جست‌وجوی استاد و پژوهشگر

Ruben Portuguesمشاهده پروفایل

استاد

• Neuroscience
• Systems Neuroscience
• Behavioral Neuroscience
• +۷ مورد دیگر

Ruben Portugues is a Professor of Brain Circuit Function and Dysfunction at the Institute of Neuroscience, Technical University of Munich (TUM). He is a full member of the Graduate School of Systemic Neurosciences (GSN), an associate and advisory board member of the Munich Center for Neurosciences (MCN), and leads a research group focused on understanding the neural basis of behavior. His lab uses larval zebrafish as a model organism to investigate sensorimotor control, decision-making, and motor learning through whole-brain imaging and circuit analysis. His research interests lie at the intersection of systems neuroscience and behavior. He investigates how brain circuits process sensory information, integrate it with motor output, and enable adaptive and flexible behavior. Key areas include the function of the cerebellum, heading direction networks, sensorimotor transformations, and the neural mechanisms of decision-making. His lab employs cutting-edge techniques including custom-built microscopes, behavioral assays, and computational analysis. The recent publications and preprints from his lab demonstrate a strong trend in decoding distributed neural circuits underlying navigation and decision-making in zebrafish. There is a clear focus on identifying specific brain regions (e.g., interpeduncular nucleus, cerebellum) and cell types involved in processing visual, motor, and spatial information. The work increasingly emphasizes whole-brain functional imaging and the emergence of cognitive-like representations such as allocentric heading direction. FENS-Kavli Network of Excellence (FKNE) PhD Thesis Prize (awarded to student Luigi Petrucco) Ruben Portugues actively mentors PhD students, including current advisees Luigi Petrucco, Ot Prat, and Shuhong Huang, and has successfully graduated Dr. Elena Dragomir and Dr. Vilim Štih. His lab engages in extensive collaborations, hosts visiting researchers, participates in teaching (e.g., CSHL Imaging Course, Cajal Course), and secures resources for advanced research. The lab is known for building its own microscopes and software, fostering technical innovation. The Portugues Lab operates as a dynamic, interdisciplinary team that combines experimental neuroscience with computational and engineering approaches. They regularly hold retreats, participate in scientific events, and contribute to community initiatives like the Munich Brain Day. The lab is preparing to relocate to the Department of Neurobiology and Behavior at Cornell University, marking a new phase in its research trajectory.

Rishidev Chaudhuriمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Neural Dynamics
• Cognitive Neuroscience
• +۳ مورد دیگر

Rishidev Chaudhuri is an Associate Professor at the University of California, Davis in the Department of Neurobiology, Physiology and Behavior within the College of Biological Sciences. His research focuses on computational neuroscience and neural dynamics, employing mathematical models to investigate how neural circuits generate cognitive processes such as memory, perception, and decision-making. His work explores neural dynamics through models of memory systems, attentional mechanisms, and probabilistic inference. Recent publications highlight advances in understanding hippocampal memory scaffolds, parietal-frontal interactions, and neuromorphic computing inspired by brain architecture. Education: BA in Physics (Amherst College), PhD in Applied Mathematics (Yale University) Centers: Center for Neuroscience; affiliated with Applied Mathematics and Neuroscience Graduate Groups Scientific awards and honors are not explicitly mentioned in the provided materials.

• Neurodegenerative Diseases
• Molecular Neuroscience
• Stem Cell Research
• +۳ مورد دیگر

Professor Richard Wade-Martins is a leading academic in University of Oxford 's Department of Physiology, Anatomy and Genetics . He directs the Molecular Neurodegeneration Research Laboratory and the Oxford Parkinson’s Disease Centre (OPDC). With degrees from Cambridge (MA) and Oxford (DPhil), he has held prestigious fellowships including Wellcome Trust Research Career Development Fellowship and NIH reviewer roles. His research targets molecular mechanisms in Parkinson’s and Alzheimer’s diseases through iPSC models , transgenic mice , and lysosomal function studies . He pioneered work on SNCA , MAPT , and LRRK2 gene pathways. Current projects focus on gene therapy and mitochondrial dysfunction in neurodegeneration. Key publications (2019–2025) reveal trends in single-cell transcriptomics , calcium channel inhibition , and TFEB/TFE3 lysosome modulation . His awards include Wellcome Trust Fellowships and advisory roles for Parkinson's UK , Alzheimer's Research UK , and EU consortia like StemBANCC and EFACTS . He leads the UK Dementia Platform iPSC Initiative and serves on international boards in Luxembourg and Canada.

