Search

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 pathological insults. To validate our model, we verified that it responded to 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 pathological SDH circuit function.Significance StatementWe developed a multiscale computer model of the posterior part of spinal cord gray matter (spinal dorsal horn), involved in perception of 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.

Pain in rodents is often inferred from their withdrawal to noxious stimulation, using the threshold stimulus intensity or response latency to quantify pain sensitivity. This usually involves applying stimuli by hand and measuring responses by eye, which limits reproducibility and throughput to the detriment of preclinical pain research. Here, we describe a device that standardizes and automates pain testing by providing computer-controlled aiming, stimulation, and response measurement. Optogenetic and thermal stimuli are applied to the hind paw using blue and infrared light, respectively. Red light delivered through the same light path assists with aiming, and changes in its reflectance off the paw are used to measure paw withdrawal latency with millisecond precision at a fraction of the cost and data processing associated with high-speed video. Using standard video, aiming was automated by training a neural network to recognize the paws and move the stimulator using motorized linear actuators. Real-time data processing allows for closed-loop control of stimulus initiation and termination. We show that stimuli delivered with this device are significantly less variable than hand-delivered stimuli, and that reducing stimulus variability is crucial for resolving stimulus-dependent variations in withdrawal. Slower stimulus waveforms whose stable delivery is made possible with this device reveal details not evident with typical photostimulus pulses. Moreover, the substage video reveals a wealth of “spontaneous” behaviors occurring before and after stimulation that can considered alongside withdrawal metrics to better assess the pain experience. Automation allows comprehensive testing to be standardized and carried out efficiently.

Spinal cord stimulation (SCS) reduces chronic pain. Conventional (40-60 Hz) SCS engages spinal inhibitory mechanisms by activating low-threshold mechanoreceptive afferents with axons in the dorsal columns (DCs). But activating DC axons typically causes a buzzing sensation (paresthesia) that can be uncomfortable. Kilohertz-frequency (1-10 kHz) SCS produces analgesia without paresthesia and is thought, therefore, not to activate DC axons, leaving its mechanism unclear. Here we show in rats that kilohertz-frequency SCS activates DC axons but causes them to spike less synchronously than conventional SCS. Spikes desynchronize because axons entrain irregularly when stimulated at intervals shorter than their refractory period, a phenomenon we call overdrive desynchronization. Effects of overdrive desynchronization on evoked compound action potentials were verified in simulations, rats, pigs, and a chronic pain patient. Whereas synchronous spiking in DC axons is necessary for paresthesia, asynchronous spiking is sufficient to produce analgesia. Asynchronous activation of DC axons thus produces paresthesia-free analgesia.

Transient receptor potential canonical 4 (TRPC4) is a receptor-operated cation channel codependent on both the Gq/11–phospholipase 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 protein–activated 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/11–Gi/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.

The axon initial segment (AIS) converts graded depolarization into all-or-none spikes that are transmitted by the axon to downstream neurons. Analog-to-digital transduction and digital signal transmission call for distinct spike initiation properties (filters) and those filters should, therefore, differ between the AIS and distal axon. Here we show that unlike the AIS, which spikes repetitively during sustained depolarization, the axon spikes transiently and only if depolarization reaches threshold before KV1 channels activate. Rate of depolarization is critical. This was shown by optogenetically evoking spikes in the distal axon of CA1 pyramidal neurons using different photostimulus waveforms and pharmacological conditions while recording antidromically propagated spikes at the soma, thus circumventing the prohibitive difficulty of patching intact axons. Computational modeling shows that KV1 channels in the axon implement a high-pass filter that is matched to the axial current waveform associated with spike propagation, thus maximizing the signal-to-noise ratio to ensure high-fidelity transmission of spike-based signals.

Cortical neurons receive mixed information from collective spiking activities of primary sensory neurons in response to a sensory stimulus. A recent study demonstrated that the time underlying the onset-offset of a tactile stimulus and its varying intensity can be respectively represented by 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 can perform two different functions, namely, temporal- and rate-coding, simultaneously.

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 (100-600 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 andin vitroexperiments in which 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 physiological noise induces irregular skipping without disrupting phase locking, as required for temporal coding. This occurs because the reliability and precision of spikes evoked by small- amplitude, fast-onset signals are differentially sensitive to noise. Simulations confirmed that differences in stimulus intensity and frequency can be well discriminated based on differences in spike rate or timing, respectively, but only in the presence of noise. Our results show that multiplexed coding by S1 pyramidal neurons is facilitated rather than degraded by physiological levels of noise. In fact, multiplexing is optimal under physiologically noisy conditions.

