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Multi-modal imaging: simultaneous EEG-fMRI

Multi-modal imaging: simultaneous EEG-fMRI. Silvina G Horovitz, PhD Human Motor Control Section Medical Neurology Branch National Institute of Neurological Disorders and Stroke National Institutes of Health. S imultaneous EEG-fMRI. EEG in few minutes Why ? How? When? Examples.

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Multi-modal imaging: simultaneous EEG-fMRI

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  1. Multi-modal imaging:simultaneousEEG-fMRI Silvina G Horovitz, PhD Human Motor Control Section Medical Neurology Branch National Institute of Neurological Disorders and Stroke National Institutes of Health

  2. Simultaneous EEG-fMRI • EEG in few minutes • Why? • How? • When? • Examples

  3. Basic fMRI experiment

  4. EEG in few minutes

  5. EEG (electroencephalography): Synchronous activity of population of neuronsprimarily reflects postsynaptic potentials Eyes closed 1 s

  6. EEG amplifier (Instrumentation) • Referential • (Si vs. Ref; Sk vs. Ref) • Bipolar • (Si vs.. Sk ) • Reference: • Single • Linked • Average reference reference unit buffer output high pass filter integrator signal high pass filter ground low pass filter

  7. International 10-20 System of Electrode Placement F - Frontal lobe T - Temporal lobe C - Central lobe P - Parietal lobe O - Occipital lobe "Z" refers to an electrode placed on the mid-line. Odd: left Even: right montage

  8. Data processing • Time domain • Event Related Potentials (ERPs) • pre-processing: • detrend - filtering • epoch • baseline correction • ocular artifact reduction • (common grounded, artifact rejection) • time-locked averaging

  9. Data processing • Frequency domain • Power at different bands • Power spectra density (FFT) • Cross-spectra (correlation among different electrodes) • Coherence (measure of stability of the phase shift between electrodes) • Event related desynchronization

  10. Human EEG Spontaneous Evoked Depth ECoG Transient Steady State Scalp Cognitive Science sensory pathways, stimulus encoding, motor process, spatial task, verbal task, mathematics, short term memory, memory encoding, selective attention, task context, general intelligence, dynamic brain theory Clinical Applications epilepsy, head trauma, drug overdose, brain infection, sleep disorder, coma, stroke, Alzheimer’s disease, brain tumor, multiple sclerosis, surgical monitoring PL Nunez, EEG, Encyclopedia of the Brain, 2003

  11. Why do we want to measure EEG and fMRI simultaneously?

  12. Surface EEG Deep EEG Extra cellular recording Intra cellular recording

  13. Neuroimaging BRAIN ACTIVITY f(x,t) Metabolic/ vascular responses g[f(x,t)] fMRI k{g[f(x,t)]} • Poor time resolution (s) Good spatial resolution (mm) electrical EEG, MEG m[f(x,t)] Good time resolution (ms) Poor spatial resolution

  14. P2 P1 N170 EEG fMRI EEG is the gold standard for sleep classification and studies, epilepsy, some cognitive tasks, etc

  15. Nr. of publications YEAR Data PubMed search June 20, 2014

  16. HOW?

  17. to projector Stimulus PC fMRIstudy Scanner trigger EEGstudy Stimulus PC Acquisition PC EEG amplifier

  18. Amplifier EEG-fMRIstudy Optic fiber Acquisition PC Adapter to projector Synchronization Scanner clock Stimulus PC Scanner trigger

  19. Technical Issues Electromagnetism 101 • Maxwell's Laws. • A changing magnetic field produces an electric field • A changing electric field or current produces a magnetic field. BIG PROBLEM Luckily, the magnetic field change Form the EEG does not affect the image quality!

  20. THE not so good NEWS Remember Maxwell's Law? • MRI is noisy • Electrical noise  MRI and EEG were not meant for each other …

  21. Simultaneous EEG-fMRI - Technical issues Example from BOLD & Perfusion MRI sequence optimized for EEG-fMRI acquisition 5 slices (Fukunaga et al, JCBFM 2008) • Sources of artifacts: • gradient artifact • physiological noise: ballistocardiogram

  22. THE GOOD NEWS More on safety later • MRI compatible EEG equipment • Safe for the scanner • Safe for the subject

  23. DATA acquisition • Sample EEG at 5 kHz (or max) • Slice TR at a frequency that is not of interest (and a round number) • Low Pass Filter at 250Hz • DC acquisition • Volume (or slice) marker • Resolution: 0.5mV • Clock synchronization • Keep electrodes’ impedance low • Have a good cardiac signal

