Estimation of fMRI responses related to epileptic discharges using Bayesian hierarchical modeling.

Simultaneous electroencephalography-functional MRI (EEG-fMRI) is a unique and noninvasive method for epilepsy presurgical evaluation. When selecting voxels by null-hypothesis tests, the conventional analysis may overestimate fMRI response amplitudes related to interictal epileptic discharges (IEDs), especially when IEDs are rare. We aimed to estimate fMRI response amplitudes represented by blood oxygen level dependent (BOLD) percentage changes related to IEDs using a hierarchical model. It involves the local and distributed hemodynamic response homogeneity to regularize estimations. Bayesian inference was applied to fit the model. Eighty-two epilepsy patients who underwent EEG-fMRI and subsequent surgery were included in this study. A conventional voxel-wise general linear model was compared to the hierarchical model on estimated fMRI response amplitudes and on the concordance between the highest response cluster and the surgical cavity. The voxel-wise model overestimated fMRI responses compared to the hierarchical model, evidenced by a practically and statistically significant difference between the estimated BOLD percentage changes. Only the hierarchical model differentiated brief and long-lasting IEDs with significantly different BOLD percentage changes. Overall, the hierarchical model outperformed the voxel-wise model on presurgical evaluation, measured by higher prediction performance. When compared with a previous study, the hierarchical model showed higher performance metric values, but the same or lower sensitivity. Our results demonstrated the capability of the hierarchical model of providing more physiologically reasonable and more accurate estimations of fMRI response amplitudes induced by IEDs. To enhance the sensitivity of EEG-fMRI for presurgical evaluation, it may be necessary to incorporate more appropriate spatial priors and bespoke decision strategies.

Neurofeedback Training without Explicit Phantom Hand Movements and Hand-Like Visual Feedback to Modulate Pain: A Randomized Crossover Feasibility Trial.

Phantom limb pain is attributed to abnormal sensorimotor cortical representations, although the causal relationship between phantom limb pain and sensorimotor cortical representations suffers from the potentially confounding effects of phantom hand movements. We developed neurofeedback training to change sensorimotor cortical representations without explicit phantom hand movements or hand-like visual feedback. We tested the feasibility of neurofeedback training in fourteen patients with phantom limb pain. Neurofeedback training was performed in a single-blind, randomized, crossover trial using two decoders constructed using motor cortical currents measured during phantom hand movements; the motor cortical currents contralateral or ipsilateral to the phantom hand (contralateral and ipsilateral training) were estimated from magnetoencephalograms. Patients were instructed to control the size of a disk, which was proportional to the decoding results, but to not move their phantom hands or other body parts. The pain assessed by the visual analogue scale was significantly greater after contralateral training than after ipsilateral training. Classification accuracy of phantom hand movements significantly increased only after contralateral training. These results suggested that the proposed neurofeedback training changed phantom hand representation and modulated pain without explicit phantom hand movements or hand-like visual feedback, thus showing the relation between the phantom hand representations and pain. PERSPECTIVE: Our work demonstrates the feasibility of using neurofeedback training to change phantom hand representation and modulate pain perception without explicit phantom hand movements and hand-like visual feedback. The results enhance the mechanistic understanding of certain treatments, such as mirror therapy, that change the sensorimotor cortical representation.

Magnetoencephalography detects phase-amplitude coupling in Parkinson's disease.

To characterize Parkinson's disease, abnormal phase-amplitude coupling is assessed in the cortico-basal circuit using invasive recordings. It is unknown whether the same phenomenon might be found in regions other than the cortico-basal ganglia circuit. We hypothesized that using magnetoencephalography to assess phase-amplitude coupling in the whole brain can characterize Parkinson's disease. We recorded resting-state magnetoencephalographic signals in patients with Parkinson's disease and in healthy age- and sex-matched participants. We compared whole-brain signals from the two groups, evaluating the power spectra of 3 frequency bands (alpha, 8-12 Hz; beta, 13-25 Hz; gamma, 50-100 Hz) and the coupling between gamma amplitude and alpha or beta phases. Patients with Parkinson's disease showed significant beta-gamma phase-amplitude coupling that was widely distributed in the sensorimotor, occipital, and temporal cortices; healthy participants showed such coupling only in parts of the somatosensory and temporal cortices. Moreover, beta- and gamma-band power differed significantly between participants in the two groups (P < 0.05). Finally, beta-gamma phase-amplitude coupling in the sensorimotor cortices correlated significantly with motor symptoms of Parkinson's disease (P < 0.05); beta- and gamma-band power did not. We thus demonstrated that beta-gamma phase-amplitude coupling in the resting state characterizes Parkinson's disease.

Data-driven electrophysiological feature based on deep learning to detect epileptic seizures.

