Ionic mechanism underlying recovery of rhythmic activity in adult isolated neurons

Daily oscillations of neuronal membrane capacitance

Capacitance of biological membranes is determined by the properties of the lipid portion of the membrane as well as the morphological features of a cell. In neurons, membrane capacitance is a determining factor of synaptic integration, action potential propagation speed, and firing frequency due to its direct effect on the membrane time constant. Besides slow changes associated with increased morphological complexity during postnatal maturation, neuronal membrane capacitance is considered a stable, non-regulated, and constant magnitude. Here we report that, in two excitatory neuronal cell types, pyramidal cells of the mouse primary visual cortex and granule cells of the hippocampus, the membrane capacitance significantly changes between the start and the end of a daily light-dark cycle. The changes are large, nearly 2-fold in magnitude in pyramidal cells, but are not observed in cortical parvalbumin-expressing inhibitory interneurons. Consistent with daily capacitance fluctuations, the time window for synaptic integration also changes in pyramidal cells.

Frequency-Dependent Action of Neuromodulation

In oscillatory circuits, some actions of neuromodulators depend on the oscillation frequency. However, the mechanisms are poorly understood. We explored this problem by characterizing neuromodulation of the lateral pyloric (LP) neuron of the crab stomatogastric ganglion (STG). Many peptide modulators, including proctolin, activate the same ionic current (I_MI) in STG neurons. Because I_MI is fast and non-inactivating, its peak level does not depend on the temporal properties of neuronal activity. We found, however, that the amplitude and peak time of the proctolin-activated current in LP is frequency dependent. Because frequency affects the rate of voltage change, we measured these currents with voltage ramps of different slopes and found that proctolin activated two kinetically distinct ionic currents: the known I_MI, whose amplitude is independent of ramp slope or direction, and an inactivating current (I_MI-T), which was only activated by positive ramps and whose amplitude increased with increasing ramp slope. Using a conductance-based model we found that I_MI and I_MI-T make distinct contributions to the bursting activity, with I_MI increasing the excitability, and I_MI-T regulating the burst onset by modifying the postinhibitory rebound in a frequency-dependent manner. The voltage dependence and partial calcium permeability of I_MI-T is similar to other characterized neuromodulator-activated currents in this system, suggesting that these are isoforms of the same channel. Our computational model suggests that calcium permeability may allow this current to also activate the large calcium-dependent potassium current in LP, providing an additional mechanism to regulate burst termination. These results demonstrate a mechanism for frequency-dependent actions of neuromodulators.

Intrinsic plasticity and birdsong learning

Although information processing and storage in the brain is thought to be primarily orchestrated by synaptic plasticity, other neural mechanisms such as intrinsic plasticity are available. While a number of recent studies have described the plasticity of intrinsic excitability in several types of neurons, the significance of non-synaptic mechanisms in memory and learning remains elusive. After reviewing plasticity of intrinsic excitation in relation to learning and homeostatic mechanisms, we focus on the intrinsic properties of a class of basal-ganglia projecting song system neurons in zebra finch, how these related to each bird's unique learned song, how these properties change over development, and how they are maintained dynamically to rapidly change in response to auditory feedback perturbations. We place these results in the broader theme of learning and changes in intrinsic properties, emphasizing the computational implications of this form of plasticity, which are distinct from synaptic plasticity. The results suggest that exploring reciprocal interactions between intrinsic and network properties will be a fruitful avenue for understanding mechanisms of birdsong learning.

Neuromodulation of central pattern generators and its role in the functional recovery of central pattern generator activity

Neuromodulators play an important role in how the nervous system organizes activity that results in behavior. Disruption of the normal patterns of neuromodulatory release or production is known to be related to the onset of severe pathologies such as Parkinson's disease, Rett syndrome, Alzheimer's disease, and affective disorders. Some of these pathologies involve neuronal structures that are called central pattern generators (CPGs), which are involved in the production of rhythmic activities throughout the nervous system. Here I discuss the interplay between CPGs and neuromodulatory activity, with particular emphasis on the potential role of neuromodulators in the recovery of disrupted neuronal activity. I refer to invertebrate and vertebrate model systems and some of the lessons we have learned from research on these systems and propose a few avenues for future research. I make one suggestion that may guide future research in the field: neuromodulators restrict the parameter landscape in which CPG components operate, and the removal of neuromodulators may enable a perturbed CPG in finding a new set of parameter values that can allow it to regain normal function.

