Brent Doiron is a Professor at the University of Chicago, holding appointments in the Departments of Neurobiology and Statistics, and serving on the Committee on Computational and Applied Mathematics (CCAM). His research integrates nonlinear dynamics and statistical mechanics to study neural circuit variability, focusing on mechanisms underlying neural coding and network learning through collaborations with experimentalists in sensory systems. Education: PhD in Physics (University of Ottawa, 2004) Postdoc: Center for Neural Science at New York University (2017) Previous Roles: Mathematics Professor at University of Pittsburgh (2007-2020), Co-Director of Neural Computation Program at Carnegie Mellon Neuroscience Institute Research interests center on neuronal population dynamics, recurrent circuit mechanisms, and computational neuroscience. Current work investigates correlated variability in cortical networks, inter-areal communication, and stochastic spiking models. Recent publications emphasize cortical stability/gain modulation, asynchronous/synchronous activity balance, and Bayesian inference frameworks. Key themes include sensory processing, network plasticity, and dimensionality reduction in neural coding. Scientific Awards Alfred P. Sloan Research Fellowship in Neuroscience Vannevar Bush Faculty Fellowship Chancellor’s Distinguished Research Award (University of Pittsburgh) Active grants include NIH R01 and R90/T90 awards for neuronal dynamics research and computational neuroscience training programs.
Silvestro Micera is a Full Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) and holds the Bertarelli Foundation Chair in Translational Neuroengineering. He directs the Translational Neural Engineering Laboratory and teaches courses including Neural signals and signal processing and Translational neuroengineering . His research bridges neural interfaces, robotics, and neuroprosthetics to restore motor functions in spinal cord injuries, stroke, and amputations. Micera's research integrates implantable neural interfaces, robotic rehabilitation, and hybrid neuro-prosthetic systems. Key focus areas include: Robotic neurorehabilitation for mobility restoration Neural control mechanisms in movement CNS/PNS neural interface development Bioelectronic modulation for sensory feedback His recent publications emphasize machine learning-driven motor recovery prediction, closed-loop sensory feedback systems, and minimally invasive neuroprosthetics. Trends include AI-optimized stimulation protocols, multimodal data fusion for rehabilitation, and clinical translation of neural bypass technologies. Awards: IEEE EMBS Early Career Achievement Award (2009) IEEE EMBS Technical Achievement Award (2021) Micera leads EU-funded projects such as TIME, CLONS, and NeuWalk, focusing on neural prostheses. He advises 8 current and 18 former PhD students in neuroengineering. His lab collaborates with MIT, Harvard, and industry partners (e.g., Plexon) to advance translational neurotechnologies.
Marc V Fuccillo is an Associate Professor of Neuroscience at the Perelman School of Medicine, University of Pennsylvania, where he leads a research laboratory focused on understanding the neural circuit mechanisms underlying behavioral control. His work bridges molecular, synaptic, and behavioral approaches to investigate how striatal circuits regulate mouse behavior from simple motor patterns to complex goal-directed actions. Fuccillo holds dual appointments in the Neuroscience and Cell and Molecular Biology Graduate Groups at Penn and maintains an active laboratory investigating the synaptic and circuit basis of neuropsychiatric disorders. Education: B.A. in Molecular and Cellular Biology and Music Performance (Violin) from Brown University (1998) Ph.D. in Developmental Genetics from New York University School of Medicine (2007) M.D. from New York University School of Medicine (2008) Fuccillo's research centers on the synaptic and circuit mechanisms of behavioral control, with particular emphasis on striatal circuits. His laboratory employs a range of technologies including mouse genetics, in vitro electrophysiology, in vivo imaging, and quantitative behavioral analysis to explore how neural circuits of the striatum regulate behavior and how disruptions in these circuits contribute to neuropsychiatric disorders. His work has particularly focused on autism-associated abnormalities in behavioral control, examining how synaptic adhesion molecules like neuroligins and neurexins shape circuit function and behavior, with significant findings regarding D1 dopamine receptor positive medium spiny neurons in the nucleus accumbens. Analysis of Fuccillo's recent publications reveals a strong focus on striatal circuit function across multiple dimensions. His work spans molecular neuroscience (examining synaptic adhesion molecules), cellular physiology (studying specific neuron types in striatal circuits), systems neuroscience (mapping circuit connectivity), and behavioral neuroscience (quantifying motor learning and decision-making). A unifying theme is how disruptions in specific molecular pathways lead to circuit-level abnormalities that manifest as behavioral phenotypes relevant to neuropsychiatric disorders, with particular attention to autism, OCD, and schizophrenia models. Scientific Recognition: Publications in high-impact journals including Nature Neuroscience, Current Biology, Cell Reports, and Neuron Research supported by multiple NIH grants including NIMH F32, NIMH K01, and HHMI Gilliam Fellowship awards for lab members Fuccillo actively mentors a diverse group of trainees including postdoctoral fellows, graduate students, and undergraduates. His laboratory has produced numerous successful alumni who have gone on to faculty positions, medical residencies, and graduate programs at prestigious institutions. His mentoring approach emphasizes technical skill development across multiple neuroscience disciplines while fostering independent scientific thinking. Current research in his lab is supported by NIH funding focused on understanding the molecular architecture of striatal circuits and their role in behavioral control, with three major research directions exploring molecular logic of striatal circuits, circuit mechanisms of behavioral control, and striatal dysfunction in neuropsychiatric disease models. The Fuccillo Laboratory operates within the Department of Neuroscience at the University of Pennsylvania, with access to state-of-the-art facilities for molecular, electrophysiological, imaging, and behavioral neuroscience research. The lab maintains active collaborations with other neuroscience research groups at Penn and beyond, creating a rich intellectual environment for studying the neural basis of behavior. Current research directions include investigating whether there is a molecular logic to striatal circuit composition, how striatal circuits shape behavioral control, and what mouse models of autism, schizophrenia, and OCD can reveal about striatal circuit dysfunction in disease pathophysiology.
