Justin T Baker is an Assistant Professor of Psychiatry at McLean Hospital, where he leads the Baker Lab. His research focuses on understanding the biology of severe mental illnesses like schizophrenia and bipolar disorder through deep phenotyping, computational methods, and machine learning. He develops unobtrusive tools for naturalistic behavioral monitoring to improve diagnosis and treatment strategies. Research interests include: Neuropathology and disease mechanisms in psychiatry Computational psychiatry and machine learning applications Deep phenotyping of mental illness Longitudinal studies of brain-behavior relationships Neuroimaging and brain structure/function analysis His recent publications emphasize predictive modeling of cognitive function, trauma-related dissociation, PTSD neuroanatomy, and AI integration in psychiatric care. Collaborations span global cohorts like the AMP® SCZ initiative and ENIGMA-PGC PTSD workgroup.
Prof. Dr. med. Carsten Finke is a professor specializing in cognitive neuroscience and neuroimmunology, with a focus on memory consolidation, spatial navigation, and autoimmune neurological disorders. His research employs neuroimaging and behavioral methods to investigate conditions like encephalitis, multiple sclerosis, and post-COVID cognitive deficits. Research Focus: His work spans three core areas: Memory Systems: Examining consolidation mechanisms (e.g., pharmacological modulation via propofol) and developmental trajectories of spatial/navigational memory. Neuroimmune Disorders: Characterizing cognitive outcomes and brain network reorganization in autoimmune encephalitis (anti-NMDA, anti-LGI1) and multiple sclerosis. Post-COVID Neurology: Identifying neural correlates of fatigue/cognitive impairment and contributing to large cohorts (NAPKON) for phenotyping acute/chronic morbidity. Publication Trends: Recent articles (2023–2025) emphasize: Dynamic brain network analysis in neuroinflammatory conditions Long-term cognitive sequelae of COVID-19 Multisensory influences on spatial memory Pediatric neuroimmunology (MOG-ADEM)
Li Wang is an Associate Professor in Mathematics at the University of Texas at Arlington. She holds a Ph.D. from UC San Diego (2014), M.S. from Xi'an Jiaotong University (2009), and B.S. from China University of Mining and Technology (2006). Her research focuses on optimization, data science, and machine learning. Current research includes polynomial optimization methods, low-rank tensor approximations for big data, and structure learning algorithms. She teaches courses in discrete mathematics, optimization, and data science.
Sarah F. Muldoon is an Associate Professor in the Department of Mathematics at the University at Buffalo, SUNY. Her research focuses on network neuroscience and complex systems, integrating tools from mathematics, physics, and computational biology. Education: PhD in Physics, University of Michigan (2009) Her research explores network organization in brain function, particularly in health and pathological conditions like epilepsy. Key areas include: Development of novel network statistics (e.g., small-world propensity, multilayer analysis) Computational modeling of brain dynamics and state transitions Experimental data analysis across neuronal networks, ECoG, and fMRI Software tools for seizure detection and community structure quantification She leads a multidisciplinary group affiliated with the Computational and Data-Enabled Sciences (CDES) Program and Neuroscience Program at UB. Her work bridges theoretical and applied network science, with recent publications examining brain states, pandemic modeling, and personalized network diagnostics.
Dr. Emma Towlson is an Assistant Professor in the Department of Computer Science at the University of Calgary's Faculty of Science, serving as Assistant Head of Undergraduate Curriculum. She holds a Full Member position at the Hotchkiss Brain Institute and is a Child Health & Wellness Researcher at the Alberta Children's Hospital Research Institute. Her research focuses on network neuroscience, exploring how brain networks' structure-function relationships underpin health and disease. Key areas include network control theory, mental illness vulnerability, and brain connectivity analysis across species. Dr. Towlson's work bridges computer science, physics, neuroscience, and biology. She investigates structural brain networks' topological features (e.g., rich clubs, modules) and their spatial constraints, applying these insights to disorders like schizophrenia, depression, and Alzheimer's. Her lab uses network control principles to identify therapeutic targets for brain stimulation therapies and personalized medicine approaches. Recent grants include a $250,000 New Frontiers in Research Fund (NFRF) Explorations grant (2022) to study preterm birth's impact on brain networks and mental illness risk. She teaches courses on social network analysis (CPSC 572/672) and data visualization (DATA 601). Collaborative efforts include partnerships with Harvard Medical School and Monash University's Turner Institute. Her team’s interdisciplinary projects include analyzing mouse brain connectomes, simulating connectome perturbations, and developing open-source network neuroscience tools. Ongoing work emphasizes translating network science insights into clinical applications for mental health interventions.
