Unique features of action potential initiation in cortical neurons

Investigating the role of axonal ion channel cooperativity in action potential dynamics: Studies on Hodgkin-Huxley's model

Voltage-gated ion channels play an important role in generating action potential in neurons. These ion channels are found to be in localized cluster form on the axonal membrane surface and behave cooperatively. However, in Hodgkin & Huxley's model of action potential the ion channels are considered to function independently. According to some recent reports, the activity of an ion channel is influenced by the neighboring ion channels' activities. We have modified the Hodgkin-Huxley's model based on our previous studies on cooperativity among ion channels. Computational analysis of the proposed model shows that the initiation of the action potential, amplitude and hyperpolarization are affected significantly by the cooperative interactions among the voltage-gated ion channels present on the axonal membrane surface. These results are qualitatively supported by the existing experimental facts.

Behavioral control through the direct, focal silencing of neuronal activity

The ability to optically stimulate and inhibit neurons has revolutionized neuroscience research. Here, we present a direct, potent, user-friendly chemical approach for optically silencing neurons. We have rendered saxitoxin (STX), a naturally occurring paralytic agent, transiently inert through chemical protection with a previously undisclosed nitrobenzyl-derived photocleavable group. Exposing the caged toxin, STX-bpc, to a brief (5 ms) pulse of light effects rapid release of a potent STX derivative and transient, spatially precise blockade of voltage-gated sodium channels (NaVs). We demonstrate the efficacy of STX-bpc for parametrically manipulating action potentials in mammalian neurons and brain slice. Additionally, we show the effectiveness of this reagent for silencing neural activity by dissecting sensory-evoked swimming in larval zebrafish. Photo-uncaging of STX-bpc is a straightforward method for non-invasive, reversible, spatiotemporally precise neural silencing without the need for genetic access, thus removing barriers for comparative research.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

A review: oligodendrocytes in neuronal axonal conduction and methods for enhancing their performance

OBJECTIVES

This review explores the vital role of oligodendrocytes in axon myelination and efficient neuronal transmission and the impact of dysfunction resulting from neurotransmitter deficiencies related disorders. Furthermore, the review also provides insight into the potential of bionanotechnology for addressing neurodegenerative diseases by targeting oligodendrocytes.

METHODS

A review of literature in the field was conducted using Google scholar. Systematic searches were performed to identify relevant studies and reviews addressing the role of oligodendrocytes in neural function, the influence of neurotransmitters on oligodendrocyte differentiation, and the potential of nanotechnology-based strategies for targeted therapy of oligodendrocytes.

RESULTS

This review indicates the mechanisms underlying oligodendrocyte differentiation and the influence of neurotransmitters on this process. The importance of action potentials and neurotransmission in neural function and the susceptibility of damaged nerve axons to ischemic or toxic damage is provided in detail. The potential of bionanotechnology for targeting neurodegenerative diseases using nanotechnology-based strategies, including polymeric, lipid-based, inorganic, organic, and biomimetic nanoparticles, suggests better management of neurodegenerative disorders.

CONCLUSION

While nanotechnology-based biomaterials show promise for targeted oligodendrocyte therapy in addressing neurodegenerative disorders linked to oligodendrocyte dysfunction, encapsulating neuroprotective agents within nanoparticles offers additional advantages. Nano-based delivery systems effectively protect drugs from degradation and prolong their therapeutic effects, holding promise in overcoming the blood-brain barrier by facilitating drug transport. However, a multifaceted approach is essential to enhance oligodendrocyte differentiation, promote myelin repair, and facilitate myelin dynamics with reduced toxicity. Further research is needed to elucidate the optimal therapeutic approaches and enhance patient outcomes.

Loss of Postnatal Arx Transcriptional Activity in Parvalbumin Interneurons Reveals Non-cell Autonomous Disturbances in CA1 Pyramidal Cells

Maintenance of proper electrophysiological and connectivity profiles in the adult brain may be a perturbation point in neurodevelopmental disorders (NDDs). How these profiles are maintained within mature circuits is unclear. We recently demonstrated that postnatal ablation of the Aristaless (Arx) homeobox gene in parvalbumin interneurons (PVIs) alone led to dysregulation of their transcriptome and alterations in their functional as well as network properties in the hippocampal cornu Ammoni first region (CA1). Here, we characterized CA1 pyramidal cells (PCs) responses in this conditional knockout (CKO) mouse to further understand the circuit mechanisms by which postnatal Arx expression regulates mature CA1 circuits. Field recordings of network excitability showed that CA1 PC ensembles were less excitable in response to unpaired stimulations but exhibited enhanced excitability in response to paired-pulse stimulations. Whole-cell voltage clamp recordings revealed a significant increase in the frequency of spontaneous inhibitory postsynaptic currents onto PCs. In contrast, excitatory drive from evoked synaptic transmission was reduced while that of inhibitory synaptic transmission was increased. Current clamp recordings showed increase excitability in several sub- and threshold membrane properties that correlated with an increase in the conductance of Na+ current. Our data suggest that, in addition to cell-autonomous disruption in PVIs, loss of Arx postnatal transcriptional activity in PVIs led to complex dysfunctions in PCs in CA1 microcircuits. These non-cell autonomous effects are likely the product of breakdown in feedback and/or feedforward processes and should be considered as fundamental contributors to the circuit mechanisms of NDDs such as Arx-linked early-onset epileptic encephalopathies.

Synaptic alterations associated with disrupted sensory encoding in a mouse model of tauopathy

Synapse loss is currently the best biological correlate of cognitive decline in Alzheimer's disease and other tauopathies. Synapses seem to be highly vulnerable to tau-mediated disruption in neurodegenerative tauopathies. However, it is unclear how and when this leads to alterations in function related to the progression of tauopathy and neurodegeneration. We used the well-characterized rTg4510 mouse model of tauopathy at 5-6 months and 7-8 months of age, respectively, to study the functional impact of cortical synapse loss. The earlier age was used as a model of prodromal tauopathy, with the later age corresponding to more advanced tau pathology and presumed progression of neurodegeneration. Analysis of synaptic protein expression in the somatosensory cortex showed significant reductions in synaptic proteins and NMDA and AMPA receptor subunit expression in rTg4510 mice. Surprisingly, in vitro whole-cell patch clamp electrophysiology from putative pyramidal neurons in layer 2/3 of the somatosensory cortex suggested no functional alterations in layer 4 to layer 2/3 synaptic transmission at 5-6 months. From these same neurons, however, there were alterations in dendritic structure, with increased branching proximal to the soma in rTg4510 neurons. Therefore, in vivo whole-cell patch clamp recordings were utilized to investigate synaptic function and integration in putative pyramidal neurons in layer 2/3 of the somatosensory cortex. These recordings revealed a significant increase in the peak response to synaptically driven sensory stimulation-evoked activity and a loss of temporal fidelity of the evoked signal to the input stimulus in rTg4510 neurons. Together, these data suggest that loss of synapses, changes in receptor expression and dendritic restructuring may lead to alterations in synaptic integration at a network level. Understanding these compensatory processes could identify targets to help delay symptomatic onset of dementia.

