Supplementary Information Appendix: Default Mode Contributions to Automated Information Processing

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1 Supplementary Information Appendix: Default Mode Contributions to Automated Information Processing Authors: Deniz Vatansever a,b,c,1, David K. Menon a,d, Emmanuel A. Stamatakis a,b,d Affiliations: a Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom, CB2 0QQ. b Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom, CB2 0QQ. c Department of Psychology, University of York, Heslington, York, United Kingdom, YO10 5DD. d Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom, CB2 0QQ. 1 Corresponding author: Deniz Vatansever, PhD Division of Anaesthesia University of Cambridge Box 93, Addenbrooke's Hospital Hills Road, Cambridge, UK CB2 0QQ ddsv2@cam.ac.uk Tel: +44 (0) Table of Contents Supplementary Materials and Methods... 2 Supplementary Results... 6 Supplementary Tables... 7 Supplementary References... 13

2 Supplementary Materials and Methods Participants Ethical approval for this study was obtained from the Cambridge Psychology Research Ethics committee in accordance with the Declaration of Helsinki. All volunteers gave informed consent prior to their participation. The exclusion criteria included lefthandedness, any history of drug and/or alcohol abuse, psychiatric/neurodegenerative conditions or head injury, use of contraindicated medication (e.g. anti-depressants), motor handicap that may impede task performance, contraindication to MRI scanning, severe claustrophobia, incidental MRI findings and pregnancy. One participant s data was excluded due to an incidental finding. Consequently, a group of 28 healthy controls participated in this functional magnetic resonance imaging (fmri) study (22 34 years old, mean = 26.8, SD = 2.8, 13/15 female to male ratio) with an average National Adult Reading Test (NART) score of (SD = 3.17). Experimental Paradigm Specifications The experimental paradigm was a variant of the Wisconsin Card Sorting Task (WCST) (1) that was modified for the scanner environment utilizing a mixed design. Stimuli were delivered and responses recorded using an open source software package called PsychoPy ( (Version 1.83). A short training session was first provided before the fmri scan in order to familiarize the participants with the task design. Inside the scanner, the paradigm commenced with 20 seconds of instructions, reminding the participants about the nature of the task. In this variant of the WCST, the participants were presented with four permanent reference cards on the upper half of the screen together with an alternating target card on the bottom half. The four reference cards consisted of a red triangle, two green circles, three blue crosses and four yellow stars, respectively. The target cards were randomly drawn from a pool of 60 cards based on the permutation of four shapes (triangle, circle, cross, star), four colors (red, green, blue, yellow), four possibilities for the number of objects present (1, 2, 3, 4), but excluding the four cards that were identical to the reference cards. The goal of this task was to sort the target card to one of the reference cards using four corresponding buttons on a button-box placed under the participant s right hand. While the sorting dimensions for the task included shape, number and color, the rule for the control condition was identity i.e. the target card was identical to one of the reference cards. Thus, the control condition matched the task conditions in visuospatial and motor aspects as well as simple cognitive components such as response selection. Following the 1500 ms presentation of a white font prompt Sort according to color, shape, number or identity against a black background, the reference and target cards appeared on the screen, commencing the trials. Participants were allowed a maximum of 3500 ms seconds to make their selection and the variable response time provided the necessary jittering in our experimental design. Subsequently, visual feedback appeared for 1500 ms replacing the target stimulus, and indicated whether the selection was correct or incorrect with a 2