Gustavo Deco is a Research Professor at the Institució Catalana de Recerca i Estudis Avançats (ICREA) and holds a Professorship (Catedrático) at Pompeu Fabra University (UPF). He leads the Computational Neuroscience Group and directs the Center of Brain and Cognition at UPF. His research focuses on computational models of brain dynamics, integrating biophysics, neuroimaging, and complex systems principles. Deco’s academic journey includes a PhD in Physics (1987, thesis on Relativistic Atomic Collisions), postdoctoral work at the University of Bordeaux (France) and University of Giessen (Germany), and a Habilitation in Computer Science (1997, Technical University of Munich). He has led computational neuroscience research at Siemens Corporate Research Center (1990–2003) and pioneered whole-brain modeling frameworks like The Virtual Brain (TVB). His research interests span critical brain dynamics, non-equilibrium thermodynamics in neural systems, psychedelics’ effects on brain hierarchy, and clinical applications of computational models in disorders such as Alzheimer’s and depression. Recent work emphasizes turbulence-like dynamics in healthy and diseased brains, and biomarker discovery using AI-driven simulations. Deco’s articles (2024–2025) explore topics like entropy production in brain networks, psychedelics-induced flattening of functional hierarchies, sleep-like dynamics post-stroke, and the role of long-range connections in global brain communication. His work bridges theoretical models with clinical insights, aiming to advance personalized neurology and digital brain research.
Daniel Pederick is the Bloomberg Assistant Professor of Neuroscience and Assistant Professor of Otolaryngology-Head and Neck Surgery at Johns Hopkins University School of Medicine. He is affiliated with the Solomon H. Snyder Department of Neuroscience and conducts research on neural circuit formation in the central auditory system. His research focuses on understanding how precise neural connections are established during brain development, particularly tonotopic maps that process sound frequency. He investigates these mechanisms using Single-cell transcriptomic analysis Animal models Virus-mediated axon tracing In vivo electrophysiology with an emphasis on molecular guidance cues in circuit assembly. The recent publications (2016–2023) reflect a strong trend in neural circuit development, especially in the hippocampus and auditory brainstem. Key themes include topographic mapping, cell surface molecules (e.g., Teneurins, Latrophilin-2), and the role of genetic and signaling mechanisms in axon targeting and synaptic specificity. Much of this work bridges molecular neuroscience with systems-level circuit organization. Scientific recognition includes: Feature in Nature News and Views for work on attraction and repulsion in brain wiring Daniel Pederick mentors graduate students and recruits postdoctoral fellows and research staff. He is actively building his lab at Johns Hopkins and accepts rotations from students in the Neuroscience Graduate Program and the Biochemistry, Cellular and Molecular Biology Graduate Program. While specific grants are not listed, his research program is supported by institutional and likely federal funding given the publication output and lab structure. He leads the Pederick Lab, which focuses on: Molecular control of neural connectivity Topographic circuit organization Developmental disruptions in neurodevelopmental disorders Auditory processing deficits in autism The lab is located in the Wood Basic Science Building (WBSB 1001A) at Johns Hopkins School of Medicine.
