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Computational brain models of EEG / MEG and fMRI signals in health and disease

Explore how EEG, MEG, and fMRI signals are key in understanding brain health, with multimodal imaging and mean field theories guiding clinical applications. BRAINSPECS project focuses on personalized brain modeling for health conditions.

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Computational brain models of EEG / MEG and fMRI signals in health and disease

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  1. Computational brain models of EEG / MEG and fMRI signals in health and disease #slides Multimodal Mean fields BRAINSPECS Borromean Rings Conclusions • 3 • 6 • 2 • 1 • 1

  2. Multimodal – the six blind men and the elephant EEG MEG fMRI SPECT PET anatomy Pics - EEG: Brain Sci. Institute Swinburne; MEG: Dept. of Psychology NYU; fMRI: Dept. Cog. Neurology, MPI Leipzig; SPECT: C. Studholme UCSF; PET: N.D. Volkov et al.; Anatomy: NTVH MRI Lab; Poem: Wordinfo. 1

  3. Multimodal – why EEG / MEG and fMRI first? • EEG/MEG and fMRI are complementary modalities: • EEG and fMRI can be recorded simultaneously • EEG and MEG can be recorded simultaneously • MEG and fMRI are however technologically incompatible 2

  4. Multimodal – correlations are not enough • Activity regions for different modalities are not identical • Correlation picks out regions not prominent in single modalities • Correlated activity regions are much more localized M. Schulz, W. Chau, S.J. Graham, A.R. McIntosh, B. Ross, R. Ishii, and C. Pantev, “An Integrative MEG-fMRI study of the primary somatosensory cortex using cross-modal correspondence analysis”, NeuroImage 22 (2004) 120-133. 3

  5. Mean fields – sources for non-invasive imaging • “in phase” neurons contribute,“out of phase” • 105 neurons, 1% “in phase”: 32x stronger signal – seen only. • Imagingbehaviour neuronal mass action averaging mean field theories 4

  6. Mean fields – our model flattened simplified averaged spatially 5

  7. 0 disk frames 1 2 3 4 5 6 7 8 9 noise 10 Mean fields – whole cortex computing • 145 Dell Power Edge 1950 blades: 2 x quad-core 2.33 GHz Clovertown, 16 GB RAM • 145 TB blade hard drives, 100 TB Raid 5 disks, 77 TB robot tape • Cisco 6509 gigabit ethernet about to be upgraded to 20Gb/s infiniband • 4 -128 nodes run in parallel using MPI Fortran Green Machine Linux: CentOS 5, queue: PBS, manager: Torque, scheduler: Moab, compilers: Intel 9.1. 6

  8. MAC frequency [Hz] 0 6.0 12.0 18.0 24.0 0 0.13 0.27 0.40 wavelength-1 [cm-1] Mean fields – works well for EEG, e.g., anesthesia EEG ~ mean excitatory soma membrane potential • PSP response under Isoflurane : Banks & Pearce, MacIver et al. 7

  9. Mean fields – how to get fMRI BOLD contrast • Assume that neurovascular coupling is due to the uptake of intracellular glutamate from excitatory synapses (plus sodium) into astrocytes, resulting eventually in the glycolysis of ATP. • Hence the root cause of the Blood Oxygen Level-Dependent signal is proportional to excitatory synaptic activity. • Excitatory pulses: 8

  10. Mean fields – how to implement connectivity? • Isotropic, homogeneous, exp. connectivity: • But there’s also specific one: # synapses Felleman & Van Essen 9

  11. BRAINSPECS – the proposal • BRain Activity Imaging and Network Simulations for the Prediction and Evaluation of Clinical Syndromes - a personalizable brain model of EEG/MEG and fMRI signals in health and disease (Integrating Project for FP7-ICT-2007-2) • 40 principal researchers, budget € 9.5 million, 5 years runtime 10

  12. WP11 Dissemination WP1 Forward and inverse modeling 10 scientific Working Packages experimental main field parameters WP5 Lesions and dementia projection software connectivity constraints WP3 Model fitting WP2 Connectivity clinics functional connectivity WP6 Drug effects public relations main field programs data access connectivity database experiment WP7 Epilepsy computational mean field parameters WP8 Advanced modeling tools WP9 Data management and ontology data interface theory clinical data computing network programs data integration visualisation interface WP4 Local and detailed models WP10 Data acquisition and visualization WP12 Project management BRAINSPECS – working packages 11

  13. clinics I / O GUI I / O P P P R R internetportal computeserver R hardware software hardware storage crunch P computing R P storage database crunch code R technologycenter theory experiment R P clinics computing experi-ment theory 12

  14. Conclusions – assume it’s Loxodonta africana PET fMRI SPECT mean field theory MEG EEG anatomy 13

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