Strength-frequency curve for micromagnetic neurostimulation through excitatory postsynaptic potentials (EPSPs) on rat hippocampal neurons and numerical modeling of magnetic microcoil (μcoil)

Objective: The objective of this study was to measure the effect of micromagnetic stimulation (μMS) on hippocampal neurons, by using single microcoil (μcoil) prototype, Magnetic Pen (MagPen). MagPen will be used to stimulate the CA3 magnetically and excitatory post synaptic potential (EPSP) measurements will be made from the CA1. The threshold for μMS as a function of stimulation frequency of the current driving the µcoil will be demonstrated. Finally, the optimal stimulation frequency of the current driving the μcoil to minimize power will be estimated. Approach: A biocompatible prototype, MagPen was built, and customized such that it is easy to adjust the orientation of the μcoil over the hippocampal tissue in an in vitro setting. Finite element modeling (FEM) of the μcoil was performed to estimate the spatial profiles of the magnetic flux density (in T) and the induced electric fields (in V/m). The induced electric field profiles generated at different values of current applied to the µcoil whether can elicit a neuron response was validated by numerical modeling. The modeling settings were replicated in experiments on rat hippocampal neurons. Main results: The preferred orientation of MagPen over the Schaffer Collateral fibers was demonstrated such that they elicit a neuron response. The recorded EPSPs from CA1 due to μMS at CA3 were validated by applying tetrodotoxin (TTX). Finally, it was interpreted through numerical analysis that increasing frequency of the current driving the μcoil, led to a decrease in the current amplitude threshold for μMS. Significance: This work reports that μMS can be used to evoke population EPSPs in the CA1 of hippocampus. It demonstrates the strength-frequency curve for µMS and its unique features related to orientation dependence of the µcoils, spatial selectivity and distance dependence. Finally, the challenges related to µMS experiments were studied including ways to overcome them.

Effect of Ambient Lighting on Frequency Dependence in Transcranial Electrical Stimulation-Induced Phosphenes

Inconsistencies have been found in the relationship between ambient lighting conditions and frequency-dependence in transcranial electric current stimulation (tECS) induced phosphenes. Using a within-subjects design across lighting condition (dark, mesopic [dim], photopic [bright]) and tECS stimulation frequency (10, 13, 16, 18, 20 Hz), this study determined phosphene detection thresholds in 24 subjects receiving tECS using an FPz-Cz montage. Minima phosphene thresholds were found at 16 Hz in mesopic, 10 Hz in dark and 20 Hz in photopic lighting conditions, with these thresholds being substantially lower for mesopic than both dark (60% reduction) and photopic (56% reduction), conditions. Further, whereas the phosphene threshold-stimulation frequency relation was linear in the dark (increasing with frequency) and photopic (decreasing with frequency) conditions, a quadratic function was found for the mesopic condition (where it followed the linear increase of the dark condition from 10-16 Hz, and the linear decrease of the photopic condition from 16-20 Hz). The results clearly demonstrate that ambient lighting is an important factor in the detection of tECS-induced phosphenes, and that mesopic conditions are most suitable for obtaining overall phosphene thresholds.

Strength-frequency curve for micromagnetic neurostimulation through EPSPs on rat hippocampal neurons and numerical modeling of magnetic microcoil (μcoil)

