Electrical resonance with voltage-gated ion channels: perspectives from biophysical mechanisms and neural electrophysiology

NMDA Receptors Control Activity Hierarchy in Neural Network: Loss of Control in Hierarchy Leads to Learning Impairments, Dissociation, and Psychosis

While it is known that associative memory is preferentially encoded by memory-eligible "primed" neurons, in vivo neural activity hierarchy has not been quantified and little is known about how such a hierarchy is established. Leveraging in vivo calcium imaging of hippocampal neurons on freely behaving mice, we developed the first method to quantify real-time neural activity hierarchy in the CA1 region. Neurons on the top of activity hierarchy are identified as primed neurons. In cilia knockout mice that exhibit severe learning deficits, the percentage of primed neurons is drastically reduced. We developed a simplified neural network model that incorporates simulations of linear and non-linear weighted components, modeling the synaptic ionic conductance of AMPA and NMDA receptors, respectively. We found that moderate non-linear to linear conductance ratios naturally leads a small fraction of neurons to be primed in the simulated neural network. Removal of the non-linear component eliminates the existing activity hierarchy and reinstate it to the network stochastically primes a new pool of neurons. Blockade of NMDA receptors by ketamine not only decreases general neuronal activity causing learning impairments, but also disrupts neural activity hierarchy. Additionally, ketamine-induced super-synchronized slow oscillation during anesthesia can be simulated if the non-linear NMDAR component is removed to flatten activity hierarchy. Together, this study develops a unique method to measure neural activity hierarchy and identifies NMDA receptors as a key factor that controls the hierarchy. It presents the first evidence suggesting that hierarchy disruption by NMDAR blockade causes dissociation and psychosis.

Parametric Modeling and Deep Learning for Enhancing Pain Assessment in Postanesthesia

OBJECTIVE

The problem of reliable and widely accepted measures of pain is still open. It follows the objective of this work as pain estimation through post-surgical trauma modeling and classification, to increase the needed reliability compared to measurements only.

METHODS

This article proposes (i) a recursive identification method to obtain the frequency response and parameterization using fractional-order impedance models (FOIM), and (ii) deep learning with convolutional neural networks (CNN) classification algorithms using time-frequency data and spectrograms. The skin impedance measurements were conducted on 12 patients throughout the postanesthesia care in a proof-of-concept clinical trial. Recursive least-squares system identification was performed using a genetic algorithm for initializing the parametric model. The online parameter estimates were compared to the self-reported level by the Numeric Rating Scale (NRS) for analysis and validation of the results. Alternatively, the inputs to CNNs were the spectrograms extracted from the time-frequency dataset, being pre-labeled in four intensities classes of pain during offline and online training with the NRS.

RESULTS

The tendency of nociception could be predicted by monitoring the changes in the FOIM parameters' values or by retraining online the network. Moreover, the tissue heterogeneity, assumed during nociception, could follow the NRS trends. The online predictions of retrained CNN have more specific trends to NRS than pain predicted by the offline population-trained CNN.

CONCLUSION

We propose tailored online identification and deep learning for artefact corrupted environment. The results indicate estimations with the potential to avoid over-dosing due to the objectivity of the information.

SIGNIFICANCE

Models and artificial intelligence (AI) allow objective and personalized nociception-antinociception prediction in the patient safety era for the design and evaluation of closed-loop analgesia controllers.

Soft Bioelectronics Based on Nanomaterials

Recent advances in nanostructured materials and unconventional device designs have transformed the bioelectronics from a rigid and bulky form into a soft and ultrathin form and brought enormous advantages to the bioelectronics. For example, mechanical deformability of the soft bioelectronics and thus its conformal contact onto soft curved organs such as brain, heart, and skin have allowed researchers to measure high-quality biosignals, deliver real-time feedback treatments, and lower long-term side-effects in vivo. Here, we review various materials, fabrication methods, and device strategies for flexible and stretchable electronics, especially focusing on soft biointegrated electronics using nanomaterials and their composites. First, we summarize top-down material processing and bottom-up synthesis methods of various nanomaterials. Next, we discuss state-of-the-art technologies for intrinsically stretchable nanocomposites composed of nanostructured materials incorporated in elastomers or hydrogels. We also briefly discuss unconventional device design strategies for soft bioelectronics. Then individual device components for soft bioelectronics, such as biosensing, data storage, display, therapeutic stimulation, and power supply devices, are introduced. Afterward, representative application examples of the soft bioelectronics are described. A brief summary with a discussion on remaining challenges concludes the review.

