Biosketches
Richard Adams studied medicine at Cambridge University and University College London (UCL) and worked as a doctor for 6 years; He is now halfway through his psychiatric training. In 2010 he began a PhD at UCL, supervised by Karl Friston. Rick's interest lies in the use of hierarchical generative models of brain function - which instantiate predictive coding - to explain psychiatric pathologies, in particular those of psychosis and schizophrenia, and of 'somatoform' or 'functional' bodily symptoms which are assumed to have a psychological cause.
In his current project Rick is trying to demonstrate how NMDA-R hypofunction - a putative cause of schizophrenia - can lead to the characteristic predictive eye movement problems of the disorder. Using a hierarchical generative model of smooth pursuit eye movement (SPEM), they have shown that reducing the precision on the hidden causes at the highest level of the model reproduces these schizophrenic SPEM problems. Given that precision is thought to be encoded by synaptic gain, it is clear that NMDA-R hypofunction in prefrontal cortex could lead to this loss of high-level precision. He is now trying to demonstrate this empirically using eye tracking, MEG, and dynamic causal modelling.
Rick is also collaborating with Harriet Brown and Mark Edwards (UCL) on a project that attempts to demonstrate empirically a neurobiological mechanism by which abnormal expectations about illnesses can bring about symptoms. This mechanism involves abnormally precise priors in a generative model, and is outlined in their theoretical paper.
Contact:
University College London
Wellcome Trust Centre for Neuroimaging
12 Queen Square
London WC1N 3BG
United Kingdom
E-mail: rick.adams@ucl.ac.uk
Ryszard Auksztulewicz is in his final year as a PhD student with a background in cognitive neuroscience (MSc, Universiteit van Amsterdam) and clinical psychology (MA, Uniwersytet Adama Mickiewicza, Poznań), currently preparing his dissertation at the Berlin School of Mind and Brain. In his doctoral project he uses EEG, TMS, fMRI, and computational methods to investigate the neuronal processes underlying somatosensory awareness.
Ryszard's recent publications include a study employing dynamic causal modelling of EEG data to assess model-based evidence for feedforward and feedback neural processing in tactile detection. He has also published on the role of the inferior frontal gyrus activity in somatosensory working memory. Furthermore, he collaborated on an experiment investigating TMS-induced effects on driftdiffusion model parameters in a perceptual decision-making paradigm.
Currently, besides finishing his doctoral project, he is collaborating on an EEG study on the role of alpha oscillations in apparent motion illusion, part of a larger project investigating the impairment of prediction systems in schizophrenia.
Contact:
Humboldt-Universität zu Berlin
Berlin School of Mind and Brain
Luisenstraße 56, Haus 1
D-10099 Berlin
Germany
E-mail: ryszard.auksztulewicz@googlemail.com
David Bernal-Casas studied physics (Graduate) and telecommunications engineering (MSc) simultaneously at the University of Barcelona (UB) and the Technical University of Catalonia (UPC) respectively. From 09/2006 to 02/2007, he had an internship granted by the National Center of Microelectronics (CNM) in Barcelona where he worked in the project “Quantum probes based on quantum nanotubes”.
From 03/2007 to 08/2009, David received a scholarship from the Department of Signal Theory and Communications at the Technical University of Catalonia (UPC) in Barcelona. He worked in three different projects: "Fundamental bounds in Network Information Theory", "Cost-optimized receive high performance active phased array antenna for mobile terminals (CORPA)", and "MEOLUT: A Digital Beamforming Approach”.
Since September 2010, David has been a PhD Candidate at the Bernstein Center for Computational Neuroscience (BCCN) Heidelberg/Mannheim. The BCCN Heidelberg-Mannheim investigates implications of genetic variations for neural information processing in psychiatric conditions. In the context of the BCCN, David is mainly involved in two projects: C5: Altered brain activation and connectivity and its genetic modulation in depression and ageing, and C7: PFCHC coupling in schizophrenia and related polymorphisms in working memory. In his PhD project, he develops new computational methods for fMRI to identify neural mechanisms underlying the increased risk for psychiatric disorders and pathological ageing in carriers of particular risk genes. He uses dynamic causal modelling (DCM) and cutting-edge multivariate statistical pattern recognition methods to infer relationships of genotype with schizophrenia, depression and ageing from fMRI data. These approaches will also be combined for identifying and explaining aberrant activity and connectivity in these populations.
Contact:
Central Institute of Mental Health
Bernstein Center for Computational Neuroscience Heidelberg/Mannheim,
J5
D-68159 Mannheim
Germany
E-mail: david.bernal@zi-mannheim.de
Timothy Brick received his Master's degree in Computer Science and Engineering from the University of Notre Dame, and his PhD in Cognitive and Quantitative Psychology from the University of Virginia. He is currently a Postdoctoral Fellow at the Max Planck Institute for Human Development in Berlin, Germany. His research focuses on the application of computational techniques and modern technology to the exploration of the way humans interact with each other and the world around them. Tim's methodological research includes timescale and dynamic techniques such as dynamical systems analysis, autoregressive and autocorrelation analysis, and wavelet methods. He is also the lead developer of the computational kernel of the OpenMx software for Structural Equation Modelling. Tim's substantive work focuses on the way that emotion is expressed, perceived, and interpreted during conversation, and the functioning of the perception-action loop.
Contact:
Max Planck Institute for Human Development
Center for Lifespan Psychology
Lentzeallee 94
D-14195 Berlin
Germany
E-mail: brick@mpib-berlin.mpg.de
Molly Crockett received her undergraduate degree in Psychobiology at the University of California, Los Angeles. Her undergraduate research examined the neural correlates of emotion regulation. Molly's doctoral work at the University of Cambridge focused on the neuromodulation of social and affective decisionmaking processes in humans, under the supervision of Prof Trevor Robbins in the Department of Experimental Psychology. She initially set out to investigate the influence of serotonin on self-control in rewarding and punishing contexts. Using tryptophan depletion to temporarily lower serotonin levels in healthy volunteers, she showed that serotonin is necessary for reflexively inhibiting behaviour in response to punishments, but does not influence the intentional control of behaviour, supporting the idea that several motivational systems guide behaviour (Crockett et al., J Neurosci 2009).