Frank E. Garceaمشاهده پروفایل

عضو هیئت علمی

• Cognitive Neuroscience
• Neuroimaging
• Neurology
• +۴ مورد دیگر

Frank E. Garcea, Ph.D., is a Research Assistant Professor in the Department of Neurosurgery and Neuroscience at the University of Rochester School of Medicine and Dentistry. His research focuses on the cognitive and neural mechanisms underlying tool use, apraxia, and stroke recovery. He employs neuropsychological testing, fMRI, and lesion-symptom mapping to study brain injury effects on functional connectivity and action knowledge. Education: Bachelor of Science in Psychology, St. John Fisher College (2006–2010) PhD in Brain and Cognitive Sciences, University of Rochester (2012–2017) Research Interests: Dr. Garcea investigates how brain regions like the parietal cortex and dorsal/ventral streams mediate object manipulation and tool use. His work explores stroke-related disconnection syndromes, motor speech coordination networks, and translational brain mapping to preserve neural function during surgery. He collaborates on projects involving epilepsy patients undergoing electrocorticography to study action-related neural pathways. Labs & Affiliations: Principal Investigator of the Garcea Lab at URMC, focusing on tool use deficits in brain tumor/stroke survivors. Affiliated with the Del Monte Institute for Neuroscience and the Neurobiology & Anatomy Program. His lab integrates neuroimaging, lesion analysis, and clinical care to advance personalized brain mapping strategies.

• MRI
• Diffusion MRI
• Perfusion MRI
• +۶ مورد دیگر

Professor Fernando Calamante is a Professor of Biomedical Engineering at The University of Sydney and Director of Sydney Imaging Core Research Facility. He leads the National Imaging Facility node and focuses on advanced MRI methodologies, particularly Diffusion and Perfusion MRI, to study brain connectivity and neurological disorders. His work includes developing the MRtrix software, widely used in diffusion MRI analysis. He holds extensive funding (~$50M) and has been recognized with awards like ISMRM Fellowship and NHMRC grants. His research spans super-resolution imaging, brain connectomics, and clinical applications in stroke and tumors. Education: BSc (Physics, Argentina), PhD (Magnetic Resonance Imaging, University College London). Career highlights include leadership roles at The Florey Institute and ISMRM presidency (2021-2022). Research interests include: Novel MRI methods for brain connectivity and super-resolution imaging Applications of Diffusion and Perfusion MRI in neurology Integration of structural and functional connectomics Key achievements: Over 200 publications, software innovations, and leadership in global MRI societies.

Lawrence H. Staibمشاهده پروفایل

استاد

• Medical Image Analysis
• Machine Learning
• Nonrigid Registration
• +۶ مورد دیگر

Lawrence H. Staib is a Professor of Biomedical Engineering at Yale University, with additional academic appointments in Electrical & Computer Engineering and Radiology & Biomedical Imaging. He holds a Ph.D. from Yale University and specializes in automated medical image analysis, including techniques like model-based segmentation, nonrigid registration, and diffusion tensor imaging (DTI). His research focuses on applications in neuroscience, cardiology, and cancer imaging, emphasizing machine learning and functional MRI analysis. His key contributions include advancements in white matter tractography via anisotropic wavefront evolution, real-time neural tract parcellation (Fasciculography), and noise reduction in diffusion tensor fields. Staib is a Fellow of the American Institute for Medical and Biological Engineering (2015), recognizing his impactful work in medical imaging technologies. Staib's research also encompasses statistical deformation models, perturbation-based shape analysis, and 3D deformable models for volumetric segmentation. He has developed patented 3D ultrasound computed tomography systems (USPTO #6878115, 7025725). His work bridges clinical needs with computational methods, addressing challenges in image registration, structural connectivity analysis, and medical robotics.