Chemical modulation of Kv7 potassium channels

The rising interest in Kv7 modulators originates from their ability to evoke fundamental electrophysiological perturbations in a tissue-specific manner. A large number of therapeutic applications are, in part, based on the clinical experience with two broad-spectrum Kv7 agonists, flupirtine and retigabine. Since precise molecular structures of human Kv7 channel subtypes in closed and open states have only very recently started to emerge, computational studies have traditionally been used to analyze binding modes and direct the development of more potent and selective Kv7 modulators with improved safety profiles. Herein, the synthetic and medicinal chemistry of small molecule modulators and the representative biological properties are summarized. Furthermore, new therapeutic applications supported by in vitro and in vivo assay data are suggested.

The Effect of Resveratrol on the Composition and State of Lipids and the Activity of Phospholipase A2 During the Excitation and Regeneration of Somatic Nerves

It has been shown that in the somatic nerve's lipids, both during excitation and transection, changes occur with the composition of individual phospholipids and in phospholipids fatty acids, which changes the phase state of the myelin and nerve fiber axolemma lipid bilayer. A main contribution in the nerve degenerative processes is dependent on the composition phospholipid's fatty acid changes during the activation of both Ca²⁺-dependent and Ca²⁺-independent phospholipase A₂ forms. At the same time, we studded changes in phosphoinisitol (PI) and diacylglycerol (DAG), which depend on the phosphoinositide cycle function during nerve excitation and degeneration processes. It was found that myelin lipids and nerve fiber axolemmas are involved not only in the functioning of the peripheral nerves, but also the pathological processes underlying deep functional and structural disorders. The effect of resveratrol on regeneration processes in the damaged rat sciatic nerve has also been investigated.

Membrane potential oscillations are not essential for spontaneous firing generation in L4 Aβ-afferent neurons after L5 spinal nerve axotomy and are not mediated by HCN channels

NEW FINDINGS

What is the central question of this study? Is spontaneous activity (SA) in L4 dorsal root ganglion (DRG) neurons induced by L5 spinal nerve axotomy associated with membrane potential oscillations in these neurons, and if so, are these membrane oscillations mediated by HCN channels? What is the main finding and its importance? Unlike injured L5 DRG neurons, which have been shown to be incapable of firing spontaneously without membrane potential oscillations, membrane potential oscillations are not essential for SA generation in conducting 'uninjured' L4 neurons, and they are not mediated by HCN channels. These findings suggest that the underlying cellular mechanisms of SA in injured and 'uninjured' DRG neurons induced by spinal nerve injury are distinct.

ABSTRACT

The underlying cellular and molecular mechanisms of peripheral neuropathic pain are not fully understood. However, preclinical studies using animal models suggest that this debilitating condition is driven partly by aberrant spontaneous activity (SA) in injured and uninjured dorsal root ganglion (DRG) neurons, and that SA in injured DRG neurons is triggered by subthreshold membrane potential oscillations (SMPOs). Here, using in vivo intracellular recording from control L4-DRG neurons, and ipsilateral L4-DRG neurons in female Wistar rats that had previously undergone L5 spinal nerve axotomy (SNA), we examined whether conducting 'uninjured' L4-DRG neurons in SNA rats exhibit SMPOs, and if so, whether such SMPOs are associated with SA in those L4 neurons, and whether they are mediated by hyperpolarization-activated cyclic nucleotide gated (HCN) channels. We found that 7 days after SNA: (a) none of the control A- or C-fibre DRG neurons showed SMPOs or SA, but 50%, 43% and 0% of spontaneously active cutaneous L4 Aβ-low threshold mechanoreceptors, Aβ-nociceptors and C-nociceptors exhibited SMPOs, respectively, in SNA rats with established neuropathic pain behaviors; (b) neither SMPOs nor SA in L4 Aβ-neurons was suppressed by blocking HCN channels with ZD7288 (10 mg kg^-1 , i.v.); and (c) there is a tendency for female rats to show greater pain hypersensitivity than male rats. These results suggest that SMPOs are linked to SA only in some of the conducting L4 Aβ-neurons, that such oscillations are not a prerequisite for SA generation in those L4 A- or C-fibre neurons, and that HCN channels are not involved in their electrogenesis.

Interplay of activation kinetics and the derivative conductance determines resonance properties of neurons

In a neuron with hyperpolarization activated current (I_{h}), the correct input frequency leads to an enhancement of the output response. This behavior is known as resonance and is well described by the neuronal impedance. In a simple neuron model we derive equations for the neuron's resonance and we link its frequency and existence with the biophysical properties of I_{h}. For a small voltage change, the component of the ratio of current change to voltage change (dI/dV) due to the voltage-dependent conductance change (dg/dV) is known as derivative conductance (G_{h}^{Der}). We show that both G_{h}^{Der} and the current activation kinetics (characterized by the activation time constant τ_{h}) are mainly responsible for controlling the frequency and existence of resonance. The increment of both factors (G_{h}^{Der} and τ_{h}) greatly contributes to the appearance of resonance. We also demonstrate that resonance is voltage dependent due to the voltage dependence of G_{h}^{Der}. Our results have important implications and can be used to predict and explain resonance properties of neurons with the I_{h} current.