  24. Artifact removal (Matching filter) • Create a template of the artifact • Subtract average artifact • If proper timing • and no movement works great! Raw EEG during EPI acquisition Dr Jen Evans

  25. Raw Gradientartifact corrected Dr Jen Evans

  26. ballistocardiogram Matching filter (BV Analyzer) (Allen et al, 2000): Detect R Create a template Subtract (allows for amplitude adjustment) Single Value Decomposition (Neuroscan) Run classification Remove components Reconstruct time series Optimal base set (EEGLAB Niazy, 2005) PCA to create bases Fitting (adaptive algorithm) Subtraction Combinations i.e  Liu, 2012 use ICA, SVD & mutual information (based on Peng, IEEE 2005) software download: http://amri.ninds.nih.gov/cgi-bin/software

  27. Gradient artifactcorrected Cardioballistogramcorrected Dr Jen Evans

  28. Gradient artifactcorrected Cardioballistogramcorrected

  29. SAFETY considerations Simultaneous Electroencephalography-Functional MRI at 3 T: An Analysis of Safety Risks Imposed by Performing Anatomical Reference Scans With the EEG Equipment in Place Ulrike Nöth, Laufs, Stoermer, and Deichmann JMRI 2012 SAR: Specific Absorption Rate (or the energy deposited in the body by the radio frequency transmission)

  30. SAFETY considerations • Sequences • EPIs (in most cases ok to run an MPRAGE for localization) • be aware of high res short TR EPIs (pay attention to SAR) • Set up • Cables straight and in the center. • Avoid loops • Equipment as far back from iso-center as possible • (far front for EMG) • All scanners are not equal; gradients and coils affect electrodes’ temperature • Be aware different body shapes and weights load coil differently

  31. Interim Summary • EEG measurements have: • Good temporal resolution • Poor spatial resolution (when measure non invasively) • Electrical and hemodynamic responses are related • Simultaneous EEG-fMRI requires special equipment • SAFETY PROCEDURES ARE KEY • Dimensionality reduction is needed for data integration

  32. WHEN?

  33. When is it important to measure simultaneously? • state dependent analysis • Alertness • STATE VS TRAIT • Better understanding of BOLD signal • Physiological markers defined by EEG • Seizures • Sleep stages

  34. Type of studies • Correlations of EEG and fMRI • In time domain • In frequency domain • Dimensionality reduction • Multivariate methods • ICA • Informing one with the other • Sorting data and perform analysis in one modality

  35. EXAMPLES

  36. Correlations in the frequency domain Goldman et al. 2002 Simultaneous EEG and fMRI of the alpha rhythm.

  37. How did we include EEG information in the MRI analysis? • Direct integration of EEG and fMRI data • Inform the fMRI analysis • Divide fMRI based on EEG parameters • Use EEG “events” as regressors for fMRI

  38. Correlation between Amplitude of BOLD fluctuations and a parameter derived from the EEG DAYTIME 1 hour PARADIGM Horovitz et al HBM, 2008

  39. Changes in the level of consciousness Use EEG to sort fMRI data

  40. Do changes in connectivity over time have a physiological origin?

  41. EEG-vigilance and BOLD effect during simultaneous EEG/fMRI measurement S. Olbrich et al. / NeuroImage 45 (2009) 319–

  42. Comparison of denoised fMRI with EEG a Dr Jen Evans

  43. Single-Trial Analysis of Oddball Event-RelatedPotentials in Simultaneous EEG-fMRI Benar et al. Human Brain Mapping 28:602–613 (2007)

  44. Single-Trial Analysis of Oddball Event-RelatedPotentials in Simultaneous EEG-fMRI Benar et al. Human Brain Mapping 28:602–613 (2007)

  45. Assessing the spatiotemporal evolution of neuronal activation with single-trial event-related potentials and functional MRI Tom EichelePNAS 2005 vol. 102 no. 49

  46. Widespread epileptic networks in focalepilepsies—EEG-fMRI studyFiras Fahoum, Renaud Lopes, Francesca Pittau, Franc¸ois Dubeau, and Jean Gotman Epilepsia, **(*):1–10, 2012

  47. Moving towards intracranial recordings/fMRI Simultaneous intracranial EEG–fMRI in humans: Protocol considerations and data quality D.W. Carmichael (2012)

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