Professor Ioanna Sandvig is a leading academic at the Norwegian University of Science and Technology (NTNU) , where she serves as group leader of the Integrative Neuroscience Group within the Department of Neuromedicine and Movement Science. She is also President of the Norwegian Neuroscience Society (NNS) and actively participates in international societies including the Federation of European Neuroscience Societies (FENS), Society for Neuroscience (SfN), ALBA Network, and Clinical-Academic Group for Alzheimer's Disease. Research Interests : Her group investigates neuroplasticity mechanisms in CNS damage and repair , focusing on structure-function relationships in biological neural networks under healthy and pathological conditions. They integrate in vivo , in vitro , and computational models to identify adaptive/maladaptive plasticity in neurodegenerative diseases like ALS and Alzheimer's. The research combines connectomics , transcriptional analysis , and geometric network modeling to decode network behaviors. Scientific Contributions : Recent publications explore topics including synaptic transcript dysregulation in ALS, functional complexity of 3D-engineered networks, and platinum microelectrode technologies. Her work demonstrates interdisciplinary approaches bridging neuroscience , bioengineering , and computational systems . Scientific Recognition : President, Norwegian Neuroscience Society (2024) Member, Federation of European Neuroscience Societies Member, Society for Neuroscience Member, ALBA Network Member, Clinical-Academic Group for Alzheimer's Disease Laboratory & Collaborations : The Integrative Neuroscience Group collaborates across NTNU's neuroscience departments and clinical institutions, developing tools for neuroplasticity analysis and contributing to preclinical disease modeling.
Anne Maass is a Researcher at the German Center for Neurodegenerative Diseases (DZNE), Magdeburg , leading multidisciplinary studies at the intersection of Alzheimer's disease , neuroimaging , and cognitive resilience . Her work focuses on molecular mechanisms of aging using in vivo multimodal imaging techniques. Key affiliations: DZNE Magdeburg, Otto von Guericke University, SFB1436 "Neural Resources of Cognition" Collaboration network: Prof. Emrah Düzel (Magdeburg), Prof. Michael Heneka (Bonn), Prof. Stefanie Schreiber (Magdeburg), Prof. Sylvia Villeneuve (Montreal) Her research integrates functional and structural MRI (3T/7T) , PET imaging with novel tracers like PI-2620 , and cerebrospinal fluid proteomics to map tau pathology , Aβ accumulation , and vascular contributions to cognitive decline. She pioneered Vessel Distance Mapping for quantitative hippocampal vascularization analysis. Recent publication trends emphasize inflammatory signatures (TAM receptors, sTREM2), non-linear fMRI activation patterns in preclinical Alzheimer's, and vascular compensation mechanisms for neurodegenerative pathology. Her work on SuperAgers investigates neural resources for exceptional cognitive aging through multimodal cohort studies. Current projects include: SFB1436 Z03 : Molecular imaging of aging and SuperAgers DELCODE study : Longitudinal tracking of Alzheimer's biomarkers Collaborative network : Cross-site studies with Bonn, Göttingen, and Barcelona Her translational research aims to develop intervention strategies for neuroinflammatory regulation and cognitive reserve enhancement to prevent age-related cognitive decline.
Susan Y. Bookheimer, PhD, is Professor-in-residence in the Department of Psychiatry and Biobehavioral Sciences at the David Geffen School of Medicine, University of California, Los Angeles. From 2008 to 2024 she held the endowed Joaquin M. Fuster Chair in Cognitive Neuroscience and currently directs or co-directs several large-scale NIH consortia including the UCLA site of the Adolescent Brain Cognitive Development (ABCD) Study, the Lifespan Human Connectome Project in Aging, and newly funded initiatives on resilience to Alzheimer’s disease in centenarians. Education & Training Details of formal degrees are not provided in the source text; however, her continuous NIH funding since 1995 and leadership roles imply advanced research training in clinical neuroscience and neuroimaging. Research Focus Dr. Bookheimer’s work integrates multimodal neuroimaging (fMRI, sMRI, DTI, PET, EEG) with genetics, cognitive testing, and clinical phenotyping to understand: Typical and atypical brain development across the lifespan Neurobiological underpinnings of autism spectrum disorder and sensory phenotypes Early detection and prediction of Alzheimer’s disease and age-related cognitive decline Neuroplasticity and cognitive outcomes following epilepsy surgery Effects of environmental adversity, stress, and social support on brain networks Scientific Awards & Honors Joaquin M. Fuster Chair in