جستجوی استاد راهنمای دانشگاهی

• Autism Spectrum Disorders
• Child Psychiatry
• Developmental Disabilities
• +۸ مورد دیگر

Katarzyna Chawarska is the Emily Fraser Beede Professor of Child Psychiatry at Yale School of Medicine, with primary affiliation in the Child Study Center and secondary appointments in Pediatrics and Statistics. She is a leading expert in autism spectrum disorders (ASD), directing the NIH Autism Center of Excellence, the Social and Affective Neuroscience of Autism Program, and the Yale Toddler Developmental Disabilities Clinic. Education: PhD in Psychology, Yale University (2000) Post-Doctoral Fellowship, Yale University School of Medicine (2000) MS in Psychology, Yale University MPhil in Psychology, Yale University MA, Jagiellonian University (1986) Her research focuses on identifying early diagnostic markers and novel treatment targets in ASD, particularly in infants at risk due to familial, genetic, or perinatal factors. Her work integrates clinical assessment, neuroimaging, eye-tracking, and longitudinal design to understand the neurodevelopmental trajectories of autism. Her recent publications explore disrupted functional connectivity, atypical visual attention, social anhedonia, and familial recurrence in autism. She employs advanced methodologies including fMRI, eye movement dynamics, and machine learning to identify biomarkers. Her research spans developmental neuroscience, clinical psychology, genetics, and pediatric psychiatry, with strong emphasis on early detection and intervention. Scientific Awards: No specific awards mentioned in the provided text. Dr. Chawarska is the Principal Investigator on active clinical trials, including studies on emotional development in infants at risk for ASD and regulation of visual attention and emotion in autism. She mentors research through her lab and collaborates extensively with experts such as Fred Volkmar, James McPartland, and Frederick Shic. She leads the Chawarska Lab, which is part of the Center for Brain & Mind Health and the Wu Tsai Institute at Yale.

Daniel Keeserمشاهده پروفایل

پژوهشگر ارشد

• Multimodal Neuroimaging
• Neuromodulation
• Neurophysiology
• +۴ مورد دیگر

Dr. Daniel Keeser is a Research Fellow and Research Group Leader at the Department of Psychiatry and Psychotherapy of the University of Munich (LMU) and affiliated with the NeuroImaging Core Unit Munich (NICUM). His work focuses on clinical deep phenotyping and multimodal neuroimaging, integrating advanced MRI, EEG, and non-invasive brain stimulation methods to study severe mental and neurological disorders. Research Interests: Elucidating neurobiological mechanisms of schizophrenia, major depressive disorder, and Alzheimer's disease through multimodal neuroimaging and neuromodulation. His recent publications highlight methodologies like resting-state fMRI, diffusion tensor imaging, and transcranial magnetic stimulation combined with MRI, emphasizing personalized treatment strategies. Collaborative affiliations include the University Hospital of LMU Munich and the Clinical Deep Phenotyping (CDP) Working Group. Affiliations: NeuroImaging Core Unit Munich (NICUM) Department of Psychiatry and Psychotherapy, University of Munich (LMU)

Annemieke Apergis-Schouteمشاهده پروفایل

مدرس

• Obsessive Compulsive Disorder
• Preoccupied Thinking
• Procrastination
• +۷ مورد دیگر

Dr. Annemieke Apergis-Schoute is a Lecturer in Psychology (Teaching and Research) at Queen Mary University of London, affiliated with the School of Biological and Behavioural Sciences and the Centre for Brain and Behaviour. Her research focuses on obsessive-compulsive disorder (OCD), cognitive flexibility, prefrontal mechanisms, and student mental health. She holds a PhD from New York University, where her early work explored threat learning in rats and humans using fMRI. Subsequent roles at the University of Cambridge and UCL expanded her expertise into clinical OCD studies, including deep brain stimulation trials. Her research investigates how prefrontal control deficits and inflexible learning contribute to OCD and related disorders, with a focus on adolescents and young adults. Collaborations include pioneering DBS studies targeting basal ganglia regions to reduce compulsive behaviors. She also explores connections between brain function, interoception, and mental health in daily decision-making contexts. Key publications analyze reversal learning deficits in OCD under serotonergic modulation, neuroimaging markers of cognitive rigidity, and developmental trajectories of compulsivity. Her work bridges basic neuroscience with translational clinical interventions, emphasizing early intervention strategies and cognitive-behavioral approaches.

