal pyramidal neurons. Analyzing valid models that satisfied experimental constraints on all six functional maps, we found topographically analogous functional maps to emerge from disparate model parameters with weak pairwise correlations between parameters. Finally, we derived a methodology to assess the contribution of individual channel conductances to the various functional measurements, using virtual knockout simulations on the valid model population. We found that the virtual knockout of individual channels resulted in variable, measurement- and location-specific impacts across the population. Our results suggest collective channelostasis as a mechanism behind the robust emergence of analogous functional maps and have significant ramifications for the localization and targeting of ion channels and enzymes that regulate neural coding and homeostasis.

Synaptic excitation is regulated by the postsynaptic dSK channel at the Drosophila larval NMJ

In the mammalian central nervous system, the postsynaptic small-conductance Ca(2+)-dependent K(+) (SK) channel has been shown to reduce postsynaptic depolarization and limit Ca(2+) influx through N-methyl-d-aspartate receptors. To examine further the role of the postsynaptic SK channel in synaptic transmission, we studied its action at the Drosophila larval neuromuscular junction (NMJ). Repetitive synaptic stimulation produced an increase in postsynaptic membrane conductance leading to depression of excitatory postsynaptic potential amplitude and hyperpolarization of the resting membrane potential (RMP). This reduction in synaptic excitation was due to the postsynaptic Drosophila SK (dSK) channel; synaptic depression, increased membrane conductance and RMP hyperpolarization were reduced in dSK mutants or after expressing a Ca(2+) buffer in the muscle. Ca(2+) entering at the postsynaptic membrane was sufficient to activate dSK channels based upon studies in which the muscle membrane was voltage clamped to prevent opening voltage-dependent Ca(2+) channels. Increasing external Ca(2+) produced an increase in resting membrane conductance and RMP that was not seen in dSK mutants or after adding the glutamate-receptor blocker philanthotoxin. Thus it appeared that dSK channels were also activated by spontaneous transmitter release and played a role in setting membrane conductance and RMP. In mammals, dephosphorylation by protein phosphatase 2A (PP2A) increased the Ca(2+) sensitivity of the SK channel; PP2A appeared to increase the sensitivity of the dSK channel since PP2A inhibitors reduced activation of the dSK channel by evoked synaptic activity or increased external Ca(2+). It is proposed that spontaneous and evoked transmitter release activate the postsynaptic dSK channel to limit synaptic excitation and stabilize synapses.

A codimension-2 bifurcation controlling endogenous bursting activity and pulse-triggered responses of a neuron model

The dynamics of individual neurons are crucial for producing functional activity in neuronal networks. An open question is how temporal characteristics can be controlled in bursting activity and in transient neuronal responses to synaptic input. Bifurcation theory provides a framework to discover generic mechanisms addressing this question. We present a family of mechanisms organized around a global codimension-2 bifurcation. The cornerstone bifurcation is located at the intersection of the border between bursting and spiking and the border between bursting and silence. These borders correspond to the blue sky catastrophe bifurcation and the saddle-node bifurcation on an invariant circle (SNIC) curves, respectively. The cornerstone bifurcation satisfies the conditions for both the blue sky catastrophe and SNIC. The burst duration and interburst interval increase as the inverse of the square root of the difference between the corresponding bifurcation parameter and its bifurcation value. For a given set of burst duration and interburst interval, one can find the parameter values supporting these temporal characteristics. The cornerstone bifurcation also determines the responses of silent and spiking neurons. In a silent neuron with parameters close to the SNIC, a pulse of current triggers a single burst. In a spiking neuron with parameters close to the blue sky catastrophe, a pulse of current temporarily silences the neuron. These responses are stereotypical: the durations of the transient intervals-the duration of the burst and the duration of latency to spiking-are governed by the inverse-square-root laws. The mechanisms described here could be used to coordinate neuromuscular control in central pattern generators. As proof of principle, we construct small networks that control metachronal-wave motor pattern exhibited in locomotion. This pattern is determined by the phase relations of bursting neurons in a simple central pattern generator modeled by a chain of oscillators.

Convergent rhythm generation from divergent cellular mechanisms

Different modulatory inputs commonly elicit distinct rhythmic motor patterns from a central pattern generator (CPG), but they can instead elicit the same pattern. We are determining the rhythm-generating mechanisms in this latter situation, using the gastric mill (chewing) CPG in the crab (Cancer borealis) stomatogastric ganglion, where stimulating the projection neuron MCN1 (modulatory commissural neuron 1) or bath applying CabPK (C. borealis pyrokinin) peptide elicits the same gastric mill motor pattern, despite configuring different gastric mill circuits. In both cases, the core rhythm generator includes the same reciprocally inhibitory neurons LG (lateral gastric) and Int1 (interneuron 1), but the pyloric (food-filtering) circuit pacemaker neuron AB (anterior burster) is additionally necessary only for CabPK rhythm generation. MCN1 drives this rhythm generator by activating in the LG neuron the modulator-activated inward current (IMI), which waxes and wanes periodically due to phasic feedback inhibition of MCN1 transmitter release. Each buildup of IMI enables the LG neuron to generate a self-terminating burst and thereby alternate with Int1 activity. Here we establish that CabPK drives gastric mill rhythm generation by activating in the LG neuron IMI plus a slowly activating transient, low-threshold inward current (ITrans-LTS) that is voltage, time, and Ca(2+) dependent. Unlike MCN1, CabPK maintains a steady IMI activation, causing a subthreshold depolarization in LG that facilitates a periodic postinhibitory rebound burst caused by the regular buildup and decay of the availability of ITrans-LTS. Thus, different modulatory inputs can use different rhythm-generating mechanisms to drive the same neuronal rhythm. Additionally, the same ionic current (IMI) can play different roles under these different conditions, while different currents (IMI, ITrans-LTS) can play the same role.

