Application of eye trackers for understanding mental disorders: Cases for schizophrenia and autism spectrum disorder

Cognition and saccadic eye movement performance are impaired in chronic rhinosinusitis

BACKGROUND

Patients with chronic rhinosinusitis (CRS) can experience cognitive dysfunction. The literature on this topic mostly reflects patient-reported measurements. Our goal was to assess cognitive function in patients with CRS using objective measures, including saccadic eye movements-a behavioral response reflecting cognitive and sensory information integration that is often compromised in conditions with impaired cognition.

METHODS

Participants (N = 24 with CRS, N = 23 non-CRS healthy controls) enrolled from rhinology clinic underwent sinonasal evaluation, quality of life assessment (Sino-nasal Outcome Test 22 [SNOT-22]), and cognitive assessment with the Neuro-QOL Cognitive Function-Short Form, the Montreal Cognitive Assessment (MoCA), and recording of eye movements using video-oculography.

RESULTS

Participants with CRS were more likely to report cognitive dysfunction (Neuro-QOL; 45.8% vs. 8.7%; p = 0.005) and demonstrate mild or greater cognitive impairment (MoCA; 41.7% vs. 8.7%; p = 0.005) than controls. Additionally, participants with CRS performed worse on the MoCA overall and within the executive functioning and memory domains (all p < 0.05) and on the anti-saccade (p = 0.014) and delay saccade (p = 0.044) eye movement tasks. Poorer performance on the MoCA (r = -0.422; p = 0.003) and the anti-saccade (r = -0.347; p = 0.017) and delay saccade (r = -0.419; p = 0.004) eye movement tasks correlated with worse CRS severity according to SNOT-22 scores.

CONCLUSION

This study is the first to utilize objective eye movement assessments in addition to researcher-administered cognitive testing in patients with CRS. These patients demonstrated a high prevalence of cognitive dysfunction, most notably within executive functioning and memory domains, with the degree of dysfunction correlating with the severity of CRS.

Causal relationship between schizophrenia and sex hormone binding globulin: A Mendelian randomization study

OBJECTIVE

The underlying etiology of schizophrenia is still not fully understood, and recent studies have pointed to a potential link between hormonal factors and the risk of developing this condition. Sex Hormone-Binding Globulin (SHBG) is a protein that regulates the bioavailability of sex hormones. However, the causal relationship between SHBG levels and schizophrenia remains unclear, this study aimed to investigate the causal relationship based on two-sample Mendelian randomization (MR) analysis.

METHODS

This study was based on the summary data of genome-wide association studies (GWAS) of schizophrenia and SHBG in European populations. Two-sample MR was applied, and genetic factors were used as instrumental variables, and the causal relationship between schizophrenia and SHBG was assessed.

RESULTS

We selected 79 single nucleotide polymorphisms with genome-wide significance from the schizophrenia GWAS as instrumental variables. The inverse variance weighting (IVW) method results showed that there is a causal relationship and a positive correlation between schizophrenia and female SHBG, with an odds ratio (OR) of 1.024 (95%CI: 1.007-1.042, P = 0.005), and this result was further confirmed by the Weighted median odds ratio (OR) of 1.032 (95%CI: 1.016-1.048, P = 5.58E-05) and the Weighted mode of 1.035 (95%CI: 1.004-1.067, P = 0.028). Schizophrenia and male SHBG also have a causal relationship and a positive correlation, with an odds ratio (OR) of 1.027 (95%CI: 1.007-1.047, P = 0.008).

CONCLUSION

This study found a positive correlation between schizophrenia and SHBG in both men and women through MR analysis, indicating that the level of SHBG may be elevated in patients with schizophrenia, regardless of gender.

