Impact of Extracellular Current Flow on Action Potential Propagation in Myelinated Axons.

Myelinated axons conduct action potentials, or spikes, in a saltatory manner. Inward current caused by a spike occurring at one node of Ranvier spreads axially to the next node, which regenerates the spike when depolarized enough for voltage-gated sodium channels to activate, and so on. The rate at which this process progresses dictates the velocity at which the spike is conducted and depends on several factors including axial resistivity and axon diameter that directly affect axial current. Here we show through computational simulations in modified double-cable axon models that conduction velocity also depends on extracellular factors whose effects can be explained by their indirect influence on axial current. Specifically, we show that a conventional double-cable model, with its outside layer connected to ground, transmits less axial current than a model whose outside layer is less absorptive. A more resistive barrier exists when an axon is packed tightly between other myelinated fibers, for example. We show that realistically resistive boundary conditions can significantly increase the velocity and energy efficiency of spike propagation, while also protecting against propagation failure. Certain factors like myelin thickness may be less important than typically thought if extracellular conditions are more resistive than normally considered. We also show how realistically resistive boundary conditions affect ephaptic interactions. Overall, these results highlight the unappreciated importance of extracellular conditions for axon function.

A mutation-independent approach for muscular dystrophy via upregulation of a modifier gene.

Neuromuscular disorders are often caused by heterogeneous mutations in large, structurally complex genes. Targeting compensatory modifier genes could be beneficial to improve disease phenotypes. Here we report a mutation-independent strategy to upregulate the expression of a disease-modifying gene associated with congenital muscular dystrophy type 1A (MDC1A) using the CRISPR activation system in mice. MDC1A is caused by mutations in LAMA2 that lead to nonfunctional laminin-α2, which compromises the stability of muscle fibres and the myelination of peripheral nerves. Transgenic overexpression of Lama1, which encodes a structurally similar protein called laminin-α1, ameliorates muscle wasting and paralysis in mouse models of MDC1A, demonstrating its importance as a compensatory modifier of the disease1. However, postnatal upregulation of Lama1 is hampered by its large size, which exceeds the packaging capacity of vehicles that are clinically relevant for gene therapy. We modulate expression of Lama1 in the dy2j/dy2j mouse model of MDC1A using an adeno-associated virus (AAV9) carrying a catalytically inactive Cas9 (dCas9), VP64 transactivators and single-guide RNAs that target the Lama1 promoter. When pre-symptomatic mice were treated, Lama1 was upregulated in skeletal muscles and peripheral nerves, which prevented muscle fibrosis and paralysis. However, for many disorders it is important to investigate the therapeutic window and reversibility of symptoms. In muscular dystrophies, it has been hypothesized that fibrotic changes in skeletal muscle are irreversible. However, we show that dystrophic features and disease progression were improved and reversed when the treatment was initiated in symptomatic dy2j/dy2j mice with apparent hindlimb paralysis and muscle fibrosis. Collectively, our data demonstrate the feasibility and therapeutic benefit of CRISPR-dCas9-mediated upregulation of Lama1, which may enable mutation-independent treatment for all patients with MDC1A. This approach has a broad applicability to a variety of disease-modifying genes and could serve as a therapeutic strategy for many inherited and acquired diseases.

Physiological noise facilitates multiplexed coding of vibrotactile-like signals in somatosensory cortex.