Russell S. Witteمشاهده پروفایل

استاد

• Medical Imaging
• Biomedical Engineering
• Optical Sciences
• +۱۵ مورد دیگر

Russell S. Witte, PhD, is a Professor at the University of Arizona, jointly appointed in the departments of Medical Imaging, Optical Sciences, Biomedical Engineering, Surgery, and Neurosurgery. He is also a Professor at the BIO5 Institute and leads the Experimental Ultrasound & Neural Imaging Lab (EUNIL). His interdisciplinary work bridges physics, engineering, and medicine to develop innovative imaging technologies for diagnosing and treating neurological, cardiac, and oncological conditions. Education: PhD, Arizona State University, 2002 MS, Arizona State University, 2000 BS (Honors), Physics, University of Arizona, 1993 Dr. Witte's research centers on hybrid imaging modalities that combine ultrasound with light, microwaves, and electrical signals. His lab pioneers techniques such as photoacoustic imaging, acoustoelectric imaging, and elasticity mapping to visualize tissue function and mechanics deep within the body. These methods have transformative potential in functional brain imaging, cardiac electrophysiology, and early cancer detection. He is particularly interested in leveraging nanotechnology and smart contrast agents to enhance imaging specificity and therapeutic efficacy. His research program reflects a strong trend toward multimodal, physics-driven biomedical imaging, with applications spanning neuroscience, cardiology, and oncology. By integrating principles from biomedical engineering, optics, and applied mathematics, his work aims to bridge the gap between fundamental science and clinical translation. Scientific Affiliations and Memberships: Arizona Cancer Center Sarver Heart Center School of Mind, Brain, and Behavior Neuroscience Graduate Interdisciplinary Program Applied Mathematics Graduate Interdisciplinary Program Biomedical Engineering Graduate Interdisciplinary Program Dr. Witte is deeply committed to training the next generation of interdisciplinary scientists. He actively mentors students and encourages collaboration across engineering, medicine, and industry. His lab fosters a creative environment for dreamers, problem solvers, and innovators aiming to make transformative discoveries at the intersection of physics and medicine. He has established strong collaborative networks across the Colleges of Engineering, Optical Sciences, and Medicine, facilitating translational research with real-world clinical impact. Dr. Witte leads the Experimental Ultrasound & Neural Imaging Lab (EUNIL), a multidisciplinary research team dedicated to developing and refining cutting-edge imaging technologies. The lab focuses on translating novel physical principles into practical tools for disease diagnosis and treatment monitoring, particularly in chronic tendon disorders, arrhythmias, and breast cancer.

• Computational Psychopathology
• Learning Theory
• Cognitive Neuroscience
• +۳ مورد دیگر

Robin A. Murphy is a Professor of Experimental Psychology at the University of Oxford and a Fellow and Tutor for Admissions at Corpus Christi College. He holds a PhD from McGill University (Canada) and has contributed over 50 scientific publications on associative learning mechanisms, their role in mental disorders like depression and psychopathy, and translational neuroscientific applications. His research bridges animal and human learning, with a focus on computational psychopathology and neurochemical modulation (e.g., serotonin). Education: Undergraduate degree, Queen's University MA and PhD in Psychology, McGill University Research Interests: Dr. Murphy investigates how associative learning processes underpin mental disorders, particularly through neurochemical systems like serotonin. His work explores causal reasoning biases in depression, psychopathy's learning deficits, and translational models linking animal studies to human cognition. Key themes include agency perception, contingency judgment, and the neural substrates of prejudice. Recent projects involve peptide research in aging and computational modeling of multi-agent systems in depression. Grants and Funding: Supported by MRC, BBSRC, Wellcome Trust, and Japan Society for the Promotion of Science. He has advised UK Research Councils and NSERC (Canada). Labs and Teams: Leads a lab focusing on associative learning mechanisms, collaborating with institutions globally on computational psychopathology and translational neuroscience.