Striatal Neurons Are Recruited Dynamically into Collective Representations of Self-Initiated and Learned Actions in Freely Moving Mice

Striatal spiny projection neurons are hyperpolarized-at-rest (HaR) and driven to action potential threshold by a small number of powerful inputs-an input-output configuration that is detrimental to response reliability. Because the striatum is important for habitual behaviors and goal-directed learning, we conducted a microendoscopic imaging in freely moving mice that express a genetically encoded Ca2+ indicator sparsely in striatal HaR neurons to evaluate their response reliability during self-initiated movements and operant conditioning. The sparse expression was critical for longitudinal studies of response reliability, and for studying correlations among HaR neurons while minimizing spurious correlations arising from contamination by the background signal. We found that HaR neurons are recruited dynamically into action representation, with distinct neuronal subsets being engaged in a moment-by-moment fashion. While individual neurons respond with little reliability, the population response remained stable across days. Moreover, we found evidence for the temporal coupling between neuronal subsets during conditioned (but not innate) behaviors.

Voltage sensors of a Na+ channel dissociate from the pore domain and form inter-channel dimers in the resting state

Understanding voltage-gated sodium (Nav) channels is significant since they generate action potential. Nav channels consist of a pore domain (PD) and a voltage sensor domain (VSD). All resolved Nav structures in different gating states have VSDs that tightly interact with PDs; however, it is unclear whether VSDs attach to PDs during gating under physiological conditions. Here, we reconstituted three different voltage-dependent NavAb, which is cloned from Arcobacter butzleri, into a lipid membrane and observed their structural dynamics by high-speed atomic force microscopy on a sub-second timescale in the steady state. Surprisingly, VSDs dissociated from PDs in the mutant in the resting state and further dimerized to form cross-links between channels. This dimerization would occur at a realistic channel density, offering a potential explanation for the facilitation of positive cooperativity of channel activity in the rising phase of the action potential.

Single-compartment model of a pyramidal neuron, fitted to recordings with current and conductance injection

For single neuron models, reproducing characteristics of neuronal activity such as the firing rate, amplitude of spikes, and threshold potentials as functions of both synaptic current and conductance is a challenging task. In the present work, we measure these characteristics of regular spiking cortical neurons using the dynamic patch-clamp technique, compare the data with predictions from the standard Hodgkin-Huxley and Izhikevich models, and propose a relatively simple five-dimensional dynamical system model, based on threshold criteria. The model contains a single sodium channel with slow inactivation, fast activation and moderate deactivation, as well as, two fast repolarizing and slow shunting potassium channels. The model quantitatively reproduces characteristics of steady-state activity that are typical for a cortical pyramidal neuron, namely firing rate not exceeding 30 Hz; critical values of the stimulating current and conductance which induce the depolarization block not exceeding 80 mV and 3, respectively (both values are scaled by the resting input conductance); extremum of hyperpolarization close to the midpoint between spikes. The analysis of the model reveals that the spiking regime appears through a saddle-node-on-invariant-circle bifurcation, and the depolarization block is reached through a saddle-node bifurcation of cycles. The model can be used for realistic network simulations, and it can also be implemented within the so-called mean-field, refractory density framework.

Enhancement of neuronal excitability in the medial prefrontal cortex following prenatal morphine exposure

The clinical use and abuse of opioids during human pregnancy have been widely reported. Several studies have demonstrated that opioids cross the placenta in rats during late gestation, and prenatal morphine exposure has been shown to have negative outcomes in cognitive function. The medial prefrontal cortex (mPFC) is believed to play a crucial role in cognitive processes, motivation, and emotion, integrating neural information from several brain areas and sending converted information to other structures. Dysfunctions in this area have been observed in numerous psychiatric and neurological disorders, including addiction. This current study aimed to compare the electrophysiological properties of mPFC neurons in rat offspring prenatally exposed to morphine. Pregnant rats were injected with morphine or saline twice a day from gestational days 11-18. Whole-cell patch-clamp recordings were performed in male offspring on postnatal days 14-18. All recordings were obtained in current-clamp configuration from mPFC pyramidal neurons to assess their electrophysiological properties. The results revealed that prenatal exposure to morphine shifted the resting membrane potential (RMP) to less negative voltages and increased input resistance and duration of action potentials. However, the amplitude, rise slope, and afterhyperpolarization (AHP) amplitude of the first elicited action potentials were significantly decreased in rats prenatally exposed to morphine. Moreover, the sag voltage ratio was significantly decreased in the prenatal morphine group. Our results suggest that the changes observed in the electrophysiological properties of mPFC neurons indicate an elevation in neuronal excitability following prenatal exposure to morphine.

A biophysical perspective on the resilience of neuronal excitability across timescales

Neuronal membrane excitability must be resilient to perturbations that can take place over timescales from milliseconds to months (or even years in long-lived animals). A great deal of attention has been paid to classes of homeostatic mechanisms that contribute to long-term maintenance of neuronal excitability through processes that alter a key structural parameter: the number of ion channel proteins present at the neuronal membrane. However, less attention has been paid to the self-regulating 'automatic' mechanisms that contribute to neuronal resilience by virtue of the kinetic properties of ion channels themselves. Here, we propose that these two sets of mechanisms are complementary instantiations of feedback control, together enabling resilience on a wide range of temporal scales. We further point to several methodological and conceptual challenges entailed in studying these processes - both of which involve enmeshed feedback control loops - and consider the consequences of these mechanisms of resilience.

A detailed analysis of single-channel Nav 1.5 recordings does not reveal any cooperative gating

Cardiac voltage-gated sodium (Na+ ) channels (Nav 1.5) are crucial for myocardial electrical excitation. Recent studies based on single-channel recordings have suggested that Na+ channels interact functionally and exhibit coupled gating. However, the analysis of such recordings frequently relies on manual interventions, which can lead to bias. Here, we developed an automated pipeline to de-trend and idealize single-channel currents, and assessed possible functional interactions in cell-attached patch clamp experiments in HEK293 cells expressing human Nav 1.5 channels as well as in adult mouse and rabbit ventricular cardiomyocytes. Our pipeline involved de-trending individual sweeps by linear optimization using a library of predefined functions, followed by digital filtering and baseline offset. Subsequently, the processed sweeps were idealized based on the idea that the ensemble average of the idealized current identified by thresholds between current levels reconstructs at best the ensemble average current from the de-trended sweeps. This reconstruction was achieved by non-linear optimization. To ascertain functional interactions, we examined the distribution of the numbers of open channels at every time point during the activation protocol and compared it to the distribution expected for independent channels. We also examined whether the channels tended to synchronize their openings and closings. However, we did not uncover any solid evidence of such interactions in our recordings. Rather, our results indicate that wild-type Nav 1.5 channels are independent entities or exhibit only very weak functional interactions that are probably irrelevant under physiological conditions. Nevertheless, our unbiased analysis will be important for further studies examining whether auxiliary proteins potentiate functional Na+ channel interactions. KEY POINTS: Nav 1.5 channels are critical for cardiac excitation. They are part of macromolecular interacting complexes, and it was previously suggested that two neighbouring channels may functionally interact and exhibit coupled gating. Manual interventions when processing single-channel recordings can lead to bias and inaccurate data interpretation. We developed an automated pipeline to de-trend and idealize single-channel currents and assessed possible functional interactions between Nav 1.5 channels in HEK293 cells and cardiomyocytes during activation protocols using the cell-attached patch clamp technique. In recordings consisting of up to 1000 sweeps from the same patch, our analysis did not reveal any evidence of functional interactions or coupled gating between wild-type Nav 1.5 channels. Our unbiased analysis may be useful in further studies examining how Na+ channel interactions are affected by mutations and auxiliary proteins.