Summary Induced pluripotent stem cells (iPSC) derived from healthy individuals are important controls for disease-modeling studies. Here we apply precision health to create a high-quality resource of control iPSCs. Footprint-free lines were reprogrammed from four volunteers of the Personal Genome Project Canada (PGPC). Multilineage-directed differentiation efficiently produced functional cortical neurons, cardiomyocytes and hepatocytes. Pilot users demonstrated versatility by generating kidney organoids, T lymphocytes, and sensory neurons. A frameshift knockout was introduced into MYBPC3 and these cardiomyocytes exhibited the expected hypertrophic phenotype. Whole-genome sequencing-based annotation of PGPC lines revealed on average 20 coding variants. Importantly, nearly all annotated PGPC and HipSci lines harbored at least one pre-existing or acquired variant with cardiac, neurological, or other disease associations. Overall, PGPC lines were efficiently differentiated by multiple users into cells from six tissues for disease modeling, and variant-preferred healthy control lines were identified for specific disease settings., Graphical Abstract, Highlights • Precision health resource of high-quality control iPSC lines for disease modeling • Versatile differentiation into six functional cell types shown by resource users • CRISPR gene editing reveals expected phenotype of cardiomyopathy model • Variant annotation identified preferred lines for neurologic and cardiac disease, Ellis, Scherer, and colleagues apply precision health to upgrade iPSC quality for disease modeling. The resource provides control lines from four healthy individuals, clinical annotation of whole-genome variants, and identification of variant-preferred lines for neurologic and cardiac disease. Resource users demonstrated versatile differentiation into functional cells from six tissues, and CRISPR-edited cells phenocopied a cardiomyopathy model.

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. Recordingin vivofrom 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 (SIGNIFICANCE STATEMENTThe 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 andin vitroexperiments. Here, recordingin 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.

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.

The lionfish (Pterois volitans) is a venomous invasive species found in the Caribbean and Northwestern Atlantic. It poses a growing health problem because of the increase in frequency of painful stings, for which no treatment or antidote exists, and the long-term disability caused by the pain. Understanding the venom's algogenic properties can help identify better treatment for these envenomations. In this study, we provide the first characterization of the pain and inflammation caused by lionfish venom and examine the mechanisms through which it causes pain using a combination of in vivo and in vitro approaches including behavioral, physiological, calcium imaging, and electrophysiological testing. Intraplantar injections of the venom produce a significant increase in pain behavior, as well as a marked increase in mechanical sensitivity for up to 24 hours after injection. The algogenic substance(s) are heat-labile peptides that cause neurogenic inflammation at the site of injection and induction of Fos and microglia activation in the superficial layers of the dorsal horn. Finally, calcium imaging and electrophysiology experiments show that the venom acts predominantly on nonpeptidergic, TRPV1-negative, nociceptors, a subset of neurons implicated in sensing mechanical pain. These data provide the first characterization of the pain and inflammation caused by lionfish venom, as well as the first insight into its possible cellular mechanism of action.

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.

Primary afferents transduce environmental stimuli into electrical activity that is transmitted centrally to be decoded into corresponding sensations. However, it remains unknown how afferent populations encode different somatosensory inputs. To address this, we performed two-photon Ca2+ imaging from thousands of dorsal root ganglion (DRG) neurons in anesthetized mice while applying mechanical and thermal stimuli to hind paws. We found that approximately half of all neurons are polymodal and that heat and cold are encoded very differently. As temperature increases, more heating-sensitive neurons are activated, and most individual neurons respond more strongly, consistent with graded coding at population and single-neuron levels, respectively. In contrast, most cooling-sensitive neurons respond in an ungraded fashion, inconsistent with graded coding and suggesting combinatorial coding, based on which neurons are co-activated. Although individual neurons may respond to multiple stimuli, our results show that different stimuli activate distinct combinations of diversely tuned neurons, enabling rich population-level coding.