Neurons can use different aspects of their spiking to simultaneously represent (multiplex) different features of a stimulus. For example, some pyramidal neurons in primary somatosensory cortex (S1) use the rate and timing of their spikes to, respectively, encode the intensity and frequency of vibrotactile stimuli. Doing so has several requirements. Because they fire at low rates, pyramidal neurons cannot entrain 1:1 with high-frequency (100 to 600 Hz) inputs and, instead, must skip (i.e., not respond to) some stimulus cycles. The proportion of skipped cycles must vary inversely with stimulus intensity for firing rate to encode stimulus intensity. Spikes must phase-lock to the stimulus for spike times (intervals) to encode stimulus frequency, but, in addition, skipping must occur irregularly to avoid aliasing. Using simulations and in vitro experiments in which mouse S1 pyramidal neurons were stimulated with inputs emulating those induced by vibrotactile stimuli, we show that fewer cycles are skipped as stimulus intensity increases, as required for rate coding, and that intrinsic or synaptic noise can induce irregular skipping without disrupting phase locking, as required for temporal coding. This occurs because noise can modulate the reliability without disrupting the precision of spikes evoked by small-amplitude, fast-onset signals. Specifically, in the fluctuation-driven regime associated with sparse spiking, rate and temporal coding are both paradoxically improved by the strong synaptic noise characteristic of the intact cortex. Our results demonstrate that multiplexed coding by S1 pyramidal neurons is not only feasible under in vivo conditions, but that background synaptic noise is actually beneficial.

TRPC4 and GIRK channels underlie neuronal coding of firing patterns that reflect Gq/11-Gi/o coincidence signals of variable strengths.

Transient receptor potential canonical 4 (TRPC4) is a receptor-operated cation channel codependent on both the Gq/11­phospholipase C signaling pathway and Gi/o proteins for activation. This makes TRPC4 an excellent coincidence sensor of neurotransmission through Gq/11- and Gi/o-coupled receptors. In whole-cell slice recordings of lateral septal neurons, TRPC4 mediates a strong depolarizing plateau that shuts down action potential firing, which may or may not be followed by a hyperpolarization that extends the firing pause to varying durations depending on the strength of Gi/o stimulation. We show that the depolarizing plateau is codependent on Gq/11-coupled group I metabotropic glutamate receptors and on Gi/o-coupled γ-aminobutyric acid type B receptors. The hyperpolarization is mediated by Gi/o activation of G protein­activated inwardly rectifying K+ (GIRK) channels. Moreover, the firing patterns, elicited by either electrical stimulation or receptor agonists, encode information about the relative strengths of Gq/11 and Gi/o inputs in the following fashion. Pure Gq/11 input produces weak depolarization accompanied by firing acceleration, whereas pure Gi/o input causes hyperpolarization that pauses firing. Although coincident Gq/11­Gi/o inputs also pause firing, the pause is preceded by a burst, and both the pause duration and firing recovery patterns reflect the relative strengths of Gq/11 versus Gi/o inputs. Computer simulations demonstrate that different combinations of TRPC4 and GIRK conductances are sufficient to produce the range of firing patterns observed experimentally. Thus, concurrent neurotransmission through the Gq/11 and Gi/o pathways is converted to discernible electrical responses by the joint actions of TRPC4 and GIRK for communication to downstream neurons.

Multiscale Computer Model of the Spinal Dorsal Horn Reveals Changes in Network Processing Associated with Chronic Pain.

Pain-related sensory input is processed in the spinal dorsal horn (SDH) before being relayed to the brain. That processing profoundly influences whether stimuli are correctly or incorrectly perceived as painful. Significant advances have been made in identifying the types of excitatory and inhibitory neurons that comprise the SDH, and there is some information about how neuron types are connected, but it remains unclear how the overall circuit processes sensory input or how that processing is disrupted under chronic pain conditions. To explore SDH function, we developed a computational model of the circuit that is tightly constrained by experimental data. Our model comprises conductance-based neuron models that reproduce the characteristic firing patterns of spinal neurons. Excitatory and inhibitory neuron populations, defined by their expression of genetic markers, spiking pattern, or morphology, were synaptically connected according to available qualitative data. Using a genetic algorithm, synaptic weights were tuned to reproduce projection neuron firing rates (model output) based on primary afferent firing rates (model input) across a range of mechanical stimulus intensities. Disparate synaptic weight combinations could produce equivalent circuit function, revealing degeneracy that may underlie heterogeneous responses of different circuits to perturbations or pathologic insults. To validate our model, we verified that it responded to the reduction of inhibition (i.e., disinhibition) and ablation of specific neuron types in a manner consistent with experiments. Thus validated, our model offers a valuable resource for interpreting experimental results and testing hypotheses in silico to plan experiments for examining normal and pathologic SDH circuit function.SIGNIFICANCE STATEMENT We developed a multiscale computer model of the posterior part of spinal cord gray matter (spinal dorsal horn), which is involved in perceiving touch and pain. The model reproduces several experimental observations and makes predictions about how specific types of spinal neurons and synapses influence projection neurons that send information to the brain. Misfiring of these projection neurons can produce anomalous sensations associated with chronic pain. Our computer model will not only assist in planning future experiments, but will also be useful for developing new pharmacotherapy for chronic pain disorders, connecting the effect of drugs acting at the molecular scale with emergent properties of neurons and circuits that shape the pain experience.