Objective. To identify a new electrophysiological feature characterising the epileptic seizures, which is commonly observed in different types of epilepsy.Methods. We recorded the intracranial electroencephalogram (iEEG) of 21 patients (12 women and 9 men) with multiple types of refractory epilepsy. The raw iEEG signals of the early phase of epileptic seizures and interictal states were classified by a convolutional neural network (Epi-Net). For comparison, the same signals were classified by a support vector machine (SVM) using the spectral power and phase-amplitude coupling. The features learned by Epi-Net were derived by a modified integrated gradients method. We considered the product of powers multiplied by the relative contribution of each frequency amplitude as a data-driven epileptogenicity index (d-EI). We compared the d-EI and other conventional features in terms of accuracy to detect the epileptic seizures. Finally, we compared the d-EI among the electrodes to evaluate its relationship with the resected area and the Engel classification.Results. Epi-Net successfully identified the epileptic seizures, with an area under the receiver operating characteristic curve of 0.944 ± 0.067, which was significantly larger than that of the SVM (0.808 ± 0.253,n =21;p =0.025). The learned iEEG signals were characterised by increased powers of 17-92 Hz and >180 Hz in addition to decreased powers of other frequencies. The proposed d-EI detected them with better accuracy than the other iEEG features. Moreover, the surgical resection of areas with a larger increase in d-EI was observed for all nine patients with Engel class ⩽1, but not for the 4 of 12 patients with Engel class >1, demonstrating the significant association with seizure outcomes.Significance.We derived an iEEG feature from the trained Epi-Net, which identified the epileptic seizures with improved accuracy and might contribute to identification of the epileptogenic zone.

BCI training to move a virtual hand reduces phantom limb pain: A randomized crossover trial.

OBJECTIVE: To determine whether training with a brain-computer interface (BCI) to control an image of a phantom hand, which moves based on cortical currents estimated from magnetoencephalographic signals, reduces phantom limb pain. METHODS: Twelve patients with chronic phantom limb pain of the upper limb due to amputation or brachial plexus root avulsion participated in a randomized single-blinded crossover trial. Patients were trained to move the virtual hand image controlled by the BCI with a real decoder, which was constructed to classify intact hand movements from motor cortical currents, by moving their phantom hands for 3 days ("real training"). Pain was evaluated using a visual analogue scale (VAS) before and after training, and at follow-up for an additional 16 days. As a control, patients engaged in the training with the same hand image controlled by randomly changing values ("random training"). The 2 trainings were randomly assigned to the patients. This trial is registered at UMIN-CTR (UMIN000013608). RESULTS: VAS at day 4 was significantly reduced from the baseline after real training (mean [SD], 45.3 [24.2]-30.9 [20.6], 1/100 mm; p = 0.009 < 0.025), but not after random training (p = 0.047 > 0.025). Compared to VAS at day 1, VAS at days 4 and 8 was significantly reduced by 32% and 36%, respectively, after real training and was significantly lower than VAS after random training (p < 0.01). CONCLUSION: Three-day training to move the hand images controlled by BCI significantly reduced pain for 1 week. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that BCI reduces phantom limb pain.

Somatosensation Evoked by Cortical Surface Stimulation of the Human Primary Somatosensory Cortex.

Electrical stimulation of the primary somatosensory cortex using intracranial electrodes is crucial for the evocation of artificial somatosensations, typically tactile sensations associated with specific regions of the body, in brain-machine interface (BMI) applications. The qualitative characteristics of these artificially evoked somatosensations has been well documented. As of yet, however, the quantitative aspects of these evoked somatosensations, that is to say the quantitative relationship between intensity of electrical stimulation and perceived intensity of the resultant somatosensation remains obscure. This study aimed to explore this quantitative relationship by surface electrical stimulation of the primary somatosensory cortex in two human participants undergoing electrocorticographic monitoring prior to surgical treatment of intractable epilepsy. Electrocorticogram electrodes on the primary somatosensory cortical surface were stimulated with varying current intensities, and a visual analogue scale was employed to provide a quantitative measure of intensity of the evoked sensations. Evoked sensations included those of the thumb, tongue, and hand. A clear linear relationship between current intensity and perceived intensity of sensation was observed. These findings provide novel insight into the quantitative nature of primary somatosensory cortex electrical stimulation-evoked sensation for development of somatosensory neuroprosthetics for clinical use.

Automatic diagnosis of neurological diseases using MEG signals with a deep neural network.