In a separate line of work, she examined the influence of serotonin on social decision-making in the ultimatum game (UG), in which participants decide to accept or reject fair or unfair monetary offers from another player. A series of studies found that lowering serotonin function increased people's tendency to retaliate against unfairness, while enhancing serotonin function reduced retaliation (Crockett et al., Science 2008, PNAS 2010). Currently, Molly is studying the neural basis of reciprocity, altruism and morality with the support of a Sir Henry Wellcome Postdoctoral Fellowship. She is collaborating with Ernst Fehr at the University of Zurich (Department of Economics) and Ray Dolan and Peter Dayan at University College London. Her current projects combine economic and neuroscientific approaches to understanding social behavior.
Contact:
Laboratory for Social and Neural Systems Research
Department of Economics
University of Zurich
Blümlisalpstraße 10
CH-8006 Zurich
Switzerland
E-mail: mollycrockett@gmail.com
The focus of Maria Dauvermann's PhD research is the investigation of neural network (dys)function in the brain in neurodevelopmental mental disorders, especially in schizophrenia.
Theoretical (neurobiological) and modelling approaches are used to understand the alterations of basic neural circuits of higher cognitive functions in mental illness. The aim is to examine the neuromodulatory mechanisms mediating the dynamics of cortial dysfunctions in patients with schizophrenia using clinical multimodal neuroimaging data, i.e. fMRI, sMRI, resting fMRI, ASL and MRS. With patient fMRI data Maria utilises dynamic causal modelling with variational Bayesian techniques, specifically with nonlinear dynamical systems theory (gain control), to infer biophysically modelled mechanisms. The application of DCM allows investigation of altered neuromodulatory processes (for example, glutamate and dopamine interactions in schizophrenia). Maria models key cognitive processes which are impaired in schizophrenia (working memory, verbal fluency) and autism spectrum disorder (emotional processing). By combining multimodal neuroimaging data, specifically DCM results with other brain modalities, this methodology might increase the understanding of interacting principles leading to cortical impairment in schizophrenia.
The application of nonlinear DCM in subjects at high genetic risk of schizophrenia demonstrated altered gain control in fMRI data in people at familial risk of developing schizophrenia. A recent grant for a multimodal imaging study in autism spectrum disorder has enabled Maria to design and optimise this scanning protocol for the investigation of different modalities in adults with highfunctioning autism. Training in 3 T MRI scanners has further enabled the development and optimisation of MRI sequences for this multimodal study.
Contact:
University of Edinburgh
Royal Edinburgh Hospital
Division of Psychiatry
Edinburgh, EH10 5HF
United Kingdom
E-mail: m.r.dauvermann@sms.ed.ac.uk
Nathaniel Daw is Associate Professor of Neural Science and Psychology and Affiliated Associate Professor of Computer Science at New York University. He received his PhD in computer science from Carnegie Mellon University before conducting postdoctoral research at the Gatsby Computational Neuroscience Unit at UCL. His research concerns computational approaches to reinforcement learning and decision-making, and particularly the application of computational models to the analysis of behavioral and neural data. He is the recipient of a McKnight Scholar Award, a NARSAD Young Investigator Award, and a Scholar Award in Understanding Human Cognition from the MacDonnell Foundation.
Contact:
New York University
Department of Psychology
6 Washington Place
New York, NY 10003
USA
E-mail: daw@cns.nyu.edu
Raymond J. Dolan is Mary Kinross Professor of Neuropsychiatry at UCL and Director of the Wellcome Trust Centre for Neuroimaging at UCL. His research is concerned with a neurobiological characterisation of human emotion. He currently holds a Wellcome Trust Senior Investigator Award. He was elected a Fellow of the Royal Society (FRS) in 2010 and an External Member of the Max Planck Society in 2012.
Contact:
University College London
Wellcome Trust Centre for Neuroimaging
12 Queen Square
London Wc1N 3BG
United Kingdom
E-mail: r.dolan@ucl.ac.uk
Emrah Düzel has been trained as a neurologist in Germany (in Bonn and Magdeburg) and has a long-standing interest in the functional anatomy of human episodic memory networks, neuromodulatory circuits, their alterations in aging and early stages of neurodegeneration, and their scope for plasticity. For this purpose, his group uses and advances multimodal imaging techniques including fMRI, EEG / MEG and PET. They are particularly interested in how the degeneration of dopaminergic and noradrenergic neurotransmitter systems contribute to cognitive dysfunction in old age by impacting on motivation, decision-making, memory consolidation, and plasticity. They approach this problem from the vantage point of how declarative memory processes, motivation, and decision-making interact.
Contact:
German Center for Neurodegenerative Diseases (DZNE)
Leipziger Str. 44
D-39120 Magdeburg
Germany
E-mail: emrah.duezel@dzne.de
Michael J. Frank is Associate Professor of Cognitive, Linguistic & Psychological Sciences and Psychiatry in the Brown Institute for Brain Science at Brown University. He directs the Laboratory for Neural Computation and Cognition. He received an undergraduate degree in Electrical Engineering at Queen’s University (Canada), followed by a Master’s degree in Biomedicine Engineering at the University of Colorado at Boulder, where he went on to receive a PhD in Neuroscience and Psychology in 2004. His work focuses primarily on theoretical models of basal ganglia, frontal cortex and their modulation by dopamine, especially in terms of their cognitive functions and implications for neurological and psychiatric disorders. The models are tested and refined by empirical studies using a variety of methods. He received the Cognitive Neuroscience Society Young Investigator Award (2011) and the Janet T Spence Award for early career transformative contributions (APS 2010).
