ABSTRACT
Electroencephalography (EEG) remains pivotal in neuroscience for its non-invasive exploration of brain activity, yet traditional electrodes are plagued with artifacts and the application of conductive paste poses practical challenges. Tripolar concentric ring electrode (TCRE) sensors used for EEG (tEEG) attenuate artifacts automatically, improving the signal quality. Hydrogel tapes offer a promising alternative to conductive paste, providing mess-free application and reliable electrode-skin contact in locations without hair. Since the electrodes of the TCRE sensors are only 1.0 mm apart, the impedance of the skin-to-electrode impedance-matching medium is critical. This study evaluates four hydrogel tapes' efficacies in EEG electrode application, comparing impedance and alpha wave characteristics. Healthy adult participants underwent tEEG recordings using different tapes. The results highlight varying impedances and successful alpha wave detection despite increased tape-induced impedance. MATLAB's EEGLab facilitated signal processing. This study underscores hydrogel tapes' potential as a convenient and effective alternative to traditional paste, enriching tEEG research methodologies. Two of the conductive hydrogel tapes had significantly higher alpha wave power than the other tapes, but were never significantly lower.
Subject(s)
Electrodes , Electroencephalography , Hydrogels , Humans , Electroencephalography/methods , Hydrogels/chemistry , Adult , Male , Electric Conductivity , Female , Electric Impedance , Signal Processing, Computer-Assisted , Young Adult , Brain/physiologyABSTRACT
Recent evidence suggests that P-glycoprotein (P-gp) overexpression mediates hyperexcitability and is associated with epileptogenesis. Transcranial focal electrical stimulation (TFS) delays epileptogenesis and inhibits P-gp overexpression after a generalized seizure. Here, first we measured P-gp expression during epileptogenesis and second, we assessed if TFS antiepileptogenic effect was related with P-gp overexpression avoidance. Male Wistar rats were implanted in right basolateral amygdala and stimulated daily for electrical amygdala kindling (EAK), P-gp expression was assessed during epileptogenesis in relevant brain areas. Stage I group showed 85% increase in P-gp in ipsilateral hippocampus (p < 0.001). Stage III group presented 58% and 57% increase in P-gp in both hippocampi (p < 0.05). Kindled group had 92% and 90% increase in P-gp in both hippocampi (p < 0.01), and 93% and 143% increase in both neocortices (p < 0.01). For the second experiment, TFS was administrated daily after each EAK stimulation for 20 days and P-gp concentration was assessed. No changes were found in the TFS group (p > 0.05). Kindled group showed 132% and 138% increase in P-gp in both hippocampi (p < 0.001) and 51% and 92% increase in both cortices (p < 0.001). Kindled + TFS group presented no changes (p > 0.05). Our experiments revealed that progression of EAK is associated with increased P-gp expression. These changes are structure-specific and dependent on seizure severity. EAK-induced P-gp overexpression would be associated with neuronal hyperexcitability and thus, epileptogenesis. P-gp could be a novel therapeutical target to avoid epileptogenesis. In accordance with this, TFS inhibited P-gp overexpression and interfered with EAK. An important limitation of the present study is that P-gp neuronal expression was not evaluated under the different experimental conditions. Future studies should be carried out to determine P-gp neuronal overexpression in hyperexcitable networks during epileptogenesis. The TFS-induced lessening of P-gp overexpression could be a novel therapeutical strategy to avoid epileptogenesis in high-risk patients.
