Model-guided control of hippocampal discharges by local direct current stimulation

Connectivity Alterations in Emotional and Cognitive Networks During a Manic State Induced by Direct Electrical Stimulation

Mania is characterized by affective and cognitive alterations, with heightened external and self-awareness that are opposite to the alteration of awareness during epileptic seizures. Electrical stimulations carried out routinely during stereotactic intracerebral EEG (SEEG) recordings for presurgical evaluation of epilepsy may represent a unique opportunity to study the pathophysiology of such complex emotional-behavioral phenomenon, particularly difficult to reproduce in experimental setting. We investigated SEEG signals-based functional connectivity between different brain regions involved in emotions and in consciousness processing during a manic state induced by electrical stimulation in a patient with drug-resistant focal epilepsy. The stimulation inducing manic state and an asymptomatic stimulation of the same site, as well as a seizure with alteration of awareness (AOA) were analyzed. Functional connectivity analysis was performed by measuring interdependencies (nonlinear regression analysis based on the h2 coefficient) between broadband SEEG signals and within typical sub-bands, before and after stimulation, or before and during the seizure with AOA, respectively. Stimulation of the right lateral prefrontal cortex induced a manic state lasting several hours. Its onset was associated with significant increase of broadband-signal functional coupling between the right hemispheric limbic nodes, the temporal pole and the claustrum, whereas significant decorrelation between the right lateral prefrontal and the anterior cingulate cortex was observed in theta-band. In contrast, ictal alteration of awareness was associated with increased broadband and sub-bands synchronization within and between the internal and external awareness networks, including the anterior and middle cingulate, the mesial and lateral prefrontal, the inferior parietal and the temporopolar cortex. Our data suggest the existence of network- and frequency-specific functional connectivity patterns during manic state. A transient desynchronization of theta activity between the external and internal awareness network hubs is likely to increase awareness, with potential therapeutic effect.

On the Validity of the Stochastic Quasi-Steady-State Approximation in Open Enzyme Catalyzed Reactions: Timescale Separation or Singular Perturbation?

The quasi-steady-state approximation is widely used to develop simplified deterministic or stochastic models of enzyme catalyzed reactions. In deterministic models, the quasi-steady-state approximation can be mathematically justified from singular perturbation theory. For several closed enzymatic reactions, the homologous extension of the quasi-steady-state approximation to the stochastic regime, known as the stochastic quasi-steady-state approximation, has been shown to be accurate under the analogous conditions that permit the quasi-steady-state reduction in the deterministic counterpart. However, it was recently demonstrated that the extension of the stochastic quasi-steady-state approximation to an open Michaelis-Menten reaction mechanism is only valid under a condition that is far more restrictive than the qualifier that ensures the validity of its corresponding deterministic quasi-steady-state approximation. In this paper, we suggest a possible explanation for this discrepancy from the lens of geometric singular perturbation theory. In so doing, we illustrate a misconception in the application of the quasi-steady-state approximation: timescale separation does not imply singular perturbation.

Dynamical mesoscale model of absence seizures in genetic models

A mesoscale network model is proposed for the development of spike and wave discharges (SWDs) in the cortico-thalamo-cortical (C-T-C) circuit. It is based on experimental findings in two genetic models of childhood absence epilepsy–rats of WAG/Rij and GAERS strains. The model is organized hierarchically into two levels (brain structures and individual neurons) and composed of compartments for representation of somatosensory cortex, reticular and ventroposteriomedial thalamic nuclei. The cortex and the two thalamic compartments contain excitatory and inhibitory connections between four populations of neurons. Two connected subnetworks both including relevant parts of a C-T-C network responsible for SWD generation are modelled: a smaller subnetwork for the focal area in which the SWD generation can take place, and a larger subnetwork for surrounding areas which can be only passively involved into SWDs, but which is mostly responsible for normal brain activity. This assumption allows modeling of both normal and SWD activity as a dynamical system (no noise is necessary), providing reproducibility of results and allowing future analysis by means of theory of dynamical system theories. The model is able to reproduce most time-frequency changes in EEG activity accompanying the transition from normal to epileptiform activity and back. Three different mechanisms of SWD initiation reported previously in experimental studies were successfully reproduced in the model. The model incorporates also a separate mechanism for the maintenance of SWDs based on coupling analysis from experimental data. Finally, the model reproduces the possibility to stop ongoing SWDs with high frequency electrical stimulation, as described in the literature.

