University of Minnesota. Kâmil Uğurbil

Transcription

1 University of Minnesota Kâmil Uğurbil

2 MGH CMRR, U Minn Title Kwong et al 1992 PNAS Ogawa et al PNAS 1992: Figure 2 images superimposed

3 Submillimeter scale neuronal ensembles WHOLE BRAIN Orientation Domains in the Primary Visual Cortex Monkey Cortex Optical Imaging LAYERS ~4 mm (Bonhoeffer & Grinvald, 1991; 1993)

4 Primary visual cortex has known neural networks Output Cortico-cortical feedback Local horizontal connections ~ 3 mm Input Feedback Cortico-Thalamic

5 MR detected Mapping Signals and Physiologic Changes induced by Neuronal activity ΔS/S 4 SE fmri, TE set to tissue T 2 total fmri signal (micro-vasculature) total fmri signal (macro-vasculature) ΔCBV=0 total fmri signal [%] d) ΔCBV 16% field strength (T) K. Uludağ, B. Müller-Bierl, K. Uğurbil Neuroimage (2009) 48(1): p

6 9.4 Tesla/31 cm bore ~ Tesla/90 cm bore ~1999 Understanding functional mapping signals Developing Instrumentation with previously unavailable measurement capabilities (Particularly High Magnetic Fields) Improvements in Methods of Image acquisition and Reconstruction.

7 Combined imaging & histological study of cortical laminar specificity of fmri signals GRE (TE= 20 ms) SE BOLD (9.4 Tesla, 0.15 x 0.15 x 2 mm SE (TE= 40 ms) Harel, N., J. Lin, S. Moeller, K. Ugurbil and E. Yacoub (2006) Neuroimage 29(3):

8 FIRST fmri at 7 TESLA fmri 4 vs. 7 Tesla, as a function of echo time TE (ms) 4 TESLA TESLA Yacoub E, et al. Magn Reson Med 2001;45(4):

9 Orientation Domains in the Primary Visual Cortex Monkey Optical Imaging Human fmri (SE, 7 Tesla) ~4 mm ~4 mm Yacoub, Harel, Uğurbil PNAS 2008

10 Layer Specific fmri of Object Recognition P stim M stim Visual responses to parvocellular-targeted stimuli are maximally differentiated from magnocellular-targeted stimuli in superficial layers. Olman, C. A., et al. (2012). "Layer-specific fmri reflects different neuronal computations at different depths in human V1." PLoS One 7(3): e32536.

11 .2 ($%&%!,($ º%&%180º Organization of Axis of Motion Selective Features in Human Area MT +#$%&%))#$ '($%&%)*($!"#$%&%!"#$ 45º%&%225º 90º%&%270º 135º%&%135º -./01%" -./01%) -./01%! Zimmermann, J., R. Goebel, F. De Martino, P.F. van de Moortele, D. Feinberg, G. Adriany, D. Chaimow, A. Shmuel, K. Ugurbil, and E. Yacoub: PLoS ONE, (12): p. e (CMRR and U Maastricht)

12 Cortical Depth dependence of Tuning Curves in Human MT for Axis of Motion De Martino et al 2013 PlosOne, 8 (3) e60514 (CMRR & UMaastricht) 12

13 Tonotopic Mapping in Human Primary Auditory Cortex 7 T GE fmri 1.2x1.5x2.4 mm 3 Formisano, et al NEURON 40, 859 (2003) CMRR/U Maastricht

14 Frequency maps (tonotopy) Formisano et al. (Neuron, 2003) De Mar8no et al. (Nature Communica8ons, 2013)

15 Frequency maps (tonotopy) Formisano et al. (Neuron, 2003) Auditory Cortex Temporal Lobe Auditory Radiations Medial Geniculate Body Reticular Formation Superior Colliculus Inferior Colliculus Midbrain De Mar8no et al. (Nature Communica8ons, 2013)