ABSTRACT
Near-infrared spectroscopy (NIRS) is a promising research tool that found its way into the field of brain-computer interfacing (BCI). BCI is crucially dependent on maximized usability thus demanding lightweight, compact, and low-cost hardware. We designed, built, and validated a hybrid BCI system incorporating one optical and two electrical modalities ameliorating usability issues. The novel hardware consisted of a NIRS device integrated with an electroencephalography (EEG) system that used two different types of electrodes: Regular gelled gold disk electrodes and tri-polar concentric ring electrodes (TCRE). BCI experiments with 16 volunteers implemented a two-dimensional motor imagery paradigm in off- and online sessions. Various non-canonical signal processing methods were used to extract and classify useful features from EEG, tEEG (EEG through TCRE electrodes), and NIRS. Our analysis demonstrated evidence of improvement in classification accuracy when using the TCRE electrodes compared to disk electrodes and the NIRS system. Based on our synchronous hybrid recording system, we could show that the combination of NIRS-EEG-tEEG performed significantly better than either single modality only.
ABSTRACT
Tripolar electroencephalography (tEEG) has been found to have significantly better signal-to-noise ratio, spatial resolution, mutual information, and high-frequencies compared to EEG. This paper analyzes the tEEG signals acquired simultaneously with the EEG signals and compares their ability to map language to left and right hemispheres using convolutional neural networks (CNNs). The results show that while the time-domain features of tEEG and EEG signals lead to comparable functional mapping, the frequency domain features are significantly different. The left and right hemisphere classification performances using tEEG are equivalent in time and frequency domains. However, frequency domain classification for EEG results in less accuracy. Clinical Relevance- This technique could quickly, and noninvasively, guide clinicians about language dominance when preparing for resective surgery.
Subject(s)
Electroencephalography , Language , Electroencephalography/methods , Neural Networks, Computer , Signal-To-Noise RatioABSTRACT
The COVID-19 pandemic has accelerated neurological, mental health disorders, and neurocognitive issues. However, there is a lack of inexpensive and efficient brain evaluation and screening systems. As a result, a considerable fraction of patients with neurocognitive or psychobehavioral predicaments either do not get timely diagnosed or fail to receive personalized treatment plans. This is especially true in the elderly populations, wherein only 16% of seniors say they receive regular cognitive evaluations. Therefore, there is a great need for development of an optimized clinical brain screening workflow methodology like what is already in existence for prostate and breast exams. Such a methodology should be designed to facilitate objective early detection and cost-effective treatment of such disorders. In this paper we have reviewed the existing clinical protocols, recent technological advances and suggested reliable clinical workflows for brain screening. Such protocols range from questionnaires and smartphone apps to multi-modality brain mapping and advanced imaging where applicable. To that end, the Society for Brain Mapping and Therapeutics (SBMT) proposes the Brain, Spine and Mental Health Screening (NEUROSCREEN) as a multi-faceted approach. Beside other assessment tools, NEUROSCREEN employs smartphone guided cognitive assessments and quantitative electroencephalography (qEEG) as well as potential genetic testing for cognitive decline risk as inexpensive and effective screening tools to facilitate objective diagnosis, monitor disease progression, and guide personalized treatment interventions. Operationalizing NEUROSCREEN is expected to result in reduced healthcare costs and improving quality of life at national and later, global scales.
Subject(s)
COVID-19 , Pandemics , Aged , Brain/diagnostic imaging , Brain Mapping , Delivery of Health Care , Humans , Male , Quality of LifeABSTRACT
Transcranial focal stimulation (TFS) is a non-invasive neuromodulation strategy with neuroprotective effects. On the other hand, 6-hidroxidopamine (6-OHDA) induces neurodegeneration of the nigrostriatal system producing modifications in the dopaminergic, serotoninergic, and histaminergic systems. The present study was conducted to test whether repetitive application of TFS avoids the biogenic amines' changes induced by the intrastriatal injection of 6-OHDA. Experiments were designed to determine the tissue content of dopamine, serotonin, and histamine in the brain of animals injected with 6-OHDA and then receiving daily TFS for 21 days. Tissue content of biogenic amines was evaluated in the cerebral cortex, hippocampus, amygdala, and striatum, ipsi- and contralateral to the side of 6-OHDA injection. Results obtained were compared to animals with 6-OHDA, TFS alone, and a Sham group. The present study revealed that TFS did not avoid the changes in the tissue content of dopamine in striatum. However, TFS was able to avoid several of the changes induced by 6-OHDA in the tissue content of dopamine, serotonin, and histamine in the different brain areas evaluated. Interestingly, TFS alone did not induce significant changes in the different brain areas evaluated. The present study showed that repetitive TFS avoids the biogenic amines' changes induced by 6-OHDA. TFS can represent a new therapeutic strategy to avoid the neurotoxicity induced by 6-OHDA.
