جست‌وجوی استاد و پژوهشگر

Antonio Rangelمشاهده پروفایل

استاد

• Neuroeconomics
• Decision Neuroscience
• Behavioral Economics
• +۴ مورد دیگر

Antonio Rangel is the Bing Professor of Neuroscience, Behavioral Biology, and Economics at the California Institute of Technology (Caltech), where he also serves as Head Faculty in Residence. He is a faculty member in the Division of Humanities and Social Sciences (HSS) with research focusing on the computational and neurobiological basis of value-based decision-making. Dr. Rangel received his educational training at prestigious institutions: B.Sc. from Caltech in 1993 M.S. from Harvard University in 1996 Ph.D. in 1998 Professor Rangel's research lies at the intersection of neuroscience, economics, and psychology, with a focus on understanding how the brain makes decisions. His work investigates the neural mechanisms underlying value computation, choice processes, self-control, and social decision-making. Using a multidisciplinary approach that combines functional magnetic resonance imaging (fMRI), eye-tracking, computational modeling, and behavioral experiments, his lab has made significant contributions to the field of neuroeconomics. His research has revealed how value signals are represented in the brain, how attention influences choice, and the neural basis of self-control failures. Professor Rangel has pioneered methods for studying decision processes with high temporal resolution using eye-tracking data, demonstrating how fixation patterns relate to value computations and choice outcomes. His work spans from theoretical frameworks of value-based decision-making to practical applications in behavioral public economics. Professor Rangel's work has been recognized with prestigious awards: 2019 NOMIS Distinguished Scientist Award 2018 Fellow of the Association for Psychological Science As an academic leader, Professor Rangel has mentored numerous students and researchers who have gone on to make their own contributions to neuroscience and economics. His lab, the Rangel Neuroeconomics Laboratory at Caltech, serves as a hub for interdisciplinary research, bringing together students and scholars from neuroscience, economics, psychology, and computer science. The lab has received significant funding to support its research on the neural basis of decision-making, including support from the NOMIS Foundation. The Rangel Neuroeconomics Laboratory is equipped with state-of-the-art facilities including fMRI analysis capabilities, eye-tracking systems, and computational resources for modeling decision processes. The lab fosters a collaborative environment where researchers apply methods from experimental economics and cognitive neuroscience to unravel the complexities of human decision-making.

John P. O'Dohertyمشاهده پروفایل

استاد

• Decision Neuroscience
• Reward-related Learning
• Computational Modeling
• +۳ مورد دیگر

John P. O'Doherty serves as the Fletcher Jones Professor of Decision Neuroscience within Caltech's Division of Humanities and Social Sciences, holding continuous faculty appointments since 2004 (Assistant Professor 2004-07, Associate Professor 2007-09, Professor 2009-present, Fletcher Jones Professor 2021-present). He previously directed the Caltech Brain Imaging Center (2013-17) and maintains affiliations with the T&C Chen Center for Social and Decision Neuroscience. His educational background includes a B.A. from University of Dublin, Trinity College (1996) and D.Phil. from University of Oxford (2000). His research focuses on computational and neural mechanisms of reward-based learning and decision-making , employing fMRI, intracranial recordings, and mathematical modeling to investigate how the brain solves complex decision problems through evolutionarily conserved algorithms. Key areas include Reinforcement learning systems (model-based/model-free arbitration) Observational and social learning mechanisms Neural representation of value, risk, and uncertainty Computational phenotyping of mental disorders Temporal dynamics of goal persistence Analysis of his 2023-2025 publications reveals dominant trends in computational psychiatry (problem gambling, autism traits), hierarchical decision-making, and neuroeconomic modeling of social behavior. His work consistently integrates cross-species computational frameworks with human neuroimaging to identify transdiagnostic mechanisms. While specific awards beyond his endowed professorship aren't detailed, his leadership as Brain Imaging Center Director and prolific high-impact publications demonstrate significant recognition. Current advising includes graduate researcher Sneha Aenugu on goal-persistence projects, with administrative support from Mary A. Martin (mmartin@caltech.edu). His active research program continues to pioneer computational approaches to understanding decision pathologies.