Essa Yacoubمشاهده پروفایل

استاد

• Medical Physics
• Neuroimaging
• Biomedical Engineering
• +۶ مورد دیگر

Essa Yacoub is a Professor in the Department of Radiology at the University of Minnesota, affiliated with the PhD Program in Medical Physics and the Center for Magnetic Resonance Research. His work focuses on advancing MRI and fMRI technologies, particularly at ultrahigh magnetic fields (e.g., 10.5 T), to achieve unprecedented spatial and temporal resolution in brain imaging. He leads projects in RF coil design, noise reduction algorithms, and developmental neuroimaging. Roles: Professor, Medical Physics Program Faculty Affiliations: Center for Magnetic Resonance Research, Department of Radiology Research emphasizes high-resolution fMRI applications, including layer-specific brain mapping, pediatric neurodevelopment studies (e.g., Baby Connectome Project), and translational tools like BIBSNet for infant brain segmentation. His innovations bridge hardware engineering (RF coils) and software (denoising pipelines) to tackle challenges in mesoscopic-scale imaging. Key contributions include optimizing imaging protocols at 7T/10.5T, developing NORDIC denoising for submillimeter data, and advancing understanding of brain networks in aging and neurological disorders. His work is foundational for large-scale initiatives like the Human Connectome Project and non-human primate neuroimaging collaborations. Grants and collaborations focus on translational imaging technologies, while educational contributions include training through the Medical Physics PhD Program. Ongoing efforts aim to refine ultra-high field MRI applications for clinical and basic neuroscience research.

Andrea Greveمشاهده پروفایل

مدرس

• Cognitive Psychology
• Memory Studies
• Neuroscience
• +۳ مورد دیگر

Dr Andrea Greve is a Lecturer in the Department of Psychology at the University of Cambridge . Her research focuses on cognitive processes related to memory, prediction error, and learning mechanisms. Key areas of interest include declarative memory formation, semantic predictions, and the influence of novelty on memory retention. She has explored topics such as word learning in variable-choice paradigms, the role of hippocampal lesions in memory binding, and predictive coding in neuroimaging contexts. Her work integrates experimental psychology with neuroscience methodologies, particularly leveraging neuroimaging techniques to investigate memory systems. Notable contributions include studies on false memory effects, the nonmonotonic relationship between object-location memory and expectedness, and the impact of prior knowledge on memory encoding. Dr. Greve has also contributed to methodological advancements, such as improved MRI anonymization for MEG coregistration. While her research spans multiple decades, recent efforts (2023–2025) emphasize predictive frameworks and their applications in understanding cognitive phenomena like semantic surprise and episodic memory formation. Her findings challenge traditional assumptions about fast mapping in adults and highlight the importance of integrating computational models with empirical data. Dr. Greve collaborates extensively with neuroimaging and cognitive science teams, contributing to interdisciplinary projects that bridge theoretical and applied research in memory systems. Her work maintains a strong focus on methodological rigor, particularly in experimental design and data interpretation.

Christopher Honeyمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Cognitive Neuroscience
• Neural Dynamics
• +۳ مورد دیگر

Christopher Honey is an Associate Professor in the Department of Psychological & Brain Sciences at Johns Hopkins University, affiliated with the Krieger School of Arts & Sciences. His research focuses on computational cognitive neuroscience, exploring how the brain processes sequential information such as language and memory. He holds a PhD from Indiana University and has held positions at Princeton University and the University of Toronto before joining JHU in 2016. Education: PhD in Psychological and Brain Sciences, Indiana University Postdoctoral Fellowship at Princeton University with Uri Hasson Bachelor’s in Applied Mathematics and English Literature, University of Cape Town Research Interests: Neural dynamics of memory and perception Temporal processing in the brain Cognitive modeling using computational methods Neuroimaging data standards (e.g., BIDS) Publications highlight his work on brain state fluctuations, neuroimaging data structures, and memory enhancement. His lab develops tools for analyzing fMRI and EEG data, emphasizing real-world applications like smartphone-based cognitive interventions. Lab and Collaborations: Active projects on narrative processing and hippocampal replay Development of open-source neuroscience tools like iELVis Focus on translational research for aging populations

Alicia Cheمشاهده پروفایل

استادیار

• Neuroscience
• Developmental Neuroscience
• Behavioral Neuroscience
• +۵ مورد دیگر