3 corresponding smiley or sad face. If the participants did not respond by the allotted time, a Time Out prompt replaced the target card. Finally, a crosshair fixation period randomized between 1000 ms and 2000 ms seconds was shown on the screen until the beginning of the next trial. The variable duration for the crosshair presentation was selected to provide extra jittering and to make stimulus presentation less regular. In line with the experimental question, the sorting rule remained the same for a total of 10 trials, changing only at the presentation of another Sort prompt. Although the participants were informed about the point at which the rule was changed, they were not told what the new sorting dimension was. Thus, during the first few trials following the rule change, participants had to rely on feedback to deduce the context and make appropriate selections (i.e. trial-and-error). This we defined to be the acquisition (learning) phase of each block. However, once the rule was firmly established, the participants could then rely on the learned responses from memory for choosing the appropriate card, here referred to as the application phase. We operationally stratified the task into these two phases after completion of half the trials, to produce subsets of trials (n=5), maximized for acquisition and application. A total of 160 trials (16 blocks of 10 trials) were presented with four blocks of 10 trials for each of the three task sorting dimensions as well as the control sorting dimension, all presented in a pseudorandom order for each participant. Behavioral Data Analysis In order to test whether the experimental manipulation has produced the expected behavioral results, we calculated the percent correct responses as well as the reaction time to correct responses for both the acquisition and the application phases of the task as well as the control blocks. The reaction time to correct responses was chosen as the behavioral measure that was representative of the participants purposeful and consistent responses to the given stimuli, thus eliminating wrong or missed feedback in either phase of the WCST. Paired t-tests were employed in order to statistically assess the mean differences in percent correct responses and reaction time to correct responses for the overall task and control conditions as well as the stratified acquisition and application phases (Bonferroni corrected for multiple comparisons). This information was later used to investigate a potential brain-behavior relationship. MRI Data Acquisition The participants were scanned in a Siemens MAGNETOM Tim Trio 3T scanner (32- channel head coil) at the Wolfson Brain Imaging Centre, Cambridge. The scanning session started with a high resolution T1-weighted, magnetization-prepared rapid gradient-echo (MPRAGE) structural scan (TR = 2300 ms, TE = 2.98 ms, slice thickness = 1.00 mm). The echo planar imaging (EPI) sequence parameters for the WCST functional data acquisition were as follows: 37 slices in each volume, 3.0 mm slice thickness, 3.0 x 3.0 x 3.0 voxel size, TR = 2000 ms, TE = 30 ms, flip angle = 78 degrees. The number of 3D volumes varied according to the speed of the participants response to the task (mean = 347 volumes, SD = 12). 3

4 MRI Data Preprocessing The image analysis was carried out using SPM software package ( (Version 12.0), based on the MATLAB platform ( (Version 15a). The first five volumes were removed to eliminate saturation effects and achieve steady state magnetization. The remaining functional images were first corrected for the differences in slice timing. The motion artifacts caused by volunteer movement inside the scanner were removed using six degrees of freedom, the average values of which are provided in Table S1. Neck tissue was removed from the high-resolution T1 weighted structural data using an MRIcron-based cropping tool ( which was then coregistered to the mean motion-corrected functional image, and was subsequently segmented into probabilistic grey matter, white matter and cerebrospinal fluid maps. Next, all the corrected EPI volumes were spatially normalized through the unifiedsegmentation algorithm and utilizing the parameters calculated from transforming the grey matter map into MNI space. This procedure combines tissue segmentation, bias correction, and spatial normalization in a single unified model (2). Finally, all the functional images were smoothed using an 8 mm FWHM Gaussian kernel. Table S1. Average (absolute) motion parameters for the functional scans. X (mm) Y (mm) Z (mm) Pitch (radian) Roll (radian) Yaw (radian) Average (absolute) Standard Deviation MRI Data Analysis Task-evoked Activation Analysis The main objective of the initial task-evoked activation analysis was to confirm that the task, in comparison with the control condition, produced the expected activations as reported in the existing literature (3). For that purpose, first-level analyses with the appropriate contrasts were set up for each participant using the general linear model (GLM). For the task > control and task < control contrasts the design matrix included the onsets and durations of the task and control conditions as well as the six-movement parameters. Moreover, using another task-evoked activation model, we aimed to assess the hypothesis on the relative engagement of DMN regions in the application versus acquisition phases of the task condition. When comparing these two phases, the design matrix included the onsets of the correct/incorrect responses for the acquisition / application phases of the task and control conditions (modeled as impulses with a fixed duration of zero second) as well as the six-movement parameters. The jittered fixation periods were not modeled in order to avoid a rank deficient design. For the acquisition > application and acquisition < application contrasts, only the correct responses were taken into account. In both GLMs, a default high-pass filter of 128 seconds was employed, which removed the low-frequency signal drifts. The resulting subject-specific contrast maps were carried forward onto group-level analysis using one-sample t-tests. Functional Connectivity Analysis In addition to the task-evoked activation analysis, our next objective was to assess whether the DMN and DAN, the two robustly anti-correlated networks that are hypothesized to be driven by internal and external mentation (4, 5), respectively, would 4