Synchrony-Division Neural Multiplexing: An Encoding Model.

Cortical neurons receive mixed information from the collective spiking activities of primary sensory neurons in response to a sensory stimulus. A recent study demonstrated an abrupt increase or decrease in stimulus intensity and the stimulus intensity itself can be respectively represented by the synchronous and asynchronous spikes of S1 neurons in rats. This evidence capitalized on the ability of an ensemble of homogeneous neurons to multiplex, a coding strategy that was referred to as synchrony-division multiplexing (SDM). Although neural multiplexing can be conceived by distinct functions of individual neurons in a heterogeneous neural ensemble, the extent to which nearly identical neurons in a homogeneous neural ensemble encode multiple features of a mixed stimulus remains unknown. Here, we present a computational framework to provide a system-level understanding on how an ensemble of homogeneous neurons enable SDM. First, we simulate SDM with an ensemble of homogeneous conductance-based model neurons receiving a mixed stimulus comprising slow and fast features. Using feature-estimation techniques, we show that both features of the stimulus can be inferred from the generated spikes. Second, we utilize linear nonlinear (LNL) cascade models and calculate temporal filters and static nonlinearities of differentially synchronized spikes. We demonstrate that these filters and nonlinearities are distinct for synchronous and asynchronous spikes. Finally, we develop an augmented LNL cascade model as an encoding model for the SDM by combining individual LNLs calculated for each type of spike. The augmented LNL model reveals that a homogeneous neural ensemble model can perform two different functions, namely, temporal- and rate-coding, simultaneously.

Differentially synchronized spiking enables multiplexed neural coding.

Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural scenes, which comprise areas over which intensity varies gradually and sparse edges where intensity changes abruptly, require a different multiplexing strategy. Recording in vivo from neurons in primary somatosensory cortex during tactile stimulation, we found that stimulus onset and offset (edges) evoked highly synchronized spiking, whereas other spikes in the same neurons occurred asynchronously. Stimulus intensity modulated the rate of asynchronous spiking, but did not affect the timing of synchronous spikes. From this, we hypothesized that spikes driven by high- and low-contrast stimulus features can be distinguished on the basis of their synchronization, and that differentially synchronized spiking can thus be used to form multiplexed representations. Applying a Bayesian decoding method, we verified that information about high- and low-contrast features can be recovered from an ensemble of model neurons receiving common input. Equally good decoding was achieved by distinguishing synchronous from asynchronous spikes and applying reverse correlation methods separately to each spike type. This result, which we verified with patch clamp recordings in vitro, demonstrates that neurons receiving common input can use the rate of asynchronous spiking to encode the intensity of low-contrast features while using the timing of synchronous spikes to encode the occurrence of high-contrast features. We refer to this strategy as synchrony-division multiplexing.

Intermittent Failure of Spike Propagation in Primary Afferent Neurons during Tactile Stimulation.