The application of deep learning to neuroimaging big data will help develop computer-aided diagnosis of neurological diseases. Pattern recognition using deep learning can extract features of neuroimaging signals unique to various neurological diseases, leading to better diagnoses. In this study, we developed MNet, a novel deep neural network to classify multiple neurological diseases using resting-state magnetoencephalography (MEG) signals. We used the MEG signals of 67 healthy subjects, 26 patients with spinal cord injury, and 140 patients with epilepsy to train and test the network using 10-fold cross-validation. The trained MNet succeeded in classifying the healthy subjects and those with the two neurological diseases with an accuracy of 70.7 ± 10.6%, which significantly exceeded the accuracy of 63.4 ± 12.7% calculated from relative powers of six frequency bands (δ: 1-4 Hz; θ: 4-8 Hz; low-α: 8-10 Hz; high-α: 10-13 Hz; ß: 13-30 Hz; low-γ: 30-50 Hz) for each channel using a support vector machine as a classifier (p = 4.2 × 10-2). The specificity of classification for each disease ranged from 86-94%. Our results suggest that this technique would be useful for developing a classifier that will improve neurological diagnoses and allow high specificity in identifying diseases.

Risk Factors for Postoperative Delirium After Deep Brain Stimulation Surgery for Parkinson Disease.

OBJECTIVE: The aim of this study was to investigate the incidence of and risk factors for postoperative delirium (POD) after deep brain stimulation (DBS) surgery in patients with Parkinson disease. METHODS: We analyzed the preoperative T1-weighted magnetic resonance imaging data of 71 patients with Parkinson disease who underwent DBS surgery. Multiple regression analysis was performed with age, l-dopa equivalent daily dose, laterality of the surgery, target regions, number of electrode trajectories tried, gray matter volume, and white matter (WM) volume as explanatory variables and the duration (number of days) of POD as the response variable. In addition, regional brain atrophy associated with POD was investigated by means of voxel-based morphometry. RESULTS: Excluding patients with outliers, 61 patients were included in the analyses. POD had occurred in 26 of the 61 patients (42.6%). Age and total WM volume were shown by multiple regression analysis to correlate significantly with the duration of POD (P < 0.05 and < 0.01, respectively). WM was significantly reduced in the temporal stem, and the reduction in volume correlated significantly with the duration of POD (P < 0.001). Gray matter atrophy was not associated with POD. CONCLUSIONS: We found that age and WM atrophy in the temporal stem are factors predictive of POD after DBS surgery. In aged patients with temporal stem atrophy, surgical procedures and postoperative management should be carefully explored to reduce the risk of postoperative delirium.

Real-Time Neurofeedback to Modulate ß-Band Power in the Subthalamic Nucleus in Parkinson's Disease Patients.

The ß-band oscillation in the subthalamic nucleus (STN) is a therapeutic target for Parkinson's disease. Previous studies demonstrated that l-DOPA decreases the ß-band (13-30 Hz) oscillations with improvement of motor symptoms. However, it has not been elucidated whether patients with Parkinson's disease are able to control the ß-band oscillation voluntarily. Here, we hypothesized that neurofeedback training to control the ß-band power in the STN induces plastic changes in the STN of individuals with Parkinson's disease. We recorded the signals from STN deep-brain stimulation electrodes during operations to replace implantable pulse generators in eight human patients (3 male) with bilateral electrodes. Four patients were induced to decrease the ß-band power during the feedback training (down-training condition), whereas the other patients were induced to increase (up-training condition). All patients were blinded to their assigned condition. Adjacent contacts that showed the highest ß-band power were selected for the feedback. During the 10 min training, patients were shown a circle whose diameter was controlled by the ß-band power of the selected contacts. Powers in the ß-band during 5 min resting sessions recorded before and after the feedback were compared. In the down-training condition, the ß-band power of the selected contacts decreased significantly after feedback in all four patients (p < 0.05). In contrast, the ß-band power significantly increased after feedback in two of four patients in the up-training condition. Overall, the patients could voluntarily control the ß-band power in STN in the instructed direction (p < 0.05) through neurofeedback.

Mapping ECoG channel contributions to trajectory and muscle activity prediction in human sensorimotor cortex.

Studies on brain-machine interface techniques have shown that electrocorticography (ECoG) is an effective modality for predicting limb trajectories and muscle activity in humans. Motor control studies have also identified distributions of "extrinsic-like" and "intrinsic-like" neurons in the premotor (PM) and primary motor (M1) cortices. Here, we investigated whether trajectories and muscle activity predicted from ECoG were obtained based on signals derived from extrinsic-like or intrinsic-like neurons. Three participants carried objects of three different masses along the same counterclockwise path on a table. Trajectories of the object and upper arm muscle activity were predicted using a sparse linear regression. Weight matrices for the predictors were then compared to determine if the ECoG channels contributed more information about trajectory or muscle activity. We found that channels over both PM and M1 contributed highly to trajectory prediction, while a channel over M1 was the highest contributor for muscle activity prediction.

Navigation-assisted trans-inferotemporal cortex selective amygdalohippocampectomy for mesial temporal lobe epilepsy; preserving the temporal stem.