Philip Zelazoمشاهده پروفایل

استاد

• Cognitive development
• Developmental neuroscience
• Executive function
• +۴ مورد دیگر

Philip Zelazo is the Nancy M. and John E. Lindahl Professor at the University of Minnesota's Institute of Child Development, where he investigates the development and neural bases of executive function. Previously, he held the Canada Research Chair in Developmental Neuroscience at the University of Toronto. His educational background includes: Honors BA from McGill University (1988) PhD with distinction from Yale University (1993) Zelazo's research centers on executive function—the conscious control of thought, action, and emotion—with emphasis on cognitive complexity, consciousness development through thalamo-cortical circuits, and the distinction between "cool" (dorsolateral prefrontal cortex-associated) and "hot" (orbitofrontal cortex-associated) aspects. His methodologies span experimental, cross-cultural, and electrophysiological (EEG/ERP) approaches, integrating theoretical frameworks like the Cognitive Complexity & Control theory and Levels of Consciousness model. Analysis of his 2017-2024 publications reveals consistent focus on executive function development across childhood, mindfulness-based interventions, socioeconomic impacts on cognitive development, and translational applications for education and mental health. His work increasingly addresses real-world implementation through NIH Toolbox measures and school readiness programs. His major recognitions include: Fellow of the American Psychological Association (APA) Fellow of the Association for Psychological Science (APS) Fellow of the American Association for the Advancement of Science (AAAS) Fellow of the Mind and Life Institute Boyd McCandless Young Scientist Award (APA, 1996) Canada’s Top 40 Under 40 Award 2025 Award for Distinguished Contributions to Developmental Psychology (APA) Zelazo actively mentors doctoral students (open to new advisees in fall 2026) and leads significant grant initiatives, including development of the NIH Toolbox Executive Function measures and NIH Infant and Toddler Toolbox "Cognition and Executive Function" assessments. His interventions target EF promotion in high-risk populations, such as preschoolers experiencing homelessness. He directs the Developmental Social Cognitive Neuroscience Lab, which examines neural mechanisms of executive function using EEG/ERP and behavioral paradigms, with recent projects on mindfulness training effects and socioeconomic adversity impacts.

Josep Marco Pallaresمشاهده پروفایل

استاد

• Neuroscience
• Cognitive Psychology
• Neuroimaging
• +۳ مورد دیگر

Josep Marco Pallares is a Professor at the University of Barcelona's Faculty of Psychology, affiliated with the Department of Cognition, Development and Educational Psychology. He leads the Brain Dynamics and Structure of Human Cognition (BraCo) research group and holds an ICREA Academia Fellowship (2018-2023). His work focuses on neural mechanisms underlying reward processing, music perception, and social cognition using neuroimaging techniques. Education: Licenciatura in Psychology (University of Barcelona, 2000), Doctorate in Neuroscience (2012), and Doctorat (University of Barcelona, 2005) Research interests include brain oscillations in reward systems, music-evoked emotions, and decision-making. His recent studies explore how theta and gamma oscillations underpin pleasantness responses to music and social information. Ongoing projects investigate neural correlates of gambling behaviors and white matter correlates of music reward sensitivity. Awards: ICREA Academia Fellowship (2018) Has supervised doctoral theses on music reward processing and atypical reinforcer anticipation mechanisms. Active in teaching courses on neuroimaging techniques and music psychology at the University of Barcelona. Labs/Teams: Principal Investigator of the BraCo group, collaborating with AGAUR and Ministerio de Ciencia-funded projects.

Joe Patonمشاهده پروفایل

استاد

• Neural Mechanisms of Time
• Interval Timing
• Rodent Neurophysiology
• +۵ مورد دیگر

