Antiseizure Medication-Induced Nystagmus During Eye Closure Identified by Electroencephalography

Nystagmus is a well-known side effect of antiseizure medicines (ASMs), but it is often underestimated and overlooked. Here, we describe a case in which nystagmus during eye closure was identified early using routine electroencephalography (EEG). A 34-year-old man developed focal epilepsy after head trauma at the age of 25 years. The patient was treated with carbamazepine but liver dysfunction was observed; therefore, treatment was attempted with lacosamide (LCM) and lamotrigine. With an increase in the LCM dose, steep potential changes suggestive of horizontal nystagmus were observed in the electrooculogram, F7, and F8 on EEG, and the patient complained of eye shaking during eye closure. These symptoms and EEG findings improved with LCM dose reduction. If the presence of nystagmus is identified on EEG coincidentally and a patient's subjective symptoms with ASM are confirmed, it is advisable to taper and/or discontinue the causative agent.

Epileptic seizure clustering and accumulation at transition from activity to rest in GAERS rats

Knowing when seizures occur may help patients and can also provide insight into epileptogenesis mechanisms. We recorded seizures over periods of several days in the Genetic Absence Epileptic Rat from Strasbourg (GAERS) model of absence epilepsy, while we monitored behavioral activity with a combined head accelerometer (ACCEL), neck electromyogram (EMG), and electrooculogram (EOG). The three markers consistently discriminated between states of behavioral activity and rest. Both GAERS and control Wistar rats spent more time in rest (55-66%) than in activity (34-45%), yet GAERS showed prolonged continuous episodes of activity (23 vs. 18 min) and rest (34 vs. 30 min). On average, seizures lasted 13 s and were separated by 3.2 min. Isolated seizures were associated with a decrease in the power of the activity markers from steep for ACCEL to moderate for EMG and weak for EOG, with ACCEL and EMG power changes starting before seizure onset. Seizures tended to occur in bursts, with the probability of seizing significantly increasing around a seizure in a window of ±4 min. Furthermore, the seizure rate was strongly increased for several minutes when transitioning from activity to rest. These results point to mechanisms that control behavioral states as determining factors of seizure occurrence.

Application of Electrophysiology in Non-Macular Inherited Retinal Dystrophies

Inherited retinal dystrophies encompass a diverse group of disorders affecting the structure and function of the retina, leading to progressive visual impairment and, in severe cases, blindness. Electrophysiology testing has emerged as a valuable tool in assessing and diagnosing those conditions, offering insights into the function of different parts of the visual pathway from retina to visual cortex and aiding in disease classification. This review provides an overview of the application of electrophysiology testing in the non-macular inherited retinal dystrophies focusing on both common and rare variants, including retinitis pigmentosa, progressive cone and cone-rod dystrophy, bradyopsia, Bietti crystalline dystrophy, late-onset retinal degeneration, and fundus albipunctatus. The different applications and limitations of electrophysiology techniques, including multifocal electroretinogram (mfERG), full-field ERG (ffERG), electrooculogram (EOG), pattern electroretinogram (PERG), and visual evoked potential (VEP), in the diagnosis and management of these distinctive phenotypes are discussed. The potential for electrophysiology testing to allow for further understanding of these diseases and the possibility of using these tests for early detection, prognosis prediction, and therapeutic monitoring in the future is reviewed.

Clinical and visual electrophysiological characteristics of vitelliform macular dystrophies in the first decade of life

Purpose:

To evaluate patterns of pediatric vitelliform macular dystrophy (PVMD).

Methods:

This is a retrospective analysis of Indian children with vitelliform macular dystrophy (VMD) presenting within the first decade of life. Records were evaluated for clinical findings, family screening, and investigative findings including optical coherence tomography (OCT), fundus autofluorescence (FAF), full-field electroretinogram (ERG) and electrooculogram (EOG). Electrophysiology was scrutinized and audited for acquisition and interpretation errors. Findings on follow-up were also recorded.