OBJECTIVE: Selective amygdalohippocampectomy (SAH) can be used to obtain satisfactory seizure control in patients with mesial temporal lobe epilepsy (MTLE). Several SAH procedures have been reported to achieve satisfactory outcomes for seizure control, but none yield fully satisfactory outcomes for memory function. We hypothesized that preserving the temporal stem might play an important role. To preserve the temporal stem, we developed a minimally invasive surgical procedure, 'neuronavigation-assisted trans-inferotemporal cortex SAH' (TITC-SAH). METHODS: TITC-SAH was performed in 23 patients with MTLE (MTLE on the language-non-dominant hemisphere, n = 11). The inferior horn of the lateral ventricle was approached via the inferior or middle temporal gyrus along the inferior temporal sulcus under neuronavigation guidance. The hippocampus was dissected in a subpial manner and resected en bloc together with the parahippocampal gyrus. Seizure control at one year and memory function at 6 months postoperatively were evaluated. RESULTS: One year after TITC-SAH, 20 of the 23 patients were seizure-free (ILAE class 1), 2 were class 2, and 1 was class 3. Verbal memory improved significantly in 13 patients with a diagnosis of hippocampal sclerosis, for whom WMS-R scores were available both pre- and post-operatively. Improvements were seen regardless of whether the SAH was on the language-dominant or non-dominant hemisphere. No major complication was observed. CONCLUSION: Navigation-assisted TITC-SAH performed for MTLE offers a simple, minimally invasive procedure that appears to yield excellent outcomes in terms of seizure control and preservation of memory function, because this procedure does not damage the temporal stem. TITC-SAH should be one of the feasible surgical procedures for MTLE. ABBREVIATIONS: SAH: Amygdalohippocampectomy; MTLE: Mesial temporal lobe epilepsy (MTLE); TITC-SAH: Ttrans-inferotemporal cortex SAH; ILAE: International League Against Epilepsy (ILAE); MRI: Magnetic resonance imaging; EEG: Electroencephalography (EEG); FDG-PET: 8F-fluorodeoxyglucose (FDG)-positron emission tomography; ECoG: Electrocorticography; MEG: Magnetoencephalography; IMZ-SPECT: N-isopropyl-p(123I)-iodoamphetamine single photon emission computed tomography; WMS-R: Wechsler Memory Scale-Revised.

Detection of Epileptic Seizures Using Phase-Amplitude Coupling in Intracranial Electroencephalography.

Seizure detection using intracranial electroencephalography (iEEG) contributes to improved treatment of patients with refractory epilepsy. For that purpose, a feature of iEEG to characterize the ictal state with high specificity and sensitivity is necessary. We evaluated the use of phase-amplitude coupling (PAC) of iEEG signals over a period of 24 h to detect the ictal and interictal states. PAC was estimated by using a synchronisation index (SI) for iEEG signals from seven patients with refractory temporal lobe epilepsy. iEEG signals of the ictal state was characterised by a strong PAC between the phase of ß and the amplitude of high γ. Furthermore, using SI values, the ictal state was successfully detected with significantly higher accuracy than by using the amplitude of high γ alone. In conclusion, PAC accurately distinguished the ictal state from the interictal state.

Clinical and radiological features of endodermal cyst in the oculomotor nerve: A case report.

We present a 9-year-old girl with an endodermal cyst of the oculomotor nerve in the left interpeduncular cistern, who had a history of left ptosis. We suggest that a cyst localized at the exit of the oculomotor nerve from the midbrain associated with oculomotor palsy may suggest this rare entity.

[Surveillance study in collaboration with a university-daycare center for elderly people and nursery school for children on the use of over-the-counter drugs and health food in Fukuyama].

To estimate the extent of use of over-the-counter (OTC) drugs and health food, we administered a questionnaire to the parents of children in a nursery school and to elderly people in a daycare center in Fukuyama city. The aim of the questionnaire was to determine the percentage of children and elderly people who use OTC drugs and health food, the purpose of using them, and the types of OTC drugs and health food used. Other questions concerned the person advising them on the use of OTC and health food, the side effects of OTC drugs and health food, and the awareness of children and elderly people regarding possible interactions between prescription drugs and OTC drugs. In children, the most frequently consumed OTC drugs were cold medicines (32.1%), followed by topical creams (22.6%) and eye lotion (14.3%). In elderly people, the most frequently consumed OTC products were eye lotion (18.0%), followed by laxatives (14.8%) and fomentation agents (13.1%). The purchase ratio of health food for children and elderly people were 4.8% and 11.5%, respectively. These results suggest that the need for OTC drugs and health food in children are very different from those in elderly people. In addition, in promoting self-medication, the demand for the opinion of a specialist occupied about 80% or 70% of the total specialist time among children and elderly people, respectively. Therefore, when providing information on health food and OTC drugs, the needs of each generation should be taken into account. The information obtained from the responses received will allow us to provide better pharmaceutical care for both children and elderly people in Fukuyama city.