Transcranial Direct Current Stimulation Optimization - From Physics-Based Computer Simulations to High-Fidelity Head Phantom Fabrication and Measurements

Frontal midline theta transcranial alternating current stimulation enhances early consolidation of episodic memory

Evidence implicating theta rhythms in declarative memory encoding and retrieval, together with the notion that both retrieval and consolidation involve memory reinstatement or replay, suggests that post-learning theta rhythm modulation can promote early consolidation of newly formed memories. Building on earlier work employing theta neurofeedback, we examined whether theta-frequency transcranial alternating stimulation (tACS) can engender effective consolidation of newly formed episodic memories, compared with beta frequency stimulation or sham control conditions. We compared midline frontal and posterior parietal theta stimulation montages and examined whether benefits to memory of theta upregulation are attributable to consolidation rather than to retrieval processes by using a washout period to eliminate tACS after-effects between stimulation and memory assessment. Four groups of participants viewed object pictures followed by a free recall test during three study-test cycles. They then engaged in tACS (frontal theta montage/parietal theta montage/frontal beta montage/sham) for a period of 20 min, followed by a 2-h break. Free recall assessments were conducted after the break, 24 h later, and 7 days later. Frontal midline theta-tACS induced significant off-line retrieval gains at all assessment time points relative to all other conditions. This indicates that theta upregulation provides optimal conditions for the consolidation of episodic memory, independent of mental-state strategies.

How to assess the accuracy of volume conduction models? A validation study with stereotactic EEG data

Introduction

Volume conduction models of the human head are used in various neuroscience fields, such as for source reconstruction in EEG and MEG, and for modeling the effects of brain stimulation. Numerous studies have quantified the accuracy and sensitivity of volume conduction models by analyzing the effects of the geometrical and electrical features of the head model, the sensor model, the source model, and the numerical method. Most studies are based on simulations as it is hard to obtain sufficiently detailed measurements to compare to models. The recording of stereotactic EEG during electric stimulation mapping provides an opportunity for such empirical validation.

Methods

In the study presented here, we used the potential distribution of volume-conducted artifacts that are due to cortical stimulation to evaluate the accuracy of finite element method (FEM) volume conduction models. We adopted a widely used strategy for numerical comparison, i.e., we fixed the geometrical description of the head model and the mathematical method to perform simulations, and we gradually altered the head models, by increasing the level of detail of the conductivity profile. We compared the simulated potentials at different levels of refinement with the measured potentials in three epilepsy patients.

Results

Our results show that increasing the level of detail of the volume conduction head model only marginally improves the accuracy of the simulated potentials when compared to in-vivo sEEG measurements. The mismatch between measured and simulated potentials is, throughout all patients and models, maximally 40 microvolts (i.e., 10% relative error) in 80% of the stimulation-recording combination pairs and it is modulated by the distance between recording and stimulating electrodes.

Discussion

Our study suggests that commonly used strategies used to validate volume conduction models based solely on simulations might give an overly optimistic idea about volume conduction model accuracy. We recommend more empirical validations to be performed to identify those factors in volume conduction models that have the highest impact on the accuracy of simulated potentials. We share the dataset to allow researchers to further investigate the mismatch between measurements and FEM models and to contribute to improving volume conduction models.

Fine-grained brain tissue segmentation for brain modeling of stroke patient

Brain segmentation of stroke patients can facilitate brain modeling for electrical non-invasive brain stimulation, a therapy for stimulating brain function using an electric current. However, it remains challenging owing to its time-consuming, labor-dependent, and complicated pipeline. In addition, conventional tools that define lesions into one region rather than distinguishing between the stroke-affected regions and cerebrospinal fluid can lead to inaccurate treatment results. In this study, we first define a novel stroke-affected region as a detailed sub-region of the conventionally defined lesion. Subsequently, a novel comprehensive framework is proposed to segment head-brain and fine-level stroke-affected regions for normal controls and chronic stroke patients. The proposed framework consists of a time-efficient and precise deep learning-based segmentation model. The experiment results indicate that the proposed method perform better than the conventional deep learning-based segmentation model in terms of the evaluation metrics. The proposed method would be a valuable addition to brain modeling for non-invasive neuromodulation.

Sensitivity Analysis Highlights the Importance of Accurate Head Models for Electrical Impedance Tomography Monitoring of Intracerebral Hemorrhagic Stroke

OBJECTIVE

Electrical impedance tomography (EIT) has been proposed as a novel tool for diagnosing stroke. However, so far, the clinical feasibility is unresolved. In this study, we aim to investigate the need for accurate head modeling in EIT and how the inhomogeneities of the head contribute to the EIT measurement and affect its feasibility in monitoring the progression of a hemorrhagic stroke.

METHODS

We compared anatomically detailed six- and three-layer finite element models of a human head and computed the resulting scalp electrode potentials and the lead fields of selected electrode configurations. We visualized the resulting EIT measurement sensitivity distributions, computed the scalp electrode potentials, and examined the inverse imaging with selected cases. The effect of accurate tissue geometry and conductivity values on the EIT measurement is assessed with multiple different hemorrhagic perturbation locations and sizes.

RESULTS

Our results show that accurate tissue geometries and conductivity values inside the cranial cavity, especially the highly conductive cerebrospinal fluid, significantly affect EIT measurement sensitivity distribution and measured potentials.