AI for Psychometrics: Validating Machine Learning Models in Measuring Emotional Intelligence with Eye-Tracking Techniques

AI, or artificial intelligence, is a technology of creating algorithms and computer systems that mimic human cognitive abilities to perform tasks. Many industries are undergoing revolutions due to the advances and applications of AI technology. The current study explored a burgeoning field-Psychometric AI, which integrates AI methodologies and psychological measurement to not only improve measurement accuracy, efficiency, and effectiveness but also help reduce human bias and increase objectivity in measurement. Specifically, by leveraging unobtrusive eye-tracking sensing techniques and performing 1470 runs with seven different machine-learning classifiers, the current study systematically examined the efficacy of various (ML) models in measuring different facets and measures of the emotional intelligence (EI) construct. Our results revealed an average accuracy ranging from 50-90%, largely depending on the percentile to dichotomize the EI scores. More importantly, our study found that AI algorithms were powerful enough to achieve high accuracy with as little as 5 or 2 s of eye-tracking data. The research also explored the effects of EI facets/measures on ML measurement accuracy and identified many eye-tracking features most predictive of EI scores. Both theoretical and practical implications are discussed.

A tablet-based quantitative assessment of manual dexterity for detection of early psychosis

Background

We performed a pilot study on whether tablet-based measures of manual dexterity can provide behavioral markers for detection of first-episode psychosis (FEP), and whether cortical excitability/inhibition was altered in FEP.

Methods

Behavioral and neurophysiological testing was undertaken in persons diagnosed with FEP (N = 20), schizophrenia (SCZ, N = 20), autism spectrum disorder (ASD, N = 20), and in healthy control subjects (N = 20). Five tablet tasks assessed different motor and cognitive functions: Finger Recognition for effector (finger) selection and mental rotation, Rhythm Tapping for temporal control, Sequence Tapping for control/memorization of motor sequences, Multi Finger Tapping for finger individuation, and Line Tracking for visuomotor control. Discrimination of FEP (from other groups) based on tablet-based measures was compared to discrimination through clinical neurological soft signs (NSS). Cortical excitability/inhibition, and cerebellar brain inhibition were assessed with transcranial magnetic stimulation.

Results

Compared to controls, FEP patients showed slower reaction times and higher errors in Finger Recognition, and more variability in Rhythm Tapping. Variability in Rhythm Tapping showed highest specificity for the identification of FEP patients compared to all other groups (FEP vs. ASD/SCZ/Controls; 75% sensitivity, 90% specificity, AUC = 0.83) compared to clinical NSS (95% sensitivity, 22% specificity, AUC = 0.49). Random Forest analysis confirmed FEP discrimination vs. other groups based on dexterity variables (100% sensitivity, 85% specificity, balanced accuracy = 92%). The FEP group had reduced short-latency intra-cortical inhibition (but similar excitability) compared to controls, SCZ, and ASD. Cerebellar inhibition showed a non-significant tendency to be weaker in FEP.

Conclusion

FEP patients show a distinctive pattern of dexterity impairments and weaker cortical inhibition. Easy-to-use tablet-based measures of manual dexterity capture neurological deficits in FEP and are promising markers for detection of FEP in clinical practice.

Advances in Materials, Sensors, and Integrated Systems for Monitoring Eye Movements

Eye movements show primary responses that reflect humans' voluntary intention and conscious selection. Because visual perception is one of the fundamental sensory interactions in the brain, eye movements contain critical information regarding physical/psychological health, perception, intention, and preference. With the advancement of wearable device technologies, the performance of monitoring eye tracking has been significantly improved. It also has led to myriad applications for assisting and augmenting human activities. Among them, electrooculograms, measured by skin-mounted electrodes, have been widely used to track eye motions accurately. In addition, eye trackers that detect reflected optical signals offer alternative ways without using wearable sensors. This paper outlines a systematic summary of the latest research on various materials, sensors, and integrated systems for monitoring eye movements and enabling human-machine interfaces. Specifically, we summarize recent developments in soft materials, biocompatible materials, manufacturing methods, sensor functions, systems' performances, and their applications in eye tracking. Finally, we discuss the remaining challenges and suggest research directions for future studies.