Contact:
Brown University
Laboratory for Neural Computation and Cognition
190 Thayer St.
Providence, RI 02912-1821
USA
E-mail: michael_frank@brown.edu
Karl Friston is a neuroscientist and authority on brain imaging. He invented statistical parametric mapping: SPM is an international standard for analysing imaging data and rests on the general linear model and random field theory (developed with Keith Worsley). In 1994, his group developed voxel-based morphometry. VBM detects differences in neuroanatomy and is used clinically and as a surrogate in genetic studies. These technical contributions were motivated by schizophrenia research and theoretical studies of value-learning (with Gerry Edelman). In 1995 this work was formulated as the disconnection hypothesis of schizophrenia (with Chris Frith). In 2003, he invented dynamic causal modelling (DCM), which is used to infer the architecture of distributed systems like the brain. Mathematical contributions include variational (generalised) filtering and dynamic expectation maximization (DEM) for Bayesian model inversion and timeseries analysis. Friston currently works on models of functional integration in the human brain and the principles that underlie neuronal interactions. His main contribution to theoretical neurobiology is a free-energy principle for action and perception (active inference). Friston received the first Young Investigators Award in Human Brain Mapping (1996) and was elected a Fellow of the Academy of Medical Sciences (1999) in recognition of contributions to the bio-medical sciences. In 2000 he was President of the international Organization of Human Brain Mapping. In 2003 he was awarded the Minerva Golden Brain Award and was elected a Fellow of the Royal Society in 2006. In 2008 he received a Medal, Collège de France and an Honorary Doctorate from the University of York in 2011. He became Fellow of the Society of Biology in 2012.
Contact:
University College London
Wellcome Trust Centre for Neuroimaging
12 Queen Square
London WC1N 3BG
United Kingdom
E-mail: k.friston@ucl.ac.uk
Douglas D. Garrett attained a PhD (2011) in cognitive neuroscience/psychology from the Department of Psychology at the University of Toronto in Cheryl Grady’s lab at the Rotman Research Institute, Baycrest. He is now a postdoctoral researcher with the Max Planck Society (MPS) – University College London (UCL) Initiative for Computational Psychiatry and Ageing Research (ICPAR), and is based at the Center for Lifespan Psychology, Max Planck Institute for Human Development in Berlin, Germany. His research centres broadly on normal and pathological age-related changes in brain structure/function and behaviour. In particular, using a variety of approaches (e.g., brain imaging, behavioural methods, pharmacological intervention), Douglas focuses on the development and functional consequences of moment-to-moment human brain signal variability and dynamics. They continue to find that healthy, better functioning brains are characterized by greater signal variability across broad brain regions, cognitive domains, and task types. His most recent work examines whether low-dose amphetamine can increase deficient signal variability levels in older adults by providing greater synaptic availability of dopamine. They continue to explore signal variability in a host of other contexts, including using cognitive trainingbased parametric paradigms to increase signal variability levels in younger and older adults at multiple levels of cognitive load.
Contact:
Max Planck Institute for Human Development
Center for Lifespan Psychology
Lentzeallee 94
D-14195 Berlin
Germany
E-mail: garrett@mpib-berlin.mpg.de
Mona Garvert studied molecular medicine in Freiburg and Lyon and did a Master’s in neuro-cognitive psychology at Ludwig Maximilians-Universität Munich. Over the course of her studies, she had the opportunity to gain experience in a variety of neuroscience labs, with projects ranging from contrast adaptation in the retina (Max Planck Institute of Neurobiology, Martinsried) and the role of a brainstem nucleus in auditory processing (University of Colorado Denver) to resting state fMRI in depressed patients (Technische Universität Munich) and the computational analysis of gamma oscillations in the cortex (Universitat Pompeu Fabra Barcelona). In September 2011, Mona started her PhD at University College London. Her research focuses on the neurobiology of social cognition with a specific interest in the influence of neuropeptides and neuromodulators on decision-making in a social context. Ultimately, she is hoping to bridge the gaps from neurons to behaviour and from basic neuroscience research to psychiatry.
Contact:
University College London
Wellcome Trust Centre for Neuroimaging
12 Queen Square
London WC1N 3BG
United Kingdom
E-mail: mona.garvert.11@ucl.ac.uk
Nikos Green was educated and trained in cognitive science and cognitive neuroscience. Most recently, he has been working on perceptual and rewardbased decision-making in the lab of Hauke Heekeren in Berlin (as a graduate student using, amongst other things, neuroimaging, computational modelling and neurostimulation methods). Prior to that (as a student), Nikos worked on two topics: influences of proprioceptive signals on decision-making (together with Joe Johnson, Markus Raab, and Jerry Busemeyer) and biophysical and morphological properties of hippocampal neurons (knock-out mice and cultured neural networks) in mental retardation syndromes (together with Randal Koene, Ger Ramakers, and Jaap van Pelt).
Contact:
Freie Universität Berlin
Neurocognition of Decision Making
Habelschwerdter Allee 45
D-14195 Berlin
Germany
E-mail: nikos.green@fu-berlin.de
Hauke Heekeren is Professor of Affective Neuroscience and Psychology of Emotion at the Freie Universität Berlin. He is deputy director of the Cluster of Excellence „Languages of Emotion“ at the Freie Universität Berlin and Co-Director of the Dahlem Institute for the Neuroimaging of Emotions. Since obtaining his doctoral degree in September of 2000 for his work on neurovascular coupling, the major focus of his work has been human decision neuroscience. Hauke has received the Rudolph Virchow Award for excellence in research from the Charité (Humboldt-Universität zu Berlin) as well as the Emmy-Noether-Award by the German Research Council (DFG). He is the founding editor of the journal Frontiers in Decision Neuroscience and currently the Chief Editor of Frontiers in Human Neuroscience. He is also currently the President-elect of the Society for Neuroeconomics. Hauke’s research program ranges from perceptual to rewardbased decision-making and decision-making in social contexts. In his work, he also seeks to further the understanding of neuropsychiatric conditions that involve socio-emotional impairments, such as autism, borderline personality disorder, and narcissistic personality disorder. Hauke uses a multimodal methodological approach that integrates information from an array of methods, ranging from cognitive modelling based on behavioral data to simultaneous functional magnetic resonance imaging (fMRI) and encephalographic (EEG/MEG) experiments as well as transcranial magnetic stimulation (TMS).