ObjectiveThe objective of this study was to measure the effect of micromagnetic stimulation (μMS) on hippocampal neurons, by using single microcoil (μcoil) prototype, Magnetic Pen (MagPen). MagPen will be used to stimulate the CA3 region magnetically and excitatory post synaptic potential (EPSP) response measurements will be made from the CA1 region. The threshold for micromagnetic neurostimulation as a function of stimulation frequency of the current driving the μcoil will be demonstrated. Finally, the optimal stimulation frequency of the current driving the μcoil to minimize power will be estimated.ApproachA biocompatible, watertight, non-corrosive prototype, MagPen was built, and customized such that it is easy to adjust the orientation of the μcoil and its distance over the hippocampal tissue in an in vitro recording setting. Finite element modeling (FEM) of the μcoil design was performed to estimate the spatial profiles of the magnetic flux density (in T) and the induced electric fields (in V/m). The induced electric field profiles generated at different values of current applied to the μcoil can elicit a neuron response, which was validated by numerical modeling. The modeling settings for the μcoil were replicated in experiments on rat hippocampal neurons.Main resultsThe preferred orientation of MagPen over the Schaffer Collateral fibers was demonstrated such that they elicit a neuron response. The recorded EPSPs from CA1 region due to μMS at CA3 region were validated by applying tetrodotoxin (TTX). Application of TTX to the hippocampal slice blocked the EPSPs from μMS while after prolonged TTX washout, a partial recovery of the EPSP from μMS was observed. Finally, it was interpreted through numerical analysis that increasing frequency of the current driving the μcoil, led to a decrease in the current amplitude threshold for micromagnetic neurostimulation.SignificanceThis work reports that micromagnetic neurostimulation can be used to evoke population EPSP responses in the CA1 region of the hippocampus. It demonstrates the strengthfrequency curve for μMS and its unique features related to orientation dependence of the μcoils, spatial selectivity and stimulation threshold related to distance dependence. Finally, the challenges related to μMS experiments were studied including ways to overcome them.

Replication of Reduced Pattern Electroretinogram Amplitudes in Depression With Improved Recording Parameters

Background: The retina has gained increasing attention in non-ophthalmological research in recent years. The pattern electroretinogram (PERG), a method to evaluate retinal ganglion cell function, has been used to identify objective correlates of the essentially subjective state of depression. A reduction in the PERG contrast gain was demonstrated in patients with depression compared to healthy controls with normalization after remission. PERG responses are not only modulated by stimulus contrast, but also by check size and stimulation frequency. Therefore, the rationale was to evaluate potentially more feasible procedures for PERG recordings in daily diagnostics in psychiatry.Methods: Twenty-four participants (12 patients with major depression (MDD) and 12 age- and sex-matched healthy controls) were examined in this pilot study. We investigated PERG amplitudes for two steady-state pattern reversal frequencies (12.5/18.75 rps) and four sizes of a checkerboard stimulus (0.8°, 1.6°, 3.2°, and 16°) to optimize the PERG recordings in MDD patients.Results: Smaller PERG amplitudes in MDD patients were observed for all parameters, whereby the extent of the reduction appeared to be stimulus-specific. The most pronounced decline in the PERG of MDD patients was observed at the higher stimulation frequency and the finest pattern, whilst responses for the largest check size were less affected. Following the PERG ratio protocol for early glaucoma, where similar stimulus dependent modulations have been reported, we calculated PERG ratios (0.8°/16°) for all participants. At the higher frequency (18.75 rps), significantly reduced ratios were observed in MDD patients.Conclusion: The “normalization” of the PERG responses—via building a ratio—appears to be a very promising approach with regard to the development of an objective biomarker of the depressive state, facilitating inter-individual assessments of PERG recordings in patients with psychiatric disorders.

Towards optimization of oscillatory stimulation during sleep

Background: Oscillatory rhythms during sleep such as slow oscillations (SO) and spindles, and most importantly their coupling, are thought to underlie processes of memory consolidation. External slow oscillatory transcranial direct current stimulation (so-tDCS) with a frequency of 0.75 Hz has been shown to improve this coupling and memory consolidation, however, effects varied quite markedly between individuals, studies and species. Objective: Here, we aimed to determine how precisely the frequency of stimulation has to match the naturally occurring SO frequency in individuals to optimally improve SO-spindle coupling. Moreover, we systematically tested stimulation durations necessary to induce changes. Methods: We addressed these questions by comparing so-tDCS with individually adapted SO frequency to standardized frequency of 0.75Hz in a cross-over design with 28 healthy older participants during napping while systematically varying stimulation train durations between 30s, 2min and 5min. Results: Stimulation trains as short as 30s were sufficient to modulate the coupling between SOs and spindle activity. Contrary to our expectations, so-tDCS with standardized frequency indicated stronger aftereffects with regard to SO-spindle coupling in comparison to individualized frequency. Angle and variance of spindle maxima occurrence during the SO cycle were similarly modulated. Conclusion: Short stimulation trains were sufficient to induce significant changes in sleep physiology allowing for more trains of stimulation, which provides methodological advantages and possibly even larger effects in future studies. With regard to individualized stimulation frequency, further options of optimization need to be investigated, such as closed-loop stimulation to calibrate stimulation frequency to the SO frequency at time of stimulation onset.

