Introduction to functional MRI in humans. Michael Hallquist University of Pittsburgh

Transcription

1 Introduction to functional MRI in humans Michael Hallquist University of Pittsburgh

2 Goals of human neuroimaging Localization of brain function (mapping) Understanding large-scale functional integration among systems (connectivity) Identifying structural differences between groups (anatomy) (Potentially) understanding neural representations of psychological or physical stimuli (Davis & Poldrack, 2013)

3 Friston, 2010, Science The Rise of Imaging

4 Spatial and Temporal Resolution

5 fmri: functional magnetic resonance imaging

6 MRI vs. fmri MRI studies brain anatomy. Functional MRI (fmri) studies brain function.

7 MRI vs. fmri high resolution (1 mm) MRI fmri low resolution (~3 mm) One 3D volume series of 3D volumes (i.e., 4D data) (e.g., every 2 sec for 5 mins)

8 fmri Activation Flickering Checkerboard OFF (60 s) - ON (60 s) -OFF (60 s) - ON (60 s) - OFF (60 s) Brain Activity Source: Kwong et al., 1992 Time

9 Why did the MR signal increase during visual checkerboards? (A brief introduction to MR physics and the BOLD signal)

10 The Big Magnet Very strong 1 Tesla (T) = 10,000 Gauss Earth s magnetic field = 0.5 Gauss 3 Tesla = 3 x 10, = 60,000x Earth s magnetic field Magnet is on continuously Main field = B 0 Siemens 3T Tim Trio x 60,000 = B 0 Source:

11 MRI Scanner: Three Key Components 3T magnet RF Coil gradient coil (inside)

12 Coils are Application-Specific 12-channel head coil 32-channel head coil 16-channel breast coil 8-channel knee coil 16-channel peripheral coil Images from:

13 Step 1: Study Atoms With NMR Spin Can measure nuclei with odd number of neutrons 1 H, 13 C, 19 F, 23 Na, 31 P 1 H hydrogen (proton) abundant: high concentration in human body (5 x protons in 150 lb guy) high sensitivity: yields large signals

14 Protons: No Magnetic Field protons in random orientation (obviously not to scale!)

15 Step 2: Put Subject in Big Magnet Protons (hydrogen atoms) have spins (like tops). They have an orientation and a frequency.

16 Protons: Within Magnetic Field B0 protons align parallel or anti-parallel to B0 (parallel>antiparallel) phase is random

17 Larmor Frequency Larmor equation f = B 0 = MHz/T for hydrogen At 1.5T, f = 63.8 MHz At 3T, f = MHz At 7T f = MHz Resonance Frequency for 1 H Field Strength (Tesla)

18 Radio Frequency

19 Protons: Within Magnetic Field longitudinal axis z Longitudinal magnetization M z B0 sum of red vectors along longitudinal axis M z > 0 Transverse magnetization M xy x Now imagine viewing the spins from above y transverse plane sum of red vectors in transverse plane M xy ~0

20 Step 3: Apply RF energy M=~0 longitudinal axis z Longitudinal magnetization M z B0 sum of red vectors along longitudinal axis M z ~ 0 Transverse magnetization M xy x Now imagine viewing the spins from above y transverse plane 90 RF Pulse sum of red vectors in transverse plane M xy > 0

21 Step 4: Measure Radio Waves longitudinal axis z Longitudinal magnetization M z z Measure during recovery period z y y y Transverse magnetization M xy x transverse plane x x Before 90 pulse Immediately after 90 pulse Long after 90 pulse Measure radio waves as protons gradually return to original configuration within the magnetic field

22 Goebel (2007) book chapter Step 4: Measure Radio Waves

23 Step 4: Measure Radio Waves By selecting TR and TE, we can choose T1- vs. T2-weighting Longitudinal Magnetization M z Short T1 (e.g., fat) Long T1 (e.g., CSF) Transverse Magnetization M xy Short T2 (e.g., fat) Long T2 (e.g., CSF) Time to Repetition = TR (s) Time to Echo = TE (ms) T1 measures how quickly the protons realign with the main magnetic field T2 measures how quickly the protons give off energy as they recover to equilibrium T1-WEIGHTED ANATOMICAL IMAGE T2-WEIGHTED ANATOMICAL IMAGE