Cognitive Neuroscience, UCLA (2008–2024) Principal or Co-Principal Investigator on >15 active NIH grants totaling >$100 M Over 230 peer-reviewed publications with >25,000 citations (Google Scholar metrics) Grants & Consortia Leadership Dr. Bookheimer currently leads or co-leads the following major NIH projects: U19AG073585 – Vulnerability and Resiliency in the Aging Adult Brain Connectome (AABC) U19AG073172 – Resilience/Resistance to Alzheimer’s Disease in Centenarians and Offspring (RADCO) R01AG073480 – Modulation of Hippocampal Circuitry with Focused Ultrasound in Amnestic MCI P50HD103557 – UCLA Intellectual and Developmental Disabilities Research Center U01DA050987 – ABCD-USA Consortium Research Project Site at UCLA U01AG052564 – Mapping the Human Connectome During Typical Aging U01MH109589 – Mapping the Human Connectome During Typical Development In addition, she has served as PI on prior awards including P50HD055784 (Autism Center), R01AG013308 (Alzheimer’s Risk), and P30HD004612 (IDDRC). Laboratories & Teams Dr. Bookheimer directs the UCLA Brain Mapping Center (part of the Ahmanson-Lovelace Brain Mapping Center) and co-directs imaging cores for both the UCLA IDDRC and the ABCD Study. Her multidisciplinary teams include post-doctoral fellows, graduate students, research staff, and collaborators across neurology, radiology, psychology, and genetics departments.
Wako Yoshida is Professor of Clinical Neuroscience at the University of Oxford's Nuffield Department of Clinical Neuroscience, leading research at the intersection of computational neuroscience, decision theory, and social cognition. Her work focuses on neural mechanisms of belief construction during partially observable decision-making and social interactions, with particular emphasis on prefrontal cortex function. Her research interests include: Computational modeling of uncertainty resolution in cognitive decision-making Neural basis of Theory of Mind during cooperative social interactions Pain neuroscience and aversive learning mechanisms Application of hyper-scanning fMRI for group decision-making studies Brain-machine interfaces for pain control through co-adaptive learning Analysis of her 15 most recent publications (2016-2024) reveals three dominant trends: (1) Neural mechanisms of hierarchical belief inference in spatial navigation and social contexts, (2) Uncertainty processing in pain modulation involving prefrontal-periaqueductal circuits, and (3) Development of computational frameworks for brain-machine interfaces targeting chronic pain management. Her work consistently bridges machine learning concepts with human neuroimaging. Scientific awards: No awards mentioned in source material. Advising and grants: Source text provides no details about students, advisees, or grant funding. Yoshida directs the Pain and Aversive Learning research group at Oxford, collaborating with Ben Seymour and others to investigate computational and neural mechanisms underlying pain, aversion, and decision-making using fMRI, hyper-scanning, and computational modeling approaches.
David G. Amaral is a Professor in the Department of Psychiatry and Behavioral Sciences at the University of California, Davis School of Medicine. He serves as the Director of Research at the UC Davis MIND Institute and holds the Beneto Foundation Chair, focusing on autism and neurodevelopmental disorders. His leadership roles include coordinating the Autism Phenome Project and directing Autism BrainNet, a collaborative postmortem brain tissue initiative. From 2015, he has been Editor-in-Chief of Autism Research , the journal of the International Society for Autism Research, and was appointed to the Interagency Autism Coordinating Committee in 2016. Education: B.A., Northwestern University (1968) Ph.D., Neuroscience/Psychology, University of Rochester (1977) Fellowship in Neuroanatomy, Washington University (1980) His research spans neurobiology, psychiatry, and behavioral neuroscience, with a focus on autism spectrum disorder (ASD). He investigates neurodevelopmental mechanisms, including cortical and amygdala connectivity, metabolomics, and primate models. His work also explores maternal immune activation (MIA) and its impact on neurodevelopment, as well as longitudinal brain growth patterns in ASD. Dr. Amaral has received prestigious awards, including the NARSAD Distinguished Investigator Award (2008), University of California Distinguished Professor (2009), and Fellowship in the American Association for the Advancement of Science (AAAS) (2009). He previously served as President of the International Society for Autism Research (2009). At the MIND Institute, he leads multidisciplinary teams studying autism through neuroimaging, genetics, and metabolomics. His recent publications emphasize cortical development, neurogenetics, and biomarker discovery in ASD.
