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Jelle HabayView profile

Research Fellow

• Mental Fatigue
• Sports Science
• Human Physiology
• +9 more

Jelle Habay is an External employee at the Vrije Universiteit Brussel in the Faculty of Physical Education and Physical Therapy . His work focuses on Mental Fatigue and Physiotherapy , with a strong emphasis on Sports Science and Human Physiology . He is part of the Human Physiology and Sports Physiotherapy Research Group . Academic Affiliation : Vrije Universiteit Brussel, Faculty of Physical Education and Physical Therapy Research Focus : Mental Fatigue, Sports Science, Physiotherapy, Neuroscience Habay's research explores Mental Fatigue in athletic contexts, utilizing Systematic Reviews , Wavelet Analysis , and Electrophysiological methods. His work includes studies on Psychomotor Performance and Reaction Time in sports. Recent articles analyze Mental Fatigue induction techniques in sports, fatigue effects on Prefrontal Cortex activity, and Wavelet Analysis of brain signals during exercise. Trends show interdisciplinary work combining Sports Science , Neuroscience , and Physiology . Scientific Awards : FWOTM1144: Underlying factors in the responsiveness to Mental Fatigue (2022) K203122N: Short Stay Travel Grant FWO (2021) OZR3839: Backup mandate Research Council (2021)

Gloria Teresa Brea CalvoView profile

Associate Professor

• Cell Biology
• Molecular Biology
• Mitochondrial Diseases
• +5 more

Gloria Teresa Brea Calvo is an Associate Professor in the Department of Physiology, Anatomy and Cell Biology at Universidad Pablo de Olavide , affiliated with the Andalusian Center for Developmental Biology (CABD) . Her research focuses on Mitochondrial Diseases , particularly Coenzyme Q Deficiencies , and she contributes to the Doctoral Programs in Cellular and Molecular Biology and Genetic Engineering . Research Pillars: Primary and Secondary CoQ Deficiencies Mechanisms of Mitochondrial Bioenergetics Oxidative Stress and Redox Signaling Mitochondrial Ribosome Assembly Key Contributions: Development of CRISPR/Cas9 Human Cell Models for COQ6 mutations Identification of Vanillic Acid as Bypass Therapy for CoQ Deficiencies Mechanistic Insights into ROS Signaling in Cardiomyopathy Selected Publications (2006–2020) analyze: Mitochondrial Respiratory Chain Organization Genotype-Phenotype Correlations in Pediatric Mitochondrial Disorders Metabolic Responses to Chemotherapy and Amino Acid Starvation

Sadra SadehView profile

Research Fellow

• Computational Neuroscience
• Neural Network Modeling
• Brain Connectivity
• +5 more

Dr. Sadra Sadeh is a Senior Research Fellow at King's College London, working within the Centre for Developmental Neurobiology at the Institute of Psychiatry, Psychology & Neuroscience. His research focuses on building computational models of brain networks to understand how brain structure relates to its dynamics and function. He leads the Sadeh Lab, which approaches neuroscience problems through data-constrained computational modeling and theoretical analysis of large-scale neuronal networks. Dr. Sadeh's research interests span computational neuroscience, neural network modeling, brain connectivity, and the intersection of neuroscience with artificial intelligence (Neuro-AI). His work aims to reveal fundamental mechanisms underlying brain operation in both healthy and disease conditions, with potential applications for understanding neurological disorders such as epilepsy and Parkinson's disease. His research has significant implications for developing brain-computer interfaces and advancing artificial intelligence models. His recent publications demonstrate expertise in hippocampal networks, memory consolidation, neural dynamics, and computational modeling approaches. His work frequently appears in high-impact journals including Nature Neuroscience, Nature Reviews Neuroscience, and PNAS. Wellcome Trust Career Development Award recipient Dr. Sadeh maintains active collaborations with leading neuroscientists including Professor Oscar Marín and Professor Laura Andreae at King's College London, and researchers at the Francis Crick Institute. His current research is supported by the Wellcome Trust project 'Perturbative analysis of brain networks' where he serves as Co-Investigator.