24 T2 and T2* Dephasing of transverse magnetization due to both: 1. spin spin interactions (T 2 ) 2. static magnetic field inhomogeneities (additional T2* effects) M xy T 2 T 2 * Source: Adapted from Jorge Jovicich time

25 Step 5: Use Gradients to Encode Space B0 gradient higher magnetic field; higher frequencies 3.1 T 1 H Larmor freq = MHz (The differences aren t actually this large) gradient of field strength lower magnetic field; lower frequencies 2.9 T 1 H Larmor freq = MHz

26 Step 5: Use Gradients to Encode Space We ve seen how gradients can be used to encode one direction of space (slice selection) Other gradients and other tricks (frequency encode and phase encode) can be used to encode the other two directions, though it s more complicated

27 Slice Terminology SAGITTAL SLICE Slice Thickness e.g., 6 mm In-plane resolution e.g., 192 mm / 64 = 3 mm IN-PLANE SLICE VOXEL (Volumetric Pixel) 3 mm 3 mm 6 mm Number of Slices e.g., 10 Matrix Size e.g., 64 x 64 Field of View (FOV) e.g., 19.2 cm

28 Imaging brain function by studying cerebral blood metabolism

29 Vasculature: Brain vs. Vein Source: Menon & Kim, TICS

30 Contents of a Voxel Capillary beds within the cortex Source: Duvernoy, Delon & Vannson, 1981, Brain Research Bulletin Source: Logothetis, 2008, Nature

31 Source of blood oxygen level dependent (BOLD) contrast Neural activation Increase in oxygen utilization Slight increase in deoxyhemoglobin (initial dip) Increased blood flow Increase in oxyhemoglobin Greater proportion of oxy versus deoxyhemoglobin Stronger fmri BOLD signal

32 Deoxygenated Blood Signal Loss Oxygenated blood? Diamagnetic Doesn t distort surrounding magnetic field No signal loss rat breathing pure oxygen rat breathing normal air (less oxygen than pure oxygen) Deoxygenated blood? Paramagnetic Distorts surrounding magnetic field Signal loss!!! Images from Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging based on two papers from Ogawa et al., 1990, both in Magnetic Resonance in Medicine

33 Hemoglobin Hemoglogin (Hgb): - can attach up to four oxygen atoms (O 2 ) - oxy-hgb (four O 2 ) is diamagnetic no B effects - deoxy-hgb is paramagnetic local B Source: Jorge Jovicich

34 BOLD Time Course Blood Oxygenation Level-Dependent Signal Positive BOLD response 3 BOLD Response (% signal change) Initial Dip Overshoot Post-stimulus Undershoot Time Stimulus

35 Perhaps it should be BDLD? Blood DE-oxygenation level-dependent signal? Technically, BOLD is a misnomer The fmri signal is dependent on deoxygenation rather than oxygenation per se The more deoxy-hb there is the lower the signal fmri Signal Amount of deoxy-hb BDLD idea from Bruce Pike, MNI

36 Trial to Trial Variability Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging

37 Variability of HRF Between Subjects Aguirre, Zarahn & D Esposito, 1998 HRF shows considerable variability between subjects different subjects Within subjects, responses are more consistent, although there is still some variability between sessions same subject, same session same subject, different session

38 Variability of HRF Between Areas Possible caveat: HRF may also vary between areas, not just subjects Buckner et al., 1996: noted a delay of.5-1 sec between visual and prefrontal regions vasculature difference? processing latency? Bug or feature? Menon & Kim mental chronometry Buckner et al., 1996

39 Sampling Rate (TR) Huettel, Song & McCarthy, 2004, Functional Magnetic Resonance Imaging

40 Linearity of BOLD response Linearity: Do things add up? red = 2 1 green = 3 2 Sync each trial response to start of trial Not quite linear but good enough! Source: Dale & Buckner, 1997