Long-Lasting Desynchronization Effects of Coordinated Reset Stimulation Improved by Random Jitters

Abnormally strong synchronized activity is related to several neurological disorders, including essential tremor, epilepsy, and Parkinson's disease. Chronic high-frequency deep brain stimulation (HF DBS) is an established treatment for advanced Parkinson's disease. To reduce the delivered integral electrical current, novel theory-based stimulation techniques such as coordinated reset (CR) stimulation directly counteract the abnormal synchronous firing by delivering phase-shifted stimuli through multiple stimulation sites. In computational studies in neuronal networks with spike-timing-dependent plasticity (STDP), it was shown that CR stimulation down-regulates synaptic weights and drives the network into an attractor of a stable desynchronized state. This led to desynchronization effects that outlasted the stimulation. Corresponding long-lasting therapeutic effects were observed in preclinical and clinical studies. Computational studies suggest that long-lasting effects of CR stimulation depend on the adjustment of the stimulation frequency to the dominant synchronous rhythm. This may limit clinical applicability as different pathological rhythms may coexist. To increase the robustness of the long-lasting effects, we study randomized versions of CR stimulation in networks of leaky integrate-and-fire neurons with STDP. Randomization is obtained by adding random jitters to the stimulation times and by shuffling the sequence of stimulation site activations. We study the corresponding long-lasting effects using analytical calculations and computer simulations. We show that random jitters increase the robustness of long-lasting effects with respect to changes of the number of stimulation sites and the stimulation frequency. In contrast, shuffling does not increase parameter robustness of long-lasting effects. Studying the relation between acute, acute after-, and long-lasting effects of stimulation, we find that both acute after- and long-lasting effects are strongly determined by the stimulation-induced synaptic reshaping, whereas acute effects solely depend on the statistics of administered stimuli. We find that the stimulation duration is another important parameter, as effective stimulation only entails long-lasting effects after a sufficient stimulation duration. Our results show that long-lasting therapeutic effects of CR stimulation with random jitters are more robust than those of regular CR stimulation. This might reduce the parameter adjustment time in future clinical trials and make CR with random jitters more suitable for treating brain disorders with abnormal synchronization in multiple frequency bands.

Frequency Dependent Electrical Stimulation of PFC and ACC for Acute Pain Treatment in Rats

As pain consists of both sensory and affective components, its management by pharmaceutical agents remains difficult. Alternative forms of neuromodulation, such as electrical stimulation, have been studied in recent years as potential pain treatment options. Although electrical stimulation of the brain has shown promise, more research into stimulation frequency and targets is required to support its clinical applications. Here, we studied the effect that stimulation frequency has on pain modulation in the prefrontal cortex (PFC) and the anterior cingulate cortex (ACC) in acute pain models in rats. We found that low-frequency stimulation in the prelimbic region of the PFC (PL-PFC) provides reduction of sensory and affective pain components. Meanwhile, high-frequency stimulation of the ACC, a region involved in processing pain affect, reduces pain aversive behaviors. Our results demonstrate that frequency-dependent neuromodulation of the PFC or ACC has the potential for pain modulation.

Steady-State Visual Evoked Potential Classification Using Complex Valued Convolutional Neural Networks

The steady-state visual evoked potential (SSVEP), which is a kind of event-related potential in electroencephalograms (EEGs), has been applied to brain–computer interfaces (BCIs). SSVEP-based BCIs currently perform the best in terms of information transfer rate (ITR) among various BCI implementation methods. Canonical component analysis (CCA) or spectrum estimation, such as the Fourier transform, and their extensions have been used to extract features of SSVEPs. However, these signal extraction methods have a limitation in the available stimulation frequency; thus, the number of commands is limited. In this paper, we propose a complex valued convolutional neural network (CVCNN) to overcome the limitation of SSVEP-based BCIs. The experimental results demonstrate that the proposed method overcomes the limitation of the stimulation frequency, and it outperforms conventional SSVEP feature extraction methods.