Alicia Che is an Assistant Professor of Psychiatry at Yale University School of Medicine and serves as Director of Graduate Admissions for the Interdepartmental Neuroscience Program. She joined the Yale Department of Psychiatry in 2021 after completing her postdoctoral fellowship with Dr. Natalia De Marco García at Weill Cornell Medical College and Dr. Gord Fishell at NYU. Her research is conducted through the Che Lab at Yale, where she investigates how early life experiences impact brain circuit assembly and mature function in models of psychiatric illness. Yale School of Medicine, Department of Psychiatry Interdepartmental Neuroscience Program Center for Brain & Mind Health Division of Molecular Psychiatry Wu Tsai Institute Yale Center for the Science of Cannabis and Cannabinoids Dr. Che earned her Ph.D. in Physiology and Neurobiology from the University of Connecticut in 2014, where she worked in the laboratory of Dr. Joseph LoTurco. She received her B.S. with triple majors in Biology, Physics, and Physical Chemistry from Pacific Lutheran University in Washington state in 2009. Her research focuses on understanding developmental trajectories following early life experiences to develop diagnostics and early interventions for psychiatric illnesses. Dr. Che's research examines how sensory inputs, social bonding, stress, and substance exposure impact brain development. She employs a multi-dimensional approach to assess transcriptional, circuit, neuronal activity, and behavioral changes across the entire developmental timeline. Her lab currently focuses on four specific areas: the role of oxytocin in social behavior development, circuit dysfunction in PTSD, early-life cannabinoid exposure effects, and the impact of early life stress on development and adulthood. She utilizes advanced techniques including mouse genetics, slice electrophysiology, and longitudinal in vivo 2-photon imaging on behaving animals. Her most recent publications demonstrate significant contributions to understanding neural circuit development, PTSD mechanisms, and the effects of early life experiences on brain function. Her work spans from molecular neuroscience to behavioral outcomes, with publications in top journals including Nature, Neuron, and Nature Communications. Her research has revealed important insights into how translaminar neuronal activity strengthens cortical columns, how oxytocin facilitates social touch development, and how PTSD affects brain transcriptomics. NARSAD Young Investigator Award (2020) K99/R00 Pathway to Independence Award from NINDS (2019) Dr. Che's work has significant implications for understanding and treating neurodevelopmental disorders, PTSD, and the consequences of early life experiences on mental health. She collaborates extensively with researchers across Yale and beyond, with frequent co-authorship with colleagues including Lin Lin, Alex Kwan, and Christopher Pittenger. Her research program bridges basic neuroscience with clinical applications, aiming to translate findings into potential interventions for psychiatric conditions.

Kunihiko Kanekoمشاهده پروفایل

استاد

• Theoretical Biophysics
• Complex Systems
• Chaos
• +۶ مورد دیگر

Kunihiko Kaneko is a Professor at the Niels Bohr Institute, University of Copenhagen, with a distinguished career in theoretical biophysics and complex systems. He received his PhD and MSc in Physics from the University of Tokyo, and has held leadership roles at the Universal Biology Institute and Center for Complex Systems Biology. PhD Physics, 1984 - University of Tokyo MSc Physics, 1981 - University of Tokyo His research spans five primary areas: Universal Biology, Evolutionary Constraints, Ecosystem Dynamics, Neural Cognition, and Universal Anthropology. He has published extensively on multi-level consistency principles, dimensional reduction in biological systems, and reciprocity between robustness and plasticity across scales. Recent publications show strong focus on microbial ecosystems (2025), evolutionary game theory (2025), neural modular architectures (2024), and dimensional reduction in cellular systems (2024). His work bridges physics and biology through dynamical systems theory applied to diverse phenomena from protocells to human societies.

• Neuroimaging
• Structural brain segmentation
• Multimodal population modeling
• +۶ مورد دیگر