Background Kilohertz-frequency electric field stimulation (kEFS) applied to the spinal cord can reduce chronic pain without causing the buzzing sensation (paresthesia) associated with activation of dorsal column fibers. This suggests that high-rate spinal cord stimulation (SCS) has a mode of action distinct from conventional, parasthesia-based SCS. A recent study reported that kEFS hyperpolarizes spinal neurons, yet this potentially transformative mode of action contradicts previous evidence that kEFS induces depolarization and was based on patch clamp recordings whose accuracy in the presence of kEFS has not been verified. Objectives We sought to elucidate the basis for kEFS-induced hyperpolarization and to validate the effects of kEFS observed in patch clamp recordings by comparing with independent optical methods. Methods Using patch clamp electrophysiology and voltage-sensitive dye (VSD) imaging, we measured the response to kEFS applied in vitro to hippocampal and spinal neurons. Results The kEFS-induced hyperpolarization observed with current clamp recordings was corroborated by VSD imaging and rheobase measurements in patched neurons. However, no hyperpolarization was observed when imaging unpatched neurons or when recording with a voltage-follower amplifier rather than with a patch clamp amplifier (PCA). We found that EFS induced an artifactual current in PCAs that was injected back into current clamped neurons. The artifactual current induced by single, charge-balanced EFS pulses caused modest hyperpolarization, but these unitary hyperpolarizations accumulated when EFS pulses were repeated at kilohertz frequencies. Conclusion Our results rule out hyperpolarization as the mechanism underlying kEFS-mediated analgesia and highlight the risk of recording artifacts caused by extracellular electrical stimulation.

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.

Neuropathic pain is a debilitating condition caused by the abnormal processing of somatosensory input. Synaptic inhibition in the spinal dorsal horn plays a key role in that processing. Mechanical allodynia – the misperception of light touch as painful – occurs when inhibition is compromised. Disinhibition is due primarily to chloride dysregulation caused by hypofunction of the potassium-chloride co-transporter KCC2. Here we show, in rats, that excitatory neurons are disproportionately affected. This is not because chloride is differentially dysregulated in excitatory and inhibitory neurons, but, rather, because excitatory neurons rely more heavily on inhibition to counterbalance strong excitation. Receptive fields in both cell types have a center-surround organization but disinhibition unmasks more excitatory input to excitatory neurons. Differences in intrinsic excitability also affect how chloride dysregulation affects spiking. These results deepen understanding of how excitation and inhibition are normally balanced in the spinal dorsal horn, and how their imbalance disrupts somatosensory processing.

SummaryInduced Pluripotent Stem Cells (iPSC) derived from healthy individuals are important controls for disease modeling studies. To create a resource of genetically annotated iPSCs, we reprogrammed footprint-free lines from four volunteers in the Personal Genome Project Canada (PGPC). Multilineage directed differentiation efficiently produced functional cortical neurons, cardiomyocytes and hepatocytes. Pilot users further demonstrated line versatility by generating kidney organoids, T-lymphocytes and sensory neurons. A frameshift knockout was introduced into MYBPC3 and these cardiomyocytes exhibited the expected hypertrophic phenotype. Whole genome sequencing (WGS) based annotation of PGPC lines revealed on average 20 coding variants. Importantly, nearly all annotated PGPC and HipSci lines harboured at least one pre-existing or acquired variant with cardiac, neurological or other disease associations. Overall, PGPC lines were efficiently differentiated by multiple users into cell types found in six tissues for disease modeling, and clinical annotation highlighted variant-preferred lines for use as unaffected controls in specific disease settings.

Significance The nervous system processes phenomenal amounts of information. This processing must be conducted efficiently. In telecommunications systems, efficiency is increased by transmitting multiple signals through a single communication channel, or multiplexing. Neurons also multiplex. Here, we demonstrate a strategy for multiplexing different features of aperiodic stimuli: Cortical neurons use the rate of asynchronous spiking to encode stimulus intensity while using the timing of synchronous spikes to encode abrupt changes in stimulus intensity. This is possible because high-contrast features (e.g., edges) evoke spikes that transiently synchronize across neurons, whereas low-contrast features evoke sustained asynchronous spiking whose rate is proportional to stimulus intensity. Differentially synchronized spiking evoked in the same neurons by different stimulus features enables the formation of multiplexed representations., 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.

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. [Image: see text]

Fast synaptic inhibition relies on tight regulation of intracellular Cl(-). Chloride dysregulation is implicated in several neurological and psychiatric disorders. Beyond mere disinhibition, the consequences of Cl(-) dysregulation are multifaceted and best understood in terms of a dynamical system involving complex interactions between multiple processes operating on many spatiotemporal scales. This dynamical perspective helps explain many unintuitive manifestations of Cl(-) dysregulation. Here we discuss how taking into account dynamical regulation of intracellular Cl(-) is important for understanding how synaptic inhibition fails, how to best detect that failure, why Cl(-) regulation is energetically so expensive, and the overall consequences for therapeutics.