Results:

46 eyes of 24 patients were included. Mean age at presentation was 7.17 ± 2.17 years. Mean follow-up duration was 1.55 ± 1.69 years. Best disease was the commonest type of VMD detected (21 patients), while autosomal recessive bestrophinopathy was seen in three cases. Mean logMAR BCVA was 0.364 which decreased to 0.402 on follow-up. Hyperopia was noted in 29 out of 46 eyes (mean being +3.87 D, range ebing +0.75 to +8.75 D). Four eyes of four children had choroidal neovascular membrane at presentation, while another child developed while in follow-up. Solid type subretinal deposit was the commonest OCT finding (n = 29/38) and central hyper FAF was the commonest pattern (n = 18/32). EOG was available for review in 32 eyes, but was unreliable in 11 eyes. Seven eyes demonstrated complete absence of light rise on EOG.

Conclusion:

PVMD can present in advanced forms. Progression to complications with loss of visual acuity can happen within the first decade of life. EOG shows grossly suppressed waveforms in the light phase in a large number of such children.

Images: polysomnographic findings of nystagmus caused by a midbrain hemorrhagic stroke

Brainstem strokes can present with an array of ophthalmologic findings depending on the location of the lesion. Eye movements are recorded on electrooculogram during polysomnography for sleep staging. We present the case of a patient with a dorsal midbrain hemorrhagic stroke and nystagmus with distinct findings on the electrooculogram during polysomnography. These eye movements from nystagmus differed in many aspects (frequency and amplitude) from the classic findings of other eye movements recorded during different stages of sleep. These polysomnography findings have not been reported in the setting of midbrain stroke. Future studies comparing nystagmus in multiple sleep stages in stroke patients would be of interest.

CITATION

Shoukat U, Glick DR, Chaturvedi S, Diaz-Abad M. Images: Polysomnographic findings of nystagmus caused by a midbrain hemorrhagic stroke. J Clin Sleep Med. 2022;18(5):1479-1482.

Novel Hybrid Brain-Computer Interface for Virtual Reality Applications Using Steady-State Visual-Evoked Potential-Based Brain-Computer Interface and Electrooculogram-Based Eye Tracking for Increased Information Transfer Rate

Brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have recently attracted increasing attention in virtual reality (VR) applications as a promising tool for controlling virtual objects or generating commands in a "hands-free" manner. Video-oculography (VOG) has been frequently used as a tool to improve BCI performance by identifying the gaze location on the screen, however, current VOG devices are generally too expensive to be embedded in practical low-cost VR head-mounted display (HMD) systems. In this study, we proposed a novel calibration-free hybrid BCI system combining steady-state visual-evoked potential (SSVEP)-based BCI and electrooculogram (EOG)-based eye tracking to increase the information transfer rate (ITR) of a nine-target SSVEP-based BCI in VR environment. Experiments were repeated on three different frequency configurations of pattern-reversal checkerboard stimuli arranged in a 3 × 3 matrix. When a user was staring at one of the nine visual stimuli, the column containing the target stimulus was first identified based on the user's horizontal eye movement direction (left, middle, or right) classified using horizontal EOG recorded from a pair of electrodes that can be readily incorporated with any existing VR-HMD systems. Note that the EOG can be recorded using the same amplifier for recording SSVEP, unlike the VOG system. Then, the target visual stimulus was identified among the three visual stimuli vertically arranged in the selected column using the extension of multivariate synchronization index (EMSI) algorithm, one of the widely used SSVEP detection algorithms. In our experiments with 20 participants wearing a commercial VR-HMD system, it was shown that both the accuracy and ITR of the proposed hybrid BCI were significantly increased compared to those of the traditional SSVEP-based BCI in VR environment.

Classification of Gamers Using Multiple Physiological Signals: Distinguishing Features of Internet Gaming Disorder

The proliferating and excessive use of internet games has caused various comorbid diseases, such as game addiction, which is now a major social problem. Recently, the American Psychiatry Association classified “Internet gaming disorder (IGD)” as an addiction/mental disorder. Although many studies have been conducted on the diagnosis, treatment, and prevention of IGD, screening studies for IGD are still scarce. In this study, we classified gamers using multiple physiological signals to contribute to the treatment and prevention of IGD. Participating gamers were divided into three groups based on Young’s Internet Addiction Test score and average game time as follows: Group A, those who rarely play games; Group B, those who enjoy and play games regularly; and Group C, those classified as having IGD. In our game-related cue-based experiment, we obtained self-reported craving scores and multiple physiological data such as electrooculogram (EOG), photoplethysmogram (PPG), and electroencephalogram (EEG) from the users while they watched neutral (natural scenery) or stimulating (gameplay) videos. By analysis of covariance (ANCOVA), 13 physiological features (vertical saccadic movement from EOG, standard deviation of N-N intervals, and PNN50 from PPG, and many EEG spectral power indicators) were determined to be significant to classify the three groups. The classification was performed using a 2-layers feedforward neural network. The fusion of three physiological signals showed the best result compared to other cases (combination of EOG and PPG or EEG only). The accuracy was 0.90 and F-1 scores were 0.93 (Group A), 0.89 (Group B), and 0.88 (Group C). However, the subjective self-reported scores did not show a significant difference among the three groups by ANCOVA analysis. The results indicate that the fusion of physiological signals can be an effective method to objectively classify gamers.