Membrane Voltage Is a Direct Feedback Signal That Influences Correlated Ion Channel Expression in Neurons

The number and type of ion channels present in the membrane determines the electrophysiological function of every neuron. In many species, stereotyped output of neurons often persists for years [1], and ion channel dysregulation can change these properties to cause severe neurological disorders [2-4]. Thus, a fundamental question is how do neurons coordinate channel expression to uphold their firing patterns over long timescales [1, 5]? One major hypothesis purports that neurons homeostatically regulate their ongoing activity through mechanisms that link membrane voltage to expression relationships among ion channels [6-10]. However, experimentally establishing this feedback loop for the control of expression relationships has been a challenge: manipulations that aim to test for voltage feedback invariably disrupt trophic signaling from synaptic transmission and neuromodulation in addition to activity [9, 11, 12]. Further, neuronal activity often relies critically on these chemical mediators, obscuring the contribution of voltage activity of the membrane per se in forming the channel relationships that determine neuronal output [6, 13]. To resolve this, we isolated an identifiable neuron in crustaceans and then either kept this neuron silent or used a long-term voltage clamp protocol to artificially maintain activity. We found that physiological voltage activity-independent of all known forms of synaptic and neuromodulatory feedback-maintains most channel mRNA relationships, while metabotropic influences may play a relatively smaller role. Thus, ion channel relationships likely needed to maintain neuronal identity are actively and continually regulated at least in part at the level of channel mRNAs through feedback by membrane voltage.

Dual separable feedback systems govern firing rate homeostasis

Firing rate homeostasis (FRH) stabilizes neural activity. A pervasive and intuitive theory argues that a single variable, calcium, is detected and stabilized through regulatory feedback. A prediction is that ion channel gene mutations with equivalent effects on neuronal excitability should invoke the same homeostatic response. In agreement, we demonstrate robust FRH following either elimination of Kv4/Shal protein or elimination of the Kv4/Shal conductance. However, the underlying homeostatic signaling mechanisms are distinct. Eliminating Shal protein invokes Krüppel-dependent rebalancing of ion channel gene expression including enhanced slo, Shab, and Shaker. By contrast, expression of these genes remains unchanged in animals harboring a CRISPR-engineered, Shal pore-blocking mutation where compensation is achieved by enhanced IK_DR. These different homeostatic processes have distinct effects on homeostatic synaptic plasticity and animal behavior. We propose that FRH includes mechanisms of proteostatic feedback that act in parallel with activity-driven feedback, with implications for the pathophysiology of human channelopathies.

The Dynamic Basis of Respiratory Rhythm Generation: One Breath at a Time

Rhythmicity is a universal timing mechanism in the brain, and the rhythmogenic mechanisms are generally dynamic. This is illustrated for the neuronal control of breathing, a behavior that occurs as a one-, two-, or three-phase rhythm. Each breath is assembled stochastically, and increasing evidence suggests that each phase can be generated independently by a dedicated excitatory microcircuit. Within each microcircuit, rhythmicity emerges through three entangled mechanisms: ( a) glutamatergic transmission, which is amplified by ( b) intrinsic bursting and opposed by ( c) concurrent inhibition. This rhythmogenic triangle is dynamically tuned by neuromodulators and other network interactions. The ability of coupled oscillators to reconfigure and recombine may allow breathing to remain robust yet plastic enough to conform to nonventilatory behaviors such as vocalization, swallowing, and coughing. Lessons learned from the respiratory network may translate to other highly dynamic and integrated rhythmic systems, if approached one breath at a time.

A postsynaptic PI3K-cII dependent signaling controller for presynaptic homeostatic plasticity

Presynaptic homeostatic plasticity stabilizes information transfer at synaptic connections in organisms ranging from insect to human. By analogy with principles of engineering and control theory, the molecular implementation of PHP is thought to require postsynaptic signaling modules that encode homeostatic sensors, a set point, and a controller that regulates transsynaptic negative feedback. The molecular basis for these postsynaptic, homeostatic signaling elements remains unknown. Here, an electrophysiology-based screen of the Drosophila kinome and phosphatome defines a postsynaptic signaling platform that includes a required function for PI3K-cII, PI3K-cIII and the small GTPase Rab11 during the rapid and sustained expression of PHP. We present evidence that PI3K-cII localizes to Golgi-derived, clathrin-positive vesicles and is necessary to generate an endosomal pool of PI(3)P that recruits Rab11 to recycling endosomal membranes. A morphologically distinct subdivision of this platform concentrates postsynaptically where we propose it functions as a homeostatic controller for retrograde, trans-synaptic signaling.

