Objective. We propose a new hybrid brain-computer interface (BCI) system that integrates two different EEG tasks: tactile selective attention (TSA) using a vibro-tactile stimulator on the left/right finger and motor imagery (MI) of left/right hand movement. Event-related desynchronization (ERD) from the MI task and steady-state somatosensory evoked potential (SSSEP) from the TSA task are retrieved and combined into two hybrid senses. Approach. One hybrid approach is to measure two tasks simultaneously; the features of each task are combined for testing. Another hybrid approach is to measure two tasks consecutively (TSA first and MI next) using only MI features. For comparison with the hybrid approaches, the TSA and MI tasks are measured independently. Main results. Using a total of 16 subject datasets, we analyzed the BCI classification performance for MI, TSA and two hybrid approaches in a comparative manner; we found that the consecutive hybrid approach outperformed the others, yielding about a 10% improvement in classification accuracy relative to MI alone. It is understood that TSA may play a crucial role as a prestimulus in that it helps to generate earlier ERD prior to MI and thus sustains ERD longer and to a stronger degree; this ERD may give more discriminative information than ERD in MI alone. Significance. Overall, our proposed consecutive hybrid approach is very promising for the development of advanced BCI systems.
In recent years, research on Brain-Computer Interface (BCI) technology for healthy users has attracted considerable interest, and BCI games are especially popular. This study reviews the current status of, and describes future directions, in the field of BCI games. To this end, we conducted a literature search and found that BCI control paradigms using electroencephalographic signals (motor imagery, P300, steady state visual evoked potential and passive approach reading mental state) have been the primary focus of research. We also conducted a survey of nearly three hundred participants that included researchers, game developers and users around the world. From this survey, we found that all three groups (researchers, developers and users) agreed on the significant influence and applicability of BCI and BCI games, and they all selected prostheses, rehabilitation and games as the most promising BCI applications. User and developer groups tended to give low priority to passive BCI and the whole head sensor array. Developers gave higher priorities to "the easiness of playing" and the "development platform" as important elements for BCI games and the market. Based on our assessment, we discuss the critical point at which BCI games will be able to progress from their current stage to widespread marketing to consumers. In conclusion, we propose three critical elements important for expansion of the BCI game market: standards, gameplay and appropriate integration.
Strokes attributable to subcortical infarcts have been increasing recently in elderly patients. To gain insight how this lesion influences the motor outcome and responds to rehabilitative training, we used circumscribed photothrombotic capsular infarct models on 36 Sprague-Dawley rats (24 experimental and 12 sham-operated). We used 2-deoxy-2-[(18)F]-fluoro-D-glucose-micro positron emission tomography (FDG-microPET) to assess longitudinal changes in resting-state brain activity (rs-BA) and daily single-pellet reaching task (SPRT) trainings to evaluate motor recovery. Longitudinal FDG-microPET results showed that capsular infarct resulted in a persistent decrease in rs-BA in bilateral sensory and auditory cortices, and ipsilesional motor cortex, thalamus, and inferior colliculus (P<0.0025, false discovery rate (FDR) q<0.05). The decreased rs-BA is compatible with diaschisis and contributes to manifest the malfunctions of lesion-specific functional connectivity. In contrast, capsular infarct resulted in increase of rs-BA in the ipsilesional internal capsule, and contralesional red nucleus and ventral hippocampus in recovery group (P<0.0025, FDR q<0.05), implying that remaining subcortical structures have an important role in conducting the recovery process in capsular infarct. The SPRT training facilitated motor recovery only in rats with an incomplete destruction of the posterior limb of the internal capsule (PLIC) (Pearson's correlation, P<0.05). Alternative therapeutic interventions are required to enhance the potential for recovery in capsular infarct with complete destruction of PLIC.Journal of Cerebral Blood Flow & Metabolism advance online publication, 29 October 2014; doi:10.1038/jcbfm.2014.178.
Subdural cortical stimulation (SuCS) is a method used to inject electrical current through electrodes beneath the dura mater, and is known to be useful in treating brain disorders. However, precisely how SuCS must be applied to yield the most effective results has rarely been investigated. For this purpose, we developed a three-dimensional computational model that represents an anatomically realistic brain model including an upper chest. With this computational model, we investigated the influence of stimulation amplitudes, electrode configurations (single or paddle-array), and white matter conductivities (isotropy or anisotropy). Further, the effects of stimulation were compared with two other computational models, including an anatomically realistic brain-only model and the simplified extruded slab model representing the precentral gyrus area. The results of voltage stimulation suggested that there was a synergistic effect with the paddle-array due to the use of multiple electrodes; however, a single electrode was more efficient with current stimulation. The conventional model (simplified extruded slab) far overestimated the effects of stimulation with both voltage and current by comparison to our proposed realistic upper body model. However, the realistic upper body and full brain-only models demonstrated similar stimulation effects. In our investigation of the influence of anisotropic conductivity, model with a fixed ratio (1?10) anisotropic conductivity yielded deeper penetration depths and larger extents of stimulation than others. However, isotropic and anisotropic models with fixed ratios (1?2, 1?5) yielded similar stimulation effects. Lastly, whether the reference electrode was located on the right or left chest had no substantial effects on stimulation.