Primary afferent neurons convey somatosensory information to the CNS. Low-threshold mechanoreceptors are classified as slow-adapting (SA) or rapid-adapting (RA) based on whether or not they spike repetitively during sustained tactile stimulation; the former are subclassified as Type 1 or 2 based on the regularity of their spiking. Recording in vivo from DRGs of mice, we observed irregular- and regular-spiking units consistent with SA1 and SA2 low-threshold mechanoreceptors, but some units, which we labeled "semiregular," did not fit cleanly into the existing classification scheme. Analysis of their spiking revealed integer-multiple patterning in which spike trains comprised a fundamental interspike interval and multiples thereof. Integer-multiple-patterned spiking was reproduced by randomly removing spikes from an otherwise regular spike train, suggesting that semiregular units represent SA2 units in which some spikes are "missing." We hypothesized that missing spikes arose from intermittent failure of spikes to initiate or to propagate. Intermittent failure of spike initiation was ruled out by several observations: integer-multiple-patterned spiking was not induced by intradermal lidocaine, was independent of stimulus modality (mechanical vs optogenetic), and could not be reproduced in a conductance-based model neuron given constant input. On the other hand, integer-multiple-patterned spiking was induced by application of lidocaine to the DRG, thus pinpointing intermittent failure of spike propagation as the basis for integer-multiple-patterned spiking. Indeed, half of all SA2 units exhibited some missing spikes, mostly at low rate (<5%), which suggests that axons are efficient in using the lowest safety factor capable of producing near-perfect propagation reliability.SIGNIFICANCE STATEMENT The impedance mismatch at axon branch points can impede spike propagation. Reliability of spike propagation across branch points remains an open question and is especially important for primary afferents whose spikes must cross a T-junction to reach the CNS. Past research on propagation reliability has relied almost entirely on simulations and in vitro experiments. Here, recording in vivo, we linked a distinctive pattern of spiking to the intermittent failure of spike propagation at the T-junction. The rarity of failures argues that safety factor is high under physiological conditions, yet the occurrence of such failures argues that safety factor is just high enough to ensure near-perfect reliability, consistent with a good balance between propagation reliability and energy efficiency.

Nonlinear Relationship Between Spike-Dependent Calcium Influx and TRPC Channel Activation Enables Robust Persistent Spiking in Neurons of the Anterior Cingulate Cortex.

Continuation of spiking after a stimulus ends (i.e. persistent spiking) is thought to support working memory. Muscarinic receptor activation enables persistent spiking among synaptically isolated pyramidal neurons in anterior cingulate cortex (ACC), but a detailed characterization of that spiking is lacking and the underlying mechanisms remain unclear. Here, we show that the rate of persistent spiking in ACC neurons is insensitive to the intensity and number of triggers, but can be modulated by injected current, and that persistent spiking can resume after several seconds of hyperpolarization-imposed quiescence. Using electrophysiology and calcium imaging in brain slices from male rats, we determined that canonical transient receptor potential (TRPC) channels are necessary for persistent spiking and that TRPC-activating calcium enters in a spike-dependent manner via voltage-gated calcium channels. Constrained by these biophysical details, we built a computational model that reproduced the observed pattern of persistent spiking. Nonlinear dynamical analysis of that model revealed that TRPC channels become fully activated by the small rise in intracellular calcium caused by evoked spikes. Calcium continues to rise during persistent spiking, but because TRPC channel activation saturates, firing rate stabilizes. By calcium rising higher than required for maximal TRPC channel activation, TRPC channels are able to remain active during periods of hyperpolarization-imposed quiescence (until calcium drops below saturating levels) such that persistent spiking can resume when hyperpolarization is discontinued. Our results thus reveal that the robust intrinsic bistability exhibited by ACC neurons emerges from the nonlinear positive feedback relationship between spike-dependent calcium influx and TRPC channel activation.SIGNIFICANCE STATEMENT Neurons use action potentials, or spikes, to encode information. Some neurons can store information for short periods (seconds to minutes) by continuing to spike after a stimulus ends, thus enabling working memory. This so-called "persistent" spiking occurs in many brain areas and has been linked to activation of canonical transient receptor potential (TRPC) channels. However, TRPC activation alone is insufficient to explain many aspects of persistent spiking such as resumption of spiking after periods of imposed quiescence. Using experiments and simulations, we show that calcium influx caused by spiking is necessary and sufficient to activate TRPC channels and that the ensuing positive feedback interaction between intracellular calcium and TRPC channel activation can account for many hitherto unexplained aspects of persistent spiking.