5 display changes in their functional connectivity profiles in response to the acquisition and application phases of the task. For that purpose, the MNI coordinates of two seed regions representing DAN and DMN (5) were selected from the literature. The closest local peaks to these coordinates (in terms of Euclidean distance) were identified in the acquisition > application (for DAN) and acquisition < application (for DMN) contrasts of the grouplevel task-evoked activation analysis. Subsequently, 6 mm (radius) spheres were constructed around the MNI coordinates of the left frontal eye field (FEF) [ ] for the DAN and left posterior cingulate cortex/precuneus (PCC/PCUN) [ ] for the DMN. A strict temporal preprocessing pipeline of nuisance regression included motion and CompCor components attributable to the signal from white matter and cerebrospinal fluid (6) as well as a linear detrending term, eliminating the need for global signal normalization (7). The subject-specific six realignment parameters, the main effect of task-conditions and their first order derivatives were also included in the analysis as potential confounds. In addition to the low-frequency fluctuations that characterized early resting state investigations (4), recent studies indicate the detectable presence of largescale brain networks at high frequencies during task conditions (8). Thus, given the mixed design of this WCST task condition, a low-pass temporal filter was not employed. The Conn functional connectivity toolbox (9) (Version 15.h) was used in order to assess phase-specific changes in functional connectivity (acquisition versus application) using the weighted GLM method. For this purpose, the BOLD time series were first divided into event-specific scans as implemented by the Conn toolbox pipeline. This method accounts for the delay in hemodynamic response by convolving the event regressors (impulse onsets) for each task condition with a rectified hemodynamic response function (HRF). For each event, the scans that were associated with nonzero effects in the resulting time series were weighted by the value of the corresponding time series. This procedure not only adds the expected hemodynamic delay to different task conditions, but also de-weights the initial and final scans within when computing functional correlation measures in order to avoid spurious jumps in BOLD signal, and to minimize the potential cross-talk between adjacent task conditions (9). Following this procedure, seed-based functional connectivity analyses were performed for each subject using the average signal from the 6 mm (radius) spheres placed on the MNI coordinates for the 2 ROIs described above. Group-level analyses were carried out using t-statistics in which a one-sample t-test assessed the group-level spatial extent of DMN and DAN connectivity in the acquisition and application phases, whereas a paired t-test between these phases examined any changes in these networks functional connectivity. Brain and Behavior Correlation Analysis The final question to answer was whether the functional connectivity of the DAN and DMN in the acquisition and application phases of the task condition, respectively, would correlate with better performance as measured by the reaction time to correct responses. This consistency measure is believed to represent the participants purposeful and coherent decisions, and has been previously shown to constitute a reliable response set in WCST (10). The voxel-based correlation analysis involved using the maps obtained from 5

