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Introduction to functional neuroimaging Didem Gökçay. Imaging modalities. Lesion maps - ~5 mm -. Where do we stand historically. Brain Mapping: The systems (Toga & Mazziotta, Chap.2). Introduction to functional MRI.
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Imaging modalities Lesion maps - ~5 mm -
Where do we stand historically Brain Mapping: The systems (Toga & Mazziotta, Chap.2)
Outline of fMRI topics • 1. The basis of the fMRI signal: hemodynamic response • 2. Imaging the function: • fMRI experimental setup • fMRI paradigms • fMRI problems • 3. Data analysis techniques • fMRI Preprocessing • fMRI Block design data analysis • fMRI Event related data analysis • 4. Aggregation of activity maps from multiple people • Individual ROIs • Blurring
1. Basis of the fMRI signal: hemodynamic response
Changes in the ‘active’ brain As long as we eat and breathe we can continue to think
The working brain requires a continuous supply of glucose and oxygen This is delivered through cerebral blood flow (cbf) Human brain accounts for 2% of body weight but 15% of cardiac output (700 ml/min) Arteries Arteries contain oxygenated blood (oxyhemoglobin) Veins contain deoxygenated blood (deoxyhemoglobin) Veins
Local blood flow varies 18-fold between different brain regions (the number of capillaries in the tissue is dissimilar) The ratio of capillary density in GM:WM is 2-3:1 The CBF ratio of GM:WM is 4:1, The CBV ratio of GM:WM is 2 Neuronal activity is associated with an increase in metabolic activity and hence, blood flow
Arterioles (10 - 300 microns)precapillary sphinctersCapillaries (5-10 microns)Venules (8-50 microns)
The change in diameter of arterioles following sciatic stimulation. after activity
BEFORE ACTIVITY venous flow AFTER ACTIVITY
Obtaining the fMRI signal (intensity) T2*: The transverse relaxation time actually decays faster than T2, due to field inhomogeneity (the spinning tops gets out of phase, so we observe a rapid destruction of the alignment with the field) deoxyhaemoglobin: is contained in blood and paramagnetic, so introduces field inhomogeneity fMRI process: mainly measures the field inhomogeneity - upon stimulus, the capillary and venous blood are more oxygenated, so there is less deoxyhemoglobin - the capillaries’ susceptibility is reflected on the surrounding tissue, so the surrounding field gradients are reduced. - T2* becomes longer so the signal measured via the T2*-weighted pulse sequence increases by a few percent
BOLD: Blood oxygenated level dependent (hemodynamic response) animal study animal study human HRF (HemRespFunc)
CONFOUNDS Pial Arteries Sub-cortical Noradrenergic Dopamine 10 m Not only neuronal activity but noradrenergic or dopamine activity affects BOLD !! Krimer, Muly, Williams, Goldman-Rakic, Nature Neuroscience, 1998
1% 1% Percent Signal Change • Peak / mean(baseline) • Often used as a basic measure of “amount of processing” • Amplitude variable across subjects, age groups, etc. • Amplitude increases with increasing field strength: 1.5T < 3T 505 500 205 200
fMRI Hemodynamic Response Stimulus duration 1500ms 500ms 100ms Calcarine Sulci Magnitude increases with stimulus duration Fusiform Gyri
Correlation of Electrical and BOLD activities in monkey (Logothetis)
Dale & Buckner, 1997 • Responses to consecutive presentations of a stimulus add in a “roughly linear” fashion • Subtle departures from linearity are evident
Linear Systems • Scaling • The ratio of inputs determines the ratio of outputs • Example: if Input1 is twice as large as Input2, Output1 will be twice as large as Output2 • Superposition • The response to a sum of inputs is equivalent to the sum of the response to individual inputs • Example: Output1+2+3 = Output1+Output2+Output3
Linear additivity A B C D
Refractory Periods • Definition: a change in the responsiveness to an event based upon the presence or absence of a similar preceding event • Neuronal refractory period • Vascular refractory period
Refractory Effects in the fMRI Hemodynamic Response Stimulus latency after initial stimulus Signal Change over Baseline(%) Time since onset of second stimulus (sec) Huettel & McCarthy, 2000