Cortical stimulation (CS) is an appealing and emerging treatment for neurological disorders. CS is known to promote functional recovery effectively; however, its underlying mechanism and the optimal parameters for the effective treatment are not clearly understood. In this work, we developed a realistic three-dimensional full head and chest model for subdural CS. Our proposed model was compared at the neuron level with an existing simplified extruded slab partial head model depicting around precentral gyral cortex only. Each model was coupled with the pyramidal neuronal model in order to investigate an extent of neuronal excitation. We found that the crown of the cortex was the most excitable area in the unipolar stimulation, while in the bipolar stimulation, the lip and bank were excited more easily than other areas. Finally, it was evident that our proposed model was substantially different in excitation threshold from the existing simplified model, which is compelling to do computational CS study on more realistic head models.
Simultaneous magnetoencephalography (MEG) and electroencephalography (EEG) analysis is known generally to yield better localization performance than a single modality only. For simultaneous analysis, MEG and EEG data should be combined to maximize synergistic effects. Recently, beamformer for simultaneous MEG/EEG analysis was proposed to localize both radial and tangential components well, while single modality analyses could not detect them, or had relatively higher location bias. In practice, most interesting brain sources are likely to be activated coherently; however, conventional beamformer may not work properly for such coherent sources. To overcome this difficulty, a linearly constrained minimum variance (LCMV) beamformer may be used with a source suppression strategy. In this work, simultaneous MEG/EEG LCMV beamformer using source suppression was formulated firstly to investigate its capability over various suppression strategies. The localization performance of our proposed approach was examined mainly for coherent sources and compared thoroughly with the conventional simultaneous and single modality approaches, over various suppression strategies. For this purpose, we used numerous simulated data, as well as empirical auditory stimulation data. In addition, some strategic issues of simultaneous MEG/EEG analysis were discussed. Overall, we found that our simultaneous MEG/EEG LCMV beamformer using a source suppression strategy is greatly beneficial in localizing coherent sources.
In most brain computer interface (BCI) systems, some target users have significant difficulty in using BCI systems. Such target users are called BCI-illiterate. This phenomenon has been poorly investigated, and a clear understanding of the BCI-illiteracy mechanism or a solution to this problem has not been reported to date. In this study, we sought to demonstrate the neurophysiological differences between two groups (literate, illiterate) with a total of 52 subjects. We investigated recordings under non-task related state (NTS) which is collected during subject is relaxed with eyes open. We found that high theta and low alpha waves were noticeable in the BCI-illiterate relative to the BCI-literate people. Furthermore, these high theta and low alpha wave patterns were preserved across different mental states, such as NTS, resting before motor imagery (MI), and MI states, even though the spatial distribution of both BCI-illiterate and BCI-literate groups did not differ. From these findings, an effective strategy for pre-screening subjects for BCI illiteracy has been determined, and a performance factor that reflects potential user performance has been proposed using a simple combination of band powers. Our proposed performance factor gave an r?=?0.59 (r(2)?=?0.34) in a correlation analysis with BCI performance and yielded as much as r?=?0.70 (r(2)?=?0.50) when seven outliers were rejected during the evaluation of whole data (N?=?61), including BCI competition datasets (N?=?9). These findings may be directly applicable to online BCI systems.
Frequency-difference (FD) electrical impedance tomography (EIT) using a weighted voltage difference has recently been proposed for imaging haemorrhagic stroke, abdominal bleeding and tumors. Although its feasibility was demonstrated through two-dimensional numerical simulations and phantom experiments, we should validate the method in three-dimensional imaging objects. At the same time, we need to investigate its robustness against geometrical modeling errors in boundary shapes and electrode positions. We performed a validation study of the weighted FD method through three-dimensional numerical simulations and phantom experiments. Adopting hemispherical models and phantoms whose admittivity distributions change with frequency, we investigated the performance of the method to detect an anomaly. We found that the simple FD method fails to detect the anomaly, whereas reconstructed images using the weighted FD method clearly visualize the anomaly. The weighted FD method is robust against modeling errors of boundary-shape deformations and displaced electrode positions. We also found that the method is capable of detecting an anomaly surrounded by a shell-shaped obstacle simulating the skull. We propose the weighted FD method for future studies of animal and human experiments.