Dysfunctional sodium channel kinetics as a novel epilepsy mechanism in chromosome 15q11-q13 duplication syndrome

OBJECTIVE

Duplication of the maternal chromosome 15q11.2-q13.1 region causes Dup15q syndrome, a highly penetrant neurodevelopmental disorder characterized by severe autism and refractory seizures. Although UBE3A, the gene encoding the ubiquitin ligase E3A, is thought to be the main driver of disease phenotypes, the cellular and molecular mechanisms that contribute to the development of the syndrome are yet to be determined. We previously established the necessity of UBE3A overexpression for the development of cellular phenotypes in human Dup15q neurons, including increased action potential firing and increased inward current density, which prompted us to further investigate sodium channel kinetics.

METHODS

We used a Dup15q patient-derived induced pluripotent stem cell line that was CRISPR-edited to remove the supernumerary chromosome and create an isogenic control line. We performed whole cell patch clamp electrophysiology on Dup15q and corrected control neurons at two time points of in vitro development.

RESULTS

Compared to corrected neurons, Dup15q neurons showed increased sodium current density and a depolarizing shift in steady-state inactivation. Moreover, onset of slow inactivation was delayed, and a faster recovery from both fast and slow inactivation processes was observed in Dup15q neurons. A fraction of sodium current in Dup15q neurons (~15%) appeared to be resistant to slow inactivation. Not unexpectedly, a higher fraction of persistent sodium current was also observed in Dup15q neurons. These phenotypes were modulated by the anticonvulsant drug rufinamide.

SIGNIFICANCE

Sodium channels play a crucial role in the generation of action potentials, and sodium channelopathies have been uncovered in multiple forms of epilepsy. For the first time, our work identifies in Dup15q neurons dysfunctional inactivation kinetics, which have been previously linked to multiple forms of epilepsy. Our work can also guide therapeutic approaches to epileptic seizures in Dup15q patients and emphasize the role of drugs that modulate inactivation kinetics, such as rufinamide.

Simulations of cortical networks using spatially extended conductance-based neuronal models

The Hodgkin-Huxley model of action potential generation and propagation, published in the Journal of Physiology in 1952, initiated the field of biophysically detailed computational modelling in neuroscience, which has expanded to encompass a variety of species and components of the nervous system. Here we review the developments in this area with a focus on efforts in the community towards modelling the mammalian neocortex using spatially extended conductance-based neuronal models. The Hodgkin-Huxley formalism and related foundational contributions, such as Rall's cable theory, remain widely used in these efforts to the current day. We argue that at present the field is undergoing a qualitative change due to new very rich datasets describing the composition, connectivity and functional activity of cortical circuits, which are being integrated systematically into large-scale network models. This trend, combined with the accelerating development of convenient software tools supporting such complex modelling projects, is giving rise to highly detailed models of the cortex that are extensively constrained by the data, enabling computational investigation of a multitude of questions about cortical structure and function.

Projection-Specific Heterogeneity of the Axon Initial Segment of Pyramidal Neurons in the Prelimbic Cortex

The axon initial segment (AIS) is a highly specialized axonal compartment where the action potential is initiated. The heterogeneity of AISs has been suggested to occur between interneurons and pyramidal neurons (PyNs), which likely contributes to their unique spiking properties. However, whether the various characteristics of AISs can be linked to specific PyN subtypes remains unknown. Here, we report that in the prelimbic cortex (PL) of the mouse, two types of PyNs with axon projections either to the contralateral PL or to the ipsilateral basal lateral amygdala, possess distinct AIS properties reflected by morphology, ion channel expression, action potential initiation, and axo-axonic synaptic inputs from chandelier cells. Furthermore, projection-specific AIS diversity is more prominent in the superficial layer than in the deep layer. Thus, our study reveals the cortical layer- and axon projection-specific heterogeneity of PyN AISs, which may endow the spiking of various PyN types with exquisite modulation.

Artificial Action Potential and Ionic Power Device Inspired by Ion Channels and Excitable Cell

In vivo, the membrane potential of the excitable cell working by ion gradients plays a significant role in bioelectricity generation and nervous system operation. Conventional bioinspired power systems generally have adopted ion gradients, but overlook the functions of ion channels and Donnan effect to generate efficient ion flow in the cell. Here, cell-inspired ionic power device implementing the Donnan effect using multi-ions and monovalent ion exchange membranes as artificial ion channels is realized. Different ion-rich electrolytes on either side of the selective membrane generate the ion gradient potentials with high ionic currents and reduce the osmotic imbalance of the membrane. Based on this device, the artificial neuronal signaling is presented by the mechanical switching system of the ion selectivity like mechanosensitive ion channels in a sensory neuron. Compared with reverse electrodialysis, which requires a low concentration, a high-power device with ten times the current and 8.5 times the power density is fabricated. This device activates grown muscle cells by increasing power through serial connection like an electric eel, and shows the possibility of an ion-based artificial nervous system.

Low-dimensional models of single neurons: a review

The classical Hodgkin-Huxley (HH) point-neuron model of action potential generation is four-dimensional. It consists of four ordinary differential equations describing the dynamics of the membrane potential and three gating variables associated to a transient sodium and a delayed-rectifier potassium ionic currents. Conductance-based models of HH type are higher-dimensional extensions of the classical HH model. They include a number of supplementary state variables associated with other ionic current types, and are able to describe additional phenomena such as subthreshold oscillations, mixed-mode oscillations (subthreshold oscillations interspersed with spikes), clustering and bursting. In this manuscript we discuss biophysically plausible and phenomenological reduced models that preserve the biophysical and/or dynamic description of models of HH type and the ability to produce complex phenomena, but the number of effective dimensions (state variables) is lower. We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.

Distinct excitability of thalamocortical neurons correlates with the presence of cerebellar afferents

Thalamocortical (TC) neurons within the ventrolateral thalamus (VL) receive projections from the cerebellum and the basal ganglia (BG) to facilitate motor and non-motor functions. Tonic and rebound firing patterns in response to excitatory cerebellar and inhibitory BG inputs, respectively, are a canonical feature of TC neurons and plays a key role in signal processing. The intrinsic excitability of TC neurons has a strong influence on how they respond to synaptic inputs, however, it is unknown whether their afferents influence their firing properties. Understanding the input-specific firing patterns could shed light into movement disorders with cerebellar or BG involvement. Here, we used whole-cell electrophysiology in brain slices from C57BL/6 mice to investigate the firing of TC neurons with optogenetic confirmation of cerebellar or BG afferents. TC neurons with cerebellar afferents exhibited higher tonic and rebound firing rates than those with BG afferents. This increased firing was associated with faster action potential depolarization kinetics and a smaller afterhyperpolarization potential. We also found differences in the passive membrane properties and sag currents during hyperpolarization. Despite higher rebound firing in TC neurons with cerebellar afferents, there were no differences in T-type calcium channel function compared to those with BG inputs. These data suggest input-specific differences in sodium and SK, but not T-type calcium channels, impact firing properties in TC populations. Altogether, we showed that the pronounced divergence observed in TC neuron firing properties correlate with its heterogeneous anatomical connectivity, which could signify a distinct signal integration and processing by these neurons.