A balance of outward and linear inward ionic currents is required for generation of slow-wave oscillations

Regenerative inward currents help produce slow oscillations through a negative-slope conductance region of their current-voltage relationship that is well approximated by a linear negative conductance. We used dynamic-clamp injections of a linear current with such conductance, I_NL, to explore why some neurons can generate intrinsic slow oscillations whereas others cannot. We addressed this question in synaptically isolated neurons of the crab Cancer borealis after blocking action potentials. The pyloric network consists of a distinct pacemaker and follower neurons, all of which express the same complement of ionic currents. When the pyloric dilator (PD) neuron, a member of the pacemaker group, was injected with I_NL with dynamic clamp, it consistently produced slow oscillations. In contrast, all follower neurons failed to oscillate with I_NL To understand these distinct behaviors, we compared outward current levels of PD with those of follower lateral pyloric (LP) and ventral pyloric (VD) neurons. We found that LP and VD neurons had significantly larger high-threshold potassium currents (I_HTK) than PD and LP had lower-transient potassium current (I_A). Reducing I_HTK pharmacologically enabled both LP and VD neurons to produce I_NL-induced oscillations, whereas modifying I_A levels did not affect I_NL-induced oscillations. Using phase-plane and bifurcation analysis of a simplified model cell, we demonstrate that large levels of I_HTK can block I_NL-induced oscillatory activity whereas generation of oscillations is almost independent of I_A levels. These results demonstrate the general importance of a balance between inward pacemaking currents and high-threshold K⁺ current levels in determining slow oscillatory activity.NEW & NOTEWORTHY Pacemaker neuron-generated rhythmic activity requires the activation of at least one inward and one outward current. We have previously shown that the inward current can be a linear current (with negative conductance). Using this simple mechanism, here we demonstrate that the inward current conductance must be in relative balance with the outward current conductances to generate oscillatory activity. Surprisingly, an excess of outward conductances completely precludes the possibility of achieving such a balance.

Homeostatic plasticity of excitability in crustacean central pattern generator networks

Plasticity of excitability can come in two general forms: changes in excitability that alter neuronal output (e.g. long-term potentiation of intrinsic excitability) or excitability changes that stabilize neuronal output (homeostatic plasticity). Here we discuss the latter form of plasticity in the context of the crustacean stomatogastric nervous system, and a second central pattern generator circuit, the cardiac ganglion. We discuss this plasticity at three levels: rapid homeostatic changes in membrane conductance, longer-term effects of neuromodulation on excitability, and the impacts of activity-dependent feedback on steady-state channel mRNA levels. We then conclude with thoughts on the implications of plasticity of excitability for variability of conductance levels across populations of motor neurons.

The transient potassium outward current has different roles in modulating the pyloric and gastric mill rhythms in the stomatogastric ganglion

The crustacean stomatogastric nervous system is a classic model for understanding the effects of modulating ionic currents and synapses at both the cell and network levels. The stomatogastric ganglion in this system contains two distinct central pattern generators: a slow gastric mill network that generates flexible rhythmic outputs (8-20 s) and is often silent, and a fast pyloric network that generates more consistent rhythmic outputs (0.5-2 s) and is always active in vitro. Different ionic conductances contribute to the properties of individual neurons and therefore to the overall dynamics of the pyloric and gastric mill networks. However, the contributions of ionic currents to different dynamics between the pyloric and gastric mill networks are not well understood. The goal of this study is to evaluate how changes in outward potassium current (I _A) in the stomatogastric ganglion affect the dynamics of the pyloric and gastric mill rhythms by interfering with normal I _A activity. We bath-applied the specific I _A blocker 4-aminopyridine to reduce I _A's effect in the stomatogastric ganglion in vitro and evaluated quantitatively the changes in both rhythms. We found that blocking I _A in the stomatogastric ganglion alters the synchronization between pyloric neurons, and consistently activates the gastric mill rhythm in quiescent preparations.