Contact:
Freie Universität Berlin
Cluster Languages of Emotion
Habelschwerdter Allee 45
D-14195 Berlin
Germany
E-mail: hauke.heekeren@fu-berlin.de
Laurence Hunt recently competed his DPhil in the Department of Experimental Psychology at the University of Oxford, and is now based jointly at the FMRIB Centre in Oxford and the Functional Imaging Laboratory at UCL. His DPhil work focussed on using biophysically realistic computational modelling to generate predictions of the temporal dynamics of neural activity during value-guided choice, and applying the models to magnetoencephalography data collected from human subjects. This allows for testing of model predictions simultaneously across the entirety of human neocortex. His past work has also applied models derived from reinforcement learning to human fMRI data. This reflects his broader interests in isolating the role of human cortical subregions in reward-guided learning and decision-making.
Contact:
University of Oxford
John Radcliffe Hospital
Center for Functional MRI of the Brain (FMRIB Centre)
Oxford OX3 9DU
United Kingdom
E-mail: laurence.hunt@ndcn.ox.ac.uk
Quentin Huys received his BA from Cambridge University and his PhD from the Gatsby Computational Neuroscience Unit with Peter Dayan. He was a postdoc at Columbia University, before obtaining his medical degree from UCL. He is a psychiatry trainee at the University of Zürich and a senior research fellow at the Translational Neuromodelling unit. He is interested in applying computational techniques to decision-making, particularly in the setting of mood disorders. This involves a combination of theoretical, behavioural, pharmacological and imaging techniques.
Contact:
University College London
Gatsby Computational Neuroscience Unit
17 Queen Square
London WC1N 3AR
United Kingdom
E-mail: qhuys@gatsby.ucl.ac.uk
Thomas R. Insel, M.D., is Director of the National Institute of Mental Health (NIMH), the component of the National Institutes of Health charged with generating the knowledge needed to understand, treat, and prevent mental disorders. His tenure at NIMH has been distinguished by groundbreaking findings in the areas of practical clinical trials, autism research, and the role of genetics in mental illnesses. Dr. Insel also serves as Acting Director of the National Center for Advancing Translational Sciences (NCATS), since December 2011.
Prior to his appointment as NIMH Director in the Fall 2002, Dr. Insel was Professor of Psychiatry at Emory University. There, he was founding director of the Center for Behavioral Neuroscience, one of the largest science and technology centers funded by the National Science Foundation and, concurrently, director of an NIH-funded Center for Autism Research. From 1994 to 1999, he was Director of the Yerkes Regional Primate Research Center in Atlanta. While at Emory, Dr. Insel continued the line of research he had initiated at NIMH studying the neurobiology of complex social behaviors. He has published over 250 scientific articles and four books, including the Neurobiology of Parental Care (with Michael Numan), in 2003.
Dr. Insel has served on numerous academic, scientific, and professional committees and boards. He is a member of the Institute of Medicine, a fellow of the American College of Neuropsychopharmacology, and is a recipient of several awards, including the Outstanding Service Award from the U.S. Public Health Service and the 2010 La Fondation IPSEN Neuronal Plasticity Prize. Dr. Insel graduated from the combined B.A.-M.D. program at Boston University in 1974. He did his internship at Berkshire Medical Center, Pittsfield, Massachusetts, and his residency at the Langley Porter Neuropsychiatric Institute, at the University of California, San Francisco.
Contact:
National Institute of Mental Health
15K North Drive, Rm. 104
MSC 2670
Bethesda, MD 20892-2670
USA
E-mail: tinsel@mail.nih.gov
Julian D. Karch is a member of the Formal Methods in Lifespan Psychology project at the Max Planck Institute for Human Development. He holds a diploma in computer science from the Freie Universität Berlin. His research interests include machine learning, data mining, algorithms in psychology in general, statistical and algorithmic modelling, and statistical methods. His current research focuses on the development of machine learning algorithms for the exploratory analysis of neuroscientific data sets. In his most recent work he proposed a set of ensemble classifiers for the classification of electroencephalographic data sets. He showed their superiority in comparison to classical classification methods.
Contact:
Max Planck Institute for Human Development
Center for Lifespan Psychology
Lentzeallee 94
14195 Berlin
Germany
E-mail: karch@mpib-berlin.mpg.de
Raphael Kaplan received his undergraduate degree from Macalester College in Saint Paul, Minnesota. At Macalester, he finished with a major in neuroscience and a minor in religious studies. During his undergraduate neuroscience education, he conducted research on medial temporal lobe deterioration and mild cognitive impairment in elderly populations. After graduating, he joined the National Institute for Mental Health as a post-baccalaureate fellow in 2007. At the NIMH, Raphael worked on fear and anxiety research involving functional MRI and magneto-encephalography (MEG) neuroimaging techniques. In 2009, he embarked on a joint PhD in neuroscience between the NIH and University College London (UCL). His UCL PhD thesis is about “Brain Oscillations and Novelty in Spatial Memory” and is co-supervised by Neil Burgess and Peter Bandettini (NIH). Raphael uses fMRI and MEG neuroimaging methods to characterize neural changes related to exploratory learning, memory consolidation, and novelty processing during spatial memory tasks. In the future, he hopes to characterize these brain network changes induced by spatial learning and use them to construct large-scale computational models of spatial and episodic memory networks in health and disease.
Contact:
University College London
Institute of Cognitive Neuroscience
17 Queen Square
London WC1N 3AR
United Kingdom
E-mail: raphael.kaplan.09@ucl.ac.uk
Christoph Korn is interested in social decision making and its neural mechanisms. As a doctoral student he has been working specifically on the mechanisms of social feedback processing. In the future he would like to address questions such as: How can social influences on decisions be modelled in similar ways as non-social influences? How are reward- and mentalizing-related factors integrated? How does social decision making differ in psychiatric patients?