6 the seed-based functional connectivity analyses for the two phases in separate linear regressions with the reaction times to correct responses used as the variable of interest. All reported findings for the MRI data analyses were uncorrected at the voxel-level (p = 0.001) and multiple comparison corrected at the cluster level using the Family Wise Error (FWE) detection technique (p = 0.05). The statistical maps are available on the open access Neurovault repository ( Supplementary Results Behavioral Results Table S2 summarizes the behavioral results obtained for the task and control conditions, as well as the acquisition and application phases. In comparison with the control condition, the participants had a smaller percentage of correct responses (t (27) = , p < ) and a longer reaction time to correct responses (t (27) = 20.03, p < ) in the task condition. In regards to the stratified phases of this WCST variant, the participants were less accurate (t (27) = 17.64, p < ) and slower (t (27) = 8.28, p < ) in the acquisition phase in comparison with the application phase of the task. This phasespecific result of a slower response (t (27) = 6.82, p < ) was also significant in the control condition; however, after multiple comparison correction, no significant difference was observed in accuracy (t (27) = -2.12, p = 0.17). Task-Evoked Activation Analysis Results Table S3 summarizes the differences in brain activity between the task and control conditions. The task > control contrast demonstrated greater activity in a number of cortico-striatal brain regions, all of which have been previously implicated in cognitive flexibility tasks. However, no clusters reached significance in the control > task contrast. Tables S4 and S5 summarize the differential brain activity observed in the acquisition > application and acquisition < application contrasts, respectively. Functional Connectivity Analysis Results While Tables S6-7 summarize the peak clusters in the functional connectivity of the left frontal eye field (FEF) seed for the DAN connectivity; Tables S9-10 report the peak clusters in the functional connectivity of the left posterior cingulate cortex/precuneus (PCC/PCUN) seed for the DMN connectivity. The results of the differential comparison of these two networks between the acquisition and the application phases of the task are given in Tables S8 and S11, respectively. Brain and Behavior Correlation Analysis Results Tables S12-13 summarize the peak clusters in the correlation of reaction time to correct responses with the functional connectivity of the left FEF seed for the DAN connectivity (acquisition phase), and PCC/PCUN seed for the DMN connectivity (application phase), respectively. 6

7 Supplementary Tables Table S2. Behavioral results for the employed variant of the WCST. The average percent correct responses and reaction time to correct responses are given for both the task and control conditions as well as the stratified acquisition and application phases. Behavioral Measure Condition/Phase Mean Standard Deviation Percent correct responses (%) Task Reaction time to correct responses (ms) Acquisition Application Control Acquisition Application Task Acquisition Application Control Acquisition Application Table S3. Task-evoked activity results for the task > control contrast in this variant of the WCST. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. The reverse (control > task) contrast did not reveal any significant results. Task > Control size Peak MNI coordinates AAL label Left precentral gyrus Lobule VI of vermis Right lingual gyrus Right middle frontal gyrus Right angular gyrus Table S4. Task-evoked activity results for the acquisition > application contrast in the task condition. The table represents the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. Acquisition > Application size Peak MNI coordinates AAL label Left superior parietal lobule 7

8 Table S5. Task-evoked activity results for the acquisition < application contrast in the task condition. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. Acquisition < Application size Peak MNI Coordinates AAL label Left postcentral gyrus Left gyrus rectus Left precuneus Right Rolandic operculum Left superior temporal gyrus Left angular gyrus Left hippocampus Table S6. Functional connectivity results for the left frontal eye field seed (DAN) in the acquisition phase of the task condition in this variant of the WCST. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. DAN Acquisition size Peak MNI coordinates AAL label Left middle frontal gyrus Left precentral gyrus Right precentral gyrus Right lobule VIIB of cerebellar hemisphere Left middle frontal gyrus Right middle frontal gyrus Right angular gyrus Right superior frontal gyrus Right middle frontal gyrus Left medial frontal gyrus Left superior frontal gyrus Left angular gyrus Right Rolandic operculum 8

9 Table S7. Functional connectivity results for the left frontal eye field seed (DAN) in the application phase of the task condition in this variant of the WCST. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. DAN Application size Peak MNI coordinates AAL label Left middle frontal gyrus Left precentral gyrus Right middle frontal gyrus Right lobule VI of cerebellar hemisphere Left inferior temporal gyrus Right lobule VIII of cerebellar hemisphere Left middle frontal gyrus Left lobule VIII of cerebellar hemisphere Left inferior parietal lobule Right angular gyrus Right middle frontal gyrus Right inferior occipital cortex Left precuneus Left medial frontal gyrus Left inferior frontal gyrus, pars orbitalis Left lingual gyrus Left superior frontal gyrus Table S8. Comparison of the left frontal eye field (DAN) functional connectivity in the acquisition vs. application phases of the task. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. DAN Acquisition > Application size Peak MNI Coordinates AAL label Left superior temporal gyrus Left middle temporal gyrus Left inferior parietal lobule Left superior parietal lobule 9