• Magnetic Resonance Imaging (MRI)
• Functional MRI (fMRI)
• Biomedical Imaging Physics
• +۶ مورد دیگر

Dr. Gary Glover is a Professor of Radiology (Radiological Sciences Lab) at Stanford University , with courtesy appointments in Psychology and Electrical Engineering. His work focuses on the physics and mathematics of MRI, particularly rapid scanning methods using spiral k-space trajectories for functional brain imaging and multimodal neuroimaging (fMRI/EEG/fPET/fNIRS) combined with neuromodulation techniques like TMS and transcranial ultrasound. Academic Appointments: Radiology, Psychology, Electrical Engineering Professional Affiliations: Bio-X, Stanford Cancer Institute, Wu Tsai Neurosciences Institute Research Interests include: Development of blood oxygen level-dependent (BOLD) and viscoelastic contrast in MRI Functional MR Elastography for brain activation mapping Optimization of MR-ARFI for transcranial ultrasound guidance Automated spinal cord segmentation (EPISeg) using machine learning Scientific Awards : National Academy of Engineering (2013) Gold Medal, ISMRM (2000) Steinmetz Award, General Electric (1985) Lauterbur Lecture, ISMRM (2018) Recent Publications analyze: Fast fMRI sampling and spurious signal correction Dissociated patterns in default mode network anti-correlations Neural correlates of collaborative behavior in triadic fMRI Salience network contributions to depression pathophysiology

• Neuroimaging
• Alzheimer's Disease
• Neurodegenerative Disorders
• +۵ مورد دیگر

Dr. Elisenda Bueichekú serves as a Research Scientist at the Yale School of Medicine within the Radiology & Biomedical Imaging Department . Her work focuses on neuroimaging applications in neurodegenerative disorders, particularly Alzheimer’s disease progression and memory systems analysis. She collaborates with leading researchers in the Mental Health PET Radioligand Development (MHPRD) Program and the PET Core facility. Primary Affiliation: Yale School of Medicine Department: Radiology & Biomedical Imaging Research Programs: MHPRD Program, PET Core Her research integrates multimodal neuroimaging techniques to investigate: Tau pathology propagation patterns Connectome-based disease modeling Cortical hub analysis in memory systems Cognitive resilience mechanisms Neuroimaging of anosognosia Functional network contributions to creativity Dr. Bueichekú contributes to translational research through: Advanced PET/MRI methodologies Spatiotemporal disease progression mapping Development of imaging-based biomarkers Recent publications demonstrate expertise in: Alzheimer’s disease neuroimaging Tau and amyloid co-accumulation Functional connectivity analysis Memory system characterization Scientific contributions include: 2025 Center for Brain & Mind Health Pilot Grant Key publications in top-tier journals (Nature Aging, Alzheimer's & Dementia, etc.)

Roger Tamمشاهده پروفایل

دانشیار

• Medical Imaging
• Machine Learning
• Quantitative Image Analysis
• +۳ مورد دیگر

Roger Tam is an Associate Professor in the School of Biomedical Engineering (SBME) at the University of British Columbia (UBC), with a joint appointment in the Department of Radiology. He is also the Associate Director of Graduate Studies. His research focuses on machine learning and computer vision applied to medical imaging, particularly in personalized medicine and quantitative image analysis. Tam earned his PhD in computer science from UBC in 2004, specializing in computational geometry and visualization. Education: PhD in Computer Science, UBC (2004) MSc in Computer Science BSc (Honors) Research Interests: Medical imaging biomarkers Machine learning applications in healthcare Quantitative image analysis Personalized medicine His work bridges computer science and clinical medicine, emphasizing translational approaches to improve diagnostic accuracy and patient outcomes. Recent Research Trends: Focus on myelin content analysis in neurological disorders (e.g., multiple sclerosis) Development of efficient machine learning models for medical image classification Impact of physical activity on white matter health Labs & Programs: Directs the Engineers in Scrubs program, which integrates engineering principles into biomedical education. Active in collaborative research initiatives like the Centre for Brain Health and the Canadian Prospective Cohort Study (CanProCo).