16 Recent work on auditory cortex slides deleted 16

17 Mapping low level acoustical properties with natural sounds 7 Tesla Single Subjects (CMRR & U Maastricht) Moerel et al. J Neurosci 2013 ; 33(29): Santoro R, et al. PLoS Comput Biol 2014;10(1):e NATURAL SOUNDS > 2.5 khz MODEL NEURONAL ACTIVATION < 1 khz

18 Inferior Colliculus: Spectral Selectivity F. De Martino, E. Yacoub, E. Formisano et al. (CMRR & U Maastricht) Nature Commun, : p Bandwidth Tonotopy Natural Sounds

19 Combining computational modeling and functional neuroimaging PREDICTION

20 Origin Reconstructed Frequency (Hz) Frequency (Hz) bird Time (ms) Time (ms) Frequency (Hz) Frequency (Hz) door Time (ms) Time (ms) Moerel et al. J Neurosci 2013 ; 33(29): Santoro R, et al. PLoS Comput Biol 2014;10(1):e

21 Santoro R, Moerel M, De Martino F, Goebel R, Ugurbil K, Yacoub E, Formisano E. PLoS Comput Biol 2014;10(1):e

22 PSF slide deleted 22

23 Tonotopic Mapping in Human Primary Auditory Cortex 7 T GE fmri 1.2x1.5x2.4 mm 3 Formisano, et al NEURON 40, 859 (2003)

24 7 TESLA SINGLE SHOT GRE-EPI 0.75 mm isotropic PE Acceleration 4, pf=6/8 es= x 256 TE=20msec, 128slices TR=6 s Head gradients TR=9 s Body Gradients Single image

25 Exploiting 7T SNR & CNR Advantage for Higher Spatial Resolution...! Higher Resolution,! more slices needed to cover the whole brain,! longer TR 25

26 RESOLUTION 1/(Voxel Dimension) Multiband, Simultaneous Multi- Slice Temporal Sampling Rate (1/TR) 26

27 Conventional Multi-slice Imaging Whole Volume TR = N slice x Time per slice 27

28 Slice Accelerated, Simultaneous Multi Slice, Multiband Imaging Larkman et al JMRI 2001 (leg) Moeller, Yacoub, Auerbach, Ugurbil ISMRM 2008; # 236 Moeller et al. Magn Reson Med, 2010; 63(5): p Setsompop et al. Magn Reson Med, 2012; 67, Excite multiple slices simultaneously " Use Parallel Imaging and Multichannel receive coil array to unalias simultaneously acquired images

29 Multiband EPI at 7T 32 Channel COIL: MB=4, PI PE (ipat)=3, FOV PE Shift= ¼; 1 mm isotropic Moeller, Yacoub, Auerbach, Ugurbil ISMRM 2008; # 236 Moeller et al. Magn Reson Med, 2010; 63(5): p

30 PHASE I: DEVELOPMENT and OPTIMIZATION of INSTRUMENTATION, IMAGE ACQUISITION TECHNIQUES, and DATA ANALYSIS TOOLS PHASE II: Collection of data to generate a DATA BASE using twins and non-twin siblings for 1200 subjects at 3T 200 subjects at 7T

31 2 mm isotropic Multiband 8 TR= 0.7 s TE=33 ms 4 times 15 min acquisitions

32 RESTING STATE NETWORKS (RSNs): IMPROVED STATISTICAL SIGINIFICANCE with SHORT TR MB1 Standard EPI MB1 Multiband Accelerated MB4 MB8 MB8 2 mm isotropic Primary Visual Sensory-Motor Whole Brain TR=5.8 s Primary Visual Sensory-Motor Whole Brain TR=0.7 s S. Smith et al. For the WU-Minn-HCP; from FIMRIB (OXFORD) Multiband Motion pilo

33 Resting-State Networks from 3 Tesla HCP data (High Dimensional (200 Component) ICA) Hierarchical clustering using correlation matrix: Full correlation Partial correlation Many RSNs are spatially noncontiguous Smith, S. M., Beckmann, C. F., Anderson, J., Auerbach, E. J., Beckmann, et al. for the WU-Min HCP, 2013, Neuroimage 80:

34 Resting State ICA component 18 (HCP Q1, n = 68) dorsal ventral Task-fMRI (LEFT hand movement) (HCP Q1, unrelated 20) Van Essen, D. C., S. M. Smith, D. M. Barch, T. E. Behrens, E. Yacoub, K. Ugurbil and WU-Minn Consortium (2013). Neuroimage 80:

35 Resting State ICA component 13 (HCP Q1, n = 68) dorsal ventral Task-fMRI (RIGHT hand movement) (HCP Q1, unrelated 20) Van Essen, D. C., S. M. Smith, D. M. Barch, T. E. Behrens, E. Yacoub, K. Ugurbil and WU-Minn Consortium (2013). Neuroimage 80:

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37 Better definition of the Resting State Networks (RSNs) due to: Higher spatial fidelity between r-fmri signals and underlying neuronal activity Increased Signal-to-Noise and Contrast-to-Noise Ratios (SNR and CNR, respectively) Higher spatial resolution Detection of larger number of RSNs 37

38 7T HCP Resting State slides of unpublished data deleted 38

39 DIFFUSION WEIGHTED IMAGING TE Excite Refocus EPI Echo Train Spin Echo Diffusion Weighting ( b ) = function of Max. Gradient Amplitude S exp(-te/t2) NEW GRADIENT SET 100 mt/m maximum gradient amplitude

40 DIFFUSION WEIGHTED IMAGING TE Excite Refocus EPI Echo Train Spin Echo TE 180 Pulse EPI Echo Train G max = 100 mt/m WashU-UMinn-Oxford Consortium

41 WashU-UMinn-Oxford CONSORTIUM 100 mt/m CONNECTOME 3T 1.25 mm iso. Res. 40 mt/m 3T 2 mm iso. Res. ~¼ voxel volume b = 0 b=1000 b=2000 b=3000

42 PROBABILISTIC TRACTOGRAPHY: medial to lateral to: cortico-thalamic, corticobulbar, cortico-spinal and cortico-striatal projections. Images are shown in radiological view. Sotiropoulos, S. N., S. Jbabdi, J. Xu, J. L. Andersson, S. Moeller, E. J. Auerbach, et al for the WU-Minn HCP Consortium, 2013, Neuroimage 80:

43 Advantage: Higher Intrinsic SNR Disadvantage: Shorter T 2 (SNR is lost faster relative to 3T during diffusion encoding) Available Maximal Gradient Amplitude (70 mt/m vs. 100 mt/m) STAY at low b values but increase Spatial Resolution 2 shells b=1 & 2 K at 7T vs. 3 shells, b=1,2, and 3K at 3T 1 mm vs mm iso. (2x smaller voxel volume) 43

44 7T HCP diffusion imaging slides of unpublished data deleted 44

45 HCP 3T HCP 7T Areas with B1 inhomogeneity problem at 7T Rubix_3T+ 7T

46 10.5T 10.5T/88cm; 110 Tons Stored Energy 280 MJoules Conductor length 860 miles (1384 km); over 1.5 million turns

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49 PULSE SEQUENCE, IMAGE RECONSTRUCTION and EVALUATION Steen Moeller Eddie Auerbach Gordon Xu Essa Yacoub An (Joseph) Vu Dingxin Wang DIFFUSION IMAGING Christophe Lenglet UMinn PARALLEL TRANSMIT PULSE DESIGN Xiaoping Wu Sebastian Schmitter Pierre Francois Van de Moortele

50 DIFFUSION IMAGE ACQUISITION, PROCESSING and ANALYSIS Tim Behrens Stam Sotiropoulos Saad Jbabdi Jesper Andersson RESTING STATE ANALYSIS Steve Smith Karla Miller Matt Glaser David Van Essen

51 CMMR- MAASTRICHT COLLABORATION 51

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