Keypoints

Thalamocortical neurons in the VL with cerebellar afferents have higher intrinsic tonic and rebound firing properties than those with basal ganglia afferents.Membrane resistance and action potential depolarization slope were different based on the presence of cerebellar afferents.Despite elevated rebound burst firing, T-type mediated currents did not correlate with increased firing in neurons with cerebellar afferents.

Single-Transistor Neuron with Excitatory-Inhibitory Spatiotemporal Dynamics Applied for Neuronal Oscillations

Brain-inspired neuromorphic computing systems with the potential to drive the next wave of artificial intelligence demand a spectrum of critical components beyond simple characteristics. An emerging research trend is to achieve advanced functions with ultracompact neuromorphic devices. In this work, a single-transistor neuron is demonstrated that implements excitatory-inhibitory (E-I) spatiotemporal integration and a series of essential neuron behaviors. Neuronal oscillations, the fundamental mode of neuronal communication, that construct high-dimensional population code to achieve efficient computing in the brain, can also be demonstrated by the neuron transistors. The highly scalable E-I neuron can be the basic building block for implementing core neuronal circuit motifs and large-scale architectural plans to replicate energy-efficient neural computations, forming the foundation of future integrated neuromorphic systems.

Spintronic Integrate-Fire-Reset Neuron with Stochasticity for Neuromorphic Computing

Spintronics has been recently extended to neuromorphic computing because of its energy efficiency and scalability. However, a biorealistic spintronic neuron with probabilistic "spiking" and a spontaneous reset functionality has not been demonstrated yet. Here, we propose a biorealistic spintronic neuron device based on the heavy metal (HM)/ferromagnet (FM)/antiferromagnet (AFM) spin-orbit torque (SOT) heterostructure. The spintronic neuron can autoreset itself after firing due to the exchange bias of the AFM. The firing process is inherently stochastic because of the competition between the SOT and AFM pinning effects. We also implement a restricted Boltzmann machine (RBM) and stochastic integration multilayer perceptron (SI-MLP) using our proposed neuron. Despite the bit-width limitation, the proposed spintronic model can achieve an accuracy of 97.38% in pattern recognition, which is even higher than the baseline accuracy (96.47%). Our results offer a spintronic device solution to emulate biologically realistic spiking neurons.

Consciousness, Cognition and the Neuronal Cytoskeleton - A New Paradigm Needed in Neuroscience

Viewing the brain as a complex computer of simple neurons cannot account for consciousness nor essential features of cognition. Single cell organisms with no synapses perform purposeful intelligent functions using their cytoskeletal microtubules. A new paradigm is needed to view the brain as a scale-invariant hierarchy extending both upward from the level of neurons to larger and larger neuronal networks, but also downward, inward, to deeper, faster quantum and classical processes in cytoskeletal microtubules inside neurons. Evidence shows self-similar patterns of conductive resonances repeating in terahertz, gigahertz, megahertz, kilohertz and hertz frequency ranges in microtubules. These conductive resonances apparently originate in terahertz quantum dipole oscillations and optical interactions among pi electron resonance clouds of aromatic amino acid rings of tryptophan, phenylalanine and tyrosine within each tubulin, the component subunit of microtubules, and the brain's most abundant protein. Evidence from cultured neuronal networks also now shows that gigahertz and megahertz oscillations in dendritic-somatic microtubules regulate specific firings of distal axonal branches, causally modulating membrane and synaptic activities. The brain should be viewed as a scale-invariant hierarchy, with quantum and classical processes critical to consciousness and cognition originating in microtubules inside neurons.

Slow Inactivation of Sodium Channels Contributes to Short-Term Adaptation in Vomeronasal Sensory Neurons

Adaptation plays an important role in sensory systems as it dynamically modifies sensitivity to allow the detection of stimulus changes. The vomeronasal system controls many social behaviors in most mammals by detecting pheromones released by conspecifics. Stimuli activate a transduction cascade in vomeronasal neurons that leads to spiking activity. Whether and how these neurons adapt to stimuli is still debated and largely unknown. Here, we measured short-term adaptation performing current-clamp whole-cell recordings by using diluted urine as a stimulus, as it contains many pheromones. We measured spike frequency adaptation in response to repeated identical stimuli of 2-10 s duration that was dependent on the time interval between stimuli. Responses to paired current steps, bypassing the signal transduction cascade, also showed spike frequency adaptation. We found that voltage-gated Na+ channels in VSNs undergo slow inactivation processes. Furthermore, recovery from slow inactivation of voltage-gated Na+ channels occurs in several seconds, a time scale similar to that measured during paired-pulse adaptation protocols, suggesting that it partially contributes to short-term spike frequency adaptation. We conclude that vomeronasal neurons do exhibit a time-dependent short-term spike frequency adaptation to repeated natural stimuli and that slow inactivation of Na+ channels contributes to this form of adaptation. These findings not only increase our knowledge about adaptation in the vomeronasal system, but also raise the question of whether slow inactivation of Na+ channels may play a role in other sensory systems.

A Model for Self-Organization of Sensorimotor Function: Spinal Interneuronal Integration

Control of musculoskeletal systems depends on integration of voluntary commands and somatosensory feedback in the complex neural circuits of the spinal cord. Particular connectivity patterns have been identified experimentally, and it has been suggested that these may result from the wide variety of transcriptional types that have been observed in spinal interneurons. We ask instead whether the details of these connectivity patterns (and perhaps many others) can arise as a consequence of Hebbian adaptation during early development. We constructed an anatomically simplified model plant system with realistic muscles and sensors and connected it to a recurrent, random neuronal network consisting of both excitatory and inhibitory neurons endowed with Hebbian learning rules. We then generated a wide set of randomized muscle twitches typical of those described during fetal development and allowed the network to learn. Multiple simulations consistently resulted in diverse and stable patterns of activity and connectivity that included subsets of the interneurons that were similar to 'archetypical' interneurons described in the literature. We also found that such learning led to an increased degree of cooperativity between interneurons when performing larger limb movements on which it had not been trained. Hebbian learning gives rise to rich sets of diverse interneurons whose connectivity reflects the mechanical properties of the plant. At least some of the transcriptomic diversity may reflect the effects of this process rather than the cause of the connectivity. Such a learning process seems better suited to respond to the musculoskeletal mutations that underlie the evolution of new species.

Microtubules as Regulators of Neural Network Shape and Function: Focus on Excitability, Plasticity and Memory

Neuronal microtubules (MTs) are complex cytoskeletal protein arrays that undergo activity-dependent changes in their structure and function as a response to physiological demands throughout the lifespan of neurons. Many factors shape the allostatic dynamics of MTs and tubulin dimers in the cytosolic microenvironment, such as protein–protein interactions and activity-dependent shifts in these interactions that are responsible for their plastic capabilities. Recently, several findings have reinforced the role of MTs in behavioral and cognitive processes in normal and pathological conditions. In this review, we summarize the bidirectional relationships between MTs dynamics, neuronal processes, and brain and behavioral states. The outcomes of manipulating the dynamicity of MTs by genetic or pharmacological approaches on neuronal morphology, intrinsic and synaptic excitability, the state of the network, and behaviors are heterogeneous. We discuss the critical position of MTs as responders and adaptative elements of basic neuronal function whose impact on brain function is not fully understood, and we highlight the dilemma of artificially modulating MT dynamics for therapeutic purposes.