Recruitment of Polysynaptic Connections Underlies Functional Recovery of a Neural Circuit after Lesion

The recruitment of additional neurons to neural circuits often occurs in accordance with changing functional demands. Here we found that synaptic recruitment plays a key role in functional recovery after neural injury. Disconnection of a brain commissure in the nudibranch mollusc, Tritonia diomedea, impairs swimming behavior by eliminating particular synapses in the central pattern generator (CPG) underlying the rhythmic swim motor pattern. However, the CPG functionally recovers within a day after the lesion. The strength of a spared inhibitory synapse within the CPG from Cerebral Neuron 2 (C2) to Ventral Swim Interneuron B (VSI) determines the level of impairment caused by the lesion, which varies among individuals. In addition to this direct synaptic connection, there are polysynaptic connections from C2 and Dorsal Swim Interneurons to VSI that provide indirect excitatory drive but play only minor roles under normal conditions. After disconnecting the pedal commissure (Pedal Nerve 6), the recruitment of polysynaptic excitation became a major source of the excitatory drive to VSI. Moreover, the amount of polysynaptic recruitment, which changed over time, differed among individuals and correlated with the degree of recovery of the swim motor pattern. Thus, functional recovery was mediated by an increase in the magnitude of polysynaptic excitatory drive, compensating for the loss of direct excitation. Since the degree of susceptibility to injury corresponds to existing individual variation in the C2 to VSI synapse, the recovery relied upon the extent to which the network reorganized to incorporate additional synapses.

Dynamic compensation mechanism gives rise to period and duty-cycle level sets in oscillatory neuronal models

Rhythmic oscillation in neurons can be characterized by various attributes, such as the oscillation period and duty cycle. The values of these features depend on the amplitudes of the participating ionic currents, which can be characterized by their maximum conductance values. Recent experimental and theoretical work has shown that the values of these attributes can be maintained constant for different combinations of two or more ionic currents of varying conductances, defining what is known as level sets in conductance space. In two-dimensional conductance spaces, a level set is a curve, often a line, along which a particular oscillation attribute value is conserved. In this work, we use modeling, dynamical systems tools (phase-space analysis), and numerical simulations to investigate the possible dynamic mechanisms responsible for the generation of period and duty-cycle levels sets in simplified (linearized and FitzHugh-Nagumo) and conductance-based (Morris-Lecar) models of neuronal oscillations. A simplistic hypothesis would be that the tonic balance between ionic currents with the same or opposite effective signs is sufficient to create level sets. According to this hypothesis, the dynamics of each ionic current during a given cycle are well captured by some constant quantity (e.g., maximal conductances), and the phase-plane diagrams are identical or are almost identical (e.g., cubic-like nullclines with the same maxima and minima) for different combinations of these maximal conductances. In contrast, we show that these mechanisms are dynamic and involve the complex interaction between the nonlinear voltage dependencies and the effective time scales at which the ionic current's dynamical variables operate.

Degradation of extracellular chondroitin sulfate delays recovery of network activity after perturbation

Chondroitin sulfate proteoglycans (CSPGs) are widely studied in vertebrate systems and are known to play a key role in development, plasticity, and regulation of cortical circuitry. The mechanistic details of this role are still elusive, but increasingly central to the investigation is the homeostatic balance between network excitation and inhibition. Studying a simpler neuronal circuit may prove advantageous for discovering the mechanistic details of the cellular effects of CSPGs. In this study we used a well-established model of homeostatic change after injury in the crab Cancer borealis to show first evidence that CSPGs are necessary for network activity homeostasis. We degraded CSPGs in the pyloric circuit of the stomatogastric ganglion with the enzyme chondroitinase ABC (chABC) and found that removal of CSPGs does not influence the ongoing rhythm of the pyloric circuit but does limit its capacity for recovery after a networkwide perturbation. Without CSPGs, the postperturbation rhythm is slower than in controls and rhythm recovery is delayed. In addition to providing a new model system for the study of CSPGs, this study suggests a wider role for CSPGs, and perhaps the extracellular matrix in general, beyond simply plastic reorganization (as observed in mammals) and into a foundational regulatory role of neural circuitry.

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.