Homeostatic signaling and the stabilization of neural function

The brain is astonishing in its complexity and capacity for change. This has fascinated scientists for more than a century, filling the pages of this journal for the past 25 years. But a paradigm shift is underway. It seems likely that the plasticity that drives our ability to learn and remember can only be meaningful in the context of otherwise stable, reproducible, and predictable baseline neural function. Without the existence of potent mechanisms that stabilize neural function, our capacity to learn and remember would be lost in the chaos of daily experiential change. This underscores two great mysteries in neuroscience. How are the functional properties of individual neurons and neural circuits stably maintained throughout life? And, in the face of potent stabilizing mechanisms, how can neural circuitry be modified during neural development, learning, and memory? Answers are emerging in the rapidly developing field of homeostatic plasticity.

Correlated conductance parameters in leech heart motor neurons contribute to motor pattern formation

Neurons can have widely differing intrinsic membrane properties, in particular the density of specific conductances, but how these contribute to characteristic neuronal activity or pattern formation is not well understood. To explore the relationship between conductances, and in particular how they influence the activity of motor neurons in the well characterized leech heartbeat system, we developed a new multi-compartmental Hodgkin-Huxley style leech heart motor neuron model. To do so, we evolved a population of model instances, which differed in the density of specific conductances, capable of achieving specific output activity targets given an associated input pattern. We then examined the sensitivity of measures of output activity to conductances and how the model instances responded to hyperpolarizing current injections. We found that the strengths of many conductances, including those with differing dynamics, had strong partial correlations and that these relationships appeared to be linked by their influence on heart motor neuron activity. Conductances that had positive correlations opposed one another and had the opposite effects on activity metrics when perturbed whereas conductances that had negative correlations could compensate for one another and had similar effects on activity metrics.

Comparison of two voltage-sensitive dyes and their suitability for long-term imaging of neuronal activity

One of the key approaches for studying neural network function is the simultaneous measurement of the activity of many neurons. Voltage-sensitive dyes (VSDs) simultaneously report the membrane potential of multiple neurons, but often have pharmacological and phototoxic effects on neuronal cells. Yet, to study the homeostatic processes that regulate neural network function long-term recordings of neuronal activities are required. This study aims to test the suitability of the VSDs RH795 and Di-4-ANEPPS for optically recording pattern generating neurons in the stomatogastric nervous system of crustaceans with an emphasis on long-term recordings of the pyloric central pattern generator. We demonstrate that both dyes stain pyloric neurons and determined an optimal concentration and light intensity for optical imaging. Although both dyes provided sufficient signal-to-noise ratio for measuring membrane potentials, Di-4-ANEPPS displayed a higher signal quality indicating an advantage of this dye over RH795 when small neuronal signals need to be recorded. For Di-4-ANEPPS, higher dye concentrations resulted in faster and brighter staining. Signal quality, however, only depended on excitation light strength, but not on dye concentration. RH795 showed weak and slowly developing phototoxic effects on the pyloric motor pattern as well as slow bleaching of the staining and is thus the better choice for long-term experiments. Low concentrations and low excitation intensities can be used as, in contrast to Di-4-ANEPPS, the signal-to-noise ratio was independent of excitation light strength. In summary, RH795 and Di-4-ANEPPS are suitable for optical imaging in the stomatogastric nervous system of crustaceans. They allow simultaneous recording of the membrane potential of multiple neurons with high signal quality. While Di-4-ANEPPS is better suited for short-term experiments that require high signal quality, RH795 is a better candidate for long-term experiments since it has only minor effects on the motor pattern.

Neurons within the same network independently achieve conserved output by differentially balancing variable conductance magnitudes

Biological and theoretical evidence suggest that individual neurons may achieve similar outputs by differentially balancing variable underlying ionic conductances. Despite the substantial amount of data consistent with this idea, a direct biological demonstration that cells with conserved output, particularly within the same network, achieve these outputs via different solutions has been difficult to achieve. Here we demonstrate definitively that neurons from native neural networks with highly similar output achieve this conserved output by differentially tuning underlying conductance magnitudes. Multiple motor neurons of the crab (Cancer borealis) cardiac ganglion have highly conserved output within a preparation, despite showing a 2-4-fold range of conductance magnitudes. By blocking subsets of these currents, we demonstrate that the remaining conductances become unbalanced, causing disparate output as a result. Therefore, as strategies to understand neuronal excitability become increasingly sophisticated, it is important that such variability in excitability of neurons, even among those within the same individual, is taken into account.

Potassium conductance dynamics confer robust spike-time precision in a neuromorphic model of the auditory brain stem

A fundamental question in neuroscience is how neurons perform precise operations despite inherent variability. This question also applies to neuromorphic engineering, where low-power microchips emulate the brain using large populations of diverse silicon neurons. Biological neurons in the auditory pathway display precise spike timing, critical for sound localization and interpretation of complex waveforms such as speech, even though they are a heterogeneous population. Silicon neurons are also heterogeneous, due to a key design constraint in neuromorphic engineering: smaller transistors offer lower power consumption and more neurons per unit area of silicon, but also more variability between transistors and thus between silicon neurons. Utilizing this variability in a neuromorphic model of the auditory brain stem with 1,080 silicon neurons, we found that a low-voltage-activated potassium conductance (g(KL)) enables precise spike timing via two mechanisms: statically reducing the resting membrane time constant and dynamically suppressing late synaptic inputs. The relative contribution of these two mechanisms is unknown because blocking g(KL) in vitro eliminates dynamic adaptation but also lengthens the membrane time constant. We replaced g(KL) with a static leak in silico to recover the short membrane time constant and found that silicon neurons could mimic the spike-time precision of their biological counterparts, but only over a narrow range of stimulus intensities and biophysical parameters. The dynamics of g(KL) were required for precise spike timing robust to stimulus variation across a heterogeneous population of silicon neurons, thus explaining how neural and neuromorphic systems may perform precise operations despite inherent variability.