Zion Zibly, MD, MBA is an Associate Professor in the Department of Neurosurgery at Yale School of Medicine . He holds multiple leadership roles including Director of the Center of Neuromodulation , Director of the Center of Neurosurgical Cancer Pain , and Head of Stereotactic & Functional Neurosurgery and the Focused Ultrasound Institute . Previously served as Chair of Neurosurgery at Sheba Medical Center after graduating from Technion’s Faculty of Medicine (MD) and Coller School of Management (MBA). Research Interests: Specializes in Neuromodulation for movement disorders (Parkinson’s, tremors, dystonia), Deep Brain Stimulation , Gene Therapy for pediatric neurodegenerative conditions, Oncological Neurosurgery , and Neurological Pain Management . Combines Functional Neurosurgery with Focused Ultrasound technology. Scientific Contributions: Participated in pioneering Alzheimer’s brain stimulator procedures and Gene Therapy applications. Active member of the North American Association of Functional Neurosurgery and Israeli Neurosurgical Society . Clinical Expertise: Implantation of electrostimulators for Parkinson’s and essential tremor, treatment of Benign/Malignant CNS Tumors , and management of Neurological Pain Conditions . Affiliated with Yale Cancer Center and Center for Brain & Mind Health .
Ana Vives-Rodriguez, MD is an Assistant Professor of Neurology at Yale School of Medicine. She specializes in movement disorders and cognitive-behavioral neurology, caring for patients with Parkinson's disease, tremor, tics, dystonia, Alzheimer's disease, Dementia with Lewy bodies, and frontotemporal dementias. Based at Yale Physicians Building in New Haven, Connecticut, she provides both in-person and telehealth services to adult patients, accepting new patients without requiring referrals. Dr. Vives-Rodriguez's educational background includes: BS and MD from University of Costa Rica (2009), graduating Magna Cum Laude Residency at University Costa Rica/Calderon Guardia Hospital (2014) Clinical Fellowship in Movement Disorders at Yale New Haven Hospital (2018) Advanced Fellowship in Cognitive Behavioral Neurology at Boston University/VA Medical Center (2022) Her primary research interests focus on the behavioral and cognitive aspects of movement disorders and the early diagnosis of neurodegenerative disorders . Dr. Vives-Rodriguez examines structural and functional brain changes in conditions like Parkinson's disease, Wilson's disease, and Alzheimer's disease and their relation to clinical manifestations. Her work bridges clinical practice with translational neuroscience to improve diagnostic approaches and patient outcomes in complex neurological conditions. Analysis of her publications from 2017-2021 reveals a strong focus on movement disorders, cognitive impairment, and neuroimaging. Her research spans clinical observations of movement phenomena like index finger pointing and writing tremor, structural and functional brain changes in Wilson's disease, and innovative approaches to medical education in movement disorders. A recurring theme is the intersection between movement disorders and cognitive function, highlighting her dual expertise in both specialties. Dr. Vives-Rodriguez serves as a Sub Investigator for the Cognitive Training in Parkinson's Disease clinical trial (HIC ID 2000033352), which is recruiting participants aged 40+ through 2027. While specific grant funding isn't detailed in the available information, her active research program suggests ongoing support for her work in neurodegenerative disorders. She is affiliated with Yale's Movement Disorders and Neurodegenerative Disorders divisions, working within the Department of Neurology at Yale School of Medicine. Her clinical work at Yale Physicians Building integrates the latest research findings into patient care while contributing to the academic mission through teaching and scholarly activities.