A new therapeutic option for treating arthritis pain., Chronic joint pain such as mechanical allodynia is the most debilitating symptom of arthritis, yet effective therapies are lacking. We identify the pannexin-1 (Panx1) channel as a therapeutic target for alleviating mechanical allodynia, a cardinal sign of arthritis. In rats, joint pain caused by intra-articular injection of monosodium iodoacetate (MIA) was associated with spinal adenosine 5′-triphosphate (ATP) release and a microglia-specific up-regulation of P2X7 receptors (P2X7Rs). Blockade of P2X7R or ablation of spinal microglia prevented and reversed mechanical allodynia. P2X7Rs drive Panx1 channel activation, and in rats with mechanical allodynia, Panx1 function was increased in spinal microglia. Specifically, microglial Panx1-mediated release of the proinflammatory cytokine interleukin-1β (IL-1β) induced mechanical allodynia in the MIA-injected hindlimb. Intrathecal administration of the Panx1-blocking peptide 10panx suppressed the aberrant discharge of spinal laminae I-II neurons evoked by innocuous mechanical hindpaw stimulation in arthritic rats. Furthermore, mice with a microglia-specific genetic deletion of Panx1 were protected from developing mechanical allodynia. Treatment with probenecid, a clinically used broad-spectrum Panx1 blocker, resulted in a striking attenuation of MIA-induced mechanical allodynia and normalized responses in the dynamic weight-bearing test, without affecting acute nociception. Probenecid reversal of mechanical allodynia was also observed in rats 13 weeks after anterior cruciate ligament transection, a model of posttraumatic osteoarthritis. Thus, Panx1-targeted therapy is a new mechanistic approach for alleviating joint pain.

Summary: The behavioral features of neuropathic pain are not sexually dimorphic despite sex differences in the underlying neuroimmune signaling. This raises questions about whether neural processing is comparably altered. Here, we test whether the K+-Cl− co-transporter KCC2, which regulates synaptic inhibition, plays an equally important role in development of neuropathic pain in male and female rodents. Past studies on KCC2 tested only males. We find that inhibiting KCC2 in uninjured animals reproduces behavioral and electrophysiological features of neuropathic pain in both sexes and, consistent with equivalent injury-induced downregulation of KCC2, that counteracting chloride dysregulation reverses injury-induced behavioral and electrophysiological changes in both sexes. These findings demonstrate that KCC2 downregulation contributes equally to pain hypersensitivity in males and females. Whereas diverse (and sexually dimorphic) mechanisms regulate KCC2, regulation of intracellular chloride relies almost exclusively on KCC2. Directly targeting KCC2 thus remains a promising strategy for treatment of neuropathic pain in both sexes. : Neuropathic pain arises in males and females through distinct neuroimmune signaling. Yet the behavioral (or clinical) features of neuropathic pain are not sexually dimorphic. Mapplebeck et al. demonstrate that KCC2—though regulated in multiple, sex-specific ways—is uniquely responsible for the synaptic disinhibition causing neuropathic pain in both sexes. Keywords: K+-Cl− co-transporter KCC2, sex differences, degeneracy, neuropathic pain, disinhibition, GABA, glycine, BDNF

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 disease

Synaptic inhibition plays a key role in processing somatosensory information. Blocking inhibition at the spinal level is sufficient to produce mechanical allodynia, and many neuropathic pain conditions are associated with reduced inhibition. Disinhibition of spinal neurons can arise through decreased GABAA/glycine receptor activation or through dysregulation of intracellular chloride. We hypothesized that these distinct disinhibitory mechanisms, despite all causing allodynia, are differentially susceptible to therapeutic intervention. Specifically, we predicted that reducing bicarbonate efflux by blocking carbonic anhydrase with acetazolamide (ACTZ) would counteract disinhibition caused by chloride dysregulation without affecting normal inhibition or disinhibition caused by GABAA/glycine receptor blockade. To test this, responses to innocuous tactile stimulation were recorded in vivo from rat superficial dorsal horn neurons before and after different forms of pharmacological disinhibition and again after application of ACTZ. Blocking GABAA or glycine receptors caused hyperresponsiveness equivalent to that caused by blocking the potassium chloride cotransporter KCC2, but, consistent with our predictions, only disinhibition caused by KCC2 blockade was counteracted by ACTZ. ACTZ did not alter responses of neurons with intact inhibition. As pathological downregulation of KCC2 is triggered by brain-derived neurotrophic factor, we also confirmed that ACTZ was effective against brain-derived neurotrophic factor-induced hyperresponsiveness. Our results argue that intrathecal ACTZ has antiallodynic effects only if allodynia arises through chloride dysregulation; therefore, behavioral evidence that ACTZ is antiallodynic in nerve-injured animals affirms the contribution of chloride dysregulation as a key pathological mechanism. Although different disinhibitory mechanisms are not mutually exclusive, these results demonstrate that their relative contribution dictates which specific therapies will be effective.