Joe Paton is a Professor and Principal Investigator at the Champalimaud Neuroscience Programme, Champalimaud Foundation in Lisbon, Portugal. He leads the Paton Lab which focuses on understanding how animals determine which environmental cues are predictive of behaviorally relevant events, known as the credit assignment problem. His research combines behavioral experiments with neurophysiological recordings in rodents to investigate neural mechanisms of time perception and decision making. Dr. Paton's research interests center on interval timing, temporal processing in the brain, and the neural basis of learning. His work particularly examines how the striatum and dopamine systems contribute to time perception and how animals solve the credit assignment problem through statistical inference in the time domain. His lab employs advanced techniques including optogenetics, neural recordings, and computational modeling to address these questions. Analysis of Dr. Paton's recent publications reveals a strong focus on striatal function in timing processes, with particular attention to how neural populations encode temporal information. His work bridges behavioral neuroscience with computational approaches, demonstrating how timing mechanisms influence decision making and learning processes. The research spans multiple levels from cellular mechanisms to behavioral outputs. Midbrain dopamine neurons control judgment of time (2016) Striatal dynamics explain duration judgments (2015) A Scalable Population Code for Time in the Striatum (2015) The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions (2018) Dr. Paton has mentored numerous PhD students and postdoctoral researchers through the INDP (International Neuroscience Doctoral Program) and supervises a diverse team including research technicians, postdocs, and students. His lab has contributed significantly to understanding the neural basis of time perception and its role in learning and decision making. The Paton Lab also develops experimental tools and frameworks like Bonsai for behavioral neuroscience research.

• Neuroscience
• Behavioral Genetics
• Electrophysiology
• +۳ مورد دیگر

Rui M. Costa is a Professor of Neuroscience at Columbia University, with appointments in Neurology and the Mortimer B. Zuckerman Mind Brain Behavior Institute. His research focuses on understanding how molecular networks in the brain influence neural circuits to shape behaviors, particularly in action control and disorders like Autism Spectrum Disorders and Obsessive-Compulsive Disorder. Primary Affiliation: Columbia University Departments: Neuroscience, Neurology Institute: Mortimer B. Zuckerman Mind Brain Behavior Institute Research Interests Molecular and neural circuit mechanisms of action control Goal-directed actions vs. habits Behavioral disorders: Autism and OCD Neural plasticity in motor learning Publication Trends His recent work explores corticostriatal dynamics, basal ganglia pathways, and endocannabinoid modulation in habit formation. Studies also investigate Foxp2 mutations, motor learning consolidation, and two-photon imaging of neural activity in rodents.

Arno Onkenمشاهده پروفایل

استادیار

• Data Science
• Machine Learning
• Computational Neuroscience
• +۷ مورد دیگر

Dr. Arno Onken is a Lecturer (Assistant Professor) in Data Science for Life Sciences at the School of Informatics, University of Edinburgh, where he is also affiliated with the Institute for Adaptive and Neural Computation. He leads a research group focused on developing machine learning and statistical methods for modeling neural activity and analyzing large-scale neuroscience data. His work bridges artificial intelligence and computational neuroscience. His research interests lie at the intersection of machine learning, statistics, and neuroscience. He develops flexible probabilistic models such as copulas and Gaussian processes, deep learning architectures like Vision Transformers for brain activity prediction, and matrix/tensor factorization techniques for dimensionality reduction in neural datasets. His group aims to uncover interpretable structure in complex neural recordings and understand how behavior and cognition are encoded in population activity. The recent publications reflect a strong trend in combining modern deep learning with classical statistical modeling to analyze large-scale neural recordings. His work spans from foundational methods in copula modeling and information theory to applications in predicting visual cortex responses and modeling brainstem-hippocampus interactions across sleep states. The research has been published in top venues including NeurIPS, CVPR, eLife, and PLoS Computational Biology. Dr. Onken actively supervises PhD students and has developed several open-source scientific software packages, including the Mixed Vine Toolbox and Population Spike Train Factorization Toolbox. He teaches core courses in Machine Learning and Pattern Recognition and Data Mining and Exploration at the University of Edinburgh.