Electrophysiology equipment for reliable study of kHz electrical stimulation.

Characterizing the cellular targets of kHz (1-10 kHz) electrical stimulation remains a pressing topic in neuromodulation because expanding interest in clinical application of kHz stimulation has surpassed mechanistic understanding. The presumed cellular targets of brain stimulation do not respond to kHz frequencies according to conventional electrophysiology theory. Specifically, the low-pass characteristics of cell membranes are predicted to render kHz stimulation inert, especially given the use of limited-duty-cycle biphasic pulses. Precisely because kHz frequencies are considered supra-physiological, conventional instruments designed for neurophysiological studies such as stimulators, amplifiers and recording microelectrodes do not operate reliably at these high rates. Moreover, for pulsed waveforms, the signal frequency content is well above the pulse repetition rate. Thus, the very tools used to characterize the effects of kHz electrical stimulation may themselves be confounding factors. We illustrate custom equipment design that supports reliable electrophysiological recording during kHz-rate stimulation. Given the increased importance of kHz stimulation in clinical domains and compelling possibilities that mechanisms of actions may reflect yet undiscovered neurophysiological phenomena, attention to suitable performance of electrophysiological equipment is pivotal.

Changes in White Matter Microstructure Impact Cognition by Disrupting the Ability of Neural Assemblies to Synchronize.

Cognition is compromised by white matter (WM) injury but the neurophysiological alterations linking them remain unclear. We hypothesized that reduced neural synchronization caused by disruption of neural signal propagation is involved. To test this, we evaluated group differences in: diffusion tensor WM microstructure measures within the optic radiations, primary visual area (V1), and cuneus; neural phase synchrony to a visual attention cue during visual-motor task; and reaction time to a response cue during the same task between 26 pediatric patients (17/9: male/female) treated with cranial radiation treatment for a brain tumor (12.67 ± 2.76 years), and 26 healthy children (16/10: male/female; 12.01 ± 3.9 years). We corroborated our findings using a corticocortical computational model representing perturbed signal conduction from myelin. Patients show delayed reaction time, WM compromise, and reduced phase synchrony during visual attention compared with healthy children. Notably, using partial least-squares-path modeling we found that WM insult within the optic radiations, V1, and cuneus is a strong predictor of the slower reaction times via disruption of neural synchrony in visual cortex. Observed changes in synchronization were reproduced in a computational model of WM injury. These findings provide new evidence linking cognition with WM via the reliance of neural synchronization on propagation of neural signals.SIGNIFICANCE STATEMENT By comparing brain tumor patients to healthy children, we establish that changes in the microstructure of the optic radiations and neural synchrony during visual attention predict reaction time. Furthermore, by testing the directionality of these links through statistical modeling and verifying our findings with computational modeling, we infer a causal relationship, namely that changes in white matter microstructure impact cognition in part by disturbing the ability of neural assemblies to synchronize. Together, our human imaging data and computer simulations show a fundamental connection between WM microstructure and neural synchronization that is critical for cognitive processing.

Origin of heterogeneous spiking patterns from continuously distributed ion channel densities: a computational study in spinal dorsal horn neurons.

