A5089519991- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Traumatic Brain Injury Research
- Neurobiology of Language and Bilingualism
- Dementia and Cognitive Impairment Research
- Treatment of Major Depression
- Neural and Behavioral Psychology Studies
- Advanced Neuroimaging Techniques and Applications
- Medical Imaging and Analysis
- Gaze Tracking and Assistive Technology
- Cognitive Science and Mapping
- Epilepsy research and treatment
- Advanced Statistical Methods and Models
- Statistical Methods in Clinical Trials
- Statistical Methods and Inference
- Artificial Intelligence in Healthcare and Education
- Health, Environment, Cognitive Aging
- Neonatal and fetal brain pathology
- Speech and dialogue systems
- Mental Health Research Topics
- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
University of Zurich
2020-2024
Healthy Start
2022-2024
ETH Zurich
2020-2024
Increasing life expectancy is prompting the need to understand how brain changes during healthy aging. Research utilizing electroencephalography (EEG) has found that power of alpha oscillations decrease from adulthood on. However, non-oscillatory (aperiodic) components in data may confound results and thus require re-investigation these findings. Thus, present report analyzed a pilot two additional independent samples (total N = 533) resting-state EEG young elderly individuals. A newly...
Childhood and adolescence are critical stages of the human lifespan, in which fundamental neural reorganizational processes take place. A substantial body literature investigated accompanying neurophysiological changes, focusing on most dominant feature EEG signal: alpha oscillation. Recent developments signal-processing show that conventional measures power confounded by various factors need to be decomposed into periodic aperiodic components, represent distinct underlying brain mechanisms....
Abstract The quantification of resting‐state electroencephalography (EEG) is associated with a variety measures. These include power estimates at different frequencies, microstate analysis, and frequency‐resolved source connectivity analyses. Resting‐state EEG metrics have been widely used to delineate the manifestation cognition identify psychophysiological indicators age‐related cognitive decline. reliability utilized prerequisite for establishing robust brain–behavior relationships...
This paper extends frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack geographical diversity precluded accounting for site-specific variance, increasing nuisance variance. We ameliorate these weaknesses. (i) Create lifespan Riemannian multinational norms tensors. These result from...
We present a new machine learning benchmark for reading task classification with the goal of advancing EEG and eye-tracking research at intersection between computational language processing cognitive neuroscience. The consists cross-subject to distinguish two paradigms: normal task-specific reading. data is based on Zurich Cognitive Language Processing Corpus (ZuCo 2.0), which provides simultaneous signals from natural English sentences. training dataset publicly available, we newly...
Psychiatric disorders are among the most common and debilitating illnesses across lifespan begin usually during childhood adolescence, which emphasizes importance of studying developing brain. Most previous pediatric neuroimaging studies employed traditional univariate statistics on relatively small samples. Multivariate machine learning approaches have a great potential to overcome limitations these approaches. On other hand, vast majority existing multivariate focused differentiating...
Abstract Background Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey-Osterrieth complex figure (ROCF) is the state–of-the-art assessment tool for neuropsychologists across globe to assess degree non-verbal visual memory deterioration. To obtain score, trained clinician inspects patient’s ROCF drawing quantifies deviations from original figure. This manual procedure time-consuming, slow scores vary depending on clinician’s experience,...
Exploring the neural basis of age-related decline in working memory is vital our aging society. Previous electroencephalographic studies suggested that contralateral delay activity (CDA) may be insensitive to lateralized visual (VWM) performance. Instead, recent evidence indicated task-induced alpha power lateralization decreases older age. However, relationship between and VWM performance remains unknown, have questioned validity these findings due confounding factors aperiodic signal....
Abstract Increasing life expectancy is prompting the need to understand how brain changes during healthy aging. Research utilizing Electroencephalography (EEG) has found that power of alpha oscillations decrease from adulthood on. However, non-oscillatory (aperiodic) components in data may confound results and thus require re-investigation these findings. The present report aims at analyzing a pilot two additional independent samples (total N = 533) resting-state EEG young elderly...
Abstract Childhood and adolescence are critical stages of the human lifespan, in which fundamental neural reorganizational processes take place. A substantial body literature investigated neurophysiological changes during brain maturation by focusing on most dominant feature EEG signal: alpha oscillation. Ambiguous results were reported for developmental trajectory power Simulations this study show that conventional measures confounded various factors need to be decomposed into periodic...
A bstract Background One in three patients relapse after antidepressant discontinuation. Thus, the prevention of achieving remission is an important component long-term management Major Depressive Disorder (MDD). However, no clinical or other predictors are established. Frontal reactivity to sad mood as measured by fMRI has been reported relate independently discontinuation and interesting candidate predictor. Methods Patients (n=56) who had remitted from a depressive episode while taking...
Abstract We present a new machine learning benchmark for reading task classification with the goal of advancing EEG and eye-tracking research at intersection between computational language processing cognitive neuroscience. The consists cross-subject to distinguish two paradigms: normal task-specific reading. data is based on Zurich Cognitive Language Processing Corpus (ZuCo 2.0), which provides simultaneous signals from natural training dataset publicly available, we newly recorded hidden...
Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey–Osterrieth complex figure (ROCF) is the state-of-the-art assessment tool for neuropsychologists across globe to assess degree non-verbal visual memory deterioration. To obtain score, trained clinician inspects patient’s ROCF drawing quantifies deviations from original figure. This manual procedure time-consuming, slow scores vary depending on clinician’s experience, motivation, tiredness. Here,...
Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey-Osterrieth complex figure (ROCF) is the state–of-the-art assessment tool for neuropsychologists across globe to assess degree non-verbal visual memory deterioration. To obtain score, trained clinician inspects patient’s ROCF drawing quantifies deviations from original figure. This manual procedure time-consuming, slow scores vary depending on clinician’s experience, motivation tiredness.Here, we...
Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey-Osterrieth complex figure (ROCF) is the state–of-the-art assessment tool for neuropsychologists across globe to assess degree non-verbal visual memory deterioration. To obtain score, trained clinician inspects patient’s ROCF drawing quantifies deviations from original figure. This manual procedure time-consuming, slow scores vary depending on clinician’s experience, motivation tiredness.Here, we...
The Zurich Cognitive Language Processing Corpus (ZuCo) provides eye-tracking and EEG signals from two reading paradigms, normal task-specific reading. We analyze whether machine learning methods are able to classify these tasks using features. implement models with aggregated sentence-level features as well fine-grained word-level test the in within-subject cross-subject evaluation scenarios. All tested on ZuCo 1.0 2.0 data subsets, which characterized by differing recording procedures thus...
Abstract This paper extends our frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack geographical diversity precluded accounting for site-specific variance, increasing nuisance variance. We ameliorate these weaknesses. i) Create lifespan Hermitian Riemannian multinational norms...