ABSTRACT
Portable functional near-infrared spectroscopy (fNIRS) systems have the potential to image the brain in naturalistic settings. Experimental studies are essential to validate such fNIRS systems. Working memory (WM) is a short-term active memory that is associated with the temporary storage and manipulation of information. The prefrontal cortex (PFC) brain area is involved in the processing of WM. We assessed the PFC brain during n-back WM tasks in a group of 25 college students using our laboratory-developed portable fNIRS system, WearLight. We designed an experimental protocol with 32 n-back WM task blocks with four different pseudo-randomized task difficulty levels. The hemodynamic response of the brain was computed from the experimental data and the evaluated brain responses due to these tasks. We observed the incremental mean hemodynamic activation induced by the increasing WM load. The left-PFC area was more activated in the WM task compared to the right-PFC. The task performance was seen to be related to the hemodynamic responses. The experimental results proved the functioning of the WearLight system in cognitive load imaging. Since the portable fNIRS system was wearable and operated wirelessly, it was possible to measure the cognitive load in the naturalistic environment, which could also lead to the development of a user-friendly brain-computer interface system.
Subject(s)
Prefrontal Cortex , Spectroscopy, Near-Infrared , Humans , Memory, Short-Term , Task Performance and Analysis , WorkloadABSTRACT
Transcranial focal stimulation (TFS) is a noninvasive neuromodulation strategy that reduces seizure activity in different experimental models. Nevertheless, there is no information about the effects of TFS in the drug-resistant phenotype associated with P-glycoprotein (Pgp) overexpression. The present study focused on determining the effects of TFS on Pgp expression after an acute seizure induced by 3-mercaptopropionic acid (MPA). P-glycoprotein expression was analyzed by western blot in the cerebral cortex and hippocampus of rats receiving 5â¯min of TFS (300â¯Hz, 50â¯mA, 200⯵s, biphasic charge-balanced squared pulses) using a tripolar concentric ring electrode (TCRE) prior to administration of a single dose of MPA. An acute administration of MPA induced Pgp overexpression in cortex (68⯱â¯13.4%, pâ¯<â¯0.05 vs the control group) and hippocampus (48.5⯱â¯14%, pâ¯<â¯0.05, vs the control group). This effect was avoided when TFS was applied prior to MPA. We also investigated if TFS augments the effects of phenytoin in an experimental model of drug-resistant seizures induced by repetitive MPA administration. Animals with MPA-induced drug-resistant seizures received TFS alone or associated with phenytoin (75â¯mg/kg, i.p.). TFS alone did not modify the expression of the drug-resistant seizures. However, TFS combined with phenytoin reduced seizure intensity, an effect associated with a lower prevalence of major seizures (50%, pâ¯=â¯0.03 vs phenytoin alone). Our experiments demonstrated that TFS avoids the Pgp overexpression induced after an acute convulsive seizure. In addition, TFS augments the phenytoin effects in an experimental model of drug-resistant seizures. According with these results, it is indicated that TFS may represent a new neuromodulatory strategy to revert the drug-resistant phenotype.