KEY POINTS: Distinct spiking patterns may arise from qualitative differences in ion channel expression (i.e. when different neurons express distinct ion channels) and/or when quantitative differences in expression levels qualitatively alter the spike generation process. We hypothesized that spiking patterns in neurons of the superficial dorsal horn (SDH) of spinal cord reflect both mechanisms. We reproduced SDH neuron spiking patterns by varying densities of KV 1- and A-type potassium conductances. Plotting the spiking patterns that emerge from different density combinations revealed spiking-pattern regions separated by boundaries (bifurcations). This map suggests that certain spiking pattern combinations occur when the distribution of potassium channel densities straddle boundaries, whereas other spiking patterns reflect distinct patterns of ion channel expression. The former mechanism may explain why certain spiking patterns co-occur in genetically identified neuron types. We also present algorithms to predict spiking pattern proportions from ion channel density distributions, and vice versa. ABSTRACT: Neurons are often classified by spiking pattern. Yet, some neurons exhibit distinct patterns under subtly different test conditions, which suggests that they operate near an abrupt transition, or bifurcation. A set of such neurons may exhibit heterogeneous spiking patterns not because of qualitative differences in which ion channels they express, but rather because quantitative differences in expression levels cause neurons to operate on opposite sides of a bifurcation. Neurons in the spinal dorsal horn, for example, respond to somatic current injection with patterns that include tonic, single, gap, delayed and reluctant spiking. It is unclear whether these patterns reflect five cell populations (defined by distinct ion channel expression patterns), heterogeneity within a single population, or some combination thereof. We reproduced all five spiking patterns in a computational model by varying the densities of a low-threshold (KV 1-type) potassium conductance and an inactivating (A-type) potassium conductance and found that single, gap, delayed and reluctant spiking arise when the joint probability distribution of those channel densities spans two intersecting bifurcations that divide the parameter space into quadrants, each associated with a different spiking pattern. Tonic spiking likely arises from a separate distribution of potassium channel densities. These results argue in favour of two cell populations, one characterized by tonic spiking and the other by heterogeneous spiking patterns. We present algorithms to predict spiking pattern proportions based on ion channel density distributions and, conversely, to estimate ion channel density distributions based on spiking pattern proportions. The implications for classifying cells based on spiking pattern are discussed.

Using dynamic clamp to quantify pathological changes in the excitability of primary somatosensory neurons.

KEY POINTS: Primary somatosensory neurons normally respond to somatic depolarization with transient spiking but can switch to repetitive spiking under pathological conditions. This switch in spiking pattern reflects a qualitative change in spike initiation dynamics and contributes to the hyperexcitability associated with chronic pain. Neurons can be converted to repetitive spiking by adding a virtual conductance using dynamic clamp. By titrating the conductance to determine how much must be added to cause repetitive spiking, we found that small cells are more susceptible to switching (i.e. required less added conductance) than medium-large cells. By measuring how much less conductance is required to cause repetitive spiking when dynamic clamp was combined with other pathomimetic manipulations (e.g. application of inflammatory mediators), we measured how much each manipulation facilitated repetitive spiking. Our results suggest that many pathological factors facilitate repetitive spiking but that the switch to repetitive spiking requires the cumulative effect of many co-occurring factors. ABSTRACT: Primary somatosensory neurons become hyperexcitable in many chronic pain conditions. Hyperexcitability can include a switch from transient to repetitive spiking during sustained somatic depolarization. This switch results from diverse pathological processes that impact ion channel expression or function. Because multiple pathological processes co-occur, isolating how much each contributes to switching the spiking pattern is difficult. Our approach to this challenge involves adding a virtual sodium conductance via dynamic clamp. The magnitude of that conductance was titrated to determine the minimum required to enable rheobasic stimulation to evoke repetitive spiking. The minimum required conductance, termed g¯ Na ∗, was re-measured before and during manipulations designed to model various pathological processes in vitro. The reduction in g¯ Na ∗ caused by each pathomimetic manipulation reflects how much the modelled process contributes to switching the spiking pattern. We found that elevating extracellular potassium or applying inflammatory mediators reduced g¯ Na ∗ whereas direct hyperpolarization had no effect. Inflammatory mediators reduced g¯ Na ∗ more in medium-large (>30 µm diameter) neurons than in small (⩽30 µm diameter) neurons, but had equivalent effects in cutaneous and muscle afferents. The repetitive spiking induced by dynamic clamp was also found to differ between small and medium-large neurons, thus revealing latent differences in adaptation. Our study demonstrates a novel way to determine to what extent individual pathological factors facilitate repetitive spiking. Our results suggest that most factors facilitate but do not cause repetitive spiking on their own, and, therefore, that a switch to repetitive spiking results from the cumulative effect of many co-occurring factors.

Combined Changes in Chloride Regulation and Neuronal Excitability Enable Primary Afferent Depolarization to Elicit Spiking without Compromising its Inhibitory Effects.

