Action potential initiation in a multi-compartmental model with cooperatively gating Na channels in the axon initial segment

Dynamic Gain Decomposition Reveals Functional Effects of Dendrites, Ion Channels, and Input Statistics in Population Coding

Modern, high-density neuronal recordings reveal at ever higher precision how information is represented by neural populations. Still, we lack the tools to understand these processes bottom-up, emerging from the biophysical properties of neurons, synapses, and network structure. The concept of the dynamic gain function, a spectrally resolved approximation of a population's coding capability, has the potential to link cell-level properties to network-level performance. However, the concept is not only useful but also very complex because the dynamic gain's shape is co-determined by axonal and somato-dendritic parameters and the population's operating regime. Previously, this complexity precluded an understanding of any individual parameter's impact. Here, we decomposed the dynamic gain function into three components corresponding to separate signal transformations. This allowed attribution of network-level encoding features to specific cell-level parameters. Applying the method to data from real neurons and biophysically plausible models, we found: (1) The encoding bandwidth of real neurons, approximately 400 Hz, is constrained by the voltage dependence of axonal currents during early action potential initiation. (2) State-of-the-art models only achieve encoding bandwidths around 100 Hz and are limited mainly by subthreshold processes instead. (3) Large dendrites and low-threshold potassium currents modulate the bandwidth by shaping the subthreshold stimulus-to-voltage transformation. Our decomposition provides physiological interpretations when the dynamic gain curve changes, for instance during spectrinopathies and neurodegeneration. By pinpointing shortcomings of current models, it also guides inference of neuron models best suited for large-scale network simulations.

Microfluidic electrode array chip for electrical stimulation-mediated axonal regeneration

The precise manipulation of the neural stem cell (NSC)-derived neural differentiation is still challenging, and there is a technological barrier to regulate the axonal regeneration in a controlled manner. Here, we developed a microfluidic chip integrated with a microelectrode array as an axonal guidance platform. The microfluidic electrode array chip consisted of two compartments and a bridge microchannel that could isolate and guide the axons. We demonstrated that the NSCs were largely differentiated into neural cells as the electric field was applied to the microfluidic electrode array chip. We also confirmed the synergistic effects of the electrical stimulation (ES) and neurotrophic factor (NF) on axonal outgrowth. This microfluidic electrode array chip can serve as a central nervous system (CNS) model for axonal injury and regeneration. Therefore, it could be a potentially powerful tool for an in vitro model of the axonal regeneration.

Mechanisms and Physiological Implications of Cooperative Gating of Ion Channels Clusters

Ion channels play a central role in the regulation of nearly every cellular process. Dating back to the classic 1952 Hodgkin-Huxley model of the generation of the action potential, ion channels have always been thought of as independent agents. A myriad of recent experimental findings exploiting advances in electrophysiology, structural biology, and imaging techniques, however, have posed a serious challenge to this long-held axiom as several classes of ion channels appear to open and close in a coordinated, cooperative manner. Ion channel cooperativity ranges from variable-sized oligomeric cooperative gating in voltage-gated, dihydropyridine-sensitive Ca_v1.2 and Ca_v1.3 channels to obligatory dimeric assembly and gating of voltage-gated Na_v1.5 channels. Potassium channels, transient receptor potential channels, hyperpolarization cyclic nucleotide-activated channels, ryanodine receptors (RyRs), and inositol trisphosphate receptors (IP₃Rs) have also been shown to gate cooperatively. The implications of cooperative gating of these ion channels range from fine tuning excitation-contraction coupling in muscle cells to regulating cardiac function and vascular tone, to modulation of action potential and conduction velocity in neurons and cardiac cells, and to control of pace-making activity in the heart. In this review, we discuss the mechanisms leading to cooperative gating of ion channels, their physiological consequences and how alterations in cooperative gating of ion channels may induce a range of clinically significant pathologies.

New methods for quantifying rapidity of action potential onset differentiate neuron types

Two new methods for quantifying the rapidity of action potential onset have lower relative standard deviations and better distinguish neuron cell types than current methods. Action potentials (APs) in most central mammalian neurons exhibit sharp onset dynamics. The main views explaining such an abrupt onset differ. Some studies suggest sharp onsets reflect cooperative sodium channels activation, while others suggest they reflect AP backpropagation from the axon initial segment. However, AP onset rapidity is defined subjectively in these studies, often using the slope at an arbitrary value on the phase plot. Thus, we proposed more systematic methods using the membrane potential's second-time derivative ([Formula: see text]) peak width. Here, the AP rapidity was measured for four different cortical and hippocampal neuron types using four quantification methods: the inverse of full-width at the half maximum of the [Formula: see text] peak (IFWd2), the inverse of half-width at the half maximum of the [Formula: see text] peak (IHWd2), the phase plot slope, and the error ratio method. The IFWd2 and IHWd2 methods show the smallest variation among neurons of the same type. Furthermore, the AP rapidity, using the [Formula: see text] peak width methods, significantly differentiates between different types of neurons, indicating that AP rapidity can be used to classify neuron types. The AP rapidity measured using the IFWd2 method was able to differentiate between all four neuron types analyzed. Therefore, the [Formula: see text] peak width methods provide another sensitive tool to investigate the mechanisms impacting the AP onset dynamics.