Subject(s)
Hippocampus , Seizures , ATP Binding Cassette Transporter, Subfamily B , Animals , Disease Models, Animal , Electrodes , Rats , Seizures/chemically inducedABSTRACT
OBJECTIVE: The objective of the study was to localize sources of interictal high-frequency activity (HFA), from tripolar electroencephalography (tEEG), in patient-specific, realistic head models. METHODS: Concurrent electroencephalogram (EEG) and tEEG were recorded from nine patients undergoing video-EEG, of which eight had seizures during the recordings and the other had epileptic activity. Patient-specific, realistic boundary element head models were generated from the patient's magnetic resonance images (MRIs). Forward and inverse modeling was performed to localize the HFA to cortical surfaces. RESULTS: In the present study, performed on nine patients with epilepsy, HFA observed in the tEEG was localized to the surface of subject-specific, realistic, cortical models, and found to occur almost exclusively in the seizure onset zone (SOZ)/irritative zone (IZ). SIGNIFICANCE: High-frequency oscillations (HFOs) have been studied as precise biomarkers of the SOZ in epilepsy and have resulted in good therapeutic effect in surgical candidates. Knowing where the sources of these highly focal events are located in the brain can help with diagnosis. High-frequency oscillations are not commonly observed in noninvasive EEG recordings, and invasive electrocorticography (ECoG) is usually required to detect them. However, tEEG, i.e., EEG recorded on the scalp with tripolar concentric ring electrodes (TCREs), has been found to detect narrowband HFA from high gamma (approximately 80â¯Hz) to almost 400â¯Hz that correlates with SOZ diagnosis. Thus, source localization of HFA in tEEG may help clinicians identify brain regions of the epileptic zone. At the least, the tEEG HFA localization may help determine where to perform intracranial recordings used for precise diagnosis.
Subject(s)
Brain/physiopathology , Epilepsy/diagnosis , Seizures/diagnosis , Brain/diagnostic imaging , Brain/surgery , Brain Mapping/methods , Electrocorticography , Electroencephalography , Epilepsy/diagnostic imaging , Epilepsy/physiopathology , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Seizures/diagnostic imaging , Seizures/physiopathologyABSTRACT
Transcranial focal electrical stimulation (TFS) via tripolar concentric ring electrodes (TCRE), tripolar TFS, is proposed to treat pharmacoresistant epilepsy. We determined the effect of tripolar TFS on electrical amygdaloid kindling (AK) in freely moving cats. Fifteen cats were bilaterally implanted with electrodes in the amygdala (AM) and prefrontal cortex and assigned to three groups: the control group, which only received AK; the tripolar TFS before AK group, in which TCREs were placed over the vertex and tripolar TFS (300â¯Hz, 200⯵s biphasic equal charge, square pulses) was delivered for 40â¯min just prior to AK; and the tripolar TFS after AK group, in which the TCREs were placed over the temporal bone ipsilateral to the kindled AM, while tripolar TFS was administered for 2â¯min just after AK onset for 40â¯days, and, thereafter, only AK was applied. AK was applied daily until all animals reached kindling stage VI. A three concentric spheres finite element cat head model was developed to analyze the electric fields caused by tripolar TFS. Tripolar TFS after AK inhibited kindling development. Animals with tripolar TFS after AK remained at the focal seizure stages for 20â¯days after tripolar TFS cessation and required 80.0⯱â¯15.42 AK stimulations to reach stage VI, significantly higher than TFS before AK, and control (Pâ¯<â¯.001). Tripolar TFS before AK did not show signs of protection against epileptogenesis. The finite modeling of tripolar TFS showed that the electric field is >0.3â¯mV/mm at depths less than approximately 12.6â¯mm in the cat brain, which should be strong enough to alter brain activity. In conclusion, tripolar TFS applied via a TCRE over the ipsilateral temporal area significantly delayed AK. This taken together with other reports of tripolar TFS aborting seizures in acute seizure models suggests that tripolar TFS is a promising new modality that should be considered for further testing.
