Decision making is a dynamic, interactive process that has been studied extensively with functional magnetic resonance imaging, or FMRI. Neuroimaging evidence indicates that the anterior cingulate and the lateral prefrontal cortices are essential nodes in that neural network. However, because of its limited temporal resolution, FMRI cannot accurately reflect the timing and nature of their interplay in real time.
The present study uses an anatomically constrained magneto-and electroencephalography or MEG method, which combines distributed source modeling of the MEG signal with structural MRI forming brain movies. It allows us to examine how acute alcohol intoxication affects decision making. Demonstrating this procedure will be Joe Happer and Burke Rosen, doctoral students, and Laura Wagner, a research associate.
Begin by escorting the participant into the MEG lab to run a test scan. Put them in the scanner, and check the channels for possible magnetization. Then, measure their weight and have them blow into an electronic breathalyzer.
To assess dynamic changes in the subjective effects of alcohol, inform the subject that they will rate their momentary feelings and states on a standardized scale prior to drinking and on two additional occasions during the experiment, during the ascending and descending limb of the Breath Alcohol Concentration curb. Then, administer a practice run of the Stroop task on a laptop with stimulus presentation software to ensure that the participants understand the task before recording. Prepare the alcohol beverage by mixing premium quality vodka with chilled orange juice, based on each participant's gender and weight.
Serve the same volume of orange juice in glasses with rims swabbed with vodka as a placebo beverage. Ask the participant to consume the beverage in approximately 10 minutes. Next, position the EEG cap and the electrooculogram, EOG, electrodes on the participant's head.
Check that all impedances are below 5 kiloohms. Attach the head position indicator, HPI, coils on either side of the forehead and behind each ear. Place the reference frames on the participant's head.
Endigitize positions of the fiducial points, including the nasion and two preauricular points positions of HPI coils, EEG electrodes and obtain a large number of additional points delineating the head shape. Check the participant's breath alcohol concentration with a breathalyzer, starting at 15 minutes after drinking. And then, every five minutes, until they enter the recording chamber.
Begin by positioning the participant comfortably in the MEG scanner. Since the prefrontal activity is of particular interest, ensure that the participant is positioned so that his or her head is touching the top of the helmet and is aligned along the front. Next, connect the HPI coils and the electro cap to the respective inputs on the scanner.
Position response pads so that the buttons can be pressed comfortably. Remind the participant to minimize blinking and to avoid movements including head motion caused by talking. Examine all channels for artifacts and measure the head position in the scanner.
Then, start data acquisition and begin the task. Since electronic devices cannot be used in the shielded room, switch to using a saliva alcohol test which consists of a cotton swab saturated in saliva and is inserted into a receptacle that provides a read-out. After the task is complete, save the data and escort the participant out of the recording chamber.
After the participant has exited the scanner, acquire approximately two minutes of data from the empty room as a measure of instrumental noise. Then, ask the participant to rate perceived task difficulty, content of the imbibe beverage, how intoxicated they felt, as well as their momentary moods and feelings. Finally, obtain a high resolution anatomical MRI scan from each participant and reconstruct each participant's cortical surface with imaging software.
During data pre-processing, use a permissive band-pass filter and epuc data into segments that include padding intervals on each end. Remove noisy and flat channels as well as trials containing artifacts by visual inspection and using threshold based rejection. Then, use independent component analysis to remove eye blink and heart artifacts.
Eliminate trials with incorrect responses. Next, apply more lay wavelets to calculate complex power spectrum for each trial in one Hertz increments, fourth theta frequency band and remove any additional artifacts. To co-register the MEG data with MRI images, open the MRI lab module.
Select File, Import, Isotrak data. Select raw_data. fif file, and click on Make Points.
Then select Windows, Landmarks, and click on Adjust Fiducial Landmarks until co-registration of MEG data and MRI are acceptable. Next, create group averages of event-related theta source power by morphing each participant's estimates onto an average cortical representation. Then, to visualize the source estimates on an inflated average surface, open the MNE software.
Select File, Load Surface and load inflated group average free surfer cortical surface. This is followed by selecting File, Manage Overlays, Load STC, Load Group Averaged Data and select the loaded file from available overlays. Adjust color scale thresholding and click Show.
View brain movies of event related theta power and examine spatiotemporal stages of processing by identifying areas and time windows characterized by highest activation. Next, create unbiased regions of interest, ROI, based on overall group averaged estimates. To incorporate cortical locations with most notable source power, calculate time courses for each subject, condition, and ROI.
Finally, estimate task related changes in the long range synchronization between the main activation foci in the ACC and the lateral PFC by computing the phase locking value. Express the phase locking value as percent change relative to baseline. Behavioral results indicate that the Stroop task successfully manipulated response interference because the accuracy was the lowest and the response times the longest on incongruous trials.
Alcohol intoxication lowered accuracy but did not affect reaction times. Event related theta power is greatest on incongruous trials, which is consistent with its sensitivity to conflict demands, especially in the prefrontal cortex. However, when compared to congruous trials, alcohol decreases theta power on incongruous trials selectively in the ACC and the lateral PFC.
Further, cooscillations between the ACC and lateral PFC vary across time, with an overall early increase in cooscillations during a stimulus processing stage. Under placebo, this is followed by a sustained increase after about 400 milliseconds on incongruous trials during the integration and response preparation stage. In contrast, acute alcohol intoxication dysregulates these cooscillations which further indicates the vulnerability of top-down regulative functions to alcohol.
In this study, we have estimated spatiotemporal, the where and when stages of processing, and have investigated how different brain areas interact during decision making. We have shown how alcohol intoxication dysregulates the cognitive control network which may result in reduced ability to refrain from excessive drinking.