Giorgio Ascoli is a University Professor in the Department of Bioengineering at George Mason University, where he has been since 1997. He is the Founding Director of the Center for Neural Informatics, Structures, & Plasticity (CN3) and Founding Editor-in-Chief of the journal Neuroinformatics . His affiliations span computational neuroanatomy, neuroinformatics, and hippocampal modeling. Education : PhD in Biochemistry and Neuroscience (1996), Scuola Normale Superiore; MS in Chemistry and Biochemistry (1993), Pisa University; BS in Chemistry and Physics (1991), Scuola Normale Superiore. Dr. Ascoli investigates the relationship between brain structure, activity, and function from cellular to circuit levels. His research focuses on anatomically plausible neural networks to model mammalian brains, particularly the hippocampus, with implications for understanding human memory and consciousness . He pioneered computational neuroanatomy, developing tools like L-Neuron for neuronal shape modeling and curating NeuroMorpho.Org , a central repository for digitally reconstructed neurons. His recent publications emphasize neuronal classification , connectome analysis , and biologically informed machine learning . Awards include the 2012 Outstanding Faculty Award (Virginia), 2022 AIMBE fellowship , and 2023 Presidential Faculty Excellence Awards . He has mentored over 20 graduate students and postdoctoral fellows, with funding from NIH, NSF, DARPA, and private foundations. Scientific Contributions : Over 137 peer-reviewed articles, 4 patents, 2 authored/edited books, and leadership in NeuroMorpho.Org and Hippocampome. Grants : $20M+ in cumulative funding, including NIH R01s, NSF BRAIN EAGERs, and Burroughs-Wellcome Trust support. Labs : Leads the Computational Neuroanatomy Group within CN3, focusing on hippocampal modeling, neuronal morphology, and consciousness theories.
Julie Dethier is a Research Fellow at the University of Liège, affiliated with the Faculty of Applied Sciences and Montefiore Institute. Her research bridges cellular neuroscience and network dynamics, with focus on pathological rhythms in Parkinson's disease and brain-machine interface development. She completed her Ph.D. in 2015 under Prof. Sepulchre's supervision. Her academic journey includes: Ph.D. in Systems and Modeling (2015), University of Liège with Princeton University research stay (2014-2015) Master of Science in Bioengineering (2011), Stanford University (Brains in Silicon lab) Master of Applied Sciences in Biomedical Engineering (2010, summa cum laude), University of Liège Bachelor of Applied Sciences (2008, summa cum laude), University of Liège Dr. Dethier investigates how cellular feedback mechanisms generate pathological beta oscillations in basal ganglia circuits, disrupting motor function in Parkinson's disease. Her computational approaches model the transition from unicellular rhythms to network-level oscillations, with implications for deep-brain stimulation therapies. She integrates electrophysiological data with dynamical systems theory to explain robustness and modulation in neural circuits. Her publication record demonstrates evolving expertise from brain-machine interface hardware (2011-2012) to fundamental neural mechanism studies (2013-2015). Key themes include spiking neural network decoders, cellular feedback loops, and pathological oscillation generation. Work spans computational modeling, neuromorphic engineering, and translational neuroscience with applications in neuroprosthetics. Major recognitions include: WBI excellence grant for Princeton research (2014) LEAR Foundation Fellowship for Cambridge research (2013) Audience Award at ULg thesis competition (2013) IEEE EMBS Best Poster Award (2011) Fulbright Honorary Fellowship and Rotary International Fellowship (2010) Funded by competitive F.R.S.-FNRS and international fellowships, her research involved cross-institutional collaboration with Princeton, Cambridge, and Stanford teams. While no formal advisees are listed, her publications reflect mentorship through co-supervised projects and conference presentations. Current work extends her doctoral thesis on multiscale neural dynamics. She maintains active ties with the Systems and Modeling Research Unit at Liège, Brains in Silicon lab at Stanford, and participates in Benelux neuroscience networks through the Montefiore Institute.
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.
Zsofia Zavecz is a Research Associate at the University of Cambridge Department of Psychology. Her work focuses on the neurophysiological mechanisms underlying sleep and memory consolidation, with particular emphasis on electrophysiological correlates of lucid dreaming and sleep-dependent learning. Research highlights include: Investigation of EEG functional connectivity during statistical learning Study of transcranial stimulation effects on probabilistic learning Analysis of sleep restriction impacts on hormonal regulation Exploration of cognitive reserve mechanisms in sleep disorders Her neuroscientific investigations span procedural memory systems, neural oscillations, and cross-population studies in both healthy individuals and pediatric sleep-disordered breathing patients.