• Biomedical imaging
• Functional MRI
• MRI Systems biology
• +۳ مورد دیگر

Jozien Goense is an Associate Professor at the University of Illinois at Urbana-Champaign (UIUC), holding joint appointments in the Department of Psychology and Department of Bioengineering. She is also affiliated with the Beckman Institute for Advanced Science and Technology and the Neuroscience Program. Her primary research focuses on biomedical imaging, particularly functional MRI (fMRI) and its applications in understanding neurovascular coupling and cortical layer-specific activity. She is recognized for contributions to high-resolution fMRI methodology and laminar imaging techniques. Her work integrates advanced MRI techniques with neurophysiological studies, often using non-human primate models to validate findings in human studies. She has pioneered layer-specific fMRI approaches to map activity across cortical layers, particularly in the motor and visual cortices. Her expertise includes ultra-high field MRI (7T+), BOLD signal modeling, and software development for neuroimaging analysis (e.g., LayNII). Key research themes include the physiological basis of BOLD responses, neurovascular coupling mechanisms, and the application of laminar fMRI to study brain function in health and disease. She has collaborated extensively with neuroscientists, engineers, and clinicians to advance imaging technologies and their translational potential. Publications highlight her contributions to understanding dopamine and acetylcholine effects on neurovascular responses, resting-state gamma-band abnormalities in schizophrenia, and the development of high-resolution imaging protocols. Her work bridges basic science and clinical applications, including studies on vascular contributions to dementia and neuropharmacology. She has received the Beckman Seed Grant as part of a Bioengineering Faculty team, supporting innovative research initiatives. Her lab employs cutting-edge imaging tools and multidisciplinary approaches to unravel brain function at cellular and systems levels.

Mengsen Zhangمشاهده پروفایل

استادیار

• Complex Systems
• Neuroscience
• Computational Mathematics
• +۵ مورد دیگر

Mengsen Zhang is an Assistant Professor at Michigan State University (MSU) in the Department of Computational Mathematics, Science and Engineering and the Neuroscience Program. She bridges complex systems science, neuroscience, computational mathematics, and topological data analysis (TDA) to study brain dynamics and coordination mechanisms across scales. Education: B.S. in Psychology and Pharmaceutical Sciences (Peking University); M.S. in Criminology (University of Pennsylvania); Ph.D. in Complex Systems and Brain Sciences (Florida Atlantic University, with Drs. Emmanuelle Tognoli and J. A. Scott Kelso). Postdoctoral Training: Stanford University (with Dr. Manish Saggar) and University of North Carolina at Chapel Hill (with Dr. Flavio Frohlich). Her research focuses on the intersection of topological data analysis and dynamical systems, particularly in understanding brain oscillations, neural networks, and social coordination dynamics. She explores how third-party interventions can stabilize or disrupt coordination in biological and social systems, using both empirical and theoretical approaches. Her recent publications (2022–2025) highlight applications of transcranial alternating current stimulation (tACS) in psychiatric disorders, metastability in brain dynamics, and novel computational methods for analyzing neural and behavioral data. These works span neuroscience, psychiatry, and computational modeling. She teaches courses such as CMSE 381: Fundamentals of Data Science Methods (MSU) and STT 381: Fundamentals of Data Science Methods, integrating computational tools into academic training.

Mikail Rubinovمشاهده پروفایل

استادیار

• Network Neuroscience
• Computational Neuroscience
• Brain Connectivity
• +۴ مورد دیگر

Mikail Rubinov serves as Assistant Professor of Biomedical Engineering (primary appointment), Computer Science, Psychiatry, and Psychology at Vanderbilt University's School of Engineering. His interdisciplinary work bridges computational neuroscience, network science, and clinical applications. His research focuses on integrative statistical models of large-scale neural data , exploring brain network organization across species and scales. Key interests include evolutionary principles of brain networks, transcriptomic basis of neural individuality, information transfer in neural systems, and neuropsychiatric connectivity phenotypes. The Rubinov Lab develops computational frameworks for analyzing complex neural systems and integrates neuroscientific knowledge with multi-omics data. Recent publications reveal strong trends in network neuroscience methodology development (circular analysis frameworks, unbiased sampling techniques) and translational applications (epilepsy networks, autism spectrum connectomics, gut-brain axis interrogation). His work increasingly incorporates transcriptomic data with neuroimaging at biobank scale. NIH Grant Writing Workshop (June 2022) NIH Workshop Short Talks (April 2023) Rubinov actively mentors graduate and undergraduate students across Biomedical Engineering and Computer Science. His lab maintains collaborations with UCSF, HHMI Janelia Research Campus, Weizmann Institute, and international neuroscience consortia. Current projects include integrative models of large-scale neural data and transcriptomic basis of neural individuality. The Rubinov Lab operates within Vanderbilt's Department of Biomedical Engineering with extensive cross-school collaborations. Technical resources include GitHub repositories for constraint network models (cnm-code), volumetric segmentation (voluseg), and brain connectivity toolboxes.