Implantable Direct Current Neural Modulation: Theory, Feasibility, and Efficacy

Implantable neuroprostheses such as cochlear implants, deep brain stimulators, spinal cord stimulators, and retinal implants use charge-balanced alternating current (AC) pulses to recover delivered charge and thus mitigate toxicity from electrochemical reactions occurring at the metal-tissue interface. At low pulse rates, these short duration pulses have the effect of evoking spikes in neural tissue in a phase-locked fashion. When the therapeutic goal is to suppress neural activity, implants typically work indirectly by delivering excitation to populations of neurons that then inhibit the target neurons, or by delivering very high pulse rates that suffer from a number of undesirable side effects. Direct current (DC) neural modulation is an alternative methodology that can directly modulate extracellular membrane potential. This neuromodulation paradigm can excite or inhibit neurons in a graded fashion while maintaining their stochastic firing patterns. DC can also sensitize or desensitize neurons to input. When applied to a population of neurons, DC can modulate synaptic connectivity. Because DC delivered to metal electrodes inherently violates safe charge injection criteria, its use has not been explored for practical applicability of DC-based neural implants. Recently, several new technologies and strategies have been proposed that address this safety criteria and deliver ionic-based direct current (iDC). This, along with the increased understanding of the mechanisms behind the transcutaneous DC-based modulation of neural targets, has caused a resurgence of interest in the interaction between iDC and neural tissue both in the central and the peripheral nervous system. In this review we assess the feasibility of in-vivo iDC delivery as a form of neural modulation. We present the current understanding of DC/neural interaction. We explore the different design methodologies and technologies that attempt to safely deliver iDC to neural tissue and assess the scope of application for direct current modulation as a form of neuroprosthetic treatment in disease. Finally, we examine the safety implications of long duration iDC delivery. We conclude that DC-based neural implants are a promising new modulation technology that could benefit from further chronic safety assessments and a better understanding of the basic biological and biophysical mechanisms that underpin DC-mediated neural modulation.

Physiological effects of low-magnitude electric fields on brain activity: advances from in vitro, in vivo and in silico models

While electrical stimulation of brain tissue has been thoroughly investigated over the last decades, ongoing questions remain regarding the neurophysiological effects of low-level electric fields (on the order of 1 V/m) on brain activity. Electric fields at such levels are, for example, induced by transcranial direct/alternating current stimulation (tDCS/tACS). Action potentials can be indeed elicited when applied (supra-threshold) electric fields are in the 10-100 V/m range, while lower (subthreshold) electric fields result in more limited and subtler membrane polarization effects. In this review, we address the question of the mechanisms underlying the immediate effects (also referred to as acute, concurrent or short-term) and the lasting effects (also referred to as long-term or aftereffects) of low-level electric fields on brain tissue. We review recent evidence at the in vitro and in vivo (animal and human) level, and also present mechanistic insights gained from in silico models, which are still few but have received increased attention over the recent past years. We highlight the convergent evidence towards potential mechanisms, and also discuss discrepancies between in vitro studies and human tDCS/tACS studies that require further investigation to bridge the gap between the single-cell and large-scale network level. Possible novel avenues of research are discussed.

Extremely High Frequency Electromagnetic Fields Facilitate Electrical Signal Propagation by Increasing Transmembrane Potassium Efflux in an Artificial Axon Model

Among the many biological effects caused by low intensity extremely high frequency electromagnetic fields (EHF-EMF) reported in the literature, those on the nervous system are a promising area for further research. The mechanisms by which these fields alter neural activity are still unclear and thus far there appears to be no frequency dependence regarding neuronal responses. Therefore, proper in vitro models for preliminary screening studies of the interaction between neural cells with EMF are needed. We designed an artificial axon model consisting of a series of parallel RC networks. Each RC network contained an aqueous solution of lipid vesicles with a gradient of potassium (K⁺) concentration as the functional element. We investigated the effects of EHF-EMF (53.37 GHz–39 mW) on the propagation of the electric impulse. We report that exposure to the EHF-EMF increases the amplitude of electrical signal by inducing a potassium efflux from lipid vesicles. Further, exposure to the EHF-EMF potentiates the action of valinomycin – a K⁺ carrier – increasing the extent of K⁺ transport across the lipid membrane. We conclude that exposure to the EHF-EMF facilitates the electrical signal propagation by increasing transmembrane potassium efflux, and that the model presented is promising for future screening studies of different EMF frequency spectrum bands.

Generate the scale-free brain music from BOLD signals

Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen-Rit model, to simulate activity in several cortical brain regions. The interactions between different brain regions were represented by the average normalized diffusion tensor imaging (DTI) structural connectivity with a coupling coefficient that modulated the coupling strength. Seventy-eight brain regions were adopted from the Automated Anatomical Labeling (AAL) template. Furthermore, we used the Balloon-Windkessel hemodynamic model to transform neural activity into a blood-oxygen-level dependent (BOLD) signal. Because the fMRI BOLD signal changes slowly, we used a sampling rate of 250 Hz to produce the temporal series for music generation. Then, the BOLD music was generated for each region using these simulated BOLD signals. Because the BOLD signal is scale free, these music pieces were also scale free, which is similar to classic music. Here, to simulate the case of an epileptic patient, we changed the parameter that determined the amplitude of the excitatory postsynaptic potential (EPSP) in the neural mass model. Finally, we obtained BOLD music for healthy and epileptic patients. The differences in levels of arousal between the 2 pieces of music may provide a potential tool for discriminating the different populations if the differences can be confirmed by more real data.