Flavie Lavoie-CardinalView profile

Associate Professor

• Optical nanoscopy
• Machine learning
• Deep learning
• +3 more

Flavie Lavoie-Cardinal is an Associate Professor in the Department of Psychiatry and Neuroscience at Université Laval and holds the Canada Research Chair in Intelligent Nanoscopy of Cellular Plasticity. Her research combines optical nanoscopy , machine learning , and molecular neurosciences to develop intelligent microscopes for studying synaptic plasticity. Education: Bachelor’s, Master’s, Ph.D. in Chemistry, University of Siegen (Germany) Postdoctoral Fellow, Stefan W. Hell Lab (2011–2014), Paul De Koninck Lab (2014–2017) Research Focus: She pioneers super-resolution microscopy and deep learning frameworks to analyze molecular interactions in synaptic communication. Her work emphasizes neurophotonics and quantitative imaging , addressing challenges like data scarcity and automated optimization. Article Trends: Recent publications highlight her innovations in STED microscopy , GAN-based resolution enhancement , and AI-driven image analysis , applied to studying stress effects on barriers, synaptic dynamics, and mitochondrial transport. Scientific Awards: Canada Research Chair in Intelligent Nanoscopy of Cellular Plasticity Labs & Collaborations: Leads the FLC-Lab, collaborating with CERVO Brain Research Centre and international institutions. Her team integrates biophotonics , neuroscience , and machine learning for cutting-edge biomedical imaging.

Luca CarnevaliView profile

Associate Professor

• Psychophysiology
• Stress Research
• Cardiovascular Physiology
• +3 more

Luca Carnevali is Associate Professor of Physiology at the University of Parma, where he conducts research on the psychophysiology of stress in humans and animal models. He holds a Master's degree (2009) and PhD (2015) in biomedical fields from the University of Parma, with additional research experience at the University of Newcastle (Australia). 2009: Master's in Biology and Biomedical Applications 2015: PhD in Systemic Pathophysiology His research focuses on stress mechanisms, particularly the interplay between cardiac autonomic regulation (assessed through heart rate variability), neuroimmune interactions, and gut microbiota composition. He employs rodent models to investigate sex-specific differences in stress responses and their cardiovascular consequences. Recent work highlights: 2025: Analysis of miRNA-34 deletion effects on cardiac stress vulnerability 2025: Evaluation of witness social defeat stress models for neuroimmune-cardiovascular interactions 2025: Development of IoT-based systems for real-world stress monitoring 2024: Meta-analysis on acute stress effects across rodent and human reward processing Scientific recognition includes: American Psychosomatic Society Young Investigator Colloquium Award (2018) Best Poster Prize, Italian Society of Physiology (2013) In editorial leadership: Associate Editor, International Journal of Psychophysiology Action Editor, Journal of Psychophysiology Associate Editor, Autonomic Neuroscience (Frontiers in Neuroscience, Physiology, and Neurology)

Ryan GirtsView profile

Assistant Professor

• Exercise Science
• Rehabilitation Science
• Neuromuscular Physiology
• +3 more

Ryan Girts serves as an Assistant Professor in the Department of Health & Exercise and Science at Pfeiffer University within the Center for Health Sciences Graduate Campus. His academic role integrates teaching with research focused on neuromuscular adaptations during immobilization and rehabilitation. His research program centers on exercise science and rehabilitation physiology, examining how physical activity levels influence muscle recovery during knee immobilization, with particular attention to sex-based differences in muscle quality. He employs advanced neurophysiological techniques including transcranial magnetic stimulation (TMS) to measure corticospinal excitability and functional near-infrared spectroscopy (fNIRS) to map brain activation during lower-body motor tasks. Key investigations explore the efficacy of motor imagery and action observation as therapeutic interventions, especially in older adult populations. Analysis of his 2022-2025 publications reveals consistent methodological rigor across neuroimaging and biomechanical assessments. His work frequently addresses measurement reliability concerns in TMS protocols, ultrasound imaging, and electromyography, highlighting the impact of variables like sonographer experience and stimulation parameters. Recurring themes include sex-specific responses to immobilization, neural adaptations to resistance training, and the relationship between motor unit recruitment and muscle function. No scientific awards were documented in available sources. Information regarding student advising, research grants, or laboratory facilities was not provided in the source materials, though his publication record indicates active collaboration in exercise physiology research.