The location of the axon initial segment affects the bandwidth of spike initiation dynamics

The dynamics and the sharp onset of action potential (AP) generation have recently been the subject of intense experimental and theoretical investigations. According to the resistive coupling theory, an electrotonic interplay between the site of AP initiation in the axon and the somato-dendritic load determines the AP waveform. This phenomenon not only alters the shape of APs recorded at the soma, but also determines the dynamics of excitability across a variety of time scales. Supporting this statement, here we generalize a previous numerical study and extend it to the quantification of the input-output gain of the neuronal dynamical response. We consider three classes of multicompartmental mathematical models, ranging from ball-and-stick simplified descriptions of neuronal excitability to 3D-reconstructed biophysical models of excitatory neurons of rodent and human cortical tissue. For each model, we demonstrate that increasing the distance between the axonal site of AP initiation and the soma markedly increases the bandwidth of neuronal response properties. We finally consider the Liquid State Machine paradigm, exploring the impact of altering the site of AP initiation at the level of a neuronal population, and demonstrate that an optimal distance exists to boost the computational performance of the network in a simple classification task.

The neurons in the brain encode information through electrical impulses. The performance of a cell in terms of its ability to process and transfer information downstream thus depends heavily on the machinery of initiation of these impulses. In this work, we consider both the cell morphology and the biophysical properties of impulse initiation as the primary parameters that influence information processing in single neurons, as well as in networks. We specifically analyze the location of nerve impulse initiation along the cell’s axon and the way the neuron transfers incoming information. By using single-cell models of various complexity as well as network models, we conclude that information processing is sensitive to the geometrical details of impulse initiation.

An integrated microfluidic/microelectrode array for the study of activity-dependent intracellular dynamics in neuronal networks

In the central nervous system, neurons are organized in specific neural networks with distinct electrical patterns, input integration capacities, and intracellular dynamics. In order to better understand how neurons process information, it is crucial to keep the complex organization of brain circuits. However, performing subcellular investigations with high spatial and temporal resolution in vivo is technically challenging, especially in fine structures, such as axonal projections. Here, we present an on-a-chip system that combines a microfluidic platform with a dedicated matrix of electrodes to study activity-dependent dynamics in the physiological context of brain circuits. Because this system is compatible with high-resolution video-microscopy, it is possible to simultaneously record intracellular dynamics and electrical activity in presynaptic axonal projections and in their postsynaptic neuronal targets. Similarly, specific patterns of electrical activity can be applied to both compartments in order to investigate how intrinsic and network activities influence intracellular dynamics. The fluidic isolation of each compartment further allows the selective application of drugs at identified sites to study activity-dependent synaptic transmission. This integrated microfluidic/microelectrode array (microMEA) platform is a valuable tool for studying various intracellular and synaptic dynamics in response to neuronal activity in a physiologically relevant context that resembles in vivo brain circuits.

The basis of sharp spike onset in standard biophysical models

In most vertebrate neurons, spikes initiate in the axonal initial segment (AIS). When recorded in the soma, they have a surprisingly sharp onset, as if sodium (Na) channels opened abruptly. The main view stipulates that spikes initiate in a conventional manner at the distal end of the AIS, then progressively sharpen as they backpropagate to the soma. We examined the biophysical models used to substantiate this view, and we found that spikes do not initiate through a local axonal current loop that propagates along the axon, but through a global current loop encompassing the AIS and soma, which forms an electrical dipole. Therefore, the phenomenon is not adequately modeled as the backpropagation of an electrical wave along the axon, since the wavelength would be as large as the entire system. Instead, in these models, we found that spike initiation rather follows the critical resistive coupling model proposed recently, where the Na current entering the AIS is matched by the axial resistive current flowing to the soma. Besides demonstrating it by examining the balance of currents at spike initiation, we show that the observed increase in spike sharpness along the axon is artifactual and disappears when an appropriate measure of rapidness is used; instead, somatic onset rapidness can be predicted from spike shape at initiation site. Finally, we reproduce the phenomenon in a two-compartment model, showing that it does not rely on propagation. In these models, the sharp onset of somatic spikes is therefore not an artifact of observing spikes at the incorrect location, but rather the signature that spikes are initiated through a global soma-AIS current loop forming an electrical dipole.