Koen Haakمشاهده پروفایل

دانشیار

• Vision Science
• Neuroimaging
• Machine Learning
• +۴ مورد دیگر

Dr. Koen Haak is an Associate Professor at Tilburg University's Department of Cognitive Science and Artificial Intelligence within the Tilburg School of Humanities and Digital Sciences. His research focuses on vision science, neuroimaging, and AI applications in healthcare. He leads projects like 'Bridging the gap between visual function and functional vision' (NWO Vidi) and 'Neuroimaging biomarkers for predicting vision training success after stroke' (NWO KIC). He collaborates with institutions such as the Donders Institute and the Lifelong Vision Consortium. His work contributes to UN SDGs related to health and innovation. Research interests include analyzing brain imaging data to predict functional vision outcomes, developing machine learning tools for clinical trials, and studying visual cortex plasticity. He has authored 51+ publications, including papers in Nature Neuroscience and Translational Psychiatry . Awards include NWO Veni (2016) and Vidi (2020) fellowships. He teaches courses on computer vision and AI at Tilburg University. Current projects explore predictive analytics for eye treatments, thalamocortical connectivity, and sleep disruption effects in maritime pilots. His lab develops methods like connectopic mapping and deep learning for MRI analysis, with applications in Alzheimer's, autism, and psychiatric disorders.

Davinia Fernandez-Espejoمشاهده پروفایل

استاد

• Neuroscience
• Neuroimaging
• Clinical Neuroscience
• +۵ مورد دیگر

Professor Davinia Fernandez-Espejo holds the Chair of Neuropsychology and Clinical Neuroscience at the University of Birmingham's School of Psychology through The Centre for Human Brain Health (CHBH). Previously, she served as a Professor at Western University from 2015-2018.

Tanzil M. Arefinمشاهده پروفایل

استادیار

• Neuroimaging
• Neuroscience
• Brain Disorders
• +۵ مورد دیگر

Dr. Tanzil M. Arefin is an Assistant Professor of Neuroscience at the University of Rochester School of Medicine and Dentistry and Associate Director of the Preclinical Imaging Core at the Center for Advanced Brain Imaging and Neurophysiology (CABIN). His research focuses on developing neuroimaging techniques to study brain functions and microstructures in animal models of human disorders, including neurodegenerative and psychiatric illnesses. He holds affiliations with the Del Monte Institute for Neuroscience and the Neuroscience Ph.D. Program. **Education**: Ph.D., Neuroscience, University of Freiburg and University of Strasbourg (2017) M.Sc., Biomedical Engineering, Czech Technical University and University of Groningen (2012) B.Sc., Electrical and Electronic Engineering, Islamic University of Technology (2007) **Research Interests**: Dr. Arefin's lab employs multimodal MRI methodologies (resting-state fMRI, diffusion MRI, ASL perfusion MRI, MR spectroscopy) alongside optogenetics and chemogenetics to elucidate molecular mechanisms impairing brain plasticity. Current projects include studying cerebellar connectivity's role in non-motor behaviors and developing interventions for alcohol-dependent brains. **Awards**: Magna cum Laude, Summa Cum Laude, Erasmus Mundus Fellowships (both Doctoral and Masters). **Grants & Advising**: Not explicitly listed in texts, but lab activities suggest involvement in NIH-funded projects. Advising details are pending explicit student listings. **Lab & Affiliations**: Arefin Lab focuses on translational imaging tools. Affiliated with UR CABIN and URMC's Neuroscience programs. Location: 430 Elmwood Ave, Rochester, NY.