Deep Coupling Recurrent Auto-Encoder with Multi-Modal EEG and EOG for Vigilance Estimation

Vigilance estimation of drivers is a hot research field of current traffic safety. Wearable devices can monitor information regarding the driver’s state in real time, which is then analyzed by a data analysis model to provide an estimation of vigilance. The accuracy of the data analysis model directly affects the effect of vigilance estimation. In this paper, we propose a deep coupling recurrent auto-encoder (DCRA) that combines electroencephalography (EEG) and electrooculography (EOG). This model uses a coupling layer to connect two single-modal auto-encoders to construct a joint objective loss function optimization model, which consists of single-modal loss and multi-modal loss. The single-modal loss is measured by Euclidean distance, and the multi-modal loss is measured by a Mahalanobis distance of metric learning, which can effectively reflect the distance between different modal data so that the distance between different modes can be described more accurately in the new feature space based on the metric matrix. In order to ensure gradient stability in the long sequence learning process, a multi-layer gated recurrent unit (GRU) auto-encoder model was adopted. The DCRA integrates data feature extraction and feature fusion. Relevant comparative experiments show that the DCRA is better than the single-modal method and the latest multi-modal fusion. The DCRA has a lower root mean square error (RMSE) and a higher Pearson correlation coefficient (PCC).

An Electro-Oculogram Based Vision System for Grasp Assistive Devices-A Proof of Concept Study

Humans typically fixate on objects before moving their arm to grasp the object. Patients with ALS disorder can also select the object with their intact eye movement, but are unable to move their limb due to the loss of voluntary muscle control. Though several research works have already achieved success in generating the correct grasp type from their brain measurement, we are still searching for fine controll over an object with a grasp assistive device (orthosis/exoskeleton/robotic arm). Object orientation and object width are two important parameters for controlling the wrist angle and the grasp aperture of the assistive device to replicate a human-like stable grasp. Vision systems are already evolved to measure the geometrical attributes of the object to control the grasp with a prosthetic hand. However, most of the existing vision systems are integrated with electromyography and require some amount of voluntary muscle movement to control the vision system. Due to that reason, those systems are not beneficial for the users with brain-controlled assistive devices. Here, we implemented a vision system which can be controlled through the human gaze. We measured the vertical and horizontal electrooculogram signals and controlled the pan and tilt of a cap-mounted webcam to keep the object of interest in focus and at the centre of the picture. A simple ‘signature’ extraction procedure was also utilized to reduce the algorithmic complexity and system storage capacity. The developed device has been tested with ten healthy participants. We approximated the object orientation and the size of the object and determined an appropriate wrist orientation angle and the grasp aperture size within 22 ms. The combined accuracy exceeded 75%. The integration of the proposed system with the brain-controlled grasp assistive device and increasing the number of grasps can offer more natural manoeuvring in grasp for ALS patients.

EEG-Based Eye Movement Recognition Using Brain-Computer Interface and Random Forests