The role of linear and voltage-dependent ionic currents in the generation of slow wave oscillations

Neuronal oscillatory activity is generated by a combination of ionic currents, including at least one inward regenerative current that brings the cell towards depolarized voltages and one outward current that repolarizes the cell. Such currents have traditionally been assumed to require voltage-dependence. Here we test the hypothesis that the voltage dependence of the regenerative inward current is not necessary for generating oscillations. Instead, a current I NL that is linear in the biological voltage range and has negative conductance is sufficient to produce regenerative activity. The current I NL can be considered a linear approximation to the negative-conductance region of the current-voltage relationship of a regenerative inward current. Using a simple conductance-based model, we show that I NL , in conjunction with a voltage-gated, non-inactivating outward current, can generate oscillatory activity. We use phase-plane and bifurcation analyses to uncover a rich variety of behaviors as the conductance of I NL is varied, and show that oscillations emerge as a result of destabilization of the resting state of the model neuron. The model shows the need for well-defined relationships between the inward and outward current conductances, as well as their reversal potentials, in order to produce stable oscillatory activity. Our analysis predicts that a hyperpolarization-activated inward current can play a role in stabilizing oscillatory activity by preventing swings to very negative voltages, which is consistent with what is recorded in biological neurons in general. We confirm this prediction of the model experimentally in neurons from the crab stomatogastric ganglion.

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.

Contamination of current-clamp measurement of neuron capacitance by voltage-dependent phenomena

Measuring neuron capacitance is important for morphological description, conductance characterization, and neuron modeling. One method to estimate capacitance is to inject current pulses into a neuron and fit the resulting changes in membrane potential with multiple exponentials; if the neuron is purely passive, the amplitude and time constant of the slowest exponential give neuron capacitance (Major G, Evans JD, Jack JJ. Biophys J 65: 423-449, 1993). Golowasch et al. (Golowasch J, Thomas G, Taylor AL, Patel A, Pineda A, Khalil C, Nadim F. J Neurophysiol 102: 2161-2175, 2009) have shown that this is the best method for measuring the capacitance of nonisopotential (i.e., most) neurons. However, prior work has not tested for, or examined how much error would be introduced by, slow voltage-dependent phenomena possibly present at the membrane potentials typically used in such work. We investigated this issue in lobster (Panulirus interruptus) stomatogastric neurons by performing current clamp-based capacitance measurements at multiple membrane potentials. A slow, voltage-dependent phenomenon consistent with residual voltage-dependent conductances was present at all tested membrane potentials (-95 to -35 mV). This phenomenon was the slowest component of the neuron's voltage response, and failure to recognize and exclude it would lead to capacitance overestimates of several hundredfold. Most methods of estimating capacitance depend on the absence of voltage-dependent phenomena. Our demonstration that such phenomena make nonnegligible contributions to neuron responses even at well-hyperpolarized membrane potentials highlights the critical importance of checking for such phenomena in all work measuring neuron capacitance. We show here how to identify such phenomena and minimize their contaminating influence.

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.

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.

Recovery of rhythmic activity in a central pattern generator: analysis of the role of neuromodulator and activity-dependent mechanisms

The pyloric network of decapods crustaceans can undergo dramatic rhythmic activity changes. Under normal conditions the network generates low frequency rhythmic activity that depends obligatorily on the presence of neuromodulatory input from the central nervous system. When this input is removed (decentralization) the rhythmic activity ceases. In the continued absence of this input, periodic activity resumes after a few hours in the form of episodic bursting across the entire network that later turns into stable rhythmic activity that is nearly indistinguishable from control (recovery). It has been proposed that an activity-dependent modification of ionic conductance levels in the pyloric pacemaker neuron drives the process of recovery of activity. Previous modeling attempts have captured some aspects of the temporal changes observed experimentally, but key features could not be reproduced. Here we examined a model in which slow activity-dependent regulation of ionic conductances and slower neuromodulator-dependent regulation of intracellular Ca(2+) concentration reproduce all the temporal features of this recovery. Key aspects of these two regulatory mechanisms are their independence and their different kinetics. We also examined the role of variability (noise) in the activity-dependent regulation pathway and observe that it can help to reduce unrealistic constraints that were otherwise required on the neuromodulator-dependent pathway. We conclude that small variations in intracellular Ca(2+) concentration, a Ca(2+) uptake regulation mechanism that is directly targeted by neuromodulator-activated signaling pathways, and variability in the Ca(2+) concentration sensing signaling pathway can account for the observed changes in neuronal activity. Our conclusions are all amenable to experimental analysis.