Variability in the Hemodynamic Response SUMMARY • fMRI measurements are of amount of deoxyhemoglobin per voxel • We assume that amount of deoxygenated hemoglobin is predictive of neuronal activity • Across Subjects • Across Sessions in a Single Subject • Across Brain Regions • Across Stimuli Relative measures • fMRI provides relative change over time • Signal measured in “arbitrary MR units” • Percent signal change over baseline
2. Imaging the function (change in blood flow)
MR scanner MR console response buttons goggle experiment PC RF/TTL pulse synchronization box headphone subject MR ROOM OPERATOR ROOM fMRI experiments The environment
2. Imaging the function: experimental setup • Subject lies in the scanner awaiting for commands from the scanner • operator: • a 3d high-resolution MRI is collected for high precision localization • multiple runs of an experimental protocol is performed next. • At this phase, the subject is presented with auditory, visual or • tactile stimulation. • Stimulus presentation is achieved through headphones, • goggles/screen, air pumps • As the subject performs the experiment behavioral/physiological • data is collected through voice recording, push-buttons, electrodes • on the head/feet (either for eeg or for heart rate, skin conductance) • Stimulus presentation and recording of subject response is done via • a pc synchronized to the rf pulses of the scanner 3 msec 100 msec
fMR experiment responses and images slice j .......... t (sec) impulse 0 2 5 8 11 14 .......... 300 I I 11 2 2 5 8 14 5 8 14 11 I: Change of intensity of an active voxel in time I: Change of intensity of a passive voxel in time t t fMRI experiments Data acquisition
How large are anatomical voxels? = ~.004cm3 5.0mm .9375mm .9375mm Within a typical brain (~1300cm3), there may be about 300,000+ anatomical voxels.
How large are functional voxels? = ~.08cm3 5.0mm 3.75mm 3.75mm Within a typical brain (~1300cm3), there may be about 20,000 functional voxels.
Partial Volume Effects • A single voxel may contain multiple tissue components • Many “gray matter” voxels will contain other tissue types • Large vessels are often present • The signal recorded from a voxel is a combination of all components
Trial Averaging: Does it work? • Static signal, variable noise • Assumes that the MR data recorded on each trial are composed of a signal + (random) noise • Effects of averaging • Signal is present on every trial, so it remains constant when averaged • Noise randomly varies across trials, so it decreases with averaging • Thus, SNR increases with averaging
Caveats • Signal averaging is based on assumptions • Data = signal + temporally invariant noise • Noise is uncorrelated over time • If assumptions are violated, then averaging ignores potentially valuable information • Amount of noise varies over time • Some noise is temporally correlated (physiology) • Response latency may vary • This is why averaging methods are useless in fMRI
fMRI paradigms • There are 2 major paradigms for acquisition of fMRI: • block design • event related design
fMRI block design signal amplitude Task waveform 5-6 samples t Measures cumulative activity in the ON block Signal amplitude is about 1.5-3% in 1.5T scanner
OVERALL fMRI event-related design Measures single event activity Signal amplitude is about 1% in 3T Signal Amplitude t Task Impulse Task Impulse standard design rapid design
What temporal resolution do we want? fMRI • 10,000-30,000ms: Arousal or emotional state • 1000-10,000ms: Decisions, recall from memory • 500-1000ms: Response time • 250ms: Reaction time • 10-100ms: • Difference between response times • Initial visual processing • 10ms: Neuronal activity in one area
Basic Sampling Theory • Nyquist Sampling Theorem • To be able to identify changes at frequency X, one must sample the data at (least) 2X. • For example, if your task causes brain changes at 1 Hz (every second), you must take two images per second.
Aliasing • Mismapping of high frequencies (above the Nyquist limit) to lower frequencies • Results from insufficient sampling • Potential problem for long TRs and/or fast stimulus changes • Also problem when physiological variability is present