Discrimination of eye movements and visual states is a flourishing field of research and there is an urgent need for non-manual EEG-based wheelchair control and navigation systems. This paper presents a novel system that utilizes a brain–computer interface (BCI) to capture electroencephalographic (EEG) signals from human subjects while eye movement and subsequently classify them into six categories by applying a random forests (RF) classification algorithm. RF is an ensemble learning method that constructs a series of decision trees where each tree gives a class prediction, and the class with the highest number of class predictions becomes the model’s prediction. The categories of the proposed random forests brain–computer interface (RF-BCI) are defined according to the position of the subject’s eyes: open, closed, left, right, up, and down. The purpose of RF-BCI is to be utilized as an EEG-based control system for driving an electromechanical wheelchair (rehabilitation device). The proposed approach has been tested using a dataset containing 219 records taken from 10 different patients. The BCI implemented the EPOC Flex head cap system, which includes 32 saline felt sensors for capturing the subjects’ EEG signals. Each sensor caught four different brain waves (delta, theta, alpha, and beta) per second. Then, these signals were split in 4-second windows resulting in 512 samples per record and the band energy was extracted for each EEG rhythm. The proposed system was compared with naïve Bayes, Bayes Network, k-nearest neighbors (K-NN), multilayer perceptron (MLP), support vector machine (SVM), J48-C4.5 decision tree, and Bagging classification algorithms. The experimental results showed that the RF algorithm outperformed compared to the other approaches and high levels of accuracy (85.39%) for a 6-class classification are obtained. This method exploits high spatial information acquired from the Emotiv EPOC Flex wearable EEG recording device and examines successfully the potential of this device to be used for BCI wheelchair technology.

Automated Detection of Presymptomatic Conditions in Spinocerebellar Ataxia Type 2 Using Monte Carlo Dropout and Deep Neural Network Techniques with Electrooculogram Signals

Application of deep learning (DL) to the field of healthcare is aiding clinicians to make an accurate diagnosis. DL provides reliable results for image processing and sensor interpretation problems most of the time. However, model uncertainty should also be thoroughly quantified. This paper therefore addresses the employment of Monte Carlo dropout within the DL structure to automatically discriminate presymptomatic signs of spinocerebellar ataxia type 2 in saccadic samples obtained from electrooculograms. The current work goes beyond the common incorporation of this special type of dropout into deep neural networks and uses the uncertainty derived from the validation samples to construct a decision tree at the register level of the patients. The decision tree built from the uncertainty estimates obtained a classification accuracy of 81.18% in automatically discriminating control, presymptomatic and sick classes. This paper proposes a novel method to address both uncertainty quantification and explainability to develop reliable healthcare support systems.

Novel BEST1 gene mutations associated with two different forms of macular dystrophy in Tunisian families

BACKGROUND

Epidemiological studies of hereditary eye diseases allowed us to identify two Tunisian families suffering from macular dystrophies: Best vitelliform macular dystrophy (BVMD) and autosomal recessive bestrophinopathy (ARB). The purpose of the current study was to investigate the clinical characteristics and the underlying genetics of these two forms of macular dystrophy.

METHODS

Complete ophthalmic examination was performed including optical coherence tomography, electroretinography, electrooculography and autofluoresence imaging in all patients. Genomic DNA was extracted from peripheral blood collected from patients and family members.

RESULTS

Sanger sequencing of all exons of the BEST1 gene in both families identified two new mutations: a missense mutation c.C91A [p.L31 M] at the N-terminal transmembrane domain within the ARB family and a nonsense mutation C1550G (p.S517X) in the C-terminal domain segregating in the BVMD family.

CONCLUSIONS

Several mutations of the BEST1 gene have been reported which are responsible for numerous ocular pathologies. To the best of our knowledge, it is the first time we report mutations in this gene in Tunisian families presenting different forms of macular dystrophy. Our report also expands the list of pathogenic BEST1 genotypes and the associated clinical diagnosis.

Effectiveness of nasal continuous airway pressure therapy in patients with obstructive sleep apnea

OBJECTIVES

A prospective observational study was carried out with the aim of evaluating the effectiveness of nasal continuous positive airway pressure (nCPAP) therapy on the health-related quality of life (QoL) of patients with obstructive sleep apnea (OSA).

METHODS

The patients included in this study were those recently diagnosed with OSA (AHI > 5) and given nCPAP therapy, as well as being referred to a sleep laboratory for an assessment of their sleep disordered breathing. Prior to the start of nCPAP therapy and polysomnography evaluation, patients were asked to complete the validated Quebec sleep questionnaire (QSQ), and their baseline measurements were recorded.