Attention for Emotion-How Young Adults With Neurodevelopmental Disorders Look at Facial Expressions of Affect

While Autism Spectrum Disorder (ASD), Attention-Deficit/Hyperactivity Disorder (ADHD) and Schizophrenia (SCZ) differ in many clinically relevant features such as symptomatology and course, they may also share genetic underpinnings, affective problems, deviancies in social interactions, and are all characterized by some kind of cognitive impairment. This situation calls for a joint investigation of the specifics of cognitive (dys-)functions of the three disorders. Such endeavor should focus, among other domains, on the inter-section of processing cognitive, affective and social information that is crucial in effective real-life interactions and can be accomplished when attentional preferences for human facial expressions of emotions is studied. To that end, attention to facial expressions of basic emotions was examined in young adults with ASD, ADHD, or SCZ in the present study. The three clinical groups were compared with an age-matched group of typically-developing participants (TD) during the free contemplation of five different facial emotions presented simultaneously, by varying identities, through the registration of eye movements. We showed, that dwell times and fixation counts differed for the different emotions in TD and in a highly similar way in ADHD. Patients with ASD differed from TD by showing a stronger differentiation between emotions and partially different attentional preferences. In contrast, the SCZ group showed an overall more restricted scanning behavior and a lack of differentiation between emotions. The ADHD group, showed an emotion-specific gazing pattern that was highly similar to that of controls. Thus, by analyzing eye movements, we were able to differentiate three different viewing patterns that allowed us to distinguish between the three clinical groups. This outcome suggests that attention for emotion may not tap into common pathophysiological processes and argues for a multi-dimensional approach to the grouping of disorders with neurodevelopmental etiology.

FLUID study: study protocol for an open-label, single-centre pilot study to investigate the efFect of Lemborexant on sleep management in Japanese sUbjects aged 50 years and older with Insomnia Disorder

INTRODUCTION

Bidirectional associations have been reported between sleep disturbance and both cognitive impairment, including Alzheimer's disease and amyloid beta-peptide (Aβ) accumulation. These relationships can be explained by the glymphatic system, which acts as a garbage drainage system in the brain. As interstitial fluid dynamics are suggested to increase during sleep, clearance of Aβ can be influenced by sleep disturbance or deprivation. We hypothesised that using lemborexant, an orexin receptor antagonist, to improve sleep quality would also improve the function of the glymphatic system. We plan to examine the effect of lemborexant on sleep quality and the glymphatic system among patients with insomnia disorder.

METHODS AND ANALYSIS

This pilot study is designed as an open-label, single-arm, single-centre trial. Thirty patients aged 50 years and over with insomnia will be recruited. The participants will take lemborexant (5 mg) at bedtime for 12 weeks and undergo a home-based sleep study at baseline and weeks 4 and 12, as well as MRI examinations to evaluate the glymphatic system at baseline and week 12. The primary outcome will be changes in objective sleep parameters as evaluated using a sleep monitoring system. The secondary outcomes will be changes in subjective sleep parameters. The relationships between changes in sleep parameters and the glymphatic system will be evaluated using diffusion tensor image analysis along the perivascular space, which is called the ALPS-index. Sleep parameters and the ALPS-index will be analysed using a paired t-test or Pearson's correlation coefficient.

ETHICS AND DISSEMINATION

The study protocol was approved by Nagoya University Certified Review Board. The findings from this research will be published in peer-reviewed journals and be presented at local, national and international conferences.

TRIAL REGISTRATION NUMBER

jRCTs041210024.

Recent updates of eye movement abnormalities in patients with schizophrenia: A scoping review

AIM

Although eye-tracking technology expands beyond capturing eye data just for the sole purpose of ensuring participants maintain their gaze at the presented fixation cross, gaze technology remains of less importance in clinical research. Recently, impairments in visual information encoding processes indexed by novel gaze metrics have been frequently reported in patients with schizophrenia. This work undertakes a scoping review of research on saccadic dysfunctions and exploratory eye movement deficits among patients with schizophrenia. It gathers promising pieces of evidence of eye movement abnormalities in attention-demanding tasks on the schizophrenia spectrum that have mounted in recent years and their outcomes as potential biological markers.

METHODS

The protocol was drafted based on PRISMA for scoping review guidelines. Electronic databases were systematically searched to identify articles published between 2010 and 2020 that examined visual processing in patients with schizophrenia and reported eye movement characteristics as potential biomarkers for this mental illness.

RESULTS

The use of modern eye-tracking instrumentation has been reported by numerous neuroscientific studies to successfully and non-invasively improve the detection of visual information processing impairments among the screened population at risk of and identified with schizophrenia.

