Computational Neuroscience szeminarium: juli 9, hetfon, 14 orakor

Julius 9-en hetfon 14 orakor a KFKI RMKI Tancstermeben (III-as epulet) szimnariumi eloadas lesz: ******************************************************** Viktor Jirsa Center for Complex Systems & Brain Sciences Florida Atlantic University http://www.ccs.fau.edu/%7Ejirsa/ ************************************************************************** Neural field dynamics as a window for understanding the EEG and MEG during motor coordination ************************************************************************* Minden erdelkodot szerettel varunk. (erdi peter) ++++++++++++++++++++++++++++++++++++++++++++++++++ Az eloadas kivonata: Dynamic systems defined on the scale of neural ensembles are well-suited to model the spatiotemporal dynamics of neural fields on the cortical sheet. These represent the current flow perpendicular to the cortex and generate the electric potentials on the surface of the skull and the magnetic fields outside the skull measured by electroencephalography (EEG) and magnetoencephalography (MEG), respectively. We wish to connect spatiotemporal neural field dynamics (Jirsa-Haken, Phys.Rev.Let. 1996) to motor behavior and simultaneous brain activity and take the following approach: 1. We develop a methodological framework, which defines the activity of the neural field on a sphere in three dimensions. Using Magnetic Resonance Imaging (MRI) we map the neural field dynamics from the sphere onto the folded cortical surface and calculate the three-dimensional forward solutions of EEG and MEG. Non-trivial mappings between the multiple levels of observation are obtained which would not be predicted by inverse solution techniques. 2. Recent results mapping large-scale brain dynamics (EEG, MEG) onto behavioral motor patterns (Fuchs, Jirsa, Kelso, Neuroimage 2000) provide an entry point to the causal brain-behavior relation which we use to define a motor and sensorimotor loop between neural fields and behavioral data. For the case of bimanual coordination, we establish the neural field dynamics including short-and long range connections of neural ensembles. We make predictions of global features of brain dynamics during coordination tasks and test these against experimental MEG results. A key feature of our approach is that phenomenological laws at the behavioral level can be connected to a field theoretical description of cortical dynamics (see also Jirsa, Fuchs, Kelso, Neural Comp. 1998).