After a Bachelor's degree in biomedicine at the University of Würzburg, Christoph obtained a Master's degree in Brain and Mind Sciences, spending one year in Paris at Ecole Normale Supérieure and Université Pierre et Marie Curie and one year in London at University College London. Currently, he is a PhD student at the Berlin School of Mind and Brain, under the supervision of Hauke Heekeren.
Contact:
Freie Universität Berlin
Affective Neuroscience
Habelschwerdter Allee 45
D-14195 Berlin
Germany
E-mail: christoph.korn@fu-berlin.de
Zebulun Kurth-Nelson is currently working as a postdoc at the Wellcome Trust Centre for Neuroimaging at University College London, and is a member of the Initiative for Computational Psychiatry and Ageing Research (ICPAR). He has two interrelated areas of interest: the neural and computational basis of impulsivity disorders, and the neural mechanisms of deliberative decision- making. Zebulun did his undergraduate degree in computer science at Iowa State University and his PhD in neuroscience at the University of Minnesota.
Contact:
University College London
Wellcome Trust Centre for Neuroimaging
12 Queen Square
London WC1N 3BG
United Kingdom
E-mail: z.kurth-nelson@ucl.ac.uk
Máté Lengyel obtained his MSc in Cell, Developmental and Neuroscience in 2000, and his PhD in Neurobiology in 2004, both at Eotvos University, Budapest. He was a postdoctoral researcher at the Gatsby Computational Neuroscience Unit, UCL between 2004-2006. He was a visiting researcher at the Collegium Budapest Institute for Advanced Study, Budapest in 2007. He is a member of the faculty (Lecturer, 2007-2012, Reader, 2012-) at the Computational and Biological Learning Lab, Department of Engineering, University of Cambridge. He received a Wellcome Trust New Investigator Award in 2011, has served on the programme committee of the Neural Information Processing Systems and the Computational and Systems Neuroscience conferences since 2010, and has been one of the directors of the FENS / IBRO Advanced Course in Computational Neuroscience course since 2011.
Máté Lengyel's group studies learning and memory from computational, algorithmic/representational and neurobiological viewpoints. He also maintains an active interest in the possible computational functions of neural oscillations, particularly those present in the hippocampus and neocortex. Computationally and algorithmically, his research uses ideas from Bayesian approaches to statistical inference and reinforcement learning to characterize the goals and mechanisms of learning in terms of normative principles and behavioral results. His work also includes dynamical systems analyses of reduced biophysical models to understand the mapping of these mechanisms into cellular and network models. His group collaborates very closely with experimental neuroscience groups, doing in vitro intracellular recordings, multi-unit recordings in behaving animals, and human psychophysical and fMRI experiments.
Contact:
University of Cambridge
Department of Engineering
Computational and Biological Learning Lab
Trumpington Street
Cambridge CB2 1PZ
United Kingdom
E-mail: m.lengyel@eng.cam.ac.uk
Shu-Chen Li worked as a researcher at the Max Planck Institute for Human Development in Berlin, Germany from 1995 to 2012. In 2006 she became the senior research scientist at the Center for Lifespan Psychology and the principal investigator of the Neuromodulation of Lifespan Cognition project. Prior to her employment by the Max Planck Institute she obtained her PhD from the University of Oklahoma, USA and postdoctoral training at McGill University in Montreal, Canada. Her current research utilizes an integrated array of conceptual tools and empirical paradigms, ranging from neurocomputational studies for theory development to genetically informed behavioral and brain imaging studies to investigate developmental and individual differences in brain-behavior relations across the lifespan. In September 2012, she became a full professor of psychology and is now the chair of a new unit of Lifespan Psychology and Neuroscience in the Department of Psychology at Dresden University of Technology (Technische Universität Dresden) in Dresden, Germany. Her new unit pursues three main research themes: (i) lifespan neurocognitive development of perception, memory, and adaptive control; (ii) interfaces between neuromodulatory, hormonal, and motivational regulations of behavior and cognitive development; (iii) neuromodulation of developmental plasticity induced by non-invasive brain stimulations and behavioral interventions.
Contact:
Max Planck Institute for Human Development
Center for Lifespan Psychology
Lentzeallee 94
D-14195 Berlin
Germany
E-mail: shuchen@mpib-berlin.mpg.de
Ulman Lindenberger is the director of the Center for Lifespan Psychology at the Max Planck Institute for Human Development in Berlin, Germany. His primary research interests are behavioral and neural plasticity across the lifespan, brainbehavior relations across the lifespan, multivariate developmental methodology, and formal models of behavioural change. He studied psychology and biology at Berkeley and Berlin, and received his doctorate in psychology from the Freie Universität Berlin in 1990. He holds honorary professorships at Freie Universität Berlin, Humboldt-Universität zu Berlin, and Saarland University, Saarbrücken, Germany. He is a member of the German National Academy of Sciences Leopoldina, and was awarded the Gottfried Wilhelm Leibniz Prize of the Deutsche Forschungsgemeinschaft in 2010.
Contact:
Max Planck Institute for Human Development
Center for Lifespan Psychology
Lentzeallee 94
D-14195 Berlin
Germany
E-mail: seklindenberger@mpib-berlin.mpg.de
Christoph Mathys studied physics at ETH Zurich (master's thesis with Daniel Wyler), then ventured into the IT industry for several years, where he worked for a mobile applications company that he partly owned. After the sale of this company he returned to academia, where he completed a master's degree in psychology (University of Zurich, with Lutz Jäncke) while doing experimental work with Gottfried Schlaug at Harvard. He then returned to ETH Zurich to work as a doctoral student with Klaas Enno Stephan. There, his focus has been on Bayesian hierarchical models of learning and decision-making.