Effects of manipulating slowpoke calcium-dependent potassium channel expression on rhythmic locomotor activity in Drosophila larvae

Rhythmic motor behaviors are generated by networks of neurons. The sequence and timing of muscle contractions depends on both synaptic connections between neurons and the neurons' intrinsic properties. In particular, motor neuron ion currents may contribute significantly to motor output. Large conductance Ca(2+)-dependent K(+) (BK) currents play a role in action potential repolarization, interspike interval, repetitive and burst firing, burst termination and interburst interval in neurons. Mutations in slowpoke (slo) genes encoding BK channels result in motor disturbances. This study examined the effects of manipulating slo channel expression on rhythmic motor activity using Drosophila larva as a model system. Dual intracellular recordings from adjacent body wall muscles were made during spontaneous crawling-related activity in larvae expressing a slo mutation or a slo RNA interference construct. The incidence and duration of rhythmic activity in slo mutants were similar to wild-type control animals, while the timing of the motor pattern was altered. slo mutants showed decreased burst durations, cycle durations, and quiescence intervals, and increased duty cycles, relative to wild-type. Expressing slo RNAi in identified motor neurons phenocopied many of the effects observed in the mutant, including decreases in quiescence interval and cycle duration. Overall, these results show that altering slo expression in the whole larva, and specifically in motor neurons, changes the frequency of crawling activity. These results suggest an important role for motor neuron intrinsic properties in shaping the timing of motor output.

Lack of transient receptor potential vanilloid 1 channel modulates the development of neurogenic bladder dysfunction induced by cross-sensitization in afferent pathways

Background

Bladder pain of unknown etiology has been associated with co-morbid conditions and functional abnormalities in neighboring pelvic organs. Mechanisms underlying pain co-morbidities include cross-sensitization, which occurs predominantly via convergent neural pathways connecting distinct pelvic organs. Our previous results showed that colonic inflammation caused detrusor instability via activation of transient receptor potential vanilloid 1 (TRPV1) signaling pathways, therefore, we aimed to determine whether neurogenic bladder dysfunction can develop in the absence of TRPV1 receptors.

Methods

Adult male C57BL/6 wild-type (WT) and TRPV1^−/− (knockout) mice were used in this study. Colonic inflammation was induced by intracolonic trinitrobenzene sulfonic acid (TNBS). The effects of transient colitis on abdominal sensitivity and function of the urinary bladder were evaluated by cystometry, contractility and relaxation of detrusor smooth muscle (DSM) in vitro to various stimuli, gene and protein expression of voltage-gated sodium channels in bladder sensory neurons, and pelvic responses to mechanical stimulation.

Results

Knockout of TRPV1 gene did not eliminate the development of cross-sensitization between the colon and urinary bladder. However, TRPV1^−/− mice had prolonged intermicturition interval and increased number of non-voiding contractions at baseline followed by reduced urodynamic responses during active colitis. Contractility of DSM was up-regulated in response to KCl in TRPV1^−/− mice with inflamed colon. Application of Rho-kinase inhibitor caused relaxation of DSM in WT but not in TRPV1^−/− mice during colonic inflammation. TRPV1^−/− mice demonstrated blunted effects of TNBS-induced colitis on expression and function of voltage-gated sodium channels in bladder sensory neurons, and delayed development of abdominal hypersensitivity upon colon-bladder cross-talk in genetically modified animals.

Conclusions

The lack of TRPV1 receptors does not eliminate the development of cross-sensitization in the pelvis. However, the function of the urinary bladder significantly differs between WT and TRPV^−/− mice especially upon development of colon-bladder cross-sensitization induced by transient colitis. Our results suggest that TRPV1 pathways may participate in the development of chronic pelvic pain co-morbidities in humans.

Ionic current correlations underlie the global tuning of large numbers of neuronal activity attributes

Ionic conductances in identified neurons are highly variable. This poses the crucial question of how such neurons can produce stable activity. Coexpression of ionic currents has been observed in an increasing number of neurons in different systems, suggesting that the coregulation of ionic channel expression, by thus linking their variability, may enable neurons to maintain relatively constant neuronal activity as suggested by a number of recent theoretical studies. We examine this hypothesis experimentally using the voltage- and dynamic-clamp techniques to first measure and then modify the ionic conductance levels of three currents in identified neurons of the crab pyloric network. We quantify activity by measuring 10 different attributes (oscillation period, spiking frequency, etc.), and find linear, positive and negative relationships between conductance pairs and triplets that can enable pyloric neurons to maintain activity attributes invariant. Consistent with experimental observations, some of the features most tightly regulated appear to be phase relationships of bursting activity. We conclude that covariation (and probably a tightly controlled coregulation) of ionic conductances can help neurons maintain certain attributes of neuronal activity invariant while at the same time allowing conductances to change over wide ranges in response to internal or environmental inputs and perturbations. Our results also show that neurons can tune neuronal activity globally via coordinate expression of ion currents.

Functional maps within a single neuron

The presence and plasticity of dendritic ion channels are well established. However, the literature is divided on what specific roles these dendritic ion channels play in neuronal information processing, and there is no consensus on why neuronal dendrites should express diverse ion channels with different expression profiles. In this review, we present a case for viewing dendritic information processing through the lens of the sensory map literature, where functional gradients within neurons are considered as maps on the neuronal topograph. Under such a framework, drawing analogies from the sensory map literature, we postulate that the formation of intraneuronal functional maps is driven by the twin objectives of efficiently encoding inputs that impinge along different dendritic locations and of retaining homeostasis in the face of changes that are required in the coding process. In arriving at this postulate, we relate intraneuronal map physiology to the vast literature on sensory maps and argue that such a metaphorical association provides a fresh conceptual framework for analyzing and understanding single-neuron information encoding. We also describe instances where the metaphor presents specific directions for research on intraneuronal maps, derived from analogous pursuits in the sensory map literature. We suggest that this perspective offers a thesis for why neurons should express and alter ion channels in their dendrites and provides a framework under which active dendrites could be related to neural coding, learning theory, and homeostasis.

