Chairs
Professor Karl Friston FMedSci FRS, University College London, UK
Professor Karl Friston FMedSci FRS, University College London, UK
Karl Friston is a theoretical neuroscientist and authority on brain imaging. He invented statistical parametric mapping (SPM), voxel-based morphometry (VBM) and dynamic causal modelling (DCM). These contributions were motivated by schizophrenia research and theoretical studies of value-learning – formulated as the dysconnection hypothesis of schizophrenia. Mathematical contributions include variational Laplacian procedures and generalized filtering for hierarchical Bayesian model inversion. 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 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 of Fellow of the Society of Biology in 2012 and received the Weldon Memorial prize and Medal in 2013 for contributions to mathematical biology.
13:00-13:30
Mapping causal functional contributions in the brain from the game-theoretical analysis of stroke lesions
Professor Claus Hilgetag, University of Hamburg, Germany
Abstract
Strokes affect multiple brain regions and produce multiple functional deficits, acting as a natural experiment in brain perturbation. However, the interpretation of such perturbation data and the inference of regional functional contributions to brain function is made difficult by the multivariate interactions between different brain regions. To address this problem, we used a multivariate, game-theoretical approach to objectively quantify the causal functional contributions of brain regions, and applied it to animal model data, ground-truth simulations, as well as clinical data of stroke lesions and corresponding functional deficits. The approach reliably inferred regional contributions to brain function and revealed a wide quantitative range of contributions of multiple regions to multiple functions. It also indicated functional synergies and redundancies among brain regions and helped to identify potential targets for clinical rehabilitation
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Professor Claus Hilgetag, University of Hamburg, Germany
Professor Claus Hilgetag, University of Hamburg, Germany
Hilgetag studied Biophysics in Berlin and Neuroscience in Edinburgh, Oxford, Newcastle and Boston. He is interested in fundamental principles of the organization of brain architecture, connectivity, and dynamics. In particular, his group investigates structural factors that are predictive of anatomical connections in the brain, and explores relations between topological features of neural connectivity, such as modules and hubs, and patterns of brain activity. He also develops methods for inferring brain functions from the impact of brain lesions.
13:30-14:00
Using The Virtual Brain as an 'informatics microscope' to uncover biophysical parameters of stroke recovery
Dr Ana Solodkin, UC Irvine School of Medicine, USA
Abstract
An exciting advance in the field of neuroimaging is the acquisition and processing of very large data sets (so called “big data”), permitting large-scale inferences that foster a greater understanding of brain function in health and disease. Yet what we are clearly lacking are quantitative integrative tools to translate this understanding to the individual level to lay the basis for personalized medicine.
This challenge will be addressed through a new neuroInformatics modelling platform that has the capacity to track brain network function at different levels of inquiry, from microscopic to macroscopic and from the localized to the distributed. The multi-scale approach, The Virtual Brain (TVB), can effectively model individualized brain activity, provides unique biological interpretable data in stroke.
The talk will show how our results establish the basis for a deliberate integration of computational biology and neuroscience into clinical approaches for elucidating cellular mechanisms of disease including on the individual level via personalized therapeutic interventions.
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Dr Ana Solodkin, UC Irvine School of Medicine, USA
Dr Ana Solodkin, UC Irvine School of Medicine, USA
Dr. Solodkin’s research interest has been centered from the beginning, around brain plasticity. During her Ph.D. at the "Center for Research and Advanced Studies of the National Polytechnic Institute" (Mexico) and NIH (Mentored by Dr. P Rudomin and Dr. MA Ruda) she focused on long-term plasticity in the developing spinal cord. Later on at the University of Iowa she joined the Cognitive Neurology group under the direction of Dr. A. Damasio receiving direct training with Dr. GW van Hoesen in human neuroanatomy. Her active and long-term research has targeted the relationship between basic neurobiology and cognitive neurology where using network analyses, she has focused on disease biomarkers on AD, stroke and spinocerebellar ataxias. Dr. Solodkin’s aim with this work has been to discover anatomical and physiological substrates of disease that have a reasonable likelihood of leading to therapeutic interventions. In this context, Dr. Solodkin joined Dr. McIntosh in 2006 at the early stages of the development of The Virtual Brain. Currently Dr. Solodkin utilizes The Virtual Brain platform to determine changes in brain dynamics as they relate to stroke. These efforts, in collaboration with Dr. McIntosh and Dr. Jirsa are providing a first glimpse on basic neural mechanisms associated with brain dynamics specifically related to long-term recovery.