Ultrafast population coding and axo-somatic compartmentalization

Populations of cortical neurons respond to common input within a millisecond. Morphological features and active ion channel properties were suggested to contribute to this astonishing processing speed. Here we report an exhaustive study of ultrafast population coding for varying axon initial segment (AIS) location, soma size, and axonal current properties. In particular, we studied their impact on two experimentally observed features 1) precise action potential timing, manifested in a wide-bandwidth dynamic gain, and 2) high-frequency boost under slowly fluctuating correlated input. While the density of axonal channels and their distance from the soma had a very small impact on bandwidth, it could be moderately improved by increasing soma size. When the voltage sensitivity of axonal currents was increased we observed ultrafast coding and high-frequency boost. We conclude that these computationally relevant features are strongly dependent on axonal ion channels’ voltage sensitivity, but not their number or exact location. We point out that ion channel properties, unlike dendrite size, can undergo rapid physiological modification, suggesting that the temporal accuracy of neuronal population encoding could be dynamically regulated. Our results are in line with recent experimental findings in AIS pathologies and establish a framework to study structure-function relations in AIS molecular design.

In large nervous systems, a signal often diverges to hundreds or thousands of neurons. This population’s spike rate can track changes in this common input for frequencies up to several hundred Hertz. This ultrafast population response is experimentally well established and critically impacts cortical information processing. Its underlying biophysical determinants, however, are not understood. Experiments suggest that the ion channels at the axon initial segment strongly contribute to the ultrafast response, but recent theoretical studies emphasize the importance of neuron morphology and the resulting resistive coupling between axon and somato-dendritic compartments. We provide an exhaustive analysis of the population response of a simplified multi-compartment model. We vary the axo-somatic interaction and also active axonal properties and compare models at equivalent working points, avoiding bias. This approach provides a guideline for future experimental and theoretical studies. In this framework, the population response is closely associated with the AP generation speed at the AP initiation site, which is mostly determined by axonal ion channel voltage sensitivity. The resistive axo-somatic coupling has an additional modulatory influence. These insights are expected to hold for encoding mechanisms of more sophisticated models, suggesting that physiological changes to axonal ion channels could modulate the population response rapidly.

Theta activity paradoxically boosts gamma and ripple frequency sensitivity in prefrontal interneurons

Fast oscillations in cortical circuits critically depend on GABAergic interneurons. Which interneuron types and populations can drive different cortical rhythms, however, remains unresolved and may depend on brain state. Here, we measured the sensitivity of different GABAergic interneurons in prefrontal cortex under conditions mimicking distinct brain states. While fast-spiking neurons always exhibited a wide bandwidth of around 400 Hz, the response properties of spike-frequency adapting interneurons switched with the background input's statistics. Slowly fluctuating background activity, as typical for sleep or quiet wakefulness, dramatically boosted the neurons' sensitivity to gamma and ripple frequencies. We developed a time-resolved dynamic gain analysis and revealed rapid sensitivity modulations that enable neurons to periodically boost gamma oscillations and ripples during specific phases of ongoing low-frequency oscillations. This mechanism predicts these prefrontal interneurons to be exquisitely sensitive to high-frequency ripples, especially during brain states characterized by slow rhythms, and to contribute substantially to theta-gamma cross-frequency coupling.

Mechanisms and Physiological Implications of Cooperative Gating of Ion Channels Clusters

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

Physical and chemical properties of carbon nanotubes in view of mechanistic neuroscience investigations. Some outlook from condensed matter, materials science and physical chemistry

The open border between non-living and living matter, suggested by increasingly emerging fields of nanoscience interfaced to biological systems, requires a detailed knowledge of nanomaterials properties. An account of the wide spectrum of phenomena, belonging to physical chemistry of interfaces, materials science, solid state physics at the nanoscale and bioelectrochemistry, thus is acquainted for a comprehensive application of carbon nanotubes interphased with neuron cells. This review points out a number of conceptual tools to further address the ongoing advances in coupling neuronal networks with (carbon) nanotube meshworks, and to deepen the basic issues that govern a biological cell or tissue interacting with a nanomaterial. Emphasis is given here to the properties and roles of carbon nanotube systems at relevant spatiotemporal scales of individual molecules, junctions and molecular layers, as well as to the point of view of a condensed matter or materials scientist. Carbon nanotube interactions with blood-brain barrier, drug delivery, biocompatibility and functionalization issues are also regarded.

Modelling the spatial and temporal constrains of the GABAergic influence on neuronal excitability

GABA (γ-amino butyric acid) is an inhibitory neurotransmitter in the adult brain that can mediate depolarizing responses during development or after neuropathological insults. Under which conditions GABAergic membrane depolarizations are sufficient to impose excitatory effects is hard to predict, as shunting inhibition and GABAergic effects on spatiotemporal filtering of excitatory inputs must be considered. To evaluate at which reversal potential a net excitatory effect was imposed by GABA (E_GABA^Thr), we performed a detailed in-silico study using simple neuronal topologies and distinct spatiotemporal relations between GABAergic and glutamatergic inputs.

These simulations revealed for GABAergic synapses located at the soma an E_GABA^Thr close to action potential threshold (E_AP^Thr), while with increasing dendritic distance E_GABA^Thr shifted to positive values. The impact of GABA on AMPA-mediated inputs revealed a complex temporal and spatial dependency. E_GABA^Thr depends on the temporal relation between GABA and AMPA inputs, with a striking negative shift in E_GABA^Thr for AMPA inputs appearing after the GABA input. The spatial dependency between GABA and AMPA inputs revealed a complex profile, with E_GABA^Thr being shifted to values negative to E_AP^Thr for AMPA synapses located proximally to the GABA input, while for distally located AMPA synapses the dendritic distance had only a minor effect on E_GABA^Thr. For tonic GABAergic conductances E_GABA^Thr was negative to E_AP^Thr over a wide range of g_GABA^tonic values. In summary, these results demonstrate that for several physiologically relevant situations E_GABA^Thr is negative to E_AP^Thr, suggesting that depolarizing GABAergic responses can mediate excitatory effects even if E_GABA did not reach E_AP^Thr.

The neurotransmitter GABA mediates an inhibitory action in the mature brain, while it was found that GABA provokes depolarizations in the immature brain or after neurological insults. It is, however, not clear to which extend these GABAergic depolarizations can contribute to an excitatory effect. In the present manuscript we approached this question with a computational model of a simplified neurons to determine what amount of a GABAergic depolarizing effect, which we quantified by the so called GABA reversal potential (E_GABA), was required to turn GABAergic inhibition to excitation. The results of our simulations revealed that if GABA was applied alone a GABAergic excitation was induced when E_GABA was around the action potential threshold. When GABA was applied together with additional excitatory inputs, which is the physiological situation in the brain, only for spatially and temporally correlated inputs E_GABA was close to the action potential threshold. For situations in which the additional excitatory inputs appear after the GABA input or are distant to the GABA input, an excitatory effect of GABA could be observed already at E_GABA substantially negative to the action potential threshold. This results indicate that even slightly depolarizing GABA responses, which may be induced during or after neurological insults, can potentially turn GABAergic inhibition into GABAergic excitation.