Subject(s)
Brain , Electrodes , Transcranial Direct Current Stimulation/instrumentation , Animals , Cats , Kindling, Neurologic , Male , Movement , Seizures/prevention & controlABSTRACT
Electrodes are used to convert ionic currents to electrical currents in biological systems. Modeling the electrode-electrolyte interface and characterizing the impedance of the interface could help to optimize the performance of the electrode interface to achieve higher signal to noise ratios. Previous work has yielded accurate models for single-element biomedical electrodes. This paper introduces a model for a tripolar concentric ring electrode (TCRE) derived from impedance measurements using electrochemical impedance spectroscopy with a Ten20 electrode impedance matching paste. It is shown that the model serves well to predict the performance of the electrode-electrolyte interface for TCREs as well as standard cup electrodes. In this paper, we also discuss the comparison between the TCRE and the standard cup electrode regarding their impedance characterization and demonstrate the benefit of using TCREs in biomedical applications. We have also conducted auditory evoked potential experiments using both TCRE and standard cup electrodes. The results show that electroencephalography (EEG) recorded from tripolar concentric ring electrodes is beneficial, acquiring the auditory brainstem response with less stimuli with respect to recoding EEG using standard cup electrodes.
Subject(s)
Electrodes , Electroencephalography/instrumentation , Evoked Potentials, Auditory , Dielectric Spectroscopy , Electric Impedance , Equipment Design , Humans , Signal-To-Noise RatioABSTRACT
Functional near-infrared spectroscopy (fNIRS) has emerged as an effective brain monitoring technique to measure the hemodynamic response of the cortical surface. Its wide popularity and adoption in recent time attribute to its portability, ease of use, and flexibility in multimodal studies involving electroencephalography. While fNIRS is still emerging on various fronts including hardware, software, algorithm, and applications, it still requires overcoming several scientific challenges associated with brain monitoring in naturalistic environments where the human participants are allowed to move and required to perform various tasks stimulating brain behaviors. In response to these challenges and demands, we have developed a wearable fNIRS system, WearLight that was built upon an Internet-of-Things embedded architecture for onboard intelligence, configurability, and data transmission. In addition, we have pursued detailed research and comparative analysis on the design of the optodes encapsulating an near-infrared light source and a detector into 3-D printed material. We performed rigorous experimental studies on human participants to test reliability, signal-to-noise ratio, and configurability. Most importantly, we observed that WearLight has a capacity to measure hemodynamic responses in various setups including arterial occlusion on the forearm and frontal lobe brain activity during breathing exercises in a naturalistic environment. Our promising experimental results provide an evidence of preliminary clinical validation of WearLight. This encourages us to move toward intensive studies involving brain monitoring.
Subject(s)
Neuroimaging/methods , Spectroscopy, Near-Infrared , Wearable Electronic Devices , Adult , Forearm/physiology , Hemodynamics/physiology , Hemoglobins/metabolism , Humans , Oxyhemoglobins/metabolism , Prefrontal Cortex/physiology , Printing, Three-DimensionalABSTRACT
The Seventh International Brain-Computer Interface (BCI) Meeting was held May 21-25th, 2018 at the Asilomar Conference Grounds, Pacific Grove, California, United States. The interactive nature of this conference was embodied by 25 workshops covering topics in BCI (also called brain-machine interface) research. Workshops covered foundational topics such as hardware development and signal analysis algorithms, new and imaginative topics such as BCI for virtual reality and multi-brain BCIs, and translational topics such as clinical applications and ethical assumptions of BCI development. BCI research is expanding in the diversity of applications and populations for whom those applications are being developed. BCI applications are moving toward clinical readiness as researchers struggle with the practical considerations to make sure that BCI translational efforts will be successful. This paper summarizes each workshop, providing an overview of the topic of discussion, references for additional information, and identifying future issues for research and development that resulted from the interactions and discussion at the workshop.