Mark Jenkinson is a Professor of NeuroImaging at the University of Oxford's Nuffield Department of Clinical Neurosciences and also holds positions at the University of Adelaide's Australian Institute for Machine Learning and the South Australian Health and Medical Research Institute (SAHMRI). He heads the Structural Modelling and Analysis Group at the FMRIB Centre, where his research focuses on multimodal population modeling and structural brain segmentation. Education: DPhil in Robotics Research (University of Oxford, 1999) BSc (Hons I) in Mathematical Physics (University of Adelaide, 1994) BE (Hons I) in Electrical and Electronic Engineering (University of Adelaide, 1993) Professor Jenkinson's research spans two major themes: multimodal modeling of populations to describe disease processes and apply to individual patient diagnoses, and structural segmentation and analysis of brain anatomy and pathology, particularly focusing on sub-cortical structures and lesions. His work integrates advanced computational methods with neuroimaging to develop tools for understanding neurological disorders. As the developer of key components of the FMRIB Software Library (FSL), he has significantly contributed to standard neuroimaging analysis pipelines used worldwide. His recent publications demonstrate a strong focus on deep learning applications in neuroimaging, uncertainty quantification in medical AI, and advanced segmentation techniques. There's a clear trend toward developing more robust, anatomically plausible models that preserve topological structures while improving diagnostic capabilities for conditions like multiple sclerosis, Huntington's, and Parkinson's diseases. Scientific Awards: Highly Cited Researcher (Clarivate Analytics 2018-2021, Thomson Reuters 2014-2016) ISMRM Outstanding Teacher Award (2009, 2014) Teaching Excellence Award, University of Oxford (2012) David Phillips Fellowship from BBSRC (2005-2010) Professor Jenkinson has supervised over 25 doctoral students whose work spans brain segmentation, connectivity analysis, and clinical applications of neuroimaging. His research is supported by significant grants including the Medical Research Future Fund (AU$2m), Wellcome Trust Centre for Integrative Neuroimaging (£11m), and NIH Human Connectome Project (US$30m), reflecting the high impact and translational potential of his work. As head of the Structural Modelling and Analysis Group at FMRIB, Jenkinson leads a team developing the FSL (FMRIB Software Library), one of the most widely used neuroimaging analysis packages globally. His group collaborates extensively with clinical researchers on applications ranging from multiple sclerosis to traumatic brain injury, translating computational advances into clinical practice.

Kep Kee Lohمشاهده پروفایل

مربی ارشد

• Comparative primate neuroanatomy
• Sulcal anatomy
• Frontal cortex function
• +۴ مورد دیگر

Kep Kee Loh is a Senior Tutor in the Department of Psychology at the National University of Singapore (NUS). Currently, he also holds an NUS Overseas Postdoctoral Fellowship position at both the Montreal Neurological Institute (McGill University) and the University of Oxford. His research focuses on comparative primate neuroanatomy, examining what makes the human brain special compared to other primates through multimodal MRI techniques. Ph.D. in Neuroscience from Université Claude Bernard Lyon I (2014-2018) M.Sc. in Cognitive Neuroscience from University College London (2011-2012) B.Soc.Sci. (Hons.) in Psychology from National University of Singapore (2007-2011) Dr. Loh's research primarily investigates the anatomical organization of brains across humans and various primate species including chimpanzees, baboons, and macaques. He employs different magnetic resonance imaging techniques (anatomical, resting-state, diffusion-weighted MRI) to compare brain organization across species, with particular focus on the medial frontal cortex, sulcal anatomy, and the evolution of speech and language in the human brain. His work adopts a multimodal approach to provide an integrative view of what sets human brains apart from other primates. His recent publications demonstrate a strong focus on comparative neuroanatomy across species, with particular emphasis on primate brain evolution, frontal cortex organization, and language-related neural pathways. The research spans multiple disciplines including neuroscience, cognitive science, and evolutionary biology, with increasing attention to methodological advancements in neuroimaging techniques for cross-species comparisons. NUS Overseas Postdoctoral Fellowship (2021) Institute of Language, Communications and the Brain (ILCB) Postdoctoral Fellowship (2019) Fondation Recherche Médicale (FRM) Fin de Thèse (PhD funding) (2017) BRAIN Student Travel Award, 6th Motivation and Cognitive Control Symposium (2016) Dr. Loh has been involved in numerous collaborative research projects across international institutions, including the French Institute of Health and Medical Research (Stem Cell and Brain Research Institute), Aix-Marseille Université, and currently McGill University and the University of Oxford. His work has received significant recognition with over 1,000 citations for his 33 publications. While specific grant information isn't detailed in the provided text, his postdoctoral fellowships indicate successful competitive funding. Dr. Loh collaborates with several research groups including the Montreal Neurological Institute at McGill University and research teams at the University of Oxford. His work connects with broader initiatives like the collaborative resource platform for non-human primate neuroimaging, indicating participation in larger research networks focused on advancing primate neuroscience through shared resources and methodologies.