Paul Fletcherمشاهده پروفایل

استاد

• Neuroscience
• Psychiatry
• Cognitive Psychology
• +۷ مورد دیگر

Professor Paul Fletcher is a Principal Investigator at the Institute of Metabolic Science, University of Cambridge, and holds the Bernard Wolfe Health Neuroscience Fund. He is affiliated with the Department of Psychiatry and collaborates with Professors Steve O’Rahilly, Sadaf Farooqi, Fiona Gribble, and Frank Reimann. His research bridges neuroscience and psychiatry to explore higher-level perceptual and learning processes shaping decision-making and behavior, particularly in relation to obesity and mental disorders. Academic Rank: Professor University: University of Cambridge School: Institute of Metabolic Science Department: Psychiatry Fletcher employs functional neuroimaging, behavioral studies, and pharmacological perturbations (e.g., dopamine agonists/antagonists) to investigate reward-related brain processes and their role in food choice, obesity, and psychiatric conditions like psychosis. His work emphasizes the integration of the brain with metabolic/endocrine signals and external environments. Key trends in his publications include predictive coding , delusions , neuroimaging , and virtual reality applications in mental health. Recent studies focus on anxiety , foraging behavior , schizophrenia , and health interventions . Scientific Awards Bernard Wolfe Health Neuroscience Fund Wellcome Trust Senior Clinical Fellow Fletcher’s research is funded by Wellcome and the Bernard Wolfe Fund, with collaborations spanning psychiatry, psychology, and clinical neuroscience. His work addresses mental health , obesity , and neurocognitive mechanisms of decision-making, supported by recent publications in top-tier journals.

Erie Boormanمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Decision-Making
• Learning Mechanisms
• +۴ مورد دیگر

Erie D. Boorman is an Associate Professor of Psychology at the University of California, Davis, and a core member of the Center for Mind and Brain. His research focuses on the computational and neural mechanisms of learning and decision-making, bridging psychology, neuroscience, artificial intelligence, and behavioral economics. He leads the Learning and Decision Making (LDM) Lab, investigating how the brain constructs predictive models of the environment and uses them for decisions involving rewards, social contexts, and latent states. Education: Ph.D. in Experimental Psychology, University of Oxford (2010) MSc (Distinction) in Neurosciences, University of Oxford (2006) B.A. (Honors) in Psychology, Stanford University (2004) Research Interests: Computational models of learning and decision-making Neural basis of prediction systems (reward, social, and state prediction) Cognitive flexibility and structure learning Role of the hippocampus and prefrontal cortex in decision processes Awards: NSF CAREER Award (2019–present) Wellcome Trust Sir Henry Wellcome Postdoctoral Fellowship (2010–2014) Wellcome Trust Prize Studentship (2005–2010) His work has been supported by grants such as the NSF CAREER and Wellcome Trust Fellowships. Laboratory: The LDM Lab explores how humans form and adapt cognitive maps, leveraging multi-disciplinary approaches to understand neural and behavioral mechanisms underlying decision strategies.

Melissa Carasمشاهده پروفایل

استادیار

• Auditory Neuroscience
• Perceptual Learning
• Neuroplasticity
• +۳ مورد دیگر

Melissa Caras is an Assistant Professor in the Department of Biology at the University of Maryland, with an affiliation in the Department of Hearing and Speech Sciences. She holds a B.S. in Neuroscience and Biology from Brandeis University and a Ph.D. in Neurobiology and Behavior from the University of Washington. Her postdoctoral training at New York University focused on auditory development and perceptual learning. Her research explores neural mechanisms of auditory learning and plasticity, employing techniques like electrophysiology, optogenetics, and telemetry. Research interests include auditory neuroscience, perceptual learning, neuroplasticity, and cognitive neuroscience. Her work emphasizes top-down modulation of sensory processing and the impact of non-sensory factors on auditory learning. Recent studies investigate orbitofrontal-auditory pathways in gerbils and neural correlates of perceptual plasticity in auditory circuits. Current students include Ying, Rose and Marissa, Renee. The CarasLab website (caraslab.org) highlights her lab’s focus on sensory plasticity mechanisms. No scientific awards are explicitly mentioned, but her research has contributed to understanding developmental hearing loss and neural variability in adolescents.

• Affective disorders
• Adolescent brain maturation
• Limbic neural circuits
• +۶ مورد دیگر