10 Table S9. Functional connectivity results for the left posterior cingulate cortex/precuneus seed (DMN) in the acquisition phase of the task condition in this variant of the WCST. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. DMN Acquisition size Peak MNI Coordinates AAL label Left precuneus Left medial orbitofrontal cortex Right middle temporal gyrus Left insula Left thalamus Right superior temporal pole Left inferior frontal gyrus, pars triangularis Right crus II of cerebellar hemisphere Left supplementary motor area Right middle temporal gyrus Right inferior parietal lobule Right inferior frontal gyrus, pars opercularis Left crus II of cerebellar hemisphere Left inferior parietal lobule Right superior frontal gyrus Right crus I of cerebellar hemisphere Left superior frontal gyrus, orbital part Right middle frontal gyrus 10

11 Table S10. Functional connectivity results for the left posterior cingulate cortex/precuneus seed (DMN) in the application phase of the task condition in this variant of the WCST. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. DMN Application size Peak MNI Coordinates AAL label Left precuneus Right middle occipital gyrus Left middle temporal gyrus Right middle temporal gyrus Left lobule IX of cerebellar hemisphere Right middle frontal gyrus Left crus I of cerebellar hemisphere Right inferior temporal gyrus Right crus I of cerebellar hemisphere Right crus II of cerebellar hemisphere Left superior parietal lobule Left crus II of cerebellar hemisphere Left crus II of cerebellar hemisphere Left middle frontal gyrus, orbital part Right inferior parietal lobule Left insula Left supplementary motor area Table S11. Comparison of the left posterior cingulate cortex/precuneus seed (DMN) functional connectivity in the acquisition vs. application phases of the task. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. DMN Acquisition < Application size Peak MNI Coordinates AAL label Right medial orbitofrontal cortex Left precuneus Left angular gyrus Right inferior frontal gyrus, pars triangularis Right supramarginal gyrus Right supplementary motor area Left supramarginal gyrus Left insula Right insula 11

12 Table S12. Correlation of the left frontal eye field (DAN) connectivity and reaction time to correct responses in the acquisition phase of the task. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. FEF Connectivity (DAN) Correlation with Reaction Time in Acquisition Phase size Peak MNI Coordinates AAL Label (T) (x,y,z mm) Right paracentral lobule Table S13. Correlation of the left posterior cingulate cortex/precuneus seed (DMN) connectivity and reaction time to correct responses in the application phase of the task. The table outlines the local peaks identified in the analysis, which have been named according to the Automated Anatomical Labeling (AAL) atlas. The associated FWE-corrected (cluster-level) p value, cluster size, effect size (T value) and MNI coordinates are listed below. PCC/PCUN Connectivity (DMN) Correlation with Reaction Time in Application Phase size Peak MNI Coordinates AAL label (T) (x,y,z mm) Left inferior occipital cortex Left amygdala Right inferior occipital cortex 12

13 Supplementary References 1. Berg EA (1948) A simple objective technique for measuring flexibility in thinking. J. Gen. Psychol. 39: Ashburner J & Friston KJ (2005) Unified segmentation. Neuroimage 26(3): Buchsbaum BR, Greer S, Chang WL, & Berman KF (2005) Meta-analysis of neuroimaging studies of the Wisconsin card-sorting task and component processes. Hum. Brain Mapp. 25(1): Fox MD, et al. (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U. S. A. 102(27): Vincent JL, Kahn I, Snyder AZ, Raichle ME, & Buckner RL (2008) Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. J. Neurophysiol. 100(6): Behzadi Y, Restom K, Liau J, & Liu TT (2007) A component based noise correction method (CompCor) for BOLD and perfusion based fmri. Neuroimage 37(1): Chai XJ, Castanon AN, Ongur D, & Whitfield-Gabrieli S (2012) Anticorrelations in resting state networks without global signal regression. Neuroimage 59(2): Cole MW, Bassett DS, Power JD, Braver TS, & Petersen SE (2014) Intrinsic and task-evoked network architectures of the human brain. Neuron 83(1): Whitfield-Gabrieli S & Nieto-Castanon A (2012) Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connectivity 2(3): Provost JS & Monchi O (2015) Exploration of the dynamics between brain regions associated with the default-mode network and frontostriatal pathway with regards to task familiarity. Eur. J. Neurosci. 41(6):