Electrical match between initial segment and somatodendritic compartment for action potential backpropagation in retinal ganglion cells

The action potential of most vertebrate neurons initiates in the axon initial segment (AIS) and is then transmitted to the soma where it is regenerated by somatodendritic sodium channels. For successful transmission, the AIS must produce a strong axial current, so as to depolarize the soma to the threshold for somatic regeneration. Theoretically, this axial current depends on AIS geometry and Na⁺ conductance density. We measured the axial current of mouse retinal ganglion cells using whole cell recordings with post hoc AIS labeling. We found that this current is large, implying high Na⁺ conductance density, and carries a charge that covaries with capacitance so as to depolarize the soma by ∼30 mV. Additionally, we observed that the axial current attenuates strongly with depolarization, consistent with sodium channel inactivation, but temporally broadens so as to preserve the transmitted charge. Thus, the AIS appears to be organized so as to reliably backpropagate the axonal action potential.NEW & NOTEWORTHY We measured the axial current produced at spike initiation by the axon initial segment of mouse retinal ganglion cells. We found that it is a large current, requiring high sodium channel conductance density, which covaries with cell capacitance so as to ensure a ∼30 mV depolarization. During sustained depolarization the current attenuated, but it broadened to preserve somatic depolarization. Thus, properties of the initial segment are adjusted to ensure backpropagation of the axonal action potential.

A Non-spiking Neuron Model With Dynamic Leak to Avoid Instability in Recurrent Networks

Recurrent circuitry components are distributed widely within the brain, including both excitatory and inhibitory synaptic connections. Recurrent neuronal networks have potential stability problems, perhaps a predisposition to epilepsy. More generally, instability risks making internal representations of information unreliable. To assess the inherent stability properties of such recurrent networks, we tested a linear summation, non-spiking neuron model with and without a “dynamic leak”, corresponding to the low-pass filtering of synaptic input current by the RC circuit of the biological membrane. We first show that the output of this neuron model, in either of its two forms, follows its input at a higher fidelity than a wide range of spiking neuron models across a range of input frequencies. Then we constructed fully connected recurrent networks with equal numbers of excitatory and inhibitory neurons and randomly distributed weights across all synapses. When the networks were driven by pseudorandom sensory inputs with varying frequency, the recurrent network activity tended to induce high frequency self-amplifying components, sometimes evident as distinct transients, which were not present in the input data. The addition of a dynamic leak based on known membrane properties consistently removed such spurious high frequency noise across all networks. Furthermore, we found that the neuron model with dynamic leak imparts a network stability that seamlessly scales with the size of the network, conduction delays, the input density of the sensory signal and a wide range of synaptic weight distributions. Our findings suggest that neuronal dynamic leak serves the beneficial function of protecting recurrent neuronal circuitry from the self-induction of spurious high frequency signals, thereby permitting the brain to utilize this architectural circuitry component regardless of network size or recurrency.

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

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

Formalin-induced inflammatory pain increases excitability in locus coeruleus neurons

Chronic pain is recognized as an important problem in communities. The locus coeruleus (LC) with extensive ascending and descending projections has a critical role in modulating pain. Some studies indicate how the locus coeruleus-noradrenaline system can remain more active after nociceptive stimulation. In the present study, we examined whether formalin-induced inflammatory pain may affect the electrophysiological properties of LC neurons after 24 h. Inflammatory pain was induced by a subcutaneous injection of 2% formalin (10 μL) into the hind paw of 2-3 week-old male Wistar rats. After 24 h, horizontal slices of brain stem containing the locus coeruleus were prepared and whole-cell patch-clamp recordings were carried out on LC neurons. Findings revealed that LC neurons from formalin injected rats had a significant enhancement in firing rate, half-width and instantaneous frequency of action potentials, but their resting membrane potential, input resistance and afterhyperpolarization amplitude almost remained unchanged. In addition, action potential peak amplitude, maximum rise slope, maximum decay slope, first spike latency and rheobase current significantly decreased in LC neurons obtained from formalin-treated rats. Here, for the first time, we demonstrate that inflammatory pain after 24 h induces hyperexcitability in LC neurons, which in turn may result in changes in noradrenaline release and pain processing.

Hybrid Electrical and Optical Neural Interfaces

Neural interfaces bridge the nervous system and the outside world by recording and stimulating neurons. Combining electrical and optical modalities in a single, hybrid neural interface system could lead to complementary and powerful new ways to explore the brain. It has gained robust and exciting momentum recently in neuroscience and neural engineering research. Here, we review developments in the past several years aiming to achieve such hybrid electrical and optical microsystem platforms. Specifically, we cover three major categories of technological advances: transparent neuroelectrodes, optical neural fibers with electrodes, and neural probes/grids integrating electrodes and microscale light-emitting diodes. We discuss examples of these probes tailored to combine electrophysiological recording with optical imaging or optical neural stimulation of the brain and possible directions of future innovation.

Threshold switching memristor-based stochastic neurons for probabilistic computing

Biological neurons exhibit dynamic excitation behavior in the form of stochastic firing, rather than stiffly giving out spikes upon reaching a fixed threshold voltage, which empowers the brain to perform probabilistic inference in the face of uncertainty. However, owing to the complexity of the stochastic firing process in biological neurons, the challenge of fabricating and applying stochastic neurons with bio-realistic dynamics to probabilistic scenarios remains to be fully addressed. In this work, a novel CuS/GeSe conductive-bridge threshold switching memristor is fabricated and singled out to realize electronic stochastic neurons, which is ascribed to the similarity between the stochastic switching behavior observed in the device and that of biological ion channels. The corresponding electric circuit of a stochastic neuron is then constructed and the probabilistic firing capacity of the neuron is utilized to implement Bayesian inference in a spiking neural network (SNN). The application prospects are demonstrated on the example of a tumor diagnosis task, where common fatal diagnostic errors of a conventional artificial neural network are successfully circumvented. Moreover, in comparison to deterministic neuron-based SNNs, the stochastic neurons enable SNNs to deliver an estimate of the uncertainty in their predictions, and the fidelity of the judgement is drastically improved by 81.2%.

Channel current fluctuations conclusively explain neuronal encoding of internal potential into spike trains

Hodgkin and Huxley's seminal neuron model describes the propagation of voltage spikes in axons, but it cannot explain certain full-neuron features crucial for understanding the neural code. We consider channel current fluctuations in a trisection of the Hodgkin-Huxley model, allowing an analytic-mechanistic explanation of these features and yielding consistently excellent matches with in vivo recordings of cerebellar Purkinje neurons, which we use as model systems. This shows that the neuronal encoding is described conclusively by a soft-thresholding function having just three parameters.