Contact:
University of Zurich and ETH Zurich
Translational Neuromodeling Unit (TNU)
Wilfriedstrasse 6
8032 Zurich
Switzerland
E-mail: chmathys@ethz.ch
Anthony R. McIntosh serves as Vice-President of Research at Baycrest and Director of the Rotman Research Institute (RRI), and is a full professor of Psychology at the University of Toronto. Dr. McIntosh received his BSc and MSc in Psychology from the University of Calgary and his PhD in Psychology (Behavioural Neuroscience) from the University of Texas.
He is a world-renowned expert in the use of neuro-imaging methods (fMRI, PET, EEG and MEG) and computational modeling to understand how brain networks change with aging and how the brain recovers from damage or disease. He is the lead investigator in the international consortium, Brain NRG (brainnrg.org), whose primary focus is to build the world's first human Virtual Brain (thevirtualbrain.org). As of 2011, he has published over 150 peer-reviewed papers.
Contact:
Rotman Research Institute
Baycrest Centre
3560 Bathurst Street
Toronto, Ontario
M6A 2E1
Canada
E-mail: rmcintosh@rotman-baycrest.on.ca
Christian Meisel studied physics and medicine at the University of Freiburg. Following research in oncology at Stanford University for his MD thesis he turned to neuroscience and started a residency in neurology at the university clinic in Dresden. Besides his clinical work in the neurology department past research led him to positions at the Max Planck Institute for the Physics of Complex Systems and a short stay at the Max Planck Institute for Human Cognitive and Brain Sciences. His research interest revolves around the interface between physics and medicine with a particular interest in the application of concepts and quantitative approaches from the natural to the life sciences focusing on neurological and neuropsychiatric questions.
Contact:
University Hospital Carl Gustav Carus Dresden
Department of Neurology
Fetscherstr. 74
D-01307 Dresden
Germany
E-mail: christian@meisel.de
Rosalyn Moran is a Senior Research Associate at the Wellcome Trust Centre for Neuroimaging part of University College London’s Institute of Neurology. Her research employs both theoretical and empirical neuroscientific approaches to understand the principles of functional integration in the brain. In particular she is investigating how neuromodulators shape the dynamics of neuronal communication in neurodegenerative disease and aging.
Moran’s research aims to define and refine the network mechanisms underlying age-related changes in human cognition. To do so, she relates macroscopic measures from functional neuroimaging and electrophysiological investigations, including functional Magnetic Resonance Imaging (fMRI), electroencephalography (EEG), magnetoencephalography (MEG) and local field potentials), to their chemical substrates through models of cortical circuits. Her approach employs dynamic causal modeling (DCM), to infer physiological processes from empirical data. She applies this approach to human and animal data, examining the interaction of dopamine, acetylcholine, and serotonin with ongoing neural activity.
Contact:
University College London
Wellcome Trust Centre for Neuroimaging
12 Queen Square
London WC1N 3BG
United Kingdom
E-mail: r.moran@ucl.ac.uk
Timo von Oertzen is an interdisciplinary researcher in the field of Mathematics, Computer Science, and Psychology. He studied Computer Science and Psychology at Saarland University and completed his PhD in Computer Science in 2003. From 2006 to 2010, he was head of the Formal Methods project at the Max Planck Institute of Human Development before starting the Mathematical Psychology lab at the University of Virginia in 2011.
Dr. von Oertzen researches the information theoretical content of data sets and models. He started the theory of power equivalence that allows comparison of study designs in terms of the scientific information they may produce, in order to achieve as much outcome for as few resources as possible. This theory also improves maximum likelihood estimation processes. On the side of data analysis, Dr. von Oertzen uses data mining techniques to maximize statistical power to find group differences and allow predictions from data.
Contact:
University of Virginia
Department of Psychology
102 Gilmer Hall
Charlottesville VA 22904-4400
USA
E-mail: timovoe@gmx.de
Soyoung Park is interested in the neural mechanisms underlying reward-based decision making in humans. To investigate the neurobiological implementation of the cognitive processes essential for decision making, she combines computational modeling with brain imaging techniques (specifically functional magnetic resonance imaging). Soyoung studied psychology at the Berlin Institute of Technology (TU Berlin) and received her PhD in neuroscience at the Berlin School of Mind and Brain with Hauke R. Heekeren and Jörg Rieskamp as supervisors. Currently, she is working as a post-doctoral researcher in the Laboratory for Social and Neural Systems Research in Zurich. Her work consists of 1) cost-benefit payoff computation, especially how pain impacts our valuation of rewards; 2) adaptive coding of reward, that is, how our brain manages to cover the whole range of rewards at the same time to remain sensitive for small changes; and 3) neural learning and decision-making impairments underlying addiction, specifically alcohol dependence.
Contact:
University of Zurich
Department of Economics
Blümlisalpstrasse 10
CH-8006 Zurich
E-mail: soyoung.park@econ.uzh.ch
Naftali Raz completed his undergraduate studies at Hebrew University in Jerusalem in 1979. He continued his training in psychology and neuroscience at the University of Texas at Austin, where he received his PhD in 1985. He is currently a professor of Psychology and Director of the Life-Span Cognitive Neuroscience Program at the Institute of Gerontology, Wayne State University in Detroit, USA. Naftali’s research focuses on the neural correlates and modifiers of cognitive aging, with the emphasis on age-related changes in brain structure, their impact on cognitive performance, and their modification by vascular risk factors. In his study of differential aging of the brain structure, Naftali employs a variety of MRI approaches, including volumetry, diffusion tensor imaging, and susceptibility weighted imaging. He conducts a multi-wave longitudinal approach and is particularly interested in individual variability in the rate of change. In studying individual differences in brain aging and their influence on cognitive performance, Naftali focuses on examining the effects of vascular risk factors such as hypertension, glucose metabolism, and inflammatory biomarkers as well as genetic variations therein. Naftali enjoys productive collaborative relationships with his colleagues across the globe. Naftali Raz gratefully acknowledges the continuous support of his research by the US National Institutes of Health (National Institute on Aging) since 1993.