The magnitudes of hyperpolarization-activated and low-voltage-activated potassium currents co-vary in neurons of the ventral cochlear nucleus

In the ventral cochlear nucleus (VCN), neurons have hyperpolarization-activated conductances, which in some cells are enormous, that contribute to the ability of neurons to convey acoustic information in the timing of their firing by decreasing the input resistance and speeding-up voltage changes. Comparisons of the electrophysiological properties of neurons in the VCN of mutant mice that lack the hyperpolarization-activated cyclic nucleotide-gated channel α subunit 1 (HCN1(-/-)) (Nolan et al. 2003) with wild-type controls (HCN1(+/+)) and with outbred ICR mice reveal that octopus, T stellate, and bushy cells maintain their electrophysiological distinctions in all strains. Hyperpolarization-activated (I(h)) currents were smaller and slower, input resistances were higher, and membrane time constants were longer in HCN1(-/-) than in HCN1(+/+) in octopus, bushy, and T stellate cells. There were significant differences in the average magnitudes of I(h), input resistances, and time constants between HCN1(+/+) and ICR mice, but the resting potentials did not differ between strains. I(h) is opposed by a low-voltage-activated potassium (I(KL)) current in bushy and octopus cells, whose magnitudes varied widely between neuronal types and between strains. The magnitudes of I(h) and I(KL) were correlated across neuronal types and across mouse strains. Furthermore, these currents balanced one another at the resting potential in individual cells. The magnitude of I(h) and I(KL) is linked in bushy and octopus cells and varies not only between HCN1(-/-) and HCN1(+/+) but also between "wild-type" strains of mice, raising the question to what extent the wild-type strains reflect normal mice.

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.

Crustacean neuropeptides

Crustaceans have long been used for peptide research. For example, the process of neurosecretion was first formally demonstrated in the crustacean X-organ-sinus gland system, and the first fully characterized invertebrate neuropeptide was from a shrimp. Moreover, the crustacean stomatogastric and cardiac nervous systems have long served as models for understanding the general principles governing neural circuit functioning, including modulation by peptides. Here, we review the basic biology of crustacean neuropeptides, discuss methodologies currently driving their discovery, provide an overview of the known families, and summarize recent data on their control of physiology and behavior.

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.

Generation and preservation of the slow underlying membrane potential oscillation in model bursting neurons

The underlying membrane potential oscillation of both forced and endogenous slow-wave bursting cells affects the number of spikes per burst, which in turn affects outputs downstream. We use a biophysical model of a class of slow-wave bursting cells with six active currents to investigate and generalize correlations among maximal current conductances that might generate and preserve its underlying oscillation. We propose three phases for the underlying oscillation for this class of cells: generation, maintenance, and termination and suggest that different current modules coregulate to preserve the characteristics of each phase. Coregulation of I(Burst) and I(A) currents within distinct boundaries maintains the dynamics during the generation phase. Similarly, coregulation of I(CaT) and I(Kd) maintains the peak and duration of the underlying oscillation, whereas the calcium-activated I(KCa) ensures appropriate termination of the oscillation and adjusts the duration independent of peak.

Functional recovery after lesion of a central pattern generator

In cases of neuronal injury when regeneration is restricted, functional recovery can occur through reorganization of the remaining neural circuitry. We found an example of such recovery in the central pattern generator (CPG) for the escape swim of the mollusc Tritonia diomedea. The CPG neurons are bilaterally represented and each neuron projects an axon through one of two pedal commissures. Cutting the posterior pedal commissure [pedal nerve 6 (PdN6)] in the animal or in the isolated brain caused a deficit in the swim behavior and in the fictive motor pattern, respectively, each of which recovered over the course of 20 h. Locally blocking spiking activity in PdN6 with sodium-free saline and/or tetrodotoxin disrupted the motor pattern in a reversible manner. Maintained blockade of PdN6 led to a functional recovery of the swim motor pattern similar to that observed in response to cutting the commissure. Among the CPG neurons, cerebral neuron 2 (C2) makes functional connection onto the ventral swim interneuron-B (VSI) in both pedal ganglia. Cutting or blocking PdN6 eliminated C2-evoked excitation of VSI in the pedal ganglion distal to the lesion. Associated with the recovery of the swim motor pattern, the synaptic action of C2 onto VSI in the proximal pedal ganglion changed from being predominantly inhibitory to being predominantly excitatory. These results show that the Tritonia swim CPG undergoes adaptive plasticity in response to the loss of critical synaptic connections; reversal of synaptic action in the CPG may be at least partially responsible for this functional recovery.