Structural basis of cytoplasmic NaV1.5 and NaV1.4 regulation

Voltage-gated sodium channels (NaVs) are membrane proteins responsible for the rapid upstroke of the action potential in excitable cells. There are nine human voltage-sensitive NaV1 isoforms that, in addition to their sequence differences, differ in tissue distribution and specific function. This review focuses on isoforms NaV1.4 and NaV1.5, which are primarily expressed in skeletal and cardiac muscle cells, respectively. The determination of the structures of several eukaryotic NaVs by single-particle cryo-electron microscopy (cryo-EM) has brought new perspective to the study of the channels. Alignment of the cryo-EM structure of the transmembrane channel pore with x-ray crystallographic structures of the cytoplasmic domains illustrates the complementary nature of the techniques and highlights the intricate cellular mechanisms that modulate these channels. Here, we review structural insights into the cytoplasmic C-terminal regulation of NaV1.4 and NaV1.5 with special attention to Ca2+ sensing by calmodulin, implications for disease, and putative channel dimerization.

Modeling the Interactions Between Sodium Channels Provides Insight Into the Negative Dominance of Certain Channel Mutations

BACKGROUND

Nav1.5 cardiac Na+ channel mutations can cause arrhythmogenic syndromes. Some of these mutations exert a dominant negative effect on wild-type channels. Recent studies showed that Na+ channels can dimerize, allowing coupled gating. This leads to the hypothesis that allosteric interactions between Na+ channels modulate their function and that these interactions may contribute to the negative dominance of certain mutations.

METHODS

To investigate how allosteric interactions affect microscopic and macroscopic channel function, we developed a modeling paradigm in which Markovian models of two channels are combined. Allosteric interactions are incorporated by modifying the free energies of the composite states and/or barriers between states.

RESULTS

Simulations using two generic 2-state models (C-O, closed-open) revealed that increasing the free energy of the composite states CO/OC leads to coupled gating. Simulations using two 3-state models (closed-open-inactivated) revealed that coupled closings must also involve interactions between further composite states. Using two 6-state cardiac Na+ channel models, we replicated previous experimental results mainly by increasing the energies of the CO/OC states and lowering the energy barriers between the CO/OC and the CO/OO states. The channel model was then modified to simulate a negative dominant mutation (Nav1.5 p.L325R). Simulations of homodimers and heterodimers in the presence and absence of interactions showed that the interactions with the variant channel impair the opening of the wild-type channel and thus contribute to negative dominance.

CONCLUSION

Our new modeling framework recapitulates qualitatively previous experimental observations and helps identifying possible interaction mechanisms between ion channels.

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

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

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

Homogeneous and Narrow Bandwidth of Spike Initiation in Rat L1 Cortical Interneurons

The cortical layer 1 (L1) contains a population of GABAergic interneurons, considered a key component of information integration, processing, and relaying in neocortical networks. In fact, L1 interneurons combine top–down information with feed-forward sensory inputs in layer 2/3 and 5 pyramidal cells (PCs), while filtering their incoming signals. Despite the importance of L1 for network emerging phenomena, little is known on the dynamics of the spike initiation and the encoding properties of its neurons. Using acute brain tissue slices from the rat neocortex, combined with the analysis of an existing database of model neurons, we investigated the dynamical transfer properties of these cells by sampling an entire population of known “electrical classes” and comparing experiments and model predictions. We found the bandwidth of spike initiation to be significantly narrower than in L2/3 and 5 PCs, with values below 100 cycle/s, but without significant heterogeneity in the cell response properties across distinct electrical types. The upper limit of the neuronal bandwidth was significantly correlated to the mean firing rate, as anticipated from theoretical studies but not reported for PCs. At high spectral frequencies, the magnitude of the neuronal response attenuated as a power-law, with an exponent significantly smaller than what was reported for pyramidal neurons and reminiscent of the dynamics of a “leaky” integrate-and-fire model of spike initiation. Finally, most of our in vitro results matched quantitatively the numerical simulations of the models as a further contribution to independently validate the models against novel experimental data.

A gain-of-function sodium channel β2-subunit mutation in painful diabetic neuropathy

Diabetes mellitus is a global challenge with many diverse health sequelae, of which diabetic peripheral neuropathy is one of the most common. A substantial number of patients with diabetic peripheral neuropathy develop chronic pain, but the genetic and epigenetic factors that predispose diabetic peripheral neuropathy patients to develop neuropathic pain are poorly understood. Recent targeted genetic studies have identified mutations in α-subunits of voltage-gated sodium channels (Na_vs) in patients with painful diabetic peripheral neuropathy. Mutations in proteins that regulate trafficking or functional properties of Na_vs could expand the spectrum of patients with Na_v-related peripheral neuropathies. The auxiliary sodium channel β-subunits (β1–4) have been reported to increase current density, alter inactivation kinetics, and modulate subcellular localization of Na_v. Mutations in β-subunits have been associated with several diseases, including epilepsy, cancer, and diseases of the cardiac conducting system. However, mutations in β-subunits have never been shown previously to contribute to neuropathic pain. We report here a patient with painful diabetic peripheral neuropathy and negative genetic screening for mutations in SCN9A, SCN10A, and SCN11A—genes encoding sodium channel α-subunit that have been previously linked to the development of neuropathic pain. Genetic analysis revealed an aspartic acid to asparagine mutation, D109N, in the β2-subunit. Functional analysis using current-clamp revealed that the β2-D109N rendered dorsal root ganglion neurons hyperexcitable, especially in response to repetitive stimulation. Underlying the hyperexcitability induced by the β2-subunit mutation, as evidenced by voltage-clamp analysis, we found a depolarizing shift in the voltage dependence of Na_v1.7 fast inactivation and reduced use-dependent inhibition of the Na_v1.7 channel.

Theoretical relation between axon initial segment geometry and excitability

In most vertebrate neurons, action potentials are triggered at the distal end of the axon initial segment (AIS). Both position and length of the AIS vary across and within neuron types, with activity, development and pathology. What is the impact of AIS geometry on excitability? Direct empirical assessment has proven difficult because of the many potential confounding factors. Here, we carried a principled theoretical analysis to answer this question. We provide a simple formula relating AIS geometry and sodium conductance density to the somatic voltage threshold. A distal shift of the AIS normally produces a (modest) increase in excitability, but we explain how this pattern can reverse if a hyperpolarizing current is present at the AIS, due to resistive coupling with the soma. This work provides a theoretical tool to assess the significance of structural AIS plasticity for electrical function.

Clusters of cooperative ion channels enable a membrane-potential-based mechanism for short-term memory

Across biological systems, cooperativity between proteins enables fast actions, supra-linear responses, and long-lasting molecular switches. In the nervous system, however, the function of cooperative interactions between voltage-dependent ionic channels remains largely unknown. Based on mathematical modeling, we here demonstrate that clusters of strongly cooperative ion channels can plausibly form bistable conductances. Consequently, clusters are permanently switched on by neuronal spiking, switched off by strong hyperpolarization, and remain in their state for seconds after stimulation. The resulting short-term memory of the membrane potential allows to generate persistent firing when clusters of cooperative channels are present together with non-cooperative spike-generating conductances. Dynamic clamp experiments in rodent cortical neurons confirm that channel cooperativity can robustly induce graded persistent activity - a single-cell based, multistable mnemonic firing mode experimentally observed in several brain regions. We therefore propose that ion channel cooperativity constitutes an efficient cell-intrinsic implementation for short-term memories at the voltage level.