Rapid homeostatic plasticity of intrinsic excitability in a central pattern generator network stabilizes functional neural network output

Neurons and networks undergo a process of homeostatic plasticity that stabilizes output by integrating activity levels with network and cellular properties to counter longer-term perturbations. Here we describe a rapid compensatory interaction among a pair of potassium currents, I(A) and I(KCa), that stabilizes both intrinsic excitability and network function in the cardiac ganglion of the crab, Cancer borealis. We determined that mRNA levels in single identified neurons for the channels which encode I(A) and I(KCa) are positively correlated, yet the ionic currents themselves are negatively correlated, across a population of motor neurons. We then determined that these currents are functionally coupled; decreasing levels of either current within a neuron causes a rapid increase in the other. This functional interdependence results in homeostatic stabilization of both the individual neuronal and the network output. Furthermore, these compensatory increases are mechanistically independent, suggesting robustness in the maintenance of neural network output that is critical for survival. Together, we generate a complete model for homeostatic plasticity from mRNA to network output where rapid post-translational compensatory mechanisms acting on a reservoir of channels proteins regulated at the level of gene expression provide homeostatic stabilization of both cellular and network activity.

Targeted deletion of Kcne2 impairs HCN channel function in mouse thalamocortical circuits

BACKGROUND

Hyperpolarization-activated, cyclic nucleotide-gated (HCN) channels generate the pacemaking current, I(h), which regulates neuronal excitability, burst firing activity, rhythmogenesis, and synaptic integration. The physiological consequence of HCN activation depends on regulation of channel gating by endogenous modulators and stabilization of the channel complex formed by principal and ancillary subunits. KCNE2 is a voltage-gated potassium channel ancillary subunit that also regulates heterologously expressed HCN channels; whether KCNE2 regulates neuronal HCN channel function is unknown.

METHODOLOGY/PRINCIPAL FINDINGS

We investigated the effects of Kcne2 gene deletion on I(h) properties and excitability in ventrobasal (VB) and cortical layer 6 pyramidal neurons using brain slices prepared from Kcne2(+/+) and Kcne2(-/-) mice. Kcne2 deletion shifted the voltage-dependence of I(h) activation to more hyperpolarized potentials, slowed gating kinetics, and decreased I(h) density. Kcne2 deletion was associated with a reduction in whole-brain expression of both HCN1 and HCN2 (but not HCN4), although co-immunoprecipitation from whole-brain lysates failed to detect interaction of KCNE2 with HCN1 or 2. Kcne2 deletion also increased input resistance and temporal summation of subthreshold voltage responses; this increased intrinsic excitability enhanced burst firing in response to 4-aminopyridine. Burst duration increased in corticothalamic, but not thalamocortical, neurons, suggesting enhanced cortical excitatory input to the thalamus; such augmented excitability did not result from changes in glutamate release machinery since miniature EPSC frequency was unaltered in Kcne2(-/-) neurons.

CONCLUSIONS/SIGNIFICANCE

Loss of KCNE2 leads to downregulation of HCN channel function associated with increased excitability in neurons in the cortico-thalamo-cortical loop. Such findings further our understanding of the normal physiology of brain circuitry critically involved in cognition and have implications for our understanding of various disorders of consciousness.

Combined application of brain-derived neurotrophic factor and neurotrophin-3 and its impact on spiral ganglion neuron firing properties and hyperpolarization-activated currents

Neurotrophins provide an effective tool for the rescue and regeneration of spiral ganglion neurons (SGNs) following sensorineural hearing loss. However, these nerve growth factors are also potent modulators of ion channel activity and expression, and in the peripheral auditory system brain-derived neurotrophic factor (BDNF) and neurotrophin-3 (NT3) have previously been shown to alter the firing properties of auditory neurons and differentially regulate the expression of some potassium channels in vitro. In this study we examined the activity of the hyperpolarization-mediated mixed-cation current (I(h)) in early post-natal cultured rat SGNs following exposure to combined BDNF and NT3. Whole-cell patch-clamp recordings made after 1 or 2 days in vitro revealed no change in the firing adaptation of neurons in the presence of BDNF and NT3. Resting membrane potentials were also maintained, but spike latency and firing threshold was subject to regulation by both neurotrophins and time in vitro. Current clamp recordings revealed an activity profile consistent with activation of the hyperpolarization-activated current. Rapid membrane hyperpolarization was followed by a voltage- and time-dependent depolarizing voltage sag. In voltage clamp, membrane hyperpolarization evoked a slowly-activating inward current that was reversibly blocked with cesium and inhibited by ZD7288. The amplitude and current density of I(h) was significantly larger in BDNF and NT3 supplemented cultures, but this did not translate to a significant alteration in voltage sag magnitude. Neurotrophins provided at 50 ng/ml produced a hyperpolarizing shift in the voltage-dependence and slower time course of I(h) activation compared to SGNs in control groups or cultured with 10 ng/ml BDNF and NT3. Our results indicate that combined BDNF and NT3 increase the activity of hyperpolarization-activated currents and that the voltage-dependence and activation kinetics of I(h) in SGNs are sensitive to changes in neurotrophin concentration. In addition, BDNF and NT3 applied together induce a decrease in firing threshold, but does not generate a shift in firing adaptation.

Adult mouse basal forebrain harbors two distinct cholinergic populations defined by their electrophysiology

We performed whole-cell recordings from basal forebrain (BF) cholinergic neurons in transgenic mice expressing enhanced green fluorescent protein (eGFP) under the control of the choline acetyltransferase promoter. BF cholinergic neurons can be differentiated into two electrophysiologically identifiable subtypes: early and late firing neurons. Early firing neurons (∼70%) are more excitable, show prominent spike frequency adaptation and are more susceptible to depolarization blockade, a phenomenon characterized by complete silencing of the neuron following initial action potentials. Late firing neurons (∼30%), albeit being less excitable, could maintain a tonic discharge at low frequencies. In voltage clamp analysis, we have shown that early firing neurons have a higher density of low voltage activated (LVA) calcium currents. These two cholinergic cell populations might be involved in distinct functions: the early firing group being more suitable for phasic changes in cortical acetylcholine release associated with attention while the late firing neurons could support general arousal by maintaining tonic acetylcholine levels.

