1Department of Psychology, Centre for Vision Research, York University, 2Department of Biology, Centre for Vision Research, York University
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DeSouza, J. F. X., Ovaysikia, S., Pynn, L. K. Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis. J. Vis. Exp. (64), e3237, doi:10.3791/3237 (2012).
The aim of this methods paper is to describe how to implement a neuroimaging technique to examine complementary brain processes engaged by two similar tasks. Participants' behavior during task performance in an fMRI scanner can then be correlated to the brain activity using the blood-oxygen-level-dependent signal. We measure behavior to be able to sort correct trials, where the subject performed the task correctly and then be able to examine the brain signals related to correct performance. Conversely, if subjects do not perform the task correctly, and these trials are included in the same analysis with the correct trials we would introduce trials that were not only for correct performance. Thus, in many cases these errors can be used themselves to then correlate brain activity to them. We describe two complementary tasks that are used in our lab to examine the brain during suppression of an automatic responses: the stroop1 and anti-saccade tasks. The emotional stroop paradigm instructs participants to either report the superimposed emotional 'word' across the affective faces or the facial 'expressions' of the face stimuli1,2. When the word and the facial expression refer to different emotions, a conflict between what must be said and what is automatically read occurs. The participant has to resolve the conflict between two simultaneously competing processes of word reading and facial expression. Our urge to read out a word leads to strong 'stimulus-response (SR)' associations; hence inhibiting these strong SR's is difficult and participants are prone to making errors. Overcoming this conflict and directing attention away from the face or the word requires the subject to inhibit bottom up processes which typically directs attention to the more salient stimulus. Similarly, in the anti-saccade task3,4,5,6, where an instruction cue is used to direct only attention to a peripheral stimulus location but then the eye movement is made to the mirror opposite position. Yet again we measure behavior by recording the eye movements of participants which allows for the sorting of the behavioral responses into correct and error trials7 which then can be correlated to brain activity. Neuroimaging now allows researchers to measure different behaviors of correct and error trials that are indicative of different cognitive processes and pinpoint the different neural networks involved.
1. Before Entering the MRI Room
2. Task Overview and Training
3. Scanner and Eye Tracking Setup
4. Scanning Procedures
5. fMRI Analysis
6. Representative Results
After the analysis we show brain regions that correlate with the emotional stroop and anti-saccade tasks recorded during scanning. The results from the emotional stroop paradigm showed an interaction effect between all three factors of expression, instruction, and brain region but there was no main effect of expression and no main effect of instruction2. We found that when the expression of the face was incongruent to the superimposed emotional word, this incongruency produced from reporting the written word showed higher BOLD signal intensity in the left IFG2 (Figure 2). The larger signal intensity on the incongruent expressions compared to the congruent expressions was statistically significant, with happy congruent showing the largest difference2.
Most importantly the RTs for the three incongruent conditions tested (sad, happy and neutral) predicted an increased BOLD signal within left IFG compared to all the congruent conditions (Figure 3). For this analysis we specifically examined the reaction times and conducted a regression analysis to test whether RT for the incongruent and congruent conditions were predictive of the BOLD signal activity within this brain region (Figure 3). We found that RT accounts for 81% of the variation in left IFG activity when reporting the word expressions of Happy, Neutral, and Sad during the incongruent and congruent conditions2. Higher RT is predictive of larger left IFG activation, with the incongruent sad condition yielding the greatest RT/signal intensity ratio compared to all other expression conditions. We analyzed the anti-saccade paradigms using similar methods as above to be able to compare the two networks of activity. In this example, we found that there was no increased signal in left IFG for the anti-saccade compared to the pro-saccade task. For more details, we refer the readers to Ford et al. (2007).
Figure 1. An example of an incongruent trial (face with a happy expression superimposed by the word SAD). The experiment will begin with the fixation dot (1 second), proceeding by the face stimulus (250 ms) and the masked image (2 seconds) which requires the participant's button response.
Figure 2. All fixation volumes were used as the baseline. Error bars signify the standard error of mean (SEM). Incongruent expressions (Happy, Neutral, Sad) showed significantly larger BOLD signal change compared to congruent expressions2. The inset image shows left inferior frontal gyrus (IFG) that was functionally localized using the contrast describe in section 5.2 for the incongruent emotional stroop versus the congruent condition during the attend to word instruction set.
Figure 3. During the "Attend to Word" instruction, incongruent-congruent contrast showed a positive correlation between the RTs and BOLD signal intensity. This graph is an average of all 10 subjects' RTs and BOLD signal during each of the six conditions. Error bars signify the standard error of mean (SEM)2 .
Figure 4. Two repetitions of each expression were displayed to the subjects. Top row is an schematic illustration of a trial sequence from one block of trials. Bottom section is a depiction of the Two-Gamma hemodynamic response function (HRF) used to discover brain regions involved in the emotional face expressions.
Identifying brain regions relies on creating an accurate contrast between the tasks scanned (i.e. in either the Stroop, incongruent versus congruent emotion and facial expression; or anti-saccade versus pro-saccade) in order to produce a map of activation related to the task. These functional maps can be more refined when behavior is collected in the scanner to remove trials where the subject made errors. These errors can be removed and if there was enough numbers of errors than functional maps could be made of these3,4,5,6. Most importantly, when examining the reaction times for the stroop task incongruent tasks that had longer reaction times also had higher BOLD signals in left frontal cortex (IFG). If we did not collect this behavioral data we would not have this new insight into prefrontal cortex2.
This technique allows for the measurement of patterns of activity in brain areas associated with a particular behaviors such as correct and error trials7 using measures of button presses2 or eye movement recordings. The challenge of using these techniques lies in the accurate correlation of the behavioral data which can be measured in the order of milliseconds, with the functional data derived from blood-flow (BOLD signal) which has a temporal resolution of 4-5s (Figure 4). Therefore, to look at neural activity associated with a particular behavior, the delay associated with hemodynamics must be taken into account. With rapidly presented stimuli, the rise in BOLD signal occurs over the course of the presentation of several face/word pair stimuli. In order to look at the effect of congruence (or of a particular facial expression) we must overcome this disparity in temporal resolution by sequentially presenting two of the same stimulus type. This is shown in Figure 4, where the first two stimuli are two incongruent-happy face presentations followed by two incongruent-neutral and two-incongruent sad. Thus, a contrast that relies on comparing congruence with incongruence will encompass a 6.5s block, long enough to capture the hemodynamic response.
Additionally, motion of the participants during scanning creates distortions within the magnetic field and this can produce artificial activation in the results or can displace functional activation onto the incorrect anatomical location. Excessive motion by subjects while in the scanner can be seen by the experimenter and subjects can be reminded to remain as still as possible between scans. Further correction for motion can be performed posthoc in software, however motion larger than a few millimeters usually results in a functional scan being discarded. Here we did not find button presses resulted in a significant displacement of the arm and head, however the motion of subjects during scans must be given careful consideration for any paradigm requiring even small movements.
We have nothing to disclose.
Funded by the National Science and Engineering Research Council (NSERC) to JFXD, Faculty of Health, York University and author SO has PhD funding by The Ontario Problem Gambling Research Centre (OPGRC).
|3-Tesla MRI machine||Siemens Magnetom Trio (Erlangen, Germany)|
|iViewX Eye Tracking||SensoMotoric Instruments, Inc.|
|BrainVoyager QX software||Brain Innovation, Maastricht, The Netherlands|
|Four-button Joystick||Current Designs, Inc., Philadelphia, PA, USA|
|Table 1. Specific Reagents and Equipment.|