RESULTS

Among the study population, 14.41% (n = 31) had mild OSA with an apnea and hypopnea index of 5 to 14.9 events/h, while 26.97% (n = 58) had moderate OSA and 40% (n = 86) had severe OSA. The overall average apnea and hypopnea index of the study population was 30.24 ± 9.73 events/h; mild OSA patients had an average apnea and hypopnea index of 10.09 ± 2.65 events/h, moderate OSA patients had 21.48 ± 4.40 events/h, and severe OSA patients had 59.16 ± 22.14 events/h. A significant difference was observed between the scores before treatment and after 6 months of therapy in all domains of the QSQ QoL scores (P < 0.0001).

CONCLUSION

Nasal continuous positive airway pressure treatment improved the QoL for patients with mild, moderate, and severe sleep apnea.

Impaired retinal pigment epithelium in paclitaxel-induced macular edema: A case report

RATIONALE

Cystoid macular edema (CME) is a rare complication of the paclitaxel. However, the pathophysiology was unknown.

PATIENT CONCERNS

A 60-year-old female presented with bilateral blurred vision due to cystoid macular edema after taking 12-course paclitaxel for her breast cancer. Optical coherence tomography (OCT), fluorescein angiography (FAG), indocyanine green angiography (ICGA), electroretinogram (ERG) and electrooculogram (EOG) were performed.

DIAGNOSES

Paclitaxel-induced macular edema.

INTERVENTIONS

Paclitaxel was discontinued and supportive treatment with pentoxifylline was given.

OUTCOMES

The OCT showed bilateral cystoid macular edema. Impaired filling of choriocapillaries was noted on the ICGA; while EOG revealed decreased Arden ratio. The visual acuity, cystoid macular edema and decreased Arden ratio improved slowly over six months.

LESSONS

Paclitaxel rarely causes cystoid macular edema. The damage of choriocapillaries and retinal pigment epithelium might be the underlying cause. Immediate discontinuation of the drug helps visual recovery.

Electrocardiographic and Electrooculographic Responses to External Emotions and Their Transitions in Bipolar I and II Disorders

Bipolar disorder has two main types, bipolar I (BD I) and II (BD II), which present different affective states and personality characteristics, they might present different modes of emotional regulation. We hypothesized that the electrocardiogram and electrooculogram to external emotions are different in BD I and BD II. We asked 69 BD I and 54 BD II patients, and 139 healthy volunteers to undergo these tests in response to disgust, erotica, fear, happiness, neutral, and sadness, and their transitions. Their affective states were also measured. The heart rate in BD I was significantly higher under background fear after target neutral. The eyeball movement was quicker in BD I under target happiness after background disgust; in BD I under target sadness after background disgust; and in BD I under background disgust after target neutral. Some electrocardiographic and electrooculographic changes were correlated with affective states in patients. BD I and BD II had different physiological responses to external emotions and their transitions, indicating different pathophysiologies and suggesting different emotional-therapies for BD I and BD II.

A Novel Wearable Forehead EOG Measurement System for Human Computer Interfaces

Amyotrophic lateral sclerosis (ALS) patients whose voluntary muscles are paralyzed commonly communicate with the outside world using eye movement. There have been many efforts to support this method of communication by tracking or detecting eye movement. An electrooculogram (EOG), an electro-physiological signal, is generated by eye movements and can be measured with electrodes placed around the eye. In this study, we proposed a new practical electrode position on the forehead to measure EOG signals, and we developed a wearable forehead EOG measurement system for use in Human Computer/Machine interfaces (HCIs/HMIs). Four electrodes, including the ground electrode, were placed on the forehead. The two channels were arranged vertically and horizontally, sharing a positive electrode. Additionally, a real-time eye movement classification algorithm was developed based on the characteristics of the forehead EOG. Three applications were employed to evaluate the proposed system: a virtual keyboard using a modified Bremen BCI speller and an automatic sequential row-column scanner, and a drivable power wheelchair. The mean typing speeds of the modified Bremen brain–computer interface (BCI) speller and automatic row-column scanner were 10.81 and 7.74 letters per minute, and the mean classification accuracies were 91.25% and 95.12%, respectively. In the power wheelchair demonstration, the user drove the wheelchair through an 8-shape course without collision with obstacles.

Metabolic and functional changes in retinitis pigmentosa: comparing retinal vessel oximetry to full-field electroretinography, electrooculogram and multifocal electroretinography

PURPOSE

To determine a relationship between the retinal vessel saturation alterations and the residual retinal function measured by means of full-field electroretinography (full-field ERG), electrooculogram (EOG) and multifocal electroretinography (mfERG) in patients with retinitis pigmentosa (RP).