Learning Invariance from Natural Images Inspired by Observations in the Primary Visual Cortex

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.

Exploiting mathematical models to illuminate electrophysiological variability between individuals

Across individuals within a population, several levels of variability are observed, from the differential expression of ion channels at the molecular level, to the various action potential morphologies observed at the cellular level, to divergent responses to drugs at the organismal level. However, the limited ability of experiments to probe complex interactions between components has hitherto hindered our understanding of the factors that cause a range of behaviours within a population. Variability is a challenging issue that is encountered in all physiological disciplines, but recent work suggests that novel methods for analysing mathematical models can assist in illuminating its causes. In this review, we discuss mathematical modelling studies in cardiac electrophysiology and neuroscience that have enhanced our understanding of variability in a number of key areas. Specifically, we discuss parameter sensitivity analysis techniques that may be applied to generate quantitative predictions based on considering behaviours within a population of models, thereby providing novel insight into variability. Our discussion focuses on four issues that have benefited from the utilization of these methods: (1) the comparison of different electrophysiological models of cardiac myocytes, (2) the determination of the individual contributions of different molecular changes in complex disease phenotypes, (3) the identification of the factors responsible for the variable response to drugs, and (4) the constraining of free parameters in electrophysiological models of heart cells. Together, the studies that we discuss suggest that rigorous analyses of mathematical models can generate quantitative predictions regarding how molecular-level variations contribute to functional differences between experimental samples. These strategies may be applicable not just in cardiac electrophysiology, but in a wide range of disciplines.

Ca²⁺/cAMP-sensitive covariation of I(A) and I(H) voltage dependences tunes rebound firing in dopaminergic neurons

The level of expression of ion channels has been demonstrated to vary over a threefold to fourfold range from neuron to neuron, although the expression of distinct channels may be strongly correlated in the same neurons. We demonstrate that variability and covariation also apply to the biophysical properties of ion channels. We show that, in rat substantia nigra pars compacta dopaminergic neurons, the voltage dependences of the A-type (I(A)) and H-type (I(H)) currents exhibit a high degree of cell-to-cell variability, although they are strongly correlated in these cells. Our data also demonstrate that this cell-to-cell covariability of voltage dependences is sensitive to cytosolic cAMP and calcium levels. Finally, using dynamic clamp, we demonstrate that covarying I(A) and I(H) voltage dependences increases the dynamic range of rebound firing while covarying their amplitudes has a homeostatic effect on rebound firing. We propose that the covariation of voltage dependences of ion channels represents a flexible and energy-efficient way of tuning firing in neurons.

Sodium channels, the electrogenisome and the electrogenistat: lessons and questions from the clinic

In the six decades that have followed the work of Hodgkin and Huxley, multiple generations of neuroscientists and biophysicists have built upon their pivotal contributions. It is now clear that, in mammals, nine genes encode nine distinct voltage-gated sodium channels with different amino acid sequences and different physiological and pharmacological properties. The different sodium channel isoforms produce a multiplicity of distinct sodium currents with different time-dependent characteristics and voltage dependencies, which interact with each other and with the currents produced by other channels (including calcium and potassium channels) to shape neuronal firing patterns. Expression of these sodium channel isoforms is highly dynamic, both in the normal nervous system, and in the injured nervous system. Recent research has shed light on the roles of sodium channels in human disease, a development that may open up new therapeutic strategies. This article examines the pain-signalling system as an example of a neuronal network where multiple sodium channel isoforms play complementary roles in electrogenesis and a strong link with human disease has been established. Recent research suggests that it may be possible to target specific sodium channel isoforms that drive hyperexcitability in pain-signalling neurons, thereby providing new therapeutic strategies for chronic pain, and providing an illustration of the impact of the Hodgkin-Huxley legacy in the clinical domain.

Diverse levels of an inwardly rectifying potassium conductance generate heterogeneous neuronal behavior in a population of dorsal cochlear nucleus pyramidal neurons

Homeostatic mechanisms maintain homogeneous neuronal behavior among neurons that exhibit substantial variability in the expression levels of their ionic conductances. In contrast, the mechanisms, which generate heterogeneous neuronal behavior across a neuronal population, remain poorly understood. We addressed this problem in the dorsal cochlear nucleus, where principal neurons exist in two qualitatively distinct states: spontaneously active or not spontaneously active. Our studies reveal that distinct activity states are generated by the differential levels of a Ba(2+)-sensitive, inwardly rectifying potassium conductance (K(ir)). Variability in K(ir) maximal conductance causes variations in the resting membrane potential (RMP). Low K(ir) conductance depolarizes RMP to voltages above the threshold for activating subthreshold-persistent sodium channels (Na(p)). Once Na(p) channels are activated, the RMP becomes unstable, and spontaneous firing is triggered. Our results provide a biophysical mechanism for generating neural heterogeneity, which may play a role in the encoding of sensory information.

Correlated variations in the parameters that regulate dendritic calcium signaling in mouse retinal ganglion cells

The amplitude and time course of stimulus-evoked second messenger signals carried by intracellular changes in free calcium ([Ca](free)) depend on the total influx of Ca(2+), the fraction bound to endogenous buffer and the rate of extrusion. Estimates of the values of these three parameters in proximal dendrites of 15 mouse α retinal ganglion cells were made using the "added buffer" method and found to vary greatly from one experiment to the next. The variations in the measured parameters were strongly correlated across the sample of cells. This reduced the variability in the amplitude and time course of the dendritic Ca(2+) signal and suggests that the expression of Ca(2+) channels, binding proteins and extrusion mechanisms is homeostatically coordinated to maintain the amplitude and kinetics of the Ca(2+) signal within a physiologically appropriate range.