Contact:
Wayne State University
Institute of Gerontology
87 East Ferry Street
226 Knapp Building
Detroit, MI 48202
USA
E-mail: nraz@wayne.edu
Francesco Rigoli's professional background involves experiences in both clinical psychology and cognitive neuroscience. After a Master's in cognitive psychology at the University of Bologna (Italy), in 2008-2009 he worked as a clinical psychologist, adopting cognitive and behavioural methodologies for the treatment of different disorders (e.g., anxiety, depression, and eating disorders). In September 2009, Francesco was awarded a 3-year PhD Scholarship in Cognitive Sciences at the University of Siena (Italy). Since then, he has conducted research in cognitive neuroscience at the Institute of Cognitive Sciences and Technologies in Rome. In particular, he has studied motivation, emotion, and decision-making, integrating computational (mainly reinforcement learning and Bayesian statistics) and behavioural methodologies. In addition, during his PhD studies, Francesco has continued to develop a special interest in psychopathologies, specifically those involving dysfunctions in emotion, motivation, and decision-making (e.g., anxiety, depression, drug abuse, etc.). Since September 2011, he has been visiting the Cognitive and Brain Sciences Unit in Cambridge (UK), where he has continued to study motivation and emotion, integrating neuropsychological measures (fMRI and skin conductance) with computational modelling.
Contact:
University of Cambridge
MRC Cognition and Brain Sciences Unit
15 Chaucer Road
CB2 7EF Cambridge
United Kingdom
E-mail: francesco.rigoli@mrc-cbu.cam.ac.uk
Robb Rutledge is a Senior Research Associate at the Wellcome Trust Centre for Neuroimaging at University College London in the group of Ray Dolan, and is a member of the Initiative for Computational Psychiatry and Ageing Research (ICPAR). His research uses measurements of neural activity to study how our brains respond to rewards using techniques from neuroscience, psychology, economics, and computer science. His PhD research with Paul Glimcher at New York University investigated the role of dopamine in reinforcement learning by studying patients with Parkinson’s disease, using functional MRI in humans, and using cyclic voltammetry to measure dopamine levels in collaboration with Paul Phillips at the University of Washington.
Contact:
University College London
Wellcome Trust Centre for Neuroimaging
12 Queen Square
London WC1N 3BG
United Kingdom
E-mail: robb.rutledge@ucl.ac.uk
Daniel J. Schad: Understanding how humans process value at different goaldirected, habitual, and affective levels is one of the most exciting enterprises in current neuroscience and psychology to Daniel Schad. While studying psychology at the University of Potsdam in Germany, Daniel learned about an empirical approach to multiple value systems in research on implicit and explicit motives based on the TAT/PSE. Interested in a theoretical understanding, he spent a year at the University of Michigan (Ann Arbor, USA) with Oliver Schultheiss to prepare his diploma thesis. There, he tested key predictions from a theoretical model about implicit and explicit motivational systems concerning (a) the formats in which each system represents and processes information, (b) the conditions under which each system controls behavior, and (c) how information can be transferred between systems.
In Michigan, he also discovered developments in the computational modelling of model-based and model-free reward learning and became very excited about the possibility of investigating these questions computationally. For his PhD, Daniel set himself the goal of learning state-of-the-art techniques in experimental design, data analysis, and computational/mathematical and statistical modelling, and decided to study eye movement control during mindless reading in Potsdam (working with Ralf Engbert, Reinhold Kliegl, and Keith Rayner). Here, he introduced an advanced version of a stochastic non-linear dynamical systems model of saccade generation (SWIFT 3) and applied diverse statistical tools like generalized linear mixed effects models, Bayesian models, and distributional analyses to learn about different processing levels in mind wandering and eye movement control.
For his post-doctoral studies, Daniel plans on returning to research on value systems. He is very interested in studying and modelling how different systems represent value and how they compete and interact to control behavior. Particular interests concern the normative role of expected reward, abstract knowledge, inhibition, and conflict between controllers.
Contact:
University of Potsdam
Cognitive and Biological Psychology
Exzellenzbereich Cognitive Sciences
Karl-Liebknecht-Straße 24/25
14476 Potsdam
Germany
E-mail: schad@uni-potsdam.de
Alexander Schäfer is a PhD student in neuroscience funded by the Max Planck Institute for Human Cognitive and Brain Science in Leipzig, Germany. His research is centered around networks derived from resting state fMRI. He is interested in the spatio-temporal organization of these networks and the changes that occur due to aging or diseases. Alexander has a diploma in computer science from the Friedrich Schiller University Jena (2009).
Contact:
Max Planck Institute for Human Cognitive and Brain Sciences
Stephanstraße 1a
04103 Leipzig
Germany
E-mail: aschaefer@cbs.mpg.de
Klaas Enno Stephan is Director and Founder of the Translational Neuromodelling Unit (TNU) at the University of Zurich and ETH Zurich where he holds a Chair in Translational Neuromodelling. Additionally, he is a Principal Investigator and Co-Founder of the Laboratory for Social and Neural Systems Research (SNS) at the University of Zurich, and an Honorary Principal at the Wellcome Trust Centre for Neuroimaging, London. Following doctoral degrees in Medicine (Düsseldorf University, with Rolf Kötter and Karl Zilles) and Neuroinformatics (Newcastle University, with Malcolm Young), Klaas worked as a post-doc in computational neuroscience with Karl Friston at London. His track record includes the development of the connectivity database CoCoMac, numerous studies of brain connectivity, and development of various neuroinformatics tools, e.g. Objective Relational Transformation (ORT), nonlinear dynamic causal models, and Bayesian model selection methods. He has published more than 110 peer-reviewed papers that have been cited more than 5’000 times (h-index: 39). The Essential Science Indicators rank Klaas among the top 0.1% most cited neuroscientists worldwide.
Klaas works on mathematical models for inferring neuronal and computational processes from non-invasive measurements of brain activity and behaviour. These models aim to quantify mechanisms of (mal)adaptive cognition and brain disease in individual subjects and patients. The long-term goal is to use these models for a mechanistic re-definition of psychiatric and neurological diseases, leading to pathophysiologically interpretable diagnostic classifications and individual treatment predictions.