Modulation of stomatogastric rhythms

Neuromodulation by peptides and amines is a primary source of plasticity in the nervous system as it adapts the animal to an ever-changing environment. The crustacean stomatogastric nervous system is one of the premier systems to study neuromodulation and its effects on motor pattern generation at the cellular level. It contains the extensively modulated central pattern generators that drive the gastric mill (chewing) and pyloric (food filtering) rhythms. Neuromodulators affect all stages of neuronal processing in this system, from membrane currents and synaptic transmission in network neurons to the properties of the effector muscles. The ease with which distinct neurons are identified and their activity is recorded in this system has provided considerable insight into the mechanisms by which neuromodulators affect their target cells and modulatory neuron function. Recent evidence suggests that neuromodulators are involved in homeostatic processes and that the modulatory system itself is under modulatory control, a fascinating topic whose surface has been barely scratched. Future challenges include exploring the behavioral conditions under which these systems are activated and how their effects are regulated.

Membrane capacitance measurements revisited: dependence of capacitance value on measurement method in nonisopotential neurons

During growth or degeneration neuronal surface area can change dramatically. Measurements of membrane protein concentration, as in ion channel or ionic conductance density, are often normalized by membrane capacitance, which is proportional to the surface area, to express changes independently from cell surface variations. Several electrophysiological protocols are used to measure cell capacitance, all based on the assumption of membrane isopotentiality. Yet, most neurons violate this assumption because of their complex anatomical structure, raising the question of which protocol yields measurements that are closest to the actual total membrane capacitance. We measured the capacitance of identified neurons from crab stomatogastric ganglia using three different protocols: the current-clamp step, the voltage-clamp step, and the voltage-clamp ramp protocols. We observed that the current-clamp protocol produced significantly higher capacitance values than those of either voltage-clamp protocol. Computational models of various anatomical complexities suggest that the current-clamp protocol can yield accurate capacitance estimates. In contrast, the voltage-clamp protocol estimates rapidly deteriorate as isopotentiality is reduced. We provide a mathematical description of these results by analyzing a simple two-compartment model neuron to facilitate an intuitive understanding of these methods. Together, the experiments, modeling, and mathematical analysis indicate that accurate total membrane capacitance measurements cannot be obtained with voltage-clamp protocols in nonisopotential neurons. Furthermore, although current-clamp steps can theoretically yield accurate measurements, experimentalists should be aware of limitations imposed by step duration and numerical errors during fitting procedures to obtain the membrane time constant.

Activity and neuromodulatory input contribute to the recovery of rhythmic output after decentralization in a central pattern generator

Central pattern generators (CPGs) are neuronal networks that control vitally important rhythmic behaviors including breathing, heartbeat, and digestion. Understanding how CPGs recover activity after their rhythmic activity is disrupted has important theoretical and practical implications. Previous experimental and modeling studies indicated that rhythm recovery after central neuromodulatory input loss (decentralization) could be based entirely on activity-dependent mechanisms, but recent evidence of long-term conductance regulation by neuromodulators suggest that neuromodulator-dependent mechanisms may also be involved. Here we examined the effects of altering activity and the neuromodulatory environment before decentralization of the pyloric CPG in Cancer borealis on the initial phase of rhythmic activity recovery after decentralization. We found that pretreatments altering the network activity through shifting the ionic balance or the membrane potential of pyloric pacemaker neurons reduced the delay of recovery initiation after decentralization, consistent with the recovery process being triggered already during the pretreatment period through an activity-dependent mechanism. However, we observed that pretreatment with neuromodulators GABA and proctolin, acting via metabotropic receptors, also affected the initial phase of the recovery of pyloric activity after decentralization. Their distinct effects appear to result from interactions of their metabotropic effects with their effects on neuronal activity. Thus we show that the initial phase of the recovery process can be accounted for by the existence of distinct activity-and neuromodulator-dependent pathways. We propose a computational model that includes activity- and neuromodulator-dependent mechanisms of the activity recovery process, which successfully explains the experimental observations and predicts the results of key biological experiments.

Long-term potentiation in rat hippocampal neurons is accompanied by spatially widespread changes in intrinsic oscillatory dynamics and excitability

Oscillations in neural activity are a prominent feature of many brain states. Individual hippocampal neurons exhibit intrinsic membrane potential oscillations and intrinsic resonance in the theta frequency range. We found that the subthreshold resonance frequency of CA1 pyramidal neurons was location dependent, varying more than 3-fold between the soma and the distal dendrites. Furthermore, activity- and NMDA-receptor-dependent long-term plasticity increased this resonance frequency through changes in h channel properties. The increase in resonance frequency and an associated reduction in excitability were nearly identical in the soma and the first 300 mum of the apical dendrites. These spatially widespread changes accompanying long-term synaptic potentiation also reduced the neuron's ability to elicit spikes evoked through a nonpotentiated synaptic pathway. Our results suggest that the frequency response of these neurons depends on the dendritic location of their inputs and that activity can regulate their response dynamics within an oscillating neural network.