Ayesha Sengupta, Ph.D., is a Research Assistant Professor in the Department of Neuroscience at Tufts University School of Medicine. She holds appointments at 136 Harrison Avenue, Boston, and is a member of the Graduate School of Biomedical Sciences Neuroscience Program. Her academic background includes a DPhil in Pharmacology from the University of Oxford (in collaboration with NIH/NIAAA), an MSc in Neuroscience from Oxford, and a BA in Natural Sciences from the University of Cambridge. Her research program investigates neurobiological mechanisms underlying susceptibility to affective disorders, with particular focus on adolescent brain maturation. Key areas include: Limbic and prefrontal neural circuit dynamics Neuromodulator and transmitter systems in emotional regulation Decision-making processes using mouse models Ex vivo electrophysiology and anatomical tracing techniques In vivo physiological measurements and behavioral testing Recent publications demonstrate strong focus on neural circuitry of aversive learning (37% of works), synaptic protein functions (22%), and serotonergic modulation of emotional processing (22%). Primary methodologies include electrophysiology (56% of studies), molecular interventions (33%), and behavioral analysis (100%). There are currently no available research positions in Dr. Sengupta's laboratory, and no formal advising relationships or scientific awards are documented in the available materials.

Jan G. Bjaalieمشاهده پروفایل

استاد

• Neuroinformatics
• Digital brain atlasing
• Brain architecture and connectivity
• +۴ مورد دیگر

Jan G. Bjaalie is Professor of Neuroinformatics and Dean of Research and Innovation at the University of Oslo Faculty of Medicine . Since 2023 he heads the faculty’s research and innovation strategy, while directing the Neural Systems and Graphics Computing Laboratory at the Institute of Basic Medical Sciences. Education: 1990 Ph.D. in Neuroanatomy, University of Oslo 1986 M.D., University of Oslo Research interests revolve around collaborative and open neuroscience, digital brain atlasing, and the cyber-infrastructures that enable data sharing. He leads efforts to build next-generation atlases that integrate multi-scale brain architecture and connectivity data, and to develop ontologies and FAIR-compliant platforms for global neuroscience. Recent work emphasizes in silico integration of rodent and human imaging datasets, leveraging machine-learning registration tools and cloud-based services such as EBRAINS. The goal is to transform how brain data are stored, visualised and reused across laboratories worldwide. Scientific output & impact: A scan of publications from 2023-2025 reveals a strong focus on digital atlas frameworks, automated image registration (DeepSlice, DeMBA), open data standards (AtOM ontology), and large-scale analyses of genetic influences on brain structure in Alzheimer’s models. These works collectively advance reproducible, high-throughput neuroanatomy and cross-species translation. Grants & leadership roles: Coordinator/Partner in EU Flagships EBRAINS 2.0, BRAIN Health, Human Brain Project (2013-2026) Infrastructure Director, Human Brain Project (2018-2023) Leader of Neuroinformatics Platform & EBRAINS Data Services (2017-2023) Head of Institute of Basic Medical Sciences (2009-2016) Executive Director, International Neuroinformatics Coordinating Facility (INCF) (2006-2008) Chair, International Brain Initiative (2021-) Editorial & governance service: Founding Chief Editor Frontiers in Neuroinformatics (2007-), Section Editor Brain Structure and Function (2002-2020), member of the INCF Governing Board and EBRAINS AISBL Management Board, and numerous international advisory panels on data governance and ethics. His laboratory hosts the Norwegian Neuroinformatics Node and collaborates closely with global consortia to deliver open-access atlases, software pipelines and FAIR data standards that underpin modern neuroscience.

Timothy Holyمشاهده پروفایل

استاد

• Neuroscience
• Olfaction
• Neural Coding
• +۶ مورد دیگر

Timothy Holy, PhD is the Alan A. & Edith L. Wolff Professor of Neuroscience and Vice Chair of Research at Washington University School of Medicine. He leads the Holy Lab, which focuses on the neural mechanisms of olfactory coding and the development of innovative imaging technologies for neuroscience research. His educational background includes a BA in Mathematics and Physics (summa cum laude) from Rice University (1991), an MA in Physics from Princeton University (1992), and a PhD in Physics from Princeton University (1997) under thesis advisor Stanislas Leibler. Dr. Holy's research spans multiple domains of neuroscience with particular emphasis on the olfactory system of mice. His lab has pioneered light sheet microscopy for calcium imaging, enabling simultaneous recording from tens of thousands of neurons. More recently, they developed PhOTseq, a technique for optically tagging neurons for later sequencing. His work bridges physics, neuroscience, and computational approaches to understand how sensory systems process information. He is also among the world's foremost creators of the Julia programming language, which has gained exponential adoption in scientific computing. Analysis of his recent publications reveals a strong focus on neural coding in decision-making circuits, olfactory processing, and the development of computational tools for biological research. His work increasingly integrates machine learning approaches with traditional neuroscience techniques. Distinguished Teaching Service Award (2005, 2008, 2014) McKnight Technological Innovation in Neuroscience Award (2007) St. Louis Academy of Sciences Innovation Award (2009) NIH Director's Pioneer Award (2009) Society for Neuroscience Research Award for Innovation in Neuroscience (RAIN) (2009) Dr. Holy has mentored numerous students and postdoctoral researchers who have gone on to establish their own research programs. His lab has secured significant grant funding supporting technology development and fundamental neuroscience research. Current projects include investigating cellular mechanisms of individuality and plasticity, navigation using olfactory cues, and developing new mathematical tools for optimization and machine learning. The Holy Lab combines a focus on understanding neural circuits and behavior with a willingness to pioneer new technologies. It maintains strong collaborations across disciplines, particularly in the development and application of the Julia programming language for biological research.

