The action potential in mammalian central neurons

Vertebrate membrane proteins: structure, function, and insights from biophysical approaches

Membrane proteins are key targets for pharmacological intervention because they are vital for cellular function. Here, we analyze recent progress made in the understanding of the structure and function of membrane proteins with a focus on rhodopsin and development of atomic force microscopy techniques to study biological membranes. Membrane proteins are compartmentalized to carry out extra- and intracellular processes. Biological membranes are densely populated with membrane proteins that occupy approximately 50% of their volume. In most cases membranes contain lipid rafts, protein patches, or paracrystalline formations that lack the higher-order symmetry that would allow them to be characterized by diffraction methods. Despite many technical difficulties, several crystal structures of membrane proteins that illustrate their internal structural organization have been determined. Moreover, high-resolution atomic force microscopy, near-field scanning optical microscopy, and other lower resolution techniques have been used to investigate these structures. Single-molecule force spectroscopy tracks interactions that stabilize membrane proteins and those that switch their functional state; this spectroscopy can be applied to locate a ligand-binding site. Recent development of this technique also reveals the energy landscape of a membrane protein, defining its folding, reaction pathways, and kinetics. Future development and application of novel approaches during the coming years should provide even greater insights to the understanding of biological membrane organization and function.

Similar properties of transient, persistent, and resurgent Na currents in GABAergic and non-GABAergic vestibular nucleus neurons

Sodium currents in fast firing neurons are tuned to support sustained firing rates >50-60 Hz. This is typically accomplished with fast channel kinetics and the ability to minimize the accumulation of Na channels into inactivated states. Neurons in the medial vestibular nuclei (MVN) can fire at exceptionally high rates, but their Na currents have never been characterized. In this study, Na current kinetics and voltage-dependent properties were compared in two classes of MVN neurons with distinct firing properties. Non-GABAergic neurons (fluorescently labeled in YFP-16 transgenic mice) have action potentials with faster rise and fall kinetics and sustain higher firing rates than GABAergic neurons (fluorescently labeled in GIN transgenic mice). A previous study showed that these neurons express a differential balance of K currents. To determine whether the Na currents in these two populations were different, their kinetics and voltage-dependent properties were measured in acutely dissociated neurons from 24- to 40-day-old mice. All neurons expressed persistent Na currents and large transient Na currents with resurgent kinetics tuned for fast firing. No differences were found between the Na currents expressed in GABAergic and non-GABAergic MVN neurons, suggesting that differences in properties of these neurons are tuned by their K currents.

Somatodendritic dynorphin release: orchestrating activity patterns of vasopressin neurons

Most neurons in the central nervous system co-express peptides alongside their principal transmitter, yet the function of these peptides is largely unknown. Vasopressin neurons of the hypothalamic supraoptic nucleus and paraventricular nucleus contain among the highest concentrations of dynorphin found in the brain. Dynorphin, an endogenous opioid peptide, is co-localized in the same neurosecretory vesicles as vasopressin and is released alongside vasopressin from the dendrites and axon terminals of vasopressin neurons. We and others have shown that neuropeptide release from the soma and dendrites of vasopressin neurons activates vasopressin receptors and kappa-opioid receptors to cause activity-dependent modulation of vasopressin neuron activity, and that this is essential for activity patterning in vasopressin neurons.

Electrical remodelling maintains firing properties in cortical pyramidal neurons lacking KCND2-encoded A-type K+ currents

Considerable experimental evidence has accumulated demonstrating a role for voltage-gated K(+) (Kv) channel pore-forming (alpha) subunits of the Kv4 subfamily in the generation of fast transient outward K(+), I(A), channels. Immunohistochemical data suggest that I(A) channels in hippocampal and cortical pyramidal neurons reflect the expression of homomeric Kv4.2 channels. The experiments here were designed to define directly the role of Kv4.2 in the generation of I(A) in cortical pyramidal neurons and to determine the functional consequences of the targeted deletion of Kv4.2 on the resting and active membrane properties of these cells. Whole-cell voltage-clamp recordings, obtained from visual cortical pyramidal neurons isolated from mice in which the KCND2 (Kv4.2) locus was disrupted (Kv4.2-/- mice), revealed that I(A) is indeed eliminated. In addition, the densities of other Kv current components, specifically I(K) and I(ss), are increased significantly (P < 0.001) in most ( approximately 80%) Kv4.2-/- cells. The deletion of KCND2 (Kv4.2) and the elimination of I(A) is also accompanied by the loss of the Kv4 channel accessory protein KChIP3, suggesting that in the absence of Kv4.2, the KChIP3 protein is targeted for degradation. The expression levels of several Kv alpha subunits (Kv4.3, Kv1.4, Kv2.1, Kv2.2), however, are not measurably altered in Kv4.2-/- cortices. Although I(A) is eliminated in Kv4.2-/- pyramidal neurons, the mean +/- s.e.m. current threshold for action potential generation and the waveforms of action potentials are indistinguishable from those recorded from wild-type cells. Repetitive firing is also maintained in Kv4.2-/- cortical pyramidal neurons, suggesting that the increased densities of I(K) and I(ss) compensate for the in vivo loss of I(A).