ABSTRACT
Recent studies show that the rate of cortical high frequency oscillations (HFOs) differentiates epileptogenic tissue in individuals with epilepsy. However, HFO occurrence can vary widely with vigilance state. In this study we attempt to characterize this variation, which has implications for the choice of a suitable diagnostic baseline for spatiotemporal analysis of HFO activity. We analyzed simultaneous recordings of the scalp electroencephalogram (EEG) and the electrocorticogram (ECoG) to examine the correlation of HFO activity with vigilance state. We detected HFOs (80-500 Hz) from all bipolar ECoG derivations using the well-known Staba algorithm in ten seizure-free overnight recordings from five patients being evaluated for surgery. In addition, we classified EEG features using a linkage tree into four vigilance states representing gradations in sleep depth from wakefulness to slow wave sleep. Finally, we examined the correlation between vigilance state and HFO occurrence in the five channels with the most HFOs in each recording. The proportion of 30-s epochs containing HFOs was found to increase significantly with sleep depth (p<0.01). Further analysis is necessary to examine the effects of epoch length and sample size in the choice of diagnostic baseline.
Subject(s)
Electrocorticography , Electroencephalography , Epilepsy/diagnosis , Wakefulness , Algorithms , Brain , Brain Mapping , Brain Waves , Humans , Incidence , Sample Size , Sleep, Slow-Wave , Spatio-Temporal AnalysisABSTRACT
Multimodal neuroimaging, such as combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), are being increasingly used to investigate the human brain in healthy and diseased conditions. However, certain neuroimaging data are typically acquired in different body positions, e.g., supine fMRI and upright EEG, overlooking the effect of body position on signal characteristics. In the current study we examined EEG signals in three different positions, i.e., supine, standing and sitting, in patients with a balance disorder called mal de debarquement syndrome (MdDS). Individuals with MdDS experience a chronic illusion of self-motion triggered by prolonged exposure to passive motion, such as from sea or air travel. The degree of perception of rocking dizziness is modulated by body position, suggesting a physiological effect related to body positions. In the present study, EEG features were quantified as peak frequency, peak amplitude, and average amplitude of the alpha band due to its strongest signal characteristics compared to other frequencies. The effect of body position was examined in EEG features from data acquired before and after the individuals received treatment with repetitive transcranial magnetic stimulation. Our results indicate a significant effect of body positions on the EEG signals in MdDS.
Subject(s)
Electroencephalography , Motion Sickness , Travel-Related Illness , Humans , Magnetic Resonance Imaging , Transcranial Magnetic Stimulation , TravelABSTRACT
Resting state networks (RSNs) have been found in human brains during awake resting states. RSNs are composed of spatially distributed regions in which spontaneous activity fluctuations are temporally and dynamically correlated. A new computational framework for reconstructing RSNs with human EEG data has been developed in the present study. The proposed framework utilizes independent component analysis (ICA) on short-time Fourier transformed inverse source maps imaged from EEG data and statistical correlation analysis to generate cortical tomography of electrophysiological RSNs. The proposed framework was evaluated on three sets of resting-state EEG data obtained in the comparison of two conditions: (1) healthy controls with eyes closed and eyes open; (2) healthy controls and individuals with a balance disorder; (3) individuals with a balance disorder before and after receiving repetitive transcranial magnetic stimulation (rTMS) treatment. In these analyses, the same group of five RSNs with similar spatial and spectral patterns were successfully reconstructed by the proposed framework from each individual EEG dataset. These EEG RSN tomographic maps showed significant similarity with RSN templates derived from functional magnetic resonance imaging (fMRI). Furthermore, significant spatial and spectral differences of RSNs among compared conditions were observed in tomographic maps as well as their spectra, which were consistent with findings reported in the literature. Beyond the success of reconstructing EEG RSNs spatially on the cortical surface as in fMRI studies, this novel approach defines RSNs further with spectra, providing a new dimension in understanding and probing basic neural mechanisms of RSNs. The findings in patients' data further demonstrate its potential in identifying biomarkers for the diagnosis and treatment evaluation of neuropsychiatric disorders.