The central terminals of primary afferent fibers experience depolarization upon activation of GABAA receptors (GABAAR) because their intracellular chloride concentration is maintained above electrochemical equilibrium. Primary afferent depolarization (PAD) normally mediates inhibition via sodium channel inactivation and shunting but can evoke spikes under certain conditions. Antidromic (centrifugal) conduction of these spikes may contribute to neurogenic inflammation while orthodromic (centripetal) conduction could contribute to pain in the case of nociceptive fibers. PAD-induced spiking is assumed to override presynaptic inhibition. Using computer simulations and dynamic clamp experiments, we sought to identify which biophysical changes are required to enable PAD-induced spiking and whether those changes necessarily compromise PAD-mediated inhibition. According to computational modeling, a depolarizing shift in GABA reversal potential (EGABA) and increased intrinsic excitability (manifest as altered spike initiation properties) were necessary for PAD-induced spiking, whereas increased GABAAR conductance density (gGABA) had mixed effects. We tested our predictions experimentally by using dynamic clamp to insert virtual GABAAR conductances with different EGABA and kinetics into acutely dissociated dorsal root ganglion (DRG) neuron somata. Comparable experiments in central axon terminals are prohibitively difficult but the biophysical requirements for PAD-induced spiking are arguably similar in soma and axon. Neurons from naïve (i.e. uninjured) rats were compared before and after pharmacological manipulation of intrinsic excitability, and against neurons from nerve-injured rats. Experimental data confirmed that, in most neurons, both predicted changes were necessary to yield PAD-induced spiking. Importantly, such changes did not prevent PAD from inhibiting other spiking or from blocking spike propagation. In fact, since the high value of gGABA required for PAD-induced spiking still mediates strong inhibition, we conclude that PAD-induced spiking does not represent failure of presynaptic inhibition. Instead, diminished PAD caused by reduction of gGABA poses a greater risk to presynaptic inhibition and the sensory processing that relies upon it.

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition.

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding.

Novel method to assess axonal excitability using channelrhodopsin-based photoactivation.

Measuring the excitability of individual axons is complicated by the prohibitive difficulty in obtaining intracellular recordings. Here, we present an innovative methodology that enables local excitability to be measured anywhere in a channelrhodopsin (ChR2)-expressing neuron. The approach hinges on activating ChR2 in a spatially and temporally precise manner while recording the resulting spike train from a remote site. We validated this approach in primary afferent neurons (PANs). Initial encoding of somatosensory stimuli relies on transduction of the physical stimulus into a receptor potential and transformation of the receptor potential into a spike train; the transformation process depends on the excitability of the most distal PAN endings but, as explained above, is extraordinarily difficult to study in situ using traditional methods. Using ChR2-based photoactivation, we show 1) that excitability differs between the distal endings and more proximal portions of PAN axons, 2) that the transformation process differs between PANs, and 3) that the transformation process is directly affected by inflammation. Beyond presenting an innovative method by which to study axonal excitability, this study has validated its utility in helping to decipher the earliest stages of somatosensory encoding.

Cooperativity between remote sites of ectopic spiking allows afterdischarge to be initiated and maintained at different locations.

Many symptoms of nerve damage arise from ectopic spiking caused by hyperexcitability. Ectopic spiking can originate at the site of axonal damage and elsewhere within affected neurons. This raises the question of whether localized damage elicits cell-wide changes in excitability and/or if localized changes in excitability can drive abnormal spiking at remote locations. Computer modeling revealed an example of the latter involving afterdischarge (AD)--stimulus-evoked spiking that outlasts stimulation. We found that AD originating in a hyperexcitable region of axon could shift to the soma where it was maintained. This repositioning of ectopic spike initiation was independent of distance between the two sites but relied on the rate and number of ectopic spikes originating from the first site. Nonlinear dynamical analysis of a reduced model demonstrated that properties which rendered the axonal site prone to initiating AD discouraged it from maintaining AD, whereas the soma had the inverse properties thus enabling the two sites to interact cooperatively. A first phase of AD originating in the axon could, by providing sufficient drive to trigger somatic AD, give way to a second phase of AD originating in the soma such that spiking continued when axonal AD failed. Ectopic spikes originating from the soma during phase 2 AD propagated successfully through the defunct site of axonal spike initiation. This novel mechanism whereby ectopic spiking at one site facilitates ectopic spiking at another site is likely to contribute to the chronification of hyperexcitability in conditions such as neuropathic pain.