Cyproheptadine Regulates Pyramidal Neuron Excitability in Mouse Medial Prefrontal Cortex

Cyproheptadine (CPH), a first-generation antihistamine, enhances the delayed rectifier outward K⁺ current (I_K) in mouse cortical neurons through a sigma-1 receptor-mediated protein kinase A pathway. In this study, we aimed to determine the effects of CPH on neuronal excitability in current-clamped pyramidal neurons in mouse medial prefrontal cortex slices. CPH (10 µmol/L) significantly reduced the current density required to generate action potentials (APs) and increased the instantaneous frequency evoked by a depolarizing current. CPH also depolarized the resting membrane potential (RMP), decreased the delay time to elicit an AP, and reduced the spike threshold potential. This effect of CPH was mimicked by a sigma-1 receptor agonist and eliminated by an antagonist. Application of tetraethylammonium (TEA) to block I_K channels hyperpolarized the RMP and reduced the instantaneous frequency of APs. TEA eliminated the effects of CPH on AP frequency and delay time, but had no effect on spike threshold or RMP. The current-voltage relationship showed that CPH increased the membrane depolarization in response to positive current pulses and hyperpolarization in response to negative current pulses, suggesting that other types of membrane ion channels might also be affected by CPH. These results suggest that CPH increases the excitability of medial prefrontal cortex neurons by regulating TEA-sensitive I_K channels as well as other TEA-insensitive K⁺ channels, probably I_D and inward-rectifier Kir channels. This effect of CPH may explain its apparent clinical efficacy as an antidepressant and antipsychotic.

Electrical resonance of Amphotericin B channel activity in lipidic membranes

In our previous work [J. Membrane Biol. 237, 31 (2010)], we showed the dependence of the time average conductance of Nystatin channels as a function of the applied potential. Specifically, it was observed that greater potential induced enhanced channel activity. This indicates that the supramolecular structure could be stabilized by a large field, possibly by giving a preferential orientation to the monomers. In the present work, we entertain the notion that the process of pore formation in the lipidic membranes has an underlying deterministic component. To verify this hypothesis, experiments were performed under potentio-dynamic conditions, i.e., a square train of pulses of different frequencies (0.05-2 Hz) were applied to a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine membrane having 30 mol. % cholesterol and the presence of 35 μM Amphotericin B. An emergence of a resonant frequency, in the present experiments, is tantamount to observing fingerprints of determinism in the activity of these channels in lipidic membranes.

Dynamic Cross-Entropy

BACKGROUND

Complexity measures for time series have been used in many applications to quantify the regularity of one dimensional time series, however many dynamical systems are spatially distributed multidimensional systems.

NEW METHOD

We introduced Dynamic Cross-Entropy (DCE) a novel multidimensional complexity measure that quantifies the degree of regularity of EEG signals in selected frequency bands. Time series generated by discrete logistic equations with varying control parameter r are used to test DCE measures.

RESULTS

Sliding window DCE analyses are able to reveal specific period doubling bifurcations that lead to chaos. A similar behavior can be observed in seizures triggered by electroconvulsive therapy (ECT). Sample entropy data show the level of signal complexity in different phases of the ictal ECT. The transition to irregular activity is preceded by the occurrence of cyclic regular behavior. A significant increase of DCE values in successive order from high frequencies in gamma to low frequencies in delta band reveals several phase transitions into less ordered states, possible chaos in the human brain.

COMPARISON WITH EXISTING METHOD

To our knowledge there are no reliable techniques able to reveal the transition to chaos in case of multidimensional times series. In addition, DCE based on sample entropy appears to be robust to EEG artifacts compared to DCE based on Shannon entropy.

CONCLUSIONS

The applied technique may offer new approaches to better understand nonlinear brain activity.

Modulation of Kv7 channels and excitability in the brain

Neuronal Kv7 channels underlie a voltage-gated non-inactivating potassium current known as the M-current. Due to its particular characteristics, Kv7 channels show pronounced control over the excitability of neurons. We will discuss various factors that have been shown to drastically alter the activity of this channel such as protein and phospholipid interactions, phosphorylation, calcium, and numerous neurotransmitters. Kv7 channels locate to key areas for the control of action potential initiation and propagation. Moreover, we will explore the dynamic surface expression of the channel modulated by neurotransmitters and neural activity. We will also focus on known principle functions of neural Kv7 channels: control of resting membrane potential and spiking threshold, setting the firing frequency, afterhyperpolarization after burst firing, theta resonance, and transient hyperexcitability from neurotransmitter-induced suppression of the M-current. Finally, we will discuss the contribution of altered Kv7 activity to pathologies such as epilepsy and cognitive deficits.