CONCLUSIONS

Eye-tracking technology has the potential to contribute to the process of early intervention and more apparent separation of the diagnostic entities, being put together by the syndrome-based approach to the diagnosis of schizophrenia. However, context-processing paradigms should be conducted and reported in equally accessible publications to build comprehensive models.

Interpretable Machine Learning Models for Three-Way Classification of Cognitive Workload Levels for Eye-Tracking Features

The paper is focussed on the assessment of cognitive workload level using selected machine learning models. In the study, eye-tracking data were gathered from 29 healthy volunteers during examination with three versions of the computerised version of the digit symbol substitution test (DSST). Understanding cognitive workload is of great importance in analysing human mental fatigue and the performance of intellectual tasks. It is also essential in the context of explanation of the brain cognitive process. Eight three-class classification machine learning models were constructed and analysed. Furthermore, the technique of interpretable machine learning model was applied to obtain the measures of feature importance and its contribution to the brain cognitive functions. The measures allowed improving the quality of classification, simultaneously lowering the number of applied features to six or eight, depending on the model. Moreover, the applied method of explainable machine learning provided valuable insights into understanding the process accompanying various levels of cognitive workload. The main classification performance metrics, such as F1, recall, precision, accuracy, and the area under the Receiver operating characteristic curve (ROC AUC) were used in order to assess the quality of classification quantitatively. The best result obtained on the complete feature set was as high as 0.95 (F1); however, feature importance interpretation allowed increasing the result up to 0.97 with only seven of 20 features applied.

An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control

In the 34 developed and 156 developing countries, there are ~132 million disabled people who need a wheelchair, constituting 1.86% of the world population. Moreover, there are millions of people suffering from diseases related to motor disabilities, which cause inability to produce controlled movement in any of the limbs or even head. This paper proposes a system to aid people with motor disabilities by restoring their ability to move effectively and effortlessly without having to rely on others utilizing an eye-controlled electric wheelchair. The system input is images of the user's eye that are processed to estimate the gaze direction and the wheelchair was moved accordingly. To accomplish such a feat, four user-specific methods were developed, implemented, and tested; all of which were based on a benchmark database created by the authors. The first three techniques were automatic, employ correlation, and were variants of template matching, whereas the last one uses convolutional neural networks (CNNs). Different metrics to quantitatively evaluate the performance of each algorithm in terms of accuracy and latency were computed and overall comparison is presented. CNN exhibited the best performance (i.e., 99.3% classification accuracy), and thus it was the model of choice for the gaze estimator, which commands the wheelchair motion. The system was evaluated carefully on eight subjects achieving 99% accuracy in changing illumination conditions outdoor and indoor. This required modifying a motorized wheelchair to adapt it to the predictions output by the gaze estimation algorithm. The wheelchair control can bypass any decision made by the gaze estimator and immediately halt its motion with the help of an array of proximity sensors, if the measured distance goes below a well-defined safety margin. This work not only empowers any immobile wheelchair user, but also provides low-cost tools for the organization assisting wheelchair users.

Application of eye trackers for understanding mental disorders: Cases for schizophrenia and autism spectrum disorder

Studies of eye movement have become an essential tool of basic neuroscience research. Measures of eye movement have been applied to higher brain functions such as cognition, social behavior, and higher‐level decision‐making. With the development of eye trackers, a growing body of research has described eye movements in relation to mental disorders, reporting that the basic oculomotor properties of patients with mental disorders differ from those of healthy controls. Using discrimination analysis, several independent research groups have used eye movements to differentiate patients with schizophrenia from a mixed population of patients and controls. Recently, in addition to traditional oculomotor measures, several new techniques have been applied to measure and analyze eye movement data. One research group investigated eye movements in relation to the risk of autism spectrum disorder several years prior to the emergence of verbal‐behavioral abnormalities. Research on eye movement in humans in social communication is therefore considered important, but has not been well explored. Since eye movement patterns vary between patients with mental disorders and healthy controls, it is necessary to collect a large amount of eye movement data from various populations and age groups. The application of eye trackers in the clinical setting could contribute to the early treatment of mental disorders.

Studies of eye movement have become an essential tool of basic neuroscience research. With the development of eye trackers, a growing body of research has described eye movements in relation to mental disorders.