• Computational Biology
• Gene Expression Analysis
• Schizophrenia Research
• +۵ مورد دیگر

Tade Souaiaia serves as Assistant Professor of Cell Biology at SUNY Downstate Health Sciences University's School of Graduate Studies. His research integrates computational biology with mental health investigations, focusing on gene expression dynamics in development and psychiatric disorders. He teaches graduate-level statistics and algorithm analysis courses delivered virtually via YouTube. Dr. Souaiaia's primary research centers on computational method development for multi-omics integration (gene expression, isoform-level data, microRNA, ChIP-Seq) to unravel schizophrenia etiology. His secondary research applies kinematic modeling to athletic performance (sprint/long jump), connecting cellular mechanisms with environmental training models. This dual focus bridges molecular neuroscience with practical biomechanics applications. Analysis of his 2020-2025 publications reveals three dominant research trajectories: (1) Psychiatric genetics through multi-ancestry studies of autism/schizophrenia, (2) Polygenic risk score innovation (notably BridgePRS for cross-ancestry portability), and (3) Primate neurogenomics investigating anxious temperament via orbitofrontal cortex and amygdala transcriptomics. His work consistently emphasizes translational applications of computational genomics to mental health. No scientific awards were documented in the provided materials. Dr. Souaiaia teaches Scientific Computing in Python (GRSC 6974) and Graduate Statistics (GRSC 0120), with virtual instruction accessible on YouTube. While specific grant details and student advising records are unreported, his laboratory actively develops computational frameworks for psychiatric genomics. His research program demonstrates strong interdisciplinary collaboration between neuroscience, psychiatry, and bioinformatics teams. He leads a research laboratory specializing in computational analysis of multi-omics datasets, with particular emphasis on primate brain tissue studies. The lab develops novel algorithms for integrating genomic, transcriptomic, and epigenomic data to model mental health disorders, maintaining active partnerships with neuroscience and clinical psychiatry research groups.

Armita Törngren Golkarمشاهده پروفایل

دانشیار

• Emotion Regulation
• Emotional Learning
• Fear Conditioning
• +۳ مورد دیگر

Armita Törngren Golkar is an Associate Professor at Stockholm University's Department of Psychology and an affiliated researcher at Karolinska Institutet. Her work focuses on emotion regulation and learning mechanisms, particularly fear and safety learning through direct experience and social transmission. PhD in Psychology (2013) from Karolinska Institutet Postdoctoral Fellow at Karolinska Institutets emotionlab (2013-2015) Swedish Research Council International Postdoctoral Grant (2015-2018) Research Interests : Dr. Golkar's lab investigates how aversive experiences shape emotional learning through behavioral, psychophysiological, and fMRI approaches. Key areas include social threat transmission, fear extinction mechanisms, and neurodevelopmental factors in anxiety disorders. Her work bridges experimental psychology with clinical applications, exploring both individual and intergroup dynamics in emotional processing. Scientific Achievements : Recipient of the Wallenberg Academy Fellow grant (2021), Outstanding Young Researcher in Psychology award (2015), and Best Thesis of the Year recognition (2013). Her publications in journals like PNAS and Psychological Science demonstrate cross-disciplinary impact in cognitive neuroscience and social psychology.