Contact:
Swiss Federal Institute of Technology (ETH)
Institute for Biomedical Engineering
Wilfriedstrasse 6
8032 Zurich
Switzerland
E-mail: stephan@biomed.ee.ethz.ch
Vincent Valton is a French doctoral student born in the city of Nantes (west coast of France) whose background is in software engineering & computer science (DUT from the Institut Universitaire de Technologie de Nantes & BSc Hons. from Heriot Watt University – Edinburgh), artificial intelligence (MSc) and computational neuroscience (MRes), both at the University of Edinburgh. Now in his 2nd year, he is being supervised by Peggy Series (theoretical research) and Stephen Lawrie (clinical research) at the Doctoral Training Centre (DTC) for Computational Neuroscience, and is a member of the Institute for Adaptive and Neural Computation in the School of Informatics at the University of Edinburgh (Scotland).
His research interests span between reinforcement learning & decision-making in psychiatric disorders, as well as computational models of psychoses in Schizophrenia and drug abuse. Vincent's PhD project, “Prediction-error in psychiatric disorders: From maladaptive decision-making to psychoses”, aims to understand the effects of imbalances in prediction-error signalling and of probabilistic inference in decision-making in mental disorders. Specifically, a Bayesian model of schizophrenia, which combines prediction-error and probabilistic inference to investigate the mechanisms leading to delusions and hallucinations, is being evaluated. In this framework, a faulty prediction-error signalling leads to learning an incorrect internal model of the world, resulting in delusions and maladaptive decision-making. Strong top-down expectations then distort perceptual inputs, leading to hallucinations.
Vincent is also interested in collecting new data to validate their models. He has been involved in behavioural studies looking at decision-making in rodents and is currently conducting visual psychophysical experiments to investigate statistical learning and hallucination formation in schizophrenic patients.
Contact:
University of Edinburgh
Informatics Forum
10 Crichton Street, Room 2.39
Edinburgh, EH8 9AB
United Kingdom
E-mail: vincent.valton@ed.ac.uk
Arno Villringer studied medicine at Freiburg University (1977-1984). He performed experimental work for his thesis on the regulation of protein synthesis by small RNAs in the Biochemistry Department of Freiburg University (summa cum laude). In 1985 he joined the NMR group at the Massachusetts General Hospital, Harvard Medical School where he worked on basic contrast mechanisms for magnetic resonance imaging and established susceptibility based contrast in animal studies. He trained in Neurology at University of Munich (1986-1992). From 1996 to 2003 he was consultant neurologist at the Charité University Hospital Berlin. From 2004 to 2007 he was head of the Department of Neurology at Benjamin Franklin Hospital, Charité. Since 2007 he has been Director at the Max Planck Institute for Human Cognitive and Brain Sciences and Director of the Clinic for Cognitive Neurology at University Hospital, Leipzig. Since 1999 he has been coordinator of the German Competence Net Stroke and since 2006 speaker of the Berlin School of Mind and Brain. His research focusses on stroke. Specifically, he is interested in identifying pathophysiological mechanisms in the brain (i) leading to arteriosclerosis and stroke (pathological brain plasticity in hypertension, obesity), and those occurring (ii) in acute (blood flow disturbance, spreading depression), and chronic stroke (mechanisms underlying brain plasticity). These research studies are performed in humans employing noninvasive techniques such as structural and functional MRI, PET, EEG, EEG/fMRI, fNIRS, TMS, and TDCS.
Contact:
Max Planck Institute for Human Cognitive and Brain Sciences
Stephanstraße 1a
04103 Leipzig
Germany
E-mail: villringer@cbs.mpg.de
Xiao-Jing Wang is Professor of Neuroscience, Physics and Psychology, and director of the Swartz Program in Theoretical Neurobiology at Yale. He obtained PhD in Theoretical Physics at the University of Brussels in 1987, when he switched to the then nascent field of Computational Neuroscience. He uses theory and biophysically realistic neural circuit modelling to study cortical dynamics and functions. His interests cover a broad range of topics, including neuronal adaptation at multiple timescales, diversity of inhibitory interneurons, and synchronous network oscillations. The main goal of research in his laboratory is to uncover circuit mechanisms of working memory and decision-making in the prefrontal cortex and other cortical areas, in close collaboration with experimentalists. Currently, his lab is pursuing large-scale neural circuit models of spiking neurons, to elucidate general principles and cellular basis of key cognitive processes, as well as their impairments associated with schizophrenia and other mental disorders.
Contact:
Yale University
School of Medicine
Department of Neurobiology and Kavli Institute of Neuroscience
PO Box 208001
New Haven, CT 06520-8001
USA
E-mail: xjwang@yale.edu
Gabriel Ziegler is a PhD student at the University of Zurich and the Structural Brain Mapping Group (with head Christian Gaser) at the Department of Psychiatry Jena. He received his Diploma Degree in Psychology from the University of Jena. His Diploma thesis explored functional integration in a visual search fMRI task. In addition he received a B.S. in mathematics with a thesis investigating the invariance of phase information in independent component analysis. From 2007 to 2008 he was a research assistant in the Autonomic Function Group at the Department of Psychiatry in Jena working on resting state fMRI coupling to autonomic correlates.
Since 2008/2009 Gabriel has focused on the development and application of models of aging brain structure using computational morphometry. His dissertation on ''Lifespan brain structural trajectories and individual differences of growth and decline'' explores brain structural differences and changes in early, middle and later life. Currently, he is involved in generative decline modelling using longitudinal MRI data, estimation of individual decline parameters, and quantifying its normative variance. In 2012 he received the Human Brain Mapping abstract award and was an invited speaker at the annual OHBM meeting in Beijing. His research interests are centered around multivariate analysis, partial least squares correlation, Bayesian estimation and inference as well as Gaussian process models.
Contact:
Jena University Hospital
Department of Psychiatry
Structural Brain Mapping Group
Jahnstraße 3
07743 Jena
Germany
E-mail: gabriel.ziegler@uni-jena.de
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