CONCLUSIONS

We can conclude that the three-layer head models commonly used in EIT literature cannot depict the current paths correctly in the head. Thus, our study highlights the need to consider the detailed geometry of the cerebrospinal fluid (CSF) in EIT.

SIGNIFICANCE

The results clearly show that the CSF should be considered in the head EIT calculations.

Standard Non-Personalized Electric Field Modeling of Twenty Typical tDCS Electrode Configurations via the Computational Finite Element Method: Contributions and Limitations of Two Different Approaches

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation procedure to modulate cortical excitability and related brain functions. tDCS can effectively alter multiple brain functions in healthy humans and is suggested as a therapeutic tool in several neurological and psychiatric diseases. However, variability of results is an important limitation of this method. This variability may be due to multiple factors, including age, head and brain anatomy (including skull, skin, CSF and meninges), cognitive reserve and baseline performance level, specific task demands, as well as comorbidities in clinical settings. Different electrode montages are a further source of variability between tDCS studies. A procedure to estimate the electric field generated by specific tDCS electrode configurations, which can be helpful to adapt stimulation protocols, is the computational finite element method. This approach is useful to provide a priori modeling of the current spread and electric field intensity that will be generated according to the implemented electrode montage. Here, we present standard, non-personalized model-based electric field simulations for motor, dorsolateral prefrontal, and posterior parietal cortex stimulation according to twenty typical tDCS electrode configurations using two different current flow modeling software packages. The resulting simulated maximum intensity of the electric field, focality, and current spread were similar, but not identical, between models. The advantages and limitations of both mathematical simulations of the electric field are presented and discussed systematically, including aspects that, at present, prevent more widespread application of respective simulation approaches in the field of non-invasive brain stimulation.

Improving the Effect of Transcranial Alternating Current Stimulation (tACS): A Systematic Review

With the development of electrical stimulation technology, traditional transcranial alternating current stimulation (tACS) technology has been found to have the drawback of not targeting a specific area accurately. Studies have shown that optimizing the number and position of electrodes during electrical stimulation has a very good effect on enhancing brain stimulation accuracy. At present, an increasing number of laboratories have begun to optimize tACS. However, there has been no study summarizing the optimization methods of tACS. Determining whether different optimization methods are effective and the optimization approach could provide information that could guide future tACS research. We describe the results of recent research on tACS optimization and integrate the optimization approaches of tACS in recent research. Optimization approaches can be classified into two groups: high-definition electrical stimulation and interference modulation electrical stimulation. The optimization methods can be divided into five categories: high-definition tACS, phase-shifted tACS, amplitude-modulated tACS, the temporally interfering (TI) method, and the intersectional short pulse (ISP) method. Finally, we summarize the latest research on hardware useful for tACS improvement and outline future directions.

EEG modulation by different transcranial direct current stimulation (tDCS) montages: a randomized double-blind sham-control mechanistic pilot trial in healthy participants

Background: Based on our Phantom study on transcranial direct current stimulation (tDCS), we hypothesized that EEG band power and field confinement would be greater following left dorsolateral prefrontal cortex (DLPFC - F3) tDCS using circular vs. rectangular electrodes.Methods: Double-blind-randomized trial comparing tDCS with anode over left DLPFC (groups: rectangular electrodes, circular electrodes, sham) and 2 active subgroup references (right shoulder vs. right DLPFC).Results: Twenty-four randomized participants were assessed. We indeed found higher average EEG power spectral density (PSD) across bands for circular vs. rectangular electrodes, largely confined to F3 and there was a significant increase at AF3 for low alpha (p = 0.037). Significant differences included: increased PSD in low beta (p = 0.024) and theta bands (p = 0.021) at F3, and in theta (p = 0.036) at FC5 for the right DLPFC vs. shoulder with no coherence changes. We found PSD differences between active vs. sham tDCS at Fz for alpha (p = 0.043), delta (p = 0.036), high delta (p = 0.030); and at FC1 for alpha (p = 0.031), with coherence differences for F3-Fz in beta (p = 0.044), theta (p = 0.044), delta (p = 0.037) and high delta (p = 0.009).Conclusion: This pilot study despite low statistical power given its small sample size shows that active left DLPFC tDCS modulates EEG frontocentrally and suggests that electrode shapes/reference locations affect its neurophysiological effects, such as increased low alpha power at AF3 using circular vs. rectangular electrodes. Further research with more participants is warranted.

Validation of Numerical Simulation for Transcranial Direct Current Stimulation with Spherical Phantom

Transcranial direct current stimulation (tDCS) is a promising brain modulation technique in clinical application. Computational models of brain current flow have been used to provide better insights into determining the stimulation parameters, but there are only a few studies to validate the numerical simulation model. The purpose of this study is to validate the simulation model of tDCS. A one-/three-layered spherical phantom model was constructed to mimic the human head. The tDCS-induced voltages were measured at different depth in the spherical phantom model with stereotactic-EEG (s-EEG) electrodes. Comparing the measured values with the simulation data from the computational models, we found that the computational and empirically measured electric field distributions on the brain surface is similar and that the deviation between the predicted and measured electric field value becomes larger near the electrode.