Justin Blau is a **Professor of Biology and Neural Science** at **New York University (NYU)**, affiliated with the **Faculty of Arts and Science** and the **Center for Neural Science**. He joined NYU in 2000 as an Assistant Professor, was promoted to Professor in 2013, and holds additional roles at the NYU Abu Dhabi Research Institute. His research focuses on **behavioral genetics, circadian rhythms, and neurobiology**, using Drosophila as a model system to study how genes control animal behavior and circadian timing mechanisms. Education: - 1996 Ph.D., Imperial Cancer Research Fund & London University - 1991 B.A., Cambridge University Research Highlights: - Investigates circadian clock neurons and their role in behavioral timing. - Developed techniques for studying gene expression in pacemaker neurons. - Explores neuronal plasticity and network dynamics in circadian systems. Teaching: - Courses include *Genes & Animal Behavior*, *The Art of Scientific Investigation*, and *Signaling in Biological Systems*. Awards: 2013 NYU Golden Dozen Teaching Award 2005 Eppendorf & Science Essay Prize Finalist 1999 Human Frontiers Science Program Fellowship Labs & Collaborations: - Organizes the NYU NeuroBiology SuperGroup and the NY Area Clock Group. - Collaborates with institutions like Rockefeller University and Columbia University.
Dr. Andrew J. Anderson is an Assistant Professor in the Department of Neurology at the Medical College of Wisconsin. His research focuses on neurophysiological and neuroimaging approaches to understand language processing, cognitive fatigue in aging, and neural networks underlying semantic meaning. He employs techniques such as fMRI, EEG, and structural connectome analysis to explore how the brain encodes and decodes linguistic and experiential information. Dr. Anderson’s work also investigates potential biomarkers for early detection of neurodegenerative diseases like Alzheimer's through pattern analysis of brain activity. Key research areas include: Neurophysiological correlates of speech comprehension and semantic processing Functional connectivity in aging populations, particularly relating to cognitive fatigue Integration of artificial neural networks to model cortical language processing Brain decoding techniques for identifying individual cognitive patterns His publications (2018-2022) emphasize interdisciplinary methods combining neuroscience with computational models, revealing distributed neural networks involved in propositional sentence meaning, and dissociable electrophysiological measures of language processing in aging. While no specific scientific awards are listed, his research contributes to foundational understanding of brain-language interactions and healthy aging processes. Advising and grants: Details not explicitly provided in the text. His affiliations include the Medical College of Wisconsin Neurology department, with potential collaborative ties to affiliated hospitals or research institutes. No lab affiliations are mentioned.
Geraint Rees is Vice-Provost (Research, Innovation and Global Engagement) at University College London (UCL), where he previously served as Dean of the Faculty of Life Sciences. His academic appointments include Professor of Cognitive Neurology and Director of the UCL Institute of Cognitive Neuroscience. His research focuses on understanding human cognition through advanced neuroimaging and machine learning techniques. Education: Doctor of Philosophy, University College London (1999) Master of Arts, University of Cambridge (1999) Bachelor of Medicine/Bachelor of Surgery, University of Oxford (1991) Bachelor of Arts, University of Cambridge (1988) Dr. Rees leads interdisciplinary research in cognitive neuroscience, investigating neural mechanisms of perception and decision-making using functional MRI and computational approaches. His work bridges clinical neurology with artificial intelligence to understand brain disorders. Research emphases include neuroplasticity, neurodegeneration biomarkers, and machine learning applications in healthcare. Recent publications (2023-2025) demonstrate strong research trends in computational neuroscience with applications to neurodegenerative diseases, particularly Huntington's and Alzheimer's. Key patterns include advanced neuroimaging techniques (7T MRI, fMRI), transformer-based deep learning models, and investigations into neuroplasticity and sensory system adaptations. Dr. Rees has extensive leadership experience in large-scale research initiatives, serving on the Executive Management Team of the Francis Crick Institute and as Non-Executive Director for UCL Business. He maintains active research collaborations with Google DeepMind and develops doctoral training programs.