Cortical stimulation (CS) has gained wide attention for its use in augmenting neurological recovery in various conditions. Noninvasive cortical stimulations using transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) are less invasive when delivering the electrical current to the patients brain, but have several limitations. Direct cortical stimulation (DCS) using an implantable stimulation system consisting of epidurally or subdurally placed electrodes and pulse generators, provides cortical stimulation and concurrent rehabilitative training in a stable fashion without limiting a patients activities. The effectiveness of these two types of DCS--epidural cortical stimulation (ECS) and subdural cortical stimulation (SCS)--has not been compared. In this work, a computer simulation study was conducted to predict the current density distributions (CDD) through cortical stimulations using subdurally or epidurally placed electrodes. The simulation study is based on the human motor cortex model with a three-dimensional finite element model (FEM). The change in CDD depending on the shape of the electrode (disc or ring) is discussed. The output current induced by SCS was about four times larger than that of ECS when voltage stimulations with the same magnitude were regulated. Thus, SCS showed substantially better penetration of the current into gray or white matter. Further, the ring electrode performed comparably or slightly inferior to the disc electrode in both cortical stimulations.
Brain-computer interface (BCI) provides a new channel for communication between brain and computers through brain signals. Cost-effective EEG provides good temporal resolution, but its spatial resolution is poor and sensor information is blurred by inherent noise. To overcome these issues, spatial filtering and feature extraction techniques have been developed. Source imaging, transformation of sensor signals into the source space through source localizer, has gained attention as a new approach for BCI. It has been reported that the source imaging yields some improvement of BCI performance. However, there exists no thorough investigation on how source imaging information overlaps with, and is complementary to, sensor information. Information (visible information) from the source space may overlap as well as be exclusive to information from the sensor space is hypothesized. Therefore, we can extract more information from the sensor and source spaces if our hypothesis is true, thereby contributing to more accurate BCI systems. In this work, features from each space (sensor or source), and two strategies combining sensor and source features are assessed. The information distribution among the sensor, source, and combined spaces is discussed through a Venn diagram for 18 motor imagery datasets. Additional 5 motor imagery datasets from the BCI Competition III site were examined. The results showed that the addition of source information yielded about 3.8% classification improvement for 18 motor imagery datasets and showed an average accuracy of 75.56% for BCI Competition data. Our proposed approach is promising, and improved performance may be possible with better head model.
A new method for producing frequency-difference images in electrical impedance tomography (EIT) has been recently suggested. It employed the use of a weighted voltage difference between two frequencies. In this paper, we first explain why the weighted difference is advantageous for some applications of the frequency-difference EIT (fdEIT). Based on a relationship between injection currents at two frequencies and a weighted difference of two corresponding complex voltages, we establish an fdEIT image reconstruction algorithm. In order to apply the algorithm to a practical setting, we propose the concept of an equivalent homogeneous admittivity whose value can be estimated by measuring induced voltages at the third frequency. To test this new fdEIT algorithm, we performed numerical simulations and imaging experiments using two-dimensional phantoms with frequency-dependent admittivity distributions. From reconstructed real- and imaginary-part fdEIT images, we could validate its advantage in terms of visualizing anomalies with fewer amounts of artifacts. We propose the method for applications in tumor or stroke imaging where we are mainly interested in contrast information within an fdEIT image. We suggest investigating the forward and inverse problems of an imaging domain with a frequency-dependent admittivity distribution, which has not been addressed rigorously until now.
Cortical stimulation (CS) is an appealing method for treating stroke and other disorders by promoting functional recovery. It is necessary to study the effect of different cortical stimulation types through numerical simulations in order to understand the underlying mechanism. In this paper, we simulated four types of invasive CS - unipolar ECS (epidural CS), bipolar ECS, unipolar SCS (subdural CS), and bipolar SCS - to investigate and compare the effects of stimulation types. Current stimulation was considered to increase the observability of the comparison between ECS and SCS. The simulation results obtained from the 3D precentral gyrus model showed ECS and SCS had similar current density distributions with higher stimulated current. However, the differences between bipolar and unipolar stimulation are significant with higher stimulated current. As stimulated current increased, unipolar CS penetrated deeper and wider regions than bipolar CS, so it can be more effective for functional recovery.
We investigated the effect of electrode type and stimulation condition (voltage stimulation and current stimulation) in bi-polar subdural cortical stimulation (SCS). For this study, we developed a 3D realistic head model using MRI data with 1 mm(3) spatial resolution and simulated the model using the finite element method (FEM). For each study, we used three types of electrodes - disc, ring, and covered-disc - and three efficiency measures - effective depth of penetration, effective volume, and amount of CSF leakage current - to compare the effectiveness of the stimulation between two stimulation conditions. With voltage stimulation, there was no difference in effectiveness between the disc and ring electrodes. However, the amount of CSF leakage current for the covered-disc type was lower than that for the others. The effective depth of penetration and volume for the ring and disc type electrodes were higher than those for the covered-disc type. The current stimulation using the covered-disc electrode penetrated deeper than the other types of electrodes, and the CSF leakage current was still low. The result for voltage and current stimulation was quite different, as the substrate design manipulated the impedance and output current. In the current simulation, if the electrode was covered with the substrate, more current flowed to the cortex. On the other hand, with voltage stimulation, this substrate design makes the impedance between electrodes high, and the total current is reduced.
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