Persistent neural activity in the prefrontal cortex: a mechanism by which BDNF regulates working memory?

Working memory is the ability to maintain representations of task-relevant information for short periods of time to guide subsequent actions or make decisions. Neurons of the prefrontal cortex exhibit persistent firing during the delay period of working memory tasks. Despite extensive studies, the mechanisms underlying this persistent neural activity remain largely obscure. The neurotransmitter systems of dopamine, NMDA, and GABA have been implicated, but further investigations are necessary to establish their precise roles and relationships. Recent research has suggested a new component: brain-derived neurotrophic factor (BDNF) and its high-affinity receptor, TrkB. We review the research on persistent activity and suggest that BDNF/TrkB signaling in a distinct class of interneurons plays an important role in organizing persistent neural activity at the single-neuron and network levels.

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

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

Molecular driving forces determining potassium channel slow inactivation

K+ channels undergo a time-dependent slow inactivation process that plays a key role in modulating cellular excitability. Here we show that in the prokaryotic proton-gated K+ channel KcsA, the number and strength of hydrogen bonds between residues in the selectivity filter and its adjacent pore helix determine the rate and extent of C-type inactivation. Upon channel activation, the interaction between residues at positions Glu71 and Asp80 promotes filter constriction parallel to the permeation pathway, which affects K+-binding sites and presumably abrogates ion conduction. Coupling between these two positions results in a quantitative correlation between their interaction strength and the stability of the inactivated state. Engineering of these interactions in the eukaryotic voltage-dependent K+ channel Kv1.2 suggests that a similar mechanistic principle applies to other K+ channels. These observations provide a plausible physical framework for understanding C-type inactivation in K+ channels.

TASK-3 two-pore domain potassium channels enable sustained high-frequency firing in cerebellar granule neurons

The ability of neurons, such as cerebellar granule neurons (CGNs), to fire action potentials (APs) at high frequencies during sustained depolarization is usually explained in relation to the functional properties of voltage-gated ion channels. Two-pore domain potassium (K(2P)) channels are considered to simply hyperpolarize the resting membrane potential (RMP) by increasing the potassium permeability of the membrane. However, we find that CGNs lacking the TASK-3 type K(2P) channel exhibit marked accommodation of action potential firing. The accommodation phenotype was not associated with any change in the functional properties of the underlying voltage-gated sodium channels, nor could it be explained by the more depolarized RMP that resulted from TASK-3 channel deletion. A functional rescue, involving the introduction of a nonlinear leak conductance with a dynamic current clamp, was able to restore wild-type firing properties to adult TASK-3 knock-out CGNs. Thus, in addition to the accepted role of TASK-3 channels in limiting neuronal excitability, by increasing the resting potassium conductance TASK-3 channels also increase excitability by supporting high-frequency firing once AP threshold is reached.

A numerical approach to ion channel modelling using whole-cell voltage-clamp recordings and a genetic algorithm

The activity of trans-membrane proteins such as ion channels is the essence of neuronal transmission. The currently most accurate method for determining ion channel kinetic mechanisms is single-channel recording and analysis. Yet, the limitations and complexities in interpreting single-channel recordings discourage many physiologists from using them. Here we show that a genetic search algorithm in combination with a gradient descent algorithm can be used to fit whole-cell voltage-clamp data to kinetic models with a high degree of accuracy. Previously, ion channel stimulation traces were analyzed one at a time, the results of these analyses being combined to produce a picture of channel kinetics. Here the entire set of traces from all stimulation protocols are analysed simultaneously. The algorithm was initially tested on simulated current traces produced by several Hodgkin-Huxley–like and Markov chain models of voltage-gated potassium and sodium channels. Currents were also produced by simulating levels of noise expected from actual patch recordings. Finally, the algorithm was used for finding the kinetic parameters of several voltage-gated sodium and potassium channels models by matching its results to data recorded from layer 5 pyramidal neurons of the rat cortex in the nucleated outside-out patch configuration. The minimization scheme gives electrophysiologists a tool for reproducing and simulating voltage-gated ion channel kinetics at the cellular level.

Voltage-gated ion channels affect neuronal integration of information. Some neurons express more than ten different types of voltage-gated ion channels, making information processing a highly convoluted process. Kinetic modelling of ion channels is an important method for unravelling the role of each channel type in neuronal function. However, the most commonly used analysis techniques suffer from shortcomings that limit the ability of researchers to rapidly produce physiologically relevant models of voltage-gated ion channels and of neuronal physiology. We show that conjugating a stochastic search algorithm with ionic currents measured using multiple voltage-clamp protocols enables the semi-automatic production of models of voltage-gated ion channels. Once fully automated, this approach may be used for high throughput analysis of voltage-gated currents. This in turn will greatly shorten the time required for building models of neuronal physiology to facilitate our understanding of neuronal behaviour.