Contribution of EAG to excitability and potassium currents in Drosophila larval motoneurons

Diversity in the expression of K(+) channels among neurons allows a wide range of excitability, growth, and functional regulation. Ether-à-go-go (EAG), a voltage-gated K(+) channel, was first characterized in Drosophila mutants by spontaneous firing in nerve terminals and enhanced neurotransmitter release. Although diverse functions have been ascribed to this protein, its role within neurons remains poorly understood. The aim of this study was to characterize the function of EAG in situ in Drosophila larval motoneurons. Whole cell patch-clamp recordings performed from the somata revealed a decrease in I(Av) and I(Kv) K(+) currents in eag mutants and with targeted eag RNAi expression. Spontaneous spike-like events were observed in eag mutants but absent in wild-type motoneurons. Thus our results provide evidence that EAG represents a unique K(+) channel contributing to multiple K(+) currents in motoneurons helping to regulate excitability, consistent with previous observations in the Drosophila larval muscle.

Cocaine sensitization inhibits the hyperpolarization-activated cation current Ih and reduces cell size in dopamine neurons of the ventral tegmental area

The progressive augmentation of motor activity that results from repeated cocaine administration is termed behavioral sensitization. This phenomenon is thought to be a critical component in compulsive drug taking and relapse. Still, the cellular mechanisms that underlie sensitization remain elusive. Cocaine abuse, nonetheless, is known to evoke neuroplastic adaptations in dopamine (DA) neurotransmission originating from the midbrain's ventral tegmental area (VTA). Here, we report that concomitant with the development of locomotor sensitization to cocaine the hyperpolarization-activated cation current (I(h)) amplitude is depressed by ∼40% in VTA DA cells. Such effect did not result from a negative shift in I(h) voltage dependence. Nonstationary fluctuation analysis indicates that this inhibition was caused by an ∼45% reduction in the number of h-channels with no change in their unitary properties. The cocaine-induced I(h) depression was accompanied by a reduction in cell capacitance of similar magnitude (∼33%), leaving h-current density unaltered. Two implications follow from these data. First, I(h) inhibition may contribute to cocaine addiction by increasing bursting probability in DA cells and this effect could be intensified by the decrease in cell capacitance. Second, the cocaine-induced diminution of DA cell capacitance may also lead to reward tolerance promoting drug-seeking behaviors.

Co-variation of ionic conductances supports phase maintenance in stomatogastric neurons

Neuronal networks produce reliable functional output throughout the lifespan of an animal despite ceaseless molecular turnover and a constantly changing environment. Central pattern generators, such as those of the crustacean stomatogastric ganglion (STG), are able to robustly maintain their functionality over a wide range of burst periods. Previous experimental work involving extracellular recordings of the pyloric pattern of the STG has demonstrated that as the burst period varies, the inter-neuronal delays are altered proportionally, resulting in burst phases that are roughly invariant. The question whether spike delays within bursts are also proportional to pyloric period has not been explored in detail. The mechanism by which the pyloric neurons accomplish phase maintenance is currently not obvious. Previous studies suggest that the co-regulation of certain ion channel properties may play a role in governing neuronal activity. Here, we observed in long-term recordings of the pyloric rhythm that spike delays can vary proportionally with burst period, so that spike phase is maintained. We then used a conductance-based model neuron to determine whether co-varying ionic membrane conductances results in neural output that emulates the experimentally observed phenomenon of spike phase maintenance. Next, we utilized a model neuron database to determine whether conductance correlations exist in model neuron populations with highly maintained spike phases. We found that co-varying certain conductances, including the sodium and transient calcium conductance pair, causes the model neuron to maintain a specific spike phase pattern. Results indicate a possible relationship between conductance co-regulation and phase maintenance in STG neurons.

Neuromodulation independently determines correlated channel expression and conductance levels in motor neurons of the stomatogastric ganglion

Neuronal identity depends on the regulated expression of numerous molecular components, especially ionic channels, which determine the electrical signature of a neuron. Such regulation depends on at least two key factors, activity itself and neuromodulatory input. Neuronal electrical activity can modify the expression of ionic currents in homeostatic or nonhomeostatic fashion. Neuromodulators typically modify activity by regulating the properties or expression levels of subsets of ionic channels. In the stomatogastric system of crustaceans, both types of regulation have been demonstrated. Furthermore, the regulation of the coordinated expression of ionic currents and the channels that carry these currents has been recently reported in diverse neuronal systems, with neuromodulators not only controlling the absolute levels of ionic current expression but also, over long periods of time, appearing to modify their correlated expression. We hypothesize that neuromodulators may regulate the correlated expression of ion channels at multiple levels and in a cell-type-dependent fashion. We report that in two identified neuronal types, three ionic currents are linearly correlated in a pairwise manner, suggesting their coexpression or direct interactions, under normal neuromodulatory conditions. In each cell, some currents remain correlated after neuromodulatory input is removed, whereas the correlations between the other pairs are either lost or altered. Interestingly, in each cell, a different suite of currents change their correlation. At the transcript level we observe distinct alterations in correlations between channel mRNA amounts, including one of the cell types lacking a correlation under normal neuromodulatory conditions and then gaining the correlation when neuromodulators are removed. Synaptic activity does not appear to contribute, with one possible exception, to the correlated expression of either ionic currents or of the transcripts that code for the respective channels. We conclude that neuromodulators regulate the correlated expression of ion channels at both the transcript and the protein levels.