ABSTRACT
Tripolar concentric ring electrodes are showing great promise in a range of applications including braincomputer interface and seizure onset detection due to their superiority to conventional disc electrodes, in particular, in accuracy of surface Laplacian estimation. Recently, we proposed a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2 that allows cancellation of all the truncation terms up to the order of 2n. This approach has been used to introduce novel multipolar and variable inter-ring distances concentric ring electrode configurations verified using finite element method. The obtained results suggest their potential to improve Laplacian estimation compared to currently used constant interring distances tripolar concentric ring electrodes. One of the main limitations of the proposed (4n + 1)-point method is that the radius of the central disc and the widths of the concentric rings are not included and therefore cannot be optimized. This study incorporates these two parameters by representing the central disc and both concentric rings as clusters of points with specific radius and widths respectively as opposed to the currently used single point and concentric circles. A proof of concept Laplacian estimate is derived for a tripolar concentric ring electrode with non-negligible radius of the central disc and non-negligible widths of the concentric rings clearly demonstrating how both of these parameters can be incorporated into the (4n + 1)-point method.
Subject(s)
Radius , Computer Simulation , Electrodes , Humans , SeizuresABSTRACT
Electrodes are used to transform ionic currents to electrical currents in biological systems. Modeling the electrode-electrolyte interface could help to optimize the performance of the electrode interface to achieve higher signal to noise ratios. There are previous reports of accurate models for single-element biomedical electrodes. In this paper, we measured the impedance on both tripolar concentric ring electrodes and standard cup electrodes by electrochemical impedance spectroscopy (EIS) using both Ten20 and TD246 electrode paste. Furthermore, we applied the model to prove that the model can predict the performance of the electrode-electrolyte interface for tripolar concentric ring electrodes (TCRE) that are used to record brain signals.
Subject(s)
Dielectric Spectroscopy , Brain , Electric Impedance , Electrodes , Signal-To-Noise RatioABSTRACT
Neural activity inside the human brain generate electrical signals that can be detected on the scalp. Electroencephalograph (EEG) is one of the most widely utilized techniques helping physicians and researchers to diagnose and understand various brain diseases. Due to its nature, EEG signals have very high temporal resolution but poor spatial resolution. To achieve higher spatial resolution, a novel tri-polar concentric ring electrode (TCRE) has been developed to directly measure Surface Laplacian (SL). The objective of the present study is to accurately calculate SL for TCRE based on a realistic geometry head model. A locally dense mesh was proposed to represent the head surface, where the local dense parts were to match the small structural components in TCRE. Other areas without dense mesh were used for the purpose of reducing computational load. We conducted computer simulations to evaluate the performance of the proposed mesh and evaluated possible numerical errors as compared with a low-density model. Finally, with achieved accuracy, we presented the computed forward lead field of SL for TCRE for the first time in a realistic geometry head model and demonstrated that it has better spatial resolution than computed SL from classic EEG recordings.
Subject(s)
Electrodes , Brain , Brain Mapping , Computer Simulation , Electroencephalography , Humans , Models, NeurologicalABSTRACT
Concentric ring electrodes have shown promise in non-invasive electrophysiological measurement demonstrating their superiority to conventional disc electrodes, in particular, in accuracy of Laplacian estimation. Recently, we have proposed novel variable inter-ring distances concentric ring electrodes. Analytic and finite element method modeling results for linearly increasing distances electrode configurations suggested they may decrease the truncation error resulting in more accurate Laplacian estimates compared to currently used constant inter-ring distances configurations. This study assesses statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes. Full factorial design of analysis of variance was used with one categorical and two numerical factors: the inter-ring distances, the electrode diameter, and the number of concentric rings in the electrode. The response variables were the Relative Error and the Maximum Error of Laplacian estimation computed using a finite element method model for each of the combinations of levels of three factors. Effects of the main factors and their interactions on Relative Error and Maximum Error were assessed and the obtained results suggest that all three factors have statistically significant effects in the model confirming the potential of using inter-ring distances as a means of improving accuracy of Laplacian estimation.