Using complicated, wide dynamic range driving to develop models of single neurons in single recording sessions

Neuron models are typically built by measuring individually, for each membrane conductance, its parameters (e.g., half-maximal voltages) and maximal conductance value (g(max)). However, neurons have extended morphologies with nonuniform conductance distributions, whereas models generally contain at most a few compartments. Both the original conductance measurements and the models therefore unavoidably contain error due to the electrical filtering of neurons and the differential placement of conductances on them. Model parameters (typically g(max) values) are therefore generally altered by hand or brute force to match model and neuron activity. We propose an alternative method in which complicated, rapidly changing driving input is used to optimize model parameters. This method also ensures that neuron and model dynamics match across a wide dynamic range, a test not performed in most modeling. We tested this concept using leech heartbeat and generic tonically firing models and lobster stomatogastric and generic bursting models as targets and g(max) values as optimized parameters. In all four cases optimization solutions excellently matched target activity. Complicated, wide dynamic range driving thus appears to be an excellent method to characterize neuron properties in detail and to build highly accurate models. In these completely defined targets, the method found each target's 8-13 g(max) values with high accuracy, and may therefore also provide an alternative, functionally based method of defining neuron g(max) values. The method uses only standard experimental and computational techniques, could be easily extended to optimize conductance parameters other than g(max), and should be readily applicable to real neurons.

A central pattern generator producing alternative outputs: pattern, strength, and dynamics of premotor synaptic input to leech heart motor neurons

The central pattern generator (CPG) for heartbeat in medicinal leeches consists of seven identified pairs of segmental heart interneurons and one unidentified pair. Four of the identified pairs and the unidentified pair of interneurons make inhibitory synaptic connections with segmental heart motor neurons. The CPG produces a side-to-side asymmetric pattern of intersegmental coordination among ipsilateral premotor interneurons corresponding to a similarly asymmetric fictive motor pattern in heart motor neurons, and asymmetric constriction pattern of the two tubular hearts, synchronous and peristaltic. Using extracellular recordings from premotor interneurons and voltage-clamp recordings of ipsilateral segmental motor neurons in 69 isolated nerve cords, we assessed the strength and dynamics of premotor inhibitory synaptic output onto the entire ensemble of heart motor neurons and the associated conduction delays in both coordination modes. We conclude that premotor interneurons establish a stereotypical pattern of intersegmental synaptic connectivity, strengths, and dynamics that is invariant across coordination modes, despite wide variations among preparations. These data coupled with a previous description of the temporal pattern of premotor interneuron activity and relative phasing of motor neuron activity in the two coordination modes enable a direct assessment of how premotor interneurons through their temporal pattern of activity and their spatial pattern of synaptic connectivity, strengths, and dynamics coordinate segmental motor neurons into a functional pattern of activity.

Neuromodulators, not activity, control coordinated expression of ionic currents

Electrical activity in identical neurons across individuals is often remarkably similar and stable over long periods. However, the ionic currents that determine the electrical activity of these neurons show wide animal-to-animal amplitude variability. This seemingly random variability of individual current amplitudes may obscure mechanisms that globally reduce variability and that contribute to the generation of similar neuronal output. One such mechanism could be the coordinated regulation of ionic current expression. Studying identified neurons of the Cancer borealis pyloric network, we discovered that the removal of neuromodulatory input to this network (decentralization) was accompanied by the loss of the coordinated regulation of ionic current levels. Additionally, decentralization induced large changes in the levels of several ionic currents. The loss of coregulation and the changes in current levels were prevented by continuous exogenous application of proctolin, an endogenous neuromodulatory peptide, to the pyloric network. This peptide does not exert fast regulatory actions on any of the currents affected by decentralization. We conclude that neuromodulatory inputs to the pyloric network have a novel role in the regulation of ionic current expression. They can control, over the long term, the coordinated expression of multiple voltage-gated ionic currents that they do not acutely modulate. Our results suggest that current coregulation places constraints on neuronal intrinsic plasticity and the ability of a network to respond to perturbations. The loss of conductance coregulation may be a mechanism to facilitate the recovery of function.