Rapid Self-Paced Event- Related Functional MRI: Feasibility and Implications of Stimulus- versus Response- Locked Timing Maccotta, Zacks & Buckner, 2001

Outline l This is a methods paper l Problems with other fMRI methods l A new Method! Rapid self-paced event-related fMRI l Empirical test l Conclusions

Blocked designs l All trials in a given block are of the same type l Can’t see what happens on individual trials l Strategies could be employed l Some questions require that events happen at unpredictable times

Event-Related Designs l Allow you to examine single trials l Stimulus onset is locked to beginning of a TR (repetition time) l Require a lot of down-time for BOLD response to return to baseline

Rapid Event-Related Designs l Dale and Buckner, 1997 l Bold signals are additive l You don’t need to wait for the BOLD signal to return to baseline before the next trial l But trials still began at the beginning of a TR

Joseph et al. (1997) l In the context of event-related designs, the stimulus does not have to be time locked to image acquisition l Gives temporal resolution better than TR l Over-samples the hemodynamic function

The questions here l Can a self-paced event-related fMRI: successfully detect task correlated activation during trials that are fully self-paced by the subject? Precisely characterize the hemodynamic response?

The Subjects l 17 right handers l 8 males l no history of significant neurological or psychiatric problems l What exactly qualifies a NON- significant neurological or psychiatric problem?

Imaging Stuff l Scanner: 1.5 T l Coil type: Circularly polarized head coil l Restraints: Thermoplastic face mask and foam cushions

Structural Images l Resolution: 1.25 x 1 x 1 mm l T1 weighted l TR (Repetition time) = 9.7 ms l TE (Time to echo) = 4 ms l flip angle = 10º l TI = 20 ms l TD = 500 ms

Functional Images l Echo-planar asymmetric spin- echo sequence l TR (repetition time)= 2.36 s l TE (Time to echo)= 37 ms l Resolution: 3.75 x 3.75 mm l Flip angle 90º

Functional Images l Each image acquisition consisted of 16 contiguous, 8 mm-thick axial images parallel to the anterior- posterior commisural plane l There were 128 image acquisitions per run l Each run took 5 minutes (4 runs per subject)

The Cognitive Paradigm l Mental rotation l A pair of human stick figures were presented left and right of fixation l Each figure was rotated by some amount (in 30º increments) l Figures could be same or mirror images

The Cognitive Paradigm (cont’d) l A left or a right hand keypress was required (counterbalanced across subjects) l Stimuli remained on-screen until a response was made l 750 ms later, the next trial began

Logic l The task is not important l The main thing here is test the feasibility of doing this l Left vs. Right respond hand should light up known areas l Manipulating the amount of rotation will manipulation response time

Functional Data Preprocessing l Rigid-body rotation and translation was performed to correct for motion (Snyder, 1996) l Images were translated into standardized atlas space (Talairach & Tournoux, 1988)

Over-Sampling l Stimulus onset could happen at any point in a TR ( ms from onset) l This means you get over- sampling of the hemodynamic response function l Usually stimulus onsets occur at integer multiples of TR

Over-Sampling l This means your smallest temporal bin that’s useful is TR l But if stimulus onsets can occur anywhere over TR, you can get smaller temporal bins l With rapid presentation and smaller temporal bins, you should be able to get better temporal resolution

Over-Sampling l To take advantage of this, each trial was rebinned to the time bin closest to the true trial onset l Bin size was varied from TR, TR/2 to TR/4 to see what would happen

Statistical Map Generation l Trials were sorted and averaged according to response hand (Left vs. Right) and response time (Slow, Medium, Fast)

Statistical Map Generation l For each voxel, difference time courses between trial types were generated (Left - Right) l This was then regressed with a set of idealized hemodynamic response curves

Statistical Map Generation l This regression represents a difference between conditions l Because conditions only differ in response hand (left vs. right) activation is expected in motor areas

Regions of Interest l Six regions of interests were located: right and left motor cortex; right and left supplementary motor area (SMA), and; right and left cerebellar cortex

Regions of Interest l ROIs were identified by 19 or more suprathreshold (Z > 3.3) 8 mm 3 cubic voxels l Most significant peaks in 12 mm radius were kept l ROIs were defined to include all voxels within 12 mm of a peak

Regions of Interest l Time courses for each trial type were extracted for each region of interest, averaging across all voxels within the region l Time course differences between trial types were then generated, which gave the BOLD hemodynamic response associated with each trial type comparison

The Hemodynamic Response l Three parameters were estimated: Amplitude Time-to-onset Time-to-peak

Signal Change Time Time-to-onset Time-to-peak Amplitude

Behavioural Results l 518 mean correct responses/session l 92 % correct ( %) l RT(Rhand) = 1303 ms SD = 666 ms l RT(Lhand) = 1348 ms SD = 792 ms

Imaging Results l Initial analysis was done to see if the procedure could get accurate maps of task correlated activation l Left - Right and Right - Left trials were examined, with bin sizes of TR, collapsed across response speed

Imaging Results l Observed activation corresponded to the left and right motor networks (motor cortex, SMA and cerebellar cortex), as expected l Results for time-to-onset (2 s) and time-to-peak (4 - 6 s) are similar to those from fixed-pace fMRI studies

Temporal Sampling of BOLD l Was the over-sampling of the hemodynamic response even across the TR? l Yep.

Temporal Resolution l Does using smaller bins (TR/2 or TR/4) still allow for estimates of hemodynamic response? l Yep. And the precision is better, because the bin size is smaller l Regardless of bin size, the hemodynamic response function can be modeled by a gamma function

Hemodynamic Response Timing and Behavioural Response Timing l What happen to the hemodynamic response (for motor cortex) as the time taken to perform the task increases? l Slow responses are associated with longer time-to-onsets, time- to-peaks and smaller amplitudes

Response-Locked Timing l You can measure time-to-onset, time-to-peak and amplitude of the hemodynamic response from both the stimulus onset and the response onset l This can tell you if a manipulation has it’s effect before or after activation reaches a site

Response-Locked Timing l Remember that trials were binned according to response time l Slower trials were probably caused by a requirement for more mental rotation l This processing should occur before neural activity hits motor cortex

Response-Locked Timing l If this is the case, hemodynamic response parameters should be invariant across behavioural response times when response- locked l This more or less happened, but there was some differences still

Summary l You can get robust hemodynamic response estimates from rapid, arbitrarily timed events in an event-related fMRI paradigm l Multiple regions known to be active during motor response execution were showed significant activation

Summary l This was true at the group and individual level l Results paralleled those from fixed-pace studies l presentation rate is not dictated by TR l Presentation rate can be less than TR

Summary l Self-paced paradigms produced even sampling of the hemodynamic response across TR, which allows for better temporal resolution (resolution better than TR) of the hemodynamic response