Juan Carlos Cerpa Gilvonio is a Research Fellow at the Oxford Department of Experimental Psychology, University of Oxford. His research focuses on neural circuits in the basal ganglia, their neuromodulation, and decision-making processes. He investigates noradrenergic systems in the prefrontal cortex and corticosteroid effects on memory consolidation in rodents. He contributes to the Neurochemistry, Action and Control research group, exploring interdisciplinary neuroscience topics. His recent publications address noradrenergic innervation patterns and corticosteroid impacts on memory, reflecting his commitment to advancing neurochemical mechanisms understanding.
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.
Professor Tim Denison FREng holds a joint appointment in the Department of Engineering Science and Nuffield Department of Clinical Neurosciences at the University of Oxford, where he serves as the Royal Academy of Engineering Chair in Emerging Technologies and an MRC Investigator. His research focuses on the fundamentals of physiologic closed-loop systems and developing next-generation neural interface technologies for treating chronic neurological diseases. Professor Denison received his A.B. in Physics from The University of Chicago, followed by M.S. and Ph.D. degrees in Electrical Engineering from MIT. He later completed an MBA at The University of Chicago, where he was named a Wallman Scholar. His research spans neural engineering, closed-loop neuromodulation systems, and computational neuroscience, with particular emphasis on deep brain stimulation, neural oscillations, and adaptive neurostimulation techniques. His work integrates engineering principles with clinical neuroscience to develop innovative treatments for neurological disorders. Professor Denison's approach combines computational modeling with experimental validation to optimize brain stimulation parameters for individual patients. Professor Denison has received numerous prestigious awards, including membership in the Bakken Society (2012, Medtronic's highest technical honor), the Wallin leadership award (2014), election to the College of Fellows for the American Institute of Medical and Biological Engineering (2015), and recognition as a Fellow of the Royal Academy of Engineering (FREng). As a former Technical Fellow at Medtronic PLC and Vice President of Research & Core Technology for the Restorative Therapies Group, Professor Denison brings significant industry experience to his academic work. His research group focuses on developing advanced neurostimulation technologies that incorporate chronobiology principles and adaptive algorithms to improve treatment outcomes for neurological conditions.
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.
Professor Rafal Bogacz is a leading academic at the University of Oxford, affiliated with St Edmund Hall and the MRC Brain Network Dynamics Unit . He teaches computational neuroscience and statistics at both undergraduate and postgraduate levels, including the MSc in Neuroscience and BSc in Biomedical Science programs. MSc: Wroclaw University of Technology PhD: University of Bristol Postdoctoral Researcher: Princeton University His research focuses on computational neuroscience , particularly modeling brain networks involved in action selection , decision making , and Parkinson's disease pathophysiology. Key themes include: Developing predictive coding models of cortical computations Understanding basal ganglia neural circuits in healthy and diseased states Designing closed-loop deep brain stimulation paradigms Recent publications highlight work in neural plasticity , dopamine signaling , and computational psychiatry , with a notable Wellcome Discovery Award supporting research on learning in neurons . The Bogacz Group maintains strong collaborations with experimental neuroscientists and shares open datasets through the MRC BNDU Data Sharing Platform . Wellcome Discovery Award (2025): For learning in neurons Europe PMC Open Access (multiple): For numerous PLoS, Nat Neurosci, and J Neural Eng publications As a computational neuroscientist, Professor Bogacz supervises D.Phil. students and leads research programs that bridge theoretical neuroscience with clinical applications . The group actively participates in MRC BNDU training initiatives and public engagement activities like Schools Open Day demonstrations.
Louis Collins is a Professor in the Department of Biomedical Engineering and Department of Neurology and Neurosurgery at McGill University, with associate membership at the Center for Intelligent Machines. His work focuses on advanced medical imaging techniques for neurological applications. Key Expertise: Non-linear image registration, model-based segmentation, neuroimaging, MRI analysis Applications: Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, schizophrenia Methodology: Development of computer vision algorithms for image-guided neurosurgery (IGNS), automated atlasing, and biomarker quantification Collins' research combines computational neuroanatomy with clinical translation, particularly in: Quantifying brain atrophy and anatomical variability across populations Optimizing MRI templates for improved diagnostic accuracy Developing tools like SEEGAtlas for surgical electrode classification Exploring neurophysiological fingerprints of neurodegenerative diseases His lab (NIST-Lab) actively pursues CIHR-funded projects on ultrasound-based image-guided neurosurgery and machine learning applications in clinical trials.