41 What aspect of neural function is captured by BOLD?

42 What does electrophysiology measure? Raw microelectrode signal Filter out low frequencies Action Potentials (APs) Filter out high frequencies Local Field Potentials (LFPs) Source: tuebingen.de/research/methods in neuroscience/networks.php

43 BOLD electrophys correspondence 24 s stimulus 12 s stimulus 4 s stimulus Local Field Potentials (LFP) reflect post-synaptic potentials similar to what EEG and MEG measure Multi-Unit Activity (MUA) reflects action potentials similar to what most electrophysiology measures Source: Logothetis et al., 2001, Nature Logothetis et al. (2001) combined BOLD fmri and electrophysiological recordings found that BOLD activity is more closely related to LFPs than MUA

44 Spatial specificity of neurovascular coupling arteriole veins Biggest changes in arteriole dilation occurred near stimulation; however, effects could also be observed several mm upstream Distance between emerging veins: mm Source: Adapted from Iadecola et al., 1997, J Neurophysiol, by Huettel, et al., 2nd ed.

45 What can we learn using fmri?

46 Category-Specific Visual Areas objects faces places Lateral Occipital (LO) object-selective objects > (faces & scenes) objects > scrambled images Malach, 2002, TICS Parahippocampal Place Area (PPA) place selective places > (objects and faces) places > scrambled images Fusiform Face Area (FFA) or pfs face selective faces > (objects & scenes) faces > scrambled images ~ posterior fusiform sulcus (pfs)

47 A Simple Experiment: LO Localizer Lateral Occipital Complex responds when subject views objects Blank Screen Intact Objects TIME One volume (12 slices) every 2 seconds for 272 seconds (4 minutes, 32 seconds) Condition changes every 16 seconds (8 volumes) Scrambled Objects

48 fmri Simplified ~2s fmri Signal Intensity ROI Time Course Time Condition Time Region of interest (ROI) ~ 5 min

49 Group-level inference To assess which regions are reliably activated across subjects, anatomical differences need to be minimized, typically by nonlinear warping and spatial smoothing. Also, to allow for comparability of region definition across studies, data are typically warped into a standard stereotactic template (e.g., MNI152).

50 Resting-state fmri Intrinsic connectivity of large-scale networks (composed of many regions) revealed by resting-state fmri During a BOLD-sensitive scan, participant lies in scanner without task for 5-30 minutes. Similarities in slow BOLD oscillations ( Hz) correlated to characterize networks. RS-fcMRI results are often remarkably robust across studies

51 Example: Fair et al Used RS-fcMRI to characterize the development of two control networks: Cingulo-opercular (sustained task set) Fronto-parietal (transient control and update)

52 Developing control networks For each subject, pairwise correlations among 39 task-control regions were computed. The matrix was then visualized by thresholding correlations and displaying the network nodes in anatomical space.

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55 Conclusion of Fair 2007 Segregation of control networks develops with age. Short-range functional connections diminish with age (increasing regional specialization). The role of long-range connections in functional networks increases with age (integration of multiple distinct sources).

56 Limitations of Neuroimaging Physical Limitations spatial limitations (~1 mm) temporal limitations (fmri limited by slow hemodynamics) Physiological Limitations noise head motion artifacts (respiration, cardiac pulse) localization of BOLD response vasculature Current Conceptual Limitations how can we analyze highly complex data sets? brain networks how are neural changes manifested in imaging data? how are stimuli represented in the brain, and can we detect this with imaging?

57 Localization Localization for its own sake has some value e.g., presurgical planning However, it is not especially interesting to the cognitive neuroscientist in and of itself

58 The Brain Before fmri (1957) Polyak, in Savoy, 2001, Acta Psychologica

59 The Brain After fmri (Incomplete) reaching and pointing motor control touch retinotopic visual maps eye movements grasping executive control motion near head memory orientation selectivity motion perception scenes moving bodies social cognition static bodies faces objects

60 They can t be serious? implies these findings justify wearing of the hijab

61 Problem of Reverse Inference For further discussion see Poldrack, 2008, Current Opinion in Neurobiology Tools activate Area X Women in bikinis activate Area X Therefore women in bikinis are viewed as tools Logic only works if and only if Area X is involved in only one mental process This is rarely (never?) true