Drosophila QVR/SSS modulates the activation and C-type inactivation kinetics of Shaker K(+) channels

The quiver/sleepless (qvr/sss) gene encodes a small, glycosylphosphatidylinositol-anchored protein that plays a critical role in the regulation of sleep in Drosophila. Loss-of-function mutations in qvr/sss severely suppress sleep and effect multiple changes in in situ Shaker K(+) currents, including decreased magnitude, slower time-to-peak, and cumulative inactivation. Recently, we demonstrated that SLEEPLESS (SSS) protein modulates Shaker channel activity, possibly through a direct interaction at the plasma membrane. We show here that SSS accelerates the activation of heterologously expressed Shaker channels with no effect on deactivation or fast N-type inactivation. Furthermore, this SSS-induced acceleration is sensitive to the pharmacological disruption of lipid rafts and sufficiently accounts for the slower time-to-peak of in situ Shaker currents seen in qvr/sss mutants. We also find that SSS decreases the rate of C-type inactivation of heterologously expressed Shaker channels, providing a potential mechanism for the cumulative inactivation phenotype induced by qvr/sss loss-of-function mutations. Kinetic modeling based on the in vitro results suggests that the SSS-dependent regulation of channel kinetics accounts for nearly 40% of the decrease in Shaker current magnitude in flies lacking SSS. Sleep duration in qvr/sss-null mutants is restored to normal by a qvr/sss transgene that fully rescues the Shaker kinetic phenotypes but only partially rescues the decrease in current magnitude. Together, these results suggest that the role of SSS in the regulation of sleep in Drosophila correlates more strongly with the effects of SSS on Shaker kinetics than current magnitude.

Network reconfiguration and neuronal plasticity in rhythm-generating networks

Neuronal networks are highly plastic and reconfigure in a state-dependent manner. The plasticity at the network level emerges through multiple intrinsic and synaptic membrane properties that imbue neurons and their interactions with numerous nonlinear properties. These properties are continuously regulated by neuromodulators and homeostatic mechanisms that are critical to maintain not only network stability and also adapt networks in a short- and long-term manner to changes in behavioral, developmental, metabolic, and environmental conditions. This review provides concrete examples from neuronal networks in invertebrates and vertebrates, and illustrates that the concepts and rules that govern neuronal networks and behaviors are universal.

Neuronal homeostasis: time for a change?

Homeostatic processes that regulate electrical activity in neurones are now an established aspect of physiology and rest on a large body of experimental evidence that points to roles in development, learning and memory, and disease. However, the concepts underlying homeostasis are too often summarized in ways that restrict their explanatory power and obviate important subtleties. Here, we present a review of the underlying theory of homeostasis--control theory--in an attempt to reconcile some existing conceptual problems in the context of neuronal physiology. In addition to clarifying the underlying theory, this review highlights the remaining challenges posed when analysing homeostatic phenomena that underlie the regulation of neuronal excitability. Moreover, we suggest approaches for future experimental and computational work that will further our understanding of neuronal homeostasis and the fundamental neurophysiological functions it serves.

Localization and function of Ih channels in a small neural network

Subthreshold ionic currents, which activate below the firing threshold and shape the cell's firing properties, play important roles in shaping neural network activity. We examined the distribution and synaptic roles of the hyperpolarization-activated inward current (I(h)) in the pyloric network of the lobster stomatogastric ganglion (STG). I(h) channels are expressed throughout the STG in a patchy distribution and are highly expressed in the fine neuropil, an area that is rich in synaptic contacts. We performed double labeling for I(h) protein and for the presynaptic marker synaptotagmin. The large majority of labeling in the fine neuropil was adjacent but nonoverlapping, suggesting that I(h) is localized in close proximity to synapses but not in the presynaptic terminals. We compared the pattern of I(h) localization with Shal transient potassium channels, whose expression is coregulated with I(h) in many STG neurons. Unlike I(h), we found significant levels of Shal protein in the soma membrane and the primary neurite. Both proteins were found in the synaptic fine neuropil, but with little evidence of colocalization in individual neurites. We performed electrophysiological experiments to study a potential role for I(h) in regulating synaptic transmission. At a synapse between two identified pyloric neurons, the amplitude of inhibitory postsynaptic potentials (IPSPs) decreased with increasing postsynaptic activation of I(h). Pharmacological block of I(h) restored IPSP amplitudes to levels seen when I(h) was not activated. These experiments suggest that modulation of postsynaptic I(h) might play an important role in the control of synaptic strength in this rhythmogenic neural network.

Neuromodulation and flexibility in Central Pattern Generator networks

Central Pattern Generator (CPG) networks, which organize rhythmic movements, have long served as models for neural network organization. Modulatory inputs are essential components of CPG function: neuromodulators set the parameters of CPG neurons and synapses to render the networks functional. Each modulator acts on the network by many effects which may oppose one another; this may serve to stabilize the modulated state. Neuromodulators also determine the active neuronal composition in the CPG, which varies with state changes such as locomotor speed. The pattern of gene expression which determines the electrophysiological personality of each CPG neuron is also under modulatory control. It is not possible to model the function of neural networks without including the actions of neuromodulators.

Multiple models to capture the variability in biological neurons and networks

How tightly tuned are the synaptic and intrinsic properties that give rise to neuron and circuit function? Experimental work shows that these properties vary considerably across identified neurons in different animals. Given this variability in experimental data, this review describes some of the complications of building computational models to aid in understanding how system dynamics arise from the interaction of system components. We argue that instead of trying to build a single model that captures the generic behavior of a neuron or circuit, it is beneficial to construct a population of models that captures the behavior of the population that provided the experimental data. Studying a population of models with different underlying structure and similar behaviors provides opportunities to discover unsuspected compensatory mechanisms that contribute to neuron and network function.

Variability, compensation, and modulation in neurons and circuits

I summarize recent computational and experimental work that addresses the inherent variability in the synaptic and intrinsic conductances in normal healthy brains and shows that multiple solutions (sets of parameters) can produce similar circuit performance. I then discuss a number of issues raised by this observation, such as which parameter variations arise from compensatory mechanisms and which reflect insensitivity to those particular parameters. I ask whether networks with different sets of underlying parameters can nonetheless respond reliably to neuromodulation and other global perturbations. At the computational level, I describe a paradigm shift in which it is becoming increasingly common to develop families of models that reflect the variance in the biological data that the models are intended to illuminate rather than single, highly tuned models. On the experimental side, I discuss the inherent limitations of overreliance on mean data and suggest that it is important to look for compensations and correlations among as many system parameters as possible, and between each system parameter and circuit performance. This second paradigm shift will require moving away from measurements of each system component in isolation but should reveal important previously undescribed principles in the organization of complex systems such as brains.