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.

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.

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 KNeurons 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 (K

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.

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 STATEMENTNeurons 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.

Noxious stimuli usually cause pain and pain usually arises from noxious stimuli, but exceptions to these apparent truisms are the basis for clinically important problems and provide valuable insight into the neural code for pain. In this Review, we discuss how painful sensations arise. We argue that, although primary somatosensory afferents are tuned to specific stimulus features, natural stimuli often activate more than one type of afferent. Manipulating coactivation patterns can alter perception in ways that argue against each type of afferent acting independently (as expected for strictly labeled lines), suggesting instead that signals conveyed by different types of afferents interact. Deciphering the central circuits that mediate those interactions is critical for explaining the generation and modulation of neural signals that ultimately elicit pain. The advent of genetic and optical dissection techniques promise to dramatically accelerate progress toward this goal, which will facilitate the rational design of future pain therapeutics.

The somatosensory system is responsible for processing proprioceptive, thermal, touch, and pain information from the body surface and internal tissues. The skin is in fact the largest sensory organ in the body. Braille readers demonstrate a capacity to use discriminative touch in ways most of us will never develop, yet all of us can appreciate different textures. Somatosensation provides sensory feedback which, although mostly subconscious, is crucial for many motor activities. Among somatic modalities, pain is notable for attracting our immediate attention. Normal pain caused by intense (noxious) stimuli alerts us to danger and thus serves an important adaptive role, and the heightened sensitivity associated with inflammatory pain facilitates our recovery from injury. But abnormal processing of somatosensory information can result in chronic neuropathic pain, a disease in its own right. This chapter addresses normal somatosensation and how its disruption can result in chronic pain.

Pain, itch, heat, cold, and touch represent different percepts arising from somatosensory input. How stimuli give rise to these percepts has been debated for over a century. Recent work supports the view that primary afferents are highly specialized to transduce and encode specific stimulus modalities. However, cross-modal interactions (e.g. inhibition or exacerbation of pain by touch) support convergence rather than specificity in central circuits. We outline how peripheral specialization together with central convergence could enable spinal microcircuits to combine inputs from distinctly specialized, co-activated afferents and to modulate the output signals thus formed through computations like normalization. These issues will be discussed alongside recent advances in our understanding of microcircuitry in the superficial dorsal horn.

Synaptic inhibition by GABAAreceptors requires a transmembrane chloride gradient. Hyperpolarization or shunting results from outward current produced by chloride flowing down this gradient, into the cell. Chloride influx necessarily depletes the chloride gradient. Therefore, mechanisms that replenish the gradient (by reducing intracellular chloride concentration, [Cl−]i) are crucial for maintaining the efficacy of GABAAreceptor-mediated inhibition. ClC-2 is an inward-rectifying chloride channel that is thought to help extrude chloride because inward rectification should, in principle, allow ClC-2 to act as a one-way chloride exit valve. But chloride efflux via ClC-2 nevertheless requires an appropriate driving force. Using computer modeling, we reproduced voltage-clamp experiments showing chloride efflux via ClC-2, but testing the same model under physiological conditions revealed that ClC-2 normally leaks chloride into the cell. The discrepancy is explained by the driving force conditions that exist under artificial versus physiological conditions, and by the fact that ClC-2 rectification is neither complete nor instantaneous. Thus, contrary to previous assertions that ClC-2 helps maintain synaptic inhibition by lowering [Cl−]i, our simulations show that ClC-2 mediates chloride influx, thus producing outward current and directly reducing excitability. To test how ClC-2 functions in real neurons, we used dynamic clamp to insert virtual ClC-2 channels into rat CA1 pyramidal cells with and without native ClC-2 channels blocked. Experiments confirmed that ClC-2 reduces spiking independently of inhibitory synaptic transmission. Our results highlight the importance of considering driving force when inferring how a channel functions under physiological conditions.