• Neurology
• Pediatric Epilepsy
• Computational Neuroscience
• +5 more

Danilo Bernardo, MD is an Associate Professor in Neurology at the University of California, San Francisco (UCSF) School of Medicine . He is affiliated with the UCSF Weill Institute for Neurosciences , focusing on pediatric neurological disorders. Education: MD from University of North Carolina (2010) Neurology residency at University of North Carolina (2014) Child Neurology at UCLA (2017) Clinical Neurophysiology at UCLA (2018) Pediatric Epilepsy at UCLA (2019) Research Interests: Dr. Bernardo develops computational approaches for diagnosing and treating childhood epilepsy . His work spans EEG analysis , machine learning , and biomarker development for conditions like infantile spasms and hypoxic-ischemic encephalopathy . He has also contributed to genetic studies of rare epilepsy-related disorders. Publication Trends: His recent research focuses on deep learning for seizure prediction (2025) and computational biomarkers for pediatric epilepsy. Earlier work (2009-2021) covers synaptic plasticity , NMDA receptors , and wavelet-based EEG analysis . Mentoring: Dr. Bernardo mentors UCSF students on research projects Residents and fellows in research Clinical practice for UCSF students

Herbert JelinekView profile

Associate Professor

• Biomedical Engineering
• Neuroscience
• Chronic Disease Management
• +5 more

Dr. Herbert Jelinek is an Associate Professor in the Department of Medical Sciences at Khalifa University. With over 400 publications, his research focuses on leveraging technology for rural and remote diagnostics in chronic diseases such as diabetes, cardiovascular disease, and mental health. He specializes in developing image and temporal data analysis algorithms, as well as data mining and deep learning tools. B.Sc. (Hons.) in Human Genetics, University of New South Wales Graduate Diploma in Neuroscience, Australian National University PhD in Medicine, University of Sydney Graduate Certificate in Higher Education Teaching and Learning, Charles Sturt University Dr. Jelinek’s research spans cognitive decline in chronic diseases, multimodal network physiology linking brain and heart function, and the application of biofeedback/neurofeedback for mental health improvement. His work includes: Investigating neurofeedback and biofeedback to manage diabetes, hypertension, chronic pain, and depression in collaboration with Mediclinic Abu Dhabi Exploring brain-heart interactions and multisignal analysis with the Department of Cardiology Characterizing stroke-induced gait variability using nonlinear measures, in partnership with the Healthcare Engineering Innovation Center (HEIC) and Cleveland Clinic Abu Dhabi Developing portable neurofeedback devices for noninvasive stroke rehabilitation He teaches courses such as Physiological Control Systems, Rehabilitation Engineering, and Senior Design Projects in Biomedical Engineering. Dr. Jelinek is a member of the IEEE Biomedical Engineering Society, Applied Neuroscience Society of Australasia, and the International Society for Neurofeedback and Research.