METHODS

Retinal vessel oximetry (RO), full-field ERG, EOG and mfERG were performed on 43 eyes of 22 patients suffering from RP and were compared to those of 26 eyes of 13 healthy controls. The oxygen saturation in the first and second branch retinal arterioles (A-SO2 ) and venules (V-SO2 ) was measured, and their difference (A-V SO2 ) was calculated. Full-field ERG amplitudes, EOG parameters and averaged mfERG response amplitudes (within central 3°, between 3° and 8°, 8° and 15°, 15° and 24°) were evaluated in relation to the RO measurements.

RESULTS

V-SO2 correlated negatively with the full-field ERG and EOG values, with increasing functional damage the V-SO2 was higher. The RP group was well distinguished from the controls when the RO measurements were correlated to the averaged N1 (baseline to trough), but also to the N1P1 (trough-to-peak) mfERG response amplitudes. Receiver operating characteristic (ROC) curve of V-SO2 , compared to those of N1 and N1P1 mfERG response averages (15-24°), presented a high differential margin between RP and controls (p < 0.001), shown by an area under the ROC curve of 0.912 (95% CI: 0.840-0.984).

CONCLUSION

Retinal vessel saturation showed a significant relation to full-field ERG, EOG and mfERG. Thus, retinal vessel oximetry could potentially complement electrophysiological tests in monitoring disease progression in patients with RP.

A perspective on the mechanism of the light-rise of the electrooculogram

The light-rise of the electrooculogram is believed to originate from a substance released from the rods after dark adaptation. The identity of this "elusive" light-rise substance has not been demonstrated, and therefore a new perspective on the light-rise is presented. The light-rise is caused by the depolarization of the basolateral membrane of the retinal pigment epithelium (RPE) has become clearer in the last decade with the identification of calcium as the intracellular secondary messenger and the role of bestrophin as a regulator of intracellular stores of calcium and controlling the cytosolic calcium levels through L-type calcium channels. The light-rise depends upon a change from darkness to light, which triggers the intracellular cascade resulting in the depolarization of the basolateral membrane. The same intracellular signaling molecules, notably calcium and inositol triphosphate (IP3), are strongly implicated in this cascade. Recent studies have now led to a clearer understanding of the roles and functions of the ion channels and their contribution to the light-rise with IP3 regulating the release of calcium for intracellular stores. Given that calcium and IP3 are also regulators of phagocytosis, and that the initiation of rod outer segment phagocytosis is initiated with light-onset, it may be that the light-rise is generated in response to this physiological event. Therefore, the putative light-rise substance may not be released by the rods, but follow directly from IP3 release from the RPE's phospholipid membrane following the onset of light and the initiation of phagocytosis. The light rise substance, could be considered to be light itself.

The effects of periodic limb movements in sleep (PLMS) on cardiovascular disease

Periodic limb movements in sleep (PLMS) are uncontrollable nocturnal movements that occur during sleep and increase with age. Research has implicated PLMS as a contributing factor to the development of cardiovascular disease (CVD). The purpose of this manuscript is to 1) explain the sleep disorder of PLMS and implications on CVD; 2) identify the impact of PLMS on CVD; 3) discuss treatment options for PLMS; 4) present future research needs for PLMS/RLS; 5) provide implications to health care providers to improve the care and health outcomes of persons with PLMS.

D1 receptor agonist improves sleep-wake parameters in experimental parkinsonism

Both excessive daytime sleepiness (EDS) and rapid eye movement (REM) sleep deregulation are part of Parkinson's disease (PD) non-motor symptoms and may complicate dopamine replacement therapy. We report here that dopamine agonists act differentially on sleep architecture in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine macaque monkey. Continuous sleep and wake electroencephalographic monitoring revealed no effect of the selective dopamine D2 receptor agonist quinpirole on EDS, whereas the selective dopamine D1 receptor agonist SKF38393 efficiently alleviated EDS and restored REM sleep to baseline values. The present results question the relevance of abandoning D1 receptor agonist treatment in PD as it might actually improve sleep-related disorders.