Amir Shmuelمشاهده پروفایل

استاد

• Neuroimaging
• fMRI
• Visual Perception
• +۵ مورد دیگر

Amir Shmuel is a Professor at McGill University's Faculty of Medicine, holding appointments in the Department of Neurology and Neurosurgery, Department of Biomedical Engineering, and Department of Physiology. He serves as Director of the Brain Imaging Signals Lab and Core Faculty at the McConnell Brain Imaging Centre of the Montreal Neurological Institute. His leadership includes chairing the 2018 International Society for Brain Connectivity conference and securing an $18.7M Canada Foundation for Innovation grant for Quebec's first large-bore 7 Tesla MRI scanner. Dr. Shmuel's research focuses on understanding neuronal mechanisms underlying functional brain imaging signals and visual information processing. His integrative approach combines fMRI, optical imaging, multi-channel neurophysiological recordings, and optogenetics across multiple spatial and temporal scales. Current research priorities include resting-state functional connectivity mechanisms, cortical lamina-resolved neurophysiology, and computational modeling of brain signals. His lab emphasizes parallel model development with experimental data acquisition. Recent publications demonstrate strong trends in multimodal neuroimaging integration, with emphasis on high-resolution fMRI techniques (especially 7T applications), resting-state connectivity analysis across species, and computational modeling of neurovascular coupling. Key subfields include laminar-specific activity mapping, artifact detection in medical imaging using deep learning, and cross-species functional connectivity frameworks. Dr. Shmuel's research is currently funded by the Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council of Canada (NSERC), and the US Department of Defense. His lab maintains active collaborations through initiatives like the International Society for Brain Connectivity and the PRIME-DE database consortium. Operating within the Brain Imaging Signals Lab at the Montreal Neurological Institute, Shmuel's team develops and applies advanced multimodal techniques including simultaneous fMRI-electrophysiology, voltage-sensitive dye imaging, and computational modeling frameworks. The lab maintains strong ties with the McConnell Brain Imaging Centre and participates in major open-science initiatives including the Tanenbaum Open Science Institute.

Gabriele Grattonمشاهده پروفایل

استاد

• Brain Function
• Brain Activity
• Event-related Optical Signal
• +۷ مورد دیگر

Gabriele Gratton is a Professor in the Department of Psychology and Neuroscience Program at the University of Illinois Urbana-Champaign, and serves as a Theme Lead at the Beckman Institute for Advanced Science and Technology. With over 178 research outputs, Gratton has established a distinguished career in cognitive neuroscience with a focus on brain function, aging, and neuroimaging techniques. Gratton's research interests center around brain function and activity , particularly using Event-related Optical Signal (EROS) and other neuroimaging methods. Key areas include optical imaging , aging effects on cognition , event-related brain potentials , and cerebrovascular health . Much of their work investigates how vascular health, fitness, and aging interact to affect brain structure and cognitive performance across the lifespan. The research portfolio shows a strong trend toward multimodal neuroimaging approaches, with recent work focusing on trimodal brain imaging techniques that simultaneously investigate human brain function. There's also significant emphasis on understanding how physical activity and fitness impact cognitive aging, white matter integrity, and cerebrovascular health. Association for Psychological Science Fellow (2006) Foundation of Augmented Cognition Award (2005) President of Society for Psychophysiological Research (2009) SPR Award for Distinguished Contributions to Psychophysiology (2019) SPR Early Career Award (1997) Gratton has received extensive recognition for their work, with publications being picked up by news outlets and shared across social media platforms. Their research has been referenced by numerous scholars, with several papers accumulating significant reader attention on academic platforms like Mendeley. Much of this work is conducted through the Beckman Institute, where Gratton leads research themes focused on advanced brain imaging and cognitive neuroscience.

• Medical Biometry
• Epidemiology
• Cognitive Dysfunction
• +۴ مورد دیگر

Insa Feinkohl is a Professor at the Chair of Medical Biometry and Epidemiology within the Faculty of Health at the University of Witten/Herdecke . Her research focuses on risk factors for cognitive dysfunction and mental health in older adults, particularly post-surgery, with emphasis on metabolic and cognitive risk factors. Bachelor of Science (BSc) in Psychology (1 st class honors) – University of Dundee (2006-2009) Master of Science (MSc) in Psychology of Individual Differences (with distinction) – University of Edinburgh (2009-2010) PhD in Community Health Sciences – University of Edinburgh (2010-2014) Post Doc in Knowledge Construction Group – Leibniz Institute for Knowledge Media, Tübingen (2014-2015) Postdoc in Molecular Epidemiology Group – Max Delbrück Center, Berlin (2015-2022) Habilitation in Molecular Epidemiology – Charité Universitätsmedizin Berlin (2021) Her research integrates medical biometry and epidemiology to study postoperative cognitive dysfunction (POCD), delirium, and aging-related cognitive decline. Key areas include biomarker validation (e.g., leptin, interleukins), brain connectivity (dopaminergic networks, thalamus), and metabolic risk factors (diabetes, obesity). She contributed to the BioCog project , an EU-funded initiative for personalized risk prediction of postoperative cognitive impairment. Her recent publications highlight trends in perioperative neuroscience, including brain mineralization, cytokine associations with neurocognitive disorders, and structural/functional imaging in delirium. Articles also explore metabolic syndrome, cognitive reserve, and delirium prediction models using machine learning. Insa Feinkohl is affiliated with major academic societies, including the German Society for Epidemiology , German Society for Medical Informatics, Biometry and Epidemiology , and the German University Association .