Efrat LevyView profile

Professor

• Alzheimer's Disease
• Down Syndrome
• Extracellular Vesicles
• +10 more

Efrat Levy, PhD, is a Professor in the Department of Psychiatry and Department of Biochemistry and Molecular Pharmacology at NYU Grossman School of Medicine. She leads the Levy Lab at the Center for Dementia Research, focusing on extracellular vesicle biology in neurodegenerative diseases. Education: MSc in Endocrinology and PhD in Cell Biology from The Hebrew University of Jerusalem; Postdoctoral Training at NYU Medical Center. Her research investigates vesicular trafficking in aging and Alzheimer's disease (AD), emphasizing exosomes and mitovesicles as dual-role vehicles for protein clearance or pathology propagation. Key findings include APOE4 's detrimental effects on vesicle production, cystatin C 's neuroprotective mechanisms, and vesicle-mediated spread of amyloid-beta and tau pathology. Recent publications highlight vesicle dynamics in Down syndrome , ischemic injury , and cocaine-induced pathology . Her lab developed methods for isolating brain-derived vesicles and identified mitovesicles as novel biomarkers for mitochondrial dysfunction. Lab Members: Pasquale D'Acunzo (Research Scientist), Yohan Kim (Volunteer Researcher), Galit Bleicher (Postdoctoral Researcher), Monika Pawlik (Research Manager), Griffin Arsis (Research Support Assistant), Logan Jones (Research Support Assistant).

Ian WoodView profile

Lecturer

• Statistics
• Machine Learning
• Bioinformatics
• +7 more

Dr. Ian Wood is a Lecturer in Statistics at the School of Mathematics and Physics within the Faculty of Science at The University of Queensland. He received his PhD from the same institution in 2004. His teaching responsibilities include instructing 4th-year advanced statistics, 1st-year pharmacy students, and postgraduate data science courses. Dr. Wood's research spans multiple interdisciplinary domains including: Statistical methodologies for classification and mixture models Machine learning algorithms and stochastic optimization techniques Bioinformatics applications in genomics and medical research Evolutionary computation and optimization frameworks His work frequently bridges theoretical statistics with practical applications in biomedicine and computational biology. Analysis of Dr. Wood's recent publications reveals three primary research trends: Advanced algorithm development for statistical modeling and optimization Applications in biomedical contexts including cancer research, tissue engineering, and pathogen genomics Methodological innovations in machine learning and computational statistics His research consistently demonstrates strong interdisciplinary collaboration across statistics, computer science, and life sciences. Dr. Wood maintains an active supervision portfolio, serving as principal advisor for PhD candidates working on: Evolutionary algorithms for variable-length problems MRI brain segmentation using Markov random fields Estimation of distribution algorithms He also serves as associate advisor for multiple doctoral and master's projects spanning statistics, optimization, and bioinformatics. Dr. Wood is affiliated with the Centre for Organic Photonics and Electronics and maintains collaborations across multiple research teams focused on statistical applications in health sciences and engineering.

• Behavioral Neuroscience
• Motivation
• Depression
• +3 more

Joshua Lewis Haight is an Assistant Professor of Psychology at Quinnipiac University since 2019. He holds a Ph.D. in Neuroscience from the University of Michigan (2016) and completed postdoctoral training in Psychiatry at Yale University (2016-2019). Dr. Haight teaches courses including Introduction to Psychology, Physiological Psychology, and Drugs, Brain & Behavior. Education: B.A. in Psychology (Connecticut College, 2009), Ph.D. in Neuroscience (University of Michigan, 2016) Research Focus examines neural mechanisms of motivation in healthy and diseased states, emphasizing depression-related behaviors, effort-choice decision making, and the role of reward-related brain areas. His work explores sex differences in stress responses and neural circuitry. Recent publications highlight studies on ventral tegmental area receptors, inflammation effects on motivation, and social enrichment impacts on anxiety. Collaborations span Yale, University of Michigan, and Quinnipiac University's neuroscience community. Scientific Awards: National Institute of Drug Abuse NRSA award Dr. Haight supervises research students and runs a lab program studying motivation neurobiology. He welcomes media inquiries and has presented at conferences including Society for Neuroscience and NEURON.