Integration of sensory information precedes the sensation of vection: a combined behavioral and event-related brain potential (ERP) study

Illusory self-motion (known as vection) describes the sensation of ego-motion in the absence of physical movement. Vection typically occurs in stationary observers being exposed to visual information that suggest self-motion (e.g. simulators, virtual reality). In the present study, we tested whether sensory integration of visual information triggers vection: participants (N=13) perceived patterns of moving altered black-and-white vertical stripes on a screen that was divided into a central and a surrounding peripheral visual field. In both fields the pattern was either moving or stationary, resulting in four combinations of central and peripheral motions: (1) central and peripheral stripes moved into the same direction, (2) central and peripheral stripes moved in opposite directions, or (3) either the central or (4) the peripheral stripes were stable while the other stripes were in motion. This stimulation induced vection: Results showed significantly higher vection ratings when the stationary center of the pattern was surrounded by a moving periphery. Event-related potentials mirrored this finding: The occipital N2 was largest with stationary central and moving peripheral stripes. Our findings suggest that sensory integration of peripheral and central visual information triggers the perception of vection. Furthermore, we found evidence that neural processes precede the subjective perception of vection strength prior to the actual onset of vection. We will discuss our findings with respect to the role of stimulus eccentricity, stimulus' depth, and neural correlates involved during the genesis of vection.

The effects of music on brain functional networks: a network analysis

The human brain can dynamically adapt to the changing surroundings. To explore this issue, we adopted graph theoretical tools to examine changes in electroencephalography (EEG) functional networks while listening to music. Three different excerpts of Chinese Guqin music were played to 16 non-musician subjects. For the main frequency intervals, synchronizations between all pair-wise combinations of EEG electrodes were evaluated with phase lag index (PLI). Then, weighted connectivity networks were created and their organizations were characterized in terms of an average clustering coefficient and characteristic path length. We found an enhanced synchronization level in the alpha2 band during music listening. Music perception showed a decrease of both normalized clustering coefficient and path length in the alpha2 band. Moreover, differences in network measures were not observed between musical excerpts. These experimental results demonstrate an increase of functional connectivity as well as a more random network structure in the alpha2 band during music perception. The present study offers support for the effects of music on human brain functional networks with a trend toward a more efficient but less economical architecture.

Using joint ICA to link function and structure using MEG and DTI in schizophrenia

In this study we employed joint independent component analysis (jICA) to perform a novel multivariate integration of magnetoencephalography (MEG) and diffusion tensor imaging (DTI) data to investigate the link between function and structure. This model-free approach allows one to identify covariation across modalities with different temporal and spatial scales [temporal variation in MEG and spatial variation in fractional anisotropy (FA) maps]. Healthy controls (HC) and patients with schizophrenia (SP) participated in an auditory/visual multisensory integration paradigm to probe cortical connectivity in schizophrenia. To allow direct comparisons across participants and groups, the MEG data were registered to an average head position and regional waveforms were obtained by calculating the local field power of the planar gradiometers. Diffusion tensor images obtained in the same individuals were preprocessed to provide FA maps for each participant. The MEG/FA data were then integrated using the jICA software (http://mialab.mrn.org/software/fit). We identified MEG/FA components that demonstrated significantly different (p<0.05) covariation in MEG/FA data between diagnostic groups (SP vs. HC) and three components that captured the predominant sensory responses in the MEG data. Lower FA values in bilateral posterior parietal regions, which include anterior/posterior association tracts, were associated with reduced MEG amplitude (120-170 ms) of the visual response in occipital sensors in SP relative to HC. Additionally, increased FA in a right medial frontal region was linked with larger amplitude late MEG activity (300-400 ms) in bilateral central channels for SP relative to HC. Step-wise linear regression provided evidence that right temporal, occipital and late central components were significant predictors of reaction time and cognitive performance based on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) cognitive assessment battery. These results point to dysfunction in a posterior visual processing network in schizophrenia, with reduced MEG amplitude, reduced FA and poorer overall performance on the MATRICS. Interestingly, the spatial location of the MEG activity and the associated FA regions are spatially consistent with white matter regions that subserve these brain areas. This novel approach provides evidence for significant pairing between function (neurophysiology) and structure (white matter integrity) and demonstrates that this multivariate, multimodal integration technique is sensitive to group differences in function and structure.