14:45-15:15
Stroke dys-connectome: behaviour, structure and function
Dr Maurizio Corbetta, Washington University, USA
Abstract
Since the early days of neuroscience the relative merit of structural vs. functional network accounts in explaining neurological deficits has been intensely debated. Using a large stroke cohort and a machine learning approach, we show that visual memory, and verbal memory deficits are better predicted by functional connectivity than by lesion location, while visual and motor deficits are better predicted by lesion location than functional connectivity. In addition, we show that disruption to a subset of cortical areas predicts general cognitive deficit (spanning multiple behavior domains). In a separate set of computational studies we show that these deficits affects the integration/segregation of brain regions. These results shed light on the complementary value of structural vs. functional accounts of stroke, and provide a physiological mechanism for general multi-domain deficits seen after stroke.
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Dr Maurizio Corbetta, Washington University, USA
Dr Maurizio Corbetta, Washington University, USA
Dr. Maurizio Corbetta is the Norman J. Stupp Professor of Neurology, and Professor of Radiology, Anatomy and Neurobiology, and Bioengineering at Washington University School of Medicine. He is the Chief of the Division of Neuro-Rehabilitation, and Director of Neurological Rehabilitation at the Rehabilitation Institute of St. Louis. As of 2016 Dr. Corbetta will be the Chair of Neurology in the Department of Neuroscience at the University of Padua, Italy. Dr. Corbetta has pioneered experiments on the neural mechanisms of human attention with Positron Emission Tomography (PET). He has discovered two brain networks dedicated to attention control, the dorsal and ventral attention networks, and developed, in collaboration with Dr. Gordon Shulman, a brain model of attention that has been cited in the literature more than 5,000 times. His clinical work has focused on the physiological correlates of focal injury. He has developed a pathogenetic model of the syndrome of hemispatial neglect. He is currently developing novel methods for studying the functional organization of the brain using functional connectivity MRI, magneto-encephalography (MEG), and electro-corticography (EcoG). He is also working on the effects of focal injuries on the network organization of brain systems with an eye to neuromodulation.
15:15-15:45
Predicting outcome and recovery after stroke
Professor Cathy Price, University College London, UK
Abstract
Predicting outcome and recovery after stroke is notoriously difficult because the consequences of seemingly similar brain damage are inconsistent across patients. Clearly factors other than lesion site influence the level of recovery. To investigate the main causes of variability, machine learning on a wide variety of data acquired from large cohorts of stroke survivors has been used. This indicates the importance of lesion site, lesion size and years post stroke as the most informative variables for recovery. Although machine learning does not indicate how the predictions can be improved, it does place constraints on the variables that need to be controlled and considered in models of recovery. Hence, this talk will show how predicting outcome after brain damage can be optimised by a combination of model-based and data-led approaches.
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Professor Cathy Price, University College London, UK
Professor Cathy Price, University College London, UK
Cathy Price is an expert in the use of structural and functional brain imaging for understanding cognitive processing in the neurologically healthy and damaged brain. Her basic training was in Physiology and Psychology and she has a PhD in cognitive neuropsychology. Since 1997, she has been funded by the Wellcome Trust to build a functional anatomical model of auditory and visual word processing that will predict language outcome after brain damage. In parallel, she is developing data-led approaches that provide probabilistic lesion-symptom mapping associations. Her goal is to develop a clinical tool that uses lesion site to predict the most likely outcome and recovery of language abilities after stroke.
16:00-17:00
Panel discussion/Overview (future directions)