Physiological Dynamics in Demyelinating Diseases: Unraveling Complex Relationships through Computer Modeling.

Despite intense research, few treatments are available for most neurological disorders. Demyelinating diseases are no exception. This is perhaps not surprising considering the multifactorial nature of these diseases, which involve complex interactions between immune system cells, glia and neurons. In the case of multiple sclerosis, for example, there is no unanimity among researchers about the cause or even which system or cell type could be ground zero. This situation precludes the development and strategic application of mechanism-based therapies. We will discuss how computational modeling applied to questions at different biological levels can help link together disparate observations and decipher complex mechanisms whose solutions are not amenable to simple reductionism. By making testable predictions and revealing critical gaps in existing knowledge, such models can help direct research and will provide a rigorous framework in which to integrate new data as they are collected. Nowadays, there is no shortage of data; the challenge is to make sense of it all. In that respect, computational modeling is an invaluable tool that could, ultimately, transform how we understand, diagnose, and treat demyelinating diseases.

Similar excitability through different sodium channels and implications for the analgesic efficacy of selective drugs.

Nociceptive sensory neurons convey pain-related signals to the CNS using action potentials. Loss-of-function mutations in the voltage-gated sodium channel NaV1.7 cause insensitivity to pain (presumably by reducing nociceptor excitability) but clinical trials seeking to treat pain by inhibiting NaV1.7 pharmacologically have struggled. This may reflect the variable contribution of NaV1.7 to nociceptor excitability. Contrary to claims that NaV1.7 is necessary for nociceptors to initiate action potentials, we show that nociceptors can achieve similar excitability using different combinations of NaV1.3, NaV1.7, and NaV1.8. Selectively blocking one of those NaV subtypes reduces nociceptor excitability only if the other subtypes are weakly expressed. For example, excitability relies on NaV1.8 in acutely dissociated nociceptors but responsibility shifts to NaV1.7 and NaV1.3 by the fourth day in culture. A similar shift in NaV dependence occurs in vivo after inflammation, impacting ability of the NaV1.7-selective inhibitor PF-05089771 to reduce pain in behavioral tests. Flexible use of different NaV subtypes exemplifies degeneracy - achieving similar function using different components - and compromises reliable modulation of nociceptor excitability by subtype-selective inhibitors. Identifying the dominant NaV subtype to predict drug efficacy is not trivial. Degeneracy at the cellular level must be considered when choosing drug targets at the molecular level.

Absence of paresthesia during high-rate spinal cord stimulation reveals importance of synchrony for sensations evoked by electrical stimulation.

Electrically activating mechanoreceptive afferents inhibits pain. However, paresthesia evoked by spinal cord stimulation (SCS) at 40-60 Hz becomes uncomfortable at high pulse amplitudes, limiting SCS "dosage." Kilohertz-frequency SCS produces analgesia without paresthesia and is thought, therefore, not to activate afferent axons. We show that paresthesia is absent not because axons do not spike but because they spike asynchronously. In a pain patient, selectively increasing SCS frequency abolished paresthesia and epidurally recorded evoked compound action potentials (ECAPs). Dependence of ECAP amplitude on SCS frequency was reproduced in pigs, rats, and computer simulations and is explained by overdrive desynchronization: spikes desychronize when axons are stimulated faster than their refractory period. Unlike synchronous spikes, asynchronous spikes fail to produce paresthesia because their transmission to somatosensory cortex is blocked by feedforward inhibition. Our results demonstrate how stimulation frequency impacts synchrony based on axon properties and how synchrony impacts sensation based on circuit properties.