• Developmental Genetics
• Craniosynostosis
• Human Genetics
• +4 more

Stephen Twigg is an Associate Professor of Developmental Genetics at the University of Oxford , affiliated with the Radcliffe Department of Medicine under the Medical Sciences Division . His research focuses on craniosynostosis (premature fusion of skull sutures), its genetic basis, and implications for brain and craniofacial development. Email: stephen.twigg@imm.ox.ac.uk Funding: Action Medical Research , MRC National Mouse Genetics Network , and NIH R01 (Co-I) grants Current research projects include: Elucidating cranial suture biogenesis using single-cell transcriptomics and CRISPR/Cas9 models Identifying non-coding mutations in craniosynostosis patients by mapping regulatory elements and intersecting with patient sequence data Investigating gene dosage effects (e.g., ERF mutations) and signaling pathways (ERK1/2, Hedgehog) in suture development Recent publications highlight his work on FGF4 variants in thoracic dystrophy, mouse models for congenital anomalies, and non-coding genetic mechanisms . He collaborates with institutions like University of Southern California (via Prof Gage Crump ) and MRC Weatherall Institute of Molecular Medicine . Key grants include: Action Medical Research Project Grant (2016–2019): Identified non-coding mutations in craniosynostosis MRC National Mouse Genetics Network (Oxford lead): Explores functional genomics in congenital anomalies NIH R01 grant (Co-I with Prof Andrew Wilkie ): Molecular basis of craniosynostosis

• Network Neuroscience
• Human Connectome
• Brain Networks
• +3 more

Onerva Korhonen is a post-doctoral researcher at the Department of Computer Science, Aalto University , specializing in network neuroscience and urban climate governance. She develops temporal network models of the human brain and applies network methods to study climate governance systems. Research Focus: Functional brain networks at multiple scales Multilayer network representations Impact of neurological diseases on network structure Dynamic functional homogeneity analysis Urban climate governance networks Publication Trends: Her work spans temporal network modeling, fMRI preprocessing methodologies, ROI-based network definitions, and climate governance network analysis. Key themes include consistency in network reconstruction, multiscale modeling, and structure-function relationships. Areas of Expertise: Network Neuroscience Human Connectome Brain Network Dynamics fMRI Preprocessing Urban Climate Governance Climate Action Strategies

Amos StorkeyView profile

Professor

• Machine Learning
• Deep Learning
• Generative Models
• +7 more

Amos Storkey is a Professor at the School of Informatics , University of Edinburgh , with a focus on machine learning, Bayesian methods, and their applications in neuroscience and astronomy. His research spans deep learning, generative models, and stochastic optimization under real-world constraints. Education: MA in Mathematics, Trinity College, Cambridge (1989) Part III (Theoretical Physics), Trinity College, Cambridge (1992) PhD in Neural Networks, Imperial College London (1995) Research Interests: Storkey’s work addresses core challenges in machine learning, including model understanding, efficiency, and transfer learning. Key topics include: Generative Models : Applications in medical imaging (brain/retinal) and music generation. Bayesian & Probabilistic Methods : In healthcare, astronomy, and diffusion processes. Optimization & Reinforcement Learning : Stochastic systems, meta-learning, and few-shot learning. Medical Applications : Structural connectivity analysis in ALS and aging studies. Article Trends: Recent publications emphasize interdisciplinary applications of machine learning, with 5/15 focused on neuroscience (fMRI, ALS, aging), 3/15 on optimization/sampling, and 2/15 on astronomical data analysis. Emerging themes include machine learning markets and generative models for hallucinations.

• Neuroscience
• Neuroimaging
• EEG
• +3 more

Sean Fitzgibbon is a Postdoctoral Researcher at the Nuffield Department of Clinical Neurosciences , University of Oxford, affiliated with the FMRIB Analysis Group and the Developing Human Connectome Project . His research focuses on neuroimaging methodology, particularly in EEG and fMRI data analysis, with an emphasis on artifact removal, functional connectivity, and automated processing pipelines for neonatal brain imaging.