Identifiable cells in the crustacean stomatogastric ganglion

Neural circuits rely on slight physiological differences between the component cells for proper function. When any circuit is analyzed, it is important to characterize the features that distinguish one cell type from another. This review describes the methods used to identify the neurons of the crustacean stomatogastric ganglion.

Shal/K(v)4 channels are required for maintaining excitability during repetitive firing and normal locomotion in Drosophila

BACKGROUND

Rhythmic behaviors, such as walking and breathing, involve the coordinated activity of central pattern generators in the CNS, sensory feedback from the PNS, to motoneuron output to muscles. Unraveling the intrinsic electrical properties of these cellular components is essential to understanding this coordinated activity. Here, we examine the significance of the transient A-type K(+) current (I(A)), encoded by the highly conserved Shal/K(v)4 gene, in neuronal firing patterns and repetitive behaviors. While I(A) is present in nearly all neurons across species, elimination of I(A) has been complicated in mammals because of multiple genes underlying I(A), and/or electrical remodeling that occurs in response to affecting one gene.

METHODOLOGY/PRINCIPAL FINDINGS

In Drosophila, the single Shal/K(v)4 gene encodes the predominant I(A) current in many neuronal cell bodies. Using a transgenically expressed dominant-negative subunit (DNK(v)4), we show that I(A) is completely eliminated from cell bodies, with no effect on other currents. Most notably, DNK(v)4 neurons display multiple defects during prolonged stimuli. DNK(v)4 neurons display shortened latency to firing, a lower threshold for repetitive firing, and a progressive decrement in AP amplitude to an adapted state. We record from identified motoneurons and show that Shal/K(v)4 channels are similarly required for maintaining excitability during repetitive firing. We then examine larval crawling, and adult climbing and grooming, all behaviors that rely on repetitive firing. We show that all are defective in the absence of Shal/K(v)4 function. Further, knock-out of Shal/K(v)4 function specifically in motoneurons significantly affects the locomotion behaviors tested.

CONCLUSIONS/SIGNIFICANCE

Based on our results, Shal/K(v)4 channels regulate the initiation of firing, enable neurons to continuously fire throughout a prolonged stimulus, and also influence firing frequency. This study shows that Shal/K(v)4 channels play a key role in repetitively firing neurons during prolonged input/output, and suggests that their function and regulation are important for rhythmic behaviors.

Interdependent roles for accessory KChIP2, KChIP3, and KChIP4 subunits in the generation of Kv4-encoded IA channels in cortical pyramidal neurons

The rapidly activating and inactivating voltage-dependent outward K(+) (Kv) current, I(A), is widely expressed in central and peripheral neurons. I(A) has long been recognized to play important roles in determining neuronal firing properties and regulating neuronal excitability. Previous work demonstrated that Kv4.2 and Kv4.3 α-subunits are the primary determinants of I(A) in mouse cortical pyramidal neurons. Accumulating evidence indicates that native neuronal Kv4 channels function in macromolecular protein complexes that contain accessory subunits and other regulatory molecules. The K(+) channel interacting proteins (KChIPs) are among the identified Kv4 channel accessory subunits and are thought to be important for the formation and functioning of neuronal Kv4 channel complexes. Molecular genetic, biochemical, and electrophysiological approaches were exploited in the experiments described here to examine directly the roles of KChIPs in the generation of functional Kv4-encoded I(A) channels. These combined experiments revealed that KChIP2, KChIP3, and KChIP4 are robustly expressed in adult mouse posterior (visual) cortex and that all three proteins coimmunoprecipitate with Kv4.2. In addition, in cortical pyramidal neurons from mice lacking KChIP3 (KChIP3(-/-)), mean I(A) densities were reduced modestly, whereas in mean I(A) densities in KChIP2(-/-) and WT neurons were not significantly different. Interestingly, in both KChIP3(-/-) and KChIP2(-/-) cortices, the expression levels of the other KChIPs (KChIP2 and 4 or KChIP3 and 4, respectively) were increased. In neurons expressing constructs to mediate simultaneous RNA interference-induced reductions in the expression of KChIP2, 3, and 4, I(A) densities were markedly reduced and Kv current remodeling was evident.

The membrane potential waveform of bursting pacemaker neurons is a predictor of their preferred frequency and the network cycle frequency

Many oscillatory networks involve neurons that exhibit intrinsic rhythmicity but possess a large variety of voltage-gated currents that interact in a complex fashion, making it difficult to determine which factors control frequency. Yet these neurons often have preferred (resonance) frequencies that can be close to the network frequency. Because the preferred frequency results from the dynamics of ionic currents, it can be assumed to depend on parameters that determine the neuron's oscillatory waveform shape. The pyloric network frequency in the crab Cancer borealis is correlated with the preferred frequency of its bursting pacemaker neurons anterior burster and pyloric dilator (PD). We measured the preferred frequency of the PD neuron in voltage clamp, which allows control of the oscillation voltage range and waveforms (sine waves and realistic oscillation waveforms), and showed that (1) the preferred frequency depends on the voltage range of the oscillating voltage waveform; (2) the slope of the waveform near its peak has a strongly negative correlation with the preferred frequency; and (3) correlations between parameters of the PD neuron oscillation waveform and its preferred frequency can be used to predict shifts in the network frequency. As predicted by these results, dynamic clamp shifts of the upper or lower voltage limits of the PD neuron waveform during ongoing oscillations changed the network frequency, consistent with the predictions from the preferred frequency. These results show that the voltage waveform of oscillatory neurons can be predictive of their preferred frequency and thus the network oscillation frequency.

Compensation for variable intrinsic neuronal excitability by circuit-synaptic interactions

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.