Can One Concurrently Record Electrical Spikes from Every Neuron in a Mammalian Brain?

The classic approach to measure the spiking response of neurons involves the use of metal electrodes to record extracellular potentials. Starting over 60 years ago with a single recording site, this technology now extends to ever larger numbers and densities of sites. We argue, based on the mechanical and electrical properties of existing materials, estimates of signal-to-noise ratios, assumptions regarding extracellular space in the brain, and estimates of heat generation by the electronic interface, that it should be possible to fabricate rigid electrodes to concurrently record from essentially every neuron in the cortical mantle. This will involve fabrication with existing yet nontraditional materials and procedures. We further emphasize the need to advance materials for improved flexible electrodes as an essential advance to record from neurons in brainstem and spinal cord in moving animals.

Axonal Computations

Axons functionally link the somato-dendritic compartment to synaptic terminals. Structurally and functionally diverse, they accomplish a central role in determining the delays and reliability with which neuronal ensembles communicate. By combining their active and passive biophysical properties, they ensure a plethora of physiological computations. In this review, we revisit the biophysics of generation and propagation of electrical signals in the axon and their dynamics. We further place the computational abilities of axons in the context of intracellular and intercellular coupling. We discuss how, by means of sophisticated biophysical mechanisms, axons expand the repertoire of axonal computation, and thereby, of neural computation.

Cellular and Network Mechanisms for Temporal Signal Propagation in a Cortical Network Model

The mechanisms underlying an effective propagation of high intensity information over a background of irregular firing and response latency in cognitive processes remain unclear. Here we propose a SSCCPI circuit to address this issue. We hypothesize that when a high-intensity thalamic input triggers synchronous spike events (SSEs), dense spikes are scattered to many receiving neurons within a cortical column in layer IV, many sparse spike trains are propagated in parallel along minicolumns at a substantially high speed and finally integrated into an output spike train toward or in layer Va. We derive the sufficient conditions for an effective (fast, reliable, and precise) SSCCPI circuit: (i) SSEs are asynchronous (near synchronous); (ii) cortical columns prevent both repeatedly triggering SSEs and incorrectly synaptic connections between adjacent columns; and (iii) the propagator in interneurons is temporally complete fidelity and reliable. We encode the membrane potential responses to stimuli using the non-linear autoregressive integrated process derived by applying Newton's second law to stochastic resilience systems. We introduce a multithreshold decoder to correct encoding errors. Evidence supporting an effective SSCCPI circuit includes that for the condition, (i) time delay enhances SSEs, suggesting that response latency induces SSEs in high-intensity stimuli; irregular firing causes asynchronous SSEs; asynchronous SSEs relate to healthy neurons; and rigorous SSEs relate to brain disorders. For the condition (ii) neurons within a given minicolumn are stereotypically interconnected in the vertical dimension, which prevents repeated triggering SSEs and ensures signal parallel propagation; columnar segregation avoids incorrect synaptic connections between adjacent columns; and signal propagation across layers overwhelmingly prefers columnar direction. For the condition (iii), accumulating experimental evidence supports temporal transfer precision with millisecond fidelity and reliability in interneurons; homeostasis supports a stable fixed-point encoder by regulating changes to synaptic size, synaptic strength, and ion channel function in the membrane; together all-or-none modulation, active backpropagation, additive effects of graded potentials, and response variability functionally support the multithreshold decoder; our simulations demonstrate that the encoder-decoder is temporally complete fidelity and reliable in special intervals contained within the stable fixed-point range. Hence, the SSCCPI circuit provides a possible mechanism of effective signal propagation in cortical networks.

Dynamic Gain Analysis Reveals Encoding Deficiencies in Cortical Neurons That Recover from Hypoxia-Induced Spreading Depolarizations

Cortical regions that are damaged by insults, such as ischemia, hypoxia, and trauma, frequently generate spreading depolarization (SD). At the neuronal level, SDs entail complete breakdown of ionic gradients, persisting for seconds to minutes. It is unclear whether these transient events have a more lasting influence on neuronal function. Here, we describe electrophysiological changes in cortical neurons after recovery from hypoxia-induced SD. When examined with standard measures of neuronal excitability several hours after recovery from SD, layer 5 pyramidal neurons in brain slices from mice of either sex appear surprisingly normal. However, we here introduce an additional parameter, dynamic gain, which characterizes the bandwidth of action potential encoding by a neuron, and thereby reflects its potential efficiency in a multineuronal circuit. We find that the ability of neurons that recover from SD to track high-frequency inputs is markedly curtailed; exposure to hypoxia did not have this effect when SD was prevented pharmacologically. Staining for Ankyrin G revealed at least a fourfold decrease in the number of intact axon initial segments in post-SD slices. Since this effect, along with the effect on encoding, was blocked by an inhibitor of the Ca²⁺-dependent enzyme, calpain, we conclude that both effects were mediated by the SD-induced rise in intracellular Ca²⁺ Although effects of calpain activation were detected in the axon initial segment, changes in soma-dendritic compartments may also be involved. Whatever the precise molecular mechanism, our findings indicate that in the context of cortical circuit function, effectiveness of neurons that survive SD may be limited.SIGNIFICANCE STATEMENT Spreading depolarization, which commonly accompanies cortical injury, entails transient massive breakdown of neuronal ionic gradients. The function of cortical neurons that recover from hypoxia-induced spreading depolarization is not obviously abnormal when tested for usual measures of neuronal excitability. However, we now demonstrate that they have a reduced bandwidth, reflecting a significant impairment of their ability to precisely encode high-frequency components of their synaptic input in output spike trains. Thus, neurons that recover from spreading depolarizations are less able to function normally as elements in the multineuronal cortical circuitry. These changes are correlated with activation of the calcium-dependent enzyme, calpain.

Changes in excitability and ion channel expression in neurons of the major pelvic ganglion in female type II diabetic mice

Bladder cystopathy and autonomic dysfunction are common complications of diabetes, and have been associated with changes in ganglionic transmission and some measures of neuronal excitability in male mice. To determine whether type II diabetes also impacts excitability of ganglionic neurons in females, we investigated neuronal excitability and firing properties, as well as underlying ion channel expression, in major pelvic ganglion (MPG) neurons in control, 10-week, and 21-week Lepr^db/db mice. Type II diabetes in Lepr^db/db animals caused a non-linear change in excitability and firing properties of MPG neurons. At 10 weeks, cells exhibited increased excitability as demonstrated by an increased likelihood of firing multiple spikes upon depolarization, decreased rebound spike latency, and overall narrower action potential half-widths as a result of increased depolarization and repolarization slopes. Conversely, at 21 weeks MPG neurons of Lepr^db/db mice reversed these changes, with spiking patterns and action-potential properties largely returning to control levels. These changes are associated with numerous time-specific changes in calcium, sodium, and potassium channel subunit mRNA levels. However, Principal Components Analysis of channel expression patterns revealed that rectification of excitability is not simply a return to control levels, but rather a distinct ion channel expression profile in 21-week Lepr^db/db neurons. These data indicate that type II diabetes can impact the excitability of post-ganglionic, autonomic neurons of female mice, and suggest that the non-linear progression of these properties with diabetes may be the result of compensatory changes in channel expression that act to rectify disrupted firing patterns of Lepr^db/db MPG neurons.