Dorsal striatum mediates cognitive control, not cognitive effort per se, in decision-making: An event-related fMRI study.

YNIMG-12124; No. of pages: 16; 4C: 3, 7, 8, 10, 13 NeuroImage xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

NeuroImage journal homepage: www.elsevier.com/locate/ynimg

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Full Length Articles

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Brian D. Robertson a,b, Nole M. Hiebert a,b, Ken N. Seergobin a, Adrian M. Owen a,b, Penny A. MacDonald a,b,c,⁎

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Dorsal striatum mediates cognitive control, not cognitive effort per se, in decision-making: An event-related fMRI study

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Article history: Received 9 October 2014 Accepted 28 March 2015 Available online xxxx

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Keywords: Striatum Cognitive control Cognitive effort fMRI Stroop

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Brain and Mind Institute, The Natural Sciences Centre, University of Western Ontario, London, Ontario, Canada N6A 5B7 Department of Physiology and Pharmacology, Medical Sciences Building, Room 216, University of Western Ontario, London, Ontario, Canada N6A 5C1 Clinical Neurological Sciences, London Health Sciences Centre, University Hospital, 339 Windermere Road, London, Ontario, Canada N6A 5A5

a b s t r a c t

Objective: Whether the dorsal striatum (DS) mediates cognitive control or cognitive effort per se in decision-making is unclear given that these effects are highly correlated. As the cognitive control requirements of a neuropsychological task intensify, cognitive effort increases proportionately. We implemented a task that disentangled cognitive control and cognitive effort to specify the particular function DS mediates in decision-making. Methods: Sixteen healthy young adults completed a number Stroop task with simultaneous blood-oxygenationlevel-dependent response (BOLD) measurement using functional magnetic resonance imaging. Participants selected the physically larger number of a pair. Discriminating smaller physical size differences between a number pair increases cognitive effort, but does not demand greater cognitive control. We also investigated the effect of conflict between the physical and numerical dimensions of targets (e.g., 2 6). Selections in this incongruent case are more cognitively effortful and require greater cognitive control to suppress responding to the irrelevant dimension. Enhancing cognitive effort or control increases errors and response times. Despite similar behavioural profiles, our aim was to determine whether DS simply indexes cognitive effort versus specifically mediates cognitive control, using the same data set. Results: As expected, behavioural interference effects occurred for both enhanced cognitive control and/or cognitive effort conditions. Despite similar degrees of behavioural interference, DS BOLD signal only correlated with interference arising due to increased cognitive control requirements in the incongruent case. DS was not preferentially activated for discriminations of smaller relative to larger physical size differences between number pairs, even when using liberal statistical criteria. However, our incongruent and physical size effects conjointly activated regions related to effortful processing (e.g., ACC). Interpretation: We interpret these findings as support for the increasingly-accepted notion that DS mediates cognitive control specifically and does not simply index cognitive effort per se. © 2014 Published by Elsevier Inc.

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2006; Cools et al., 2001; Ruocco, 2005; Vélez-van-Meerbeke et al., 2013; Verte et al., 2005). Identifying the brain regions that mediate cognitive control will elucidate cognitive-behavioural profiles in disease states, potentially suggesting treatment targets and options. Controlling attention and flexibly selecting between options was previously thought to be uniquely the domain of the prefrontal cortex (Butters and Rosvold, 1968; Divac, 1972; Goldman and Rosvold, 1972; Rosvold, 1972), but such higher-order processes have recently been ascribed to the dorsal striatum (DS) as well (Cools and D’Esposito, 2011; Crofts et al., 2001; Hazy et al., 2006; MacDonald and Monchi, 2011). DS is defined as the bulk of the caudate and putamen, which are input regions for a collection of subcortical nuclei known as the basal ganglia (Humphries and Prescott, 2010; Voorn et al., 2004; Wickens et al., 2007). DS lesions in both humans and non-human primates result in deficits in shifting attention between stimuli, especially away from more salient ones (Benke et al., 2003; Cools et al., 2003, 2010; Thoma et al., 2008), in flexibly altering decision-making

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Introduction

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Cognitive control processes are required to consider multiple ideas simultaneously, to direct attention from one stimulus dimension to another, and to shift response strategies in accordance with changes in the environment – often requiring override of more automatic or habitual response tendencies (Botvinick et al., 2001; Cools and D’Esposito, 2011; Liu et al., 2004; MacDonald et al., 2000). Deficits in cognitive control result in impaired decision-making in a number of neurological and psychiatric diseases (Beatty and Monson, 1996; Chamberlain et al.,

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Abbreviations: BOLD, blood-oxygenation-level-dependent; DS, dorsal striatum; FDR, false discovery rate; fMRI, functional magnetic resonance imaging; MNI, Montreal Neurological Institute; PD, Parkinson’s disease; RT, response time. ⁎ Corresponding author at: The Brain and Mind Institute, University of Western Ontario, Natural Sciences Centre, Room 235, London, Ontario, Canada, N6A 5B7. Fax: +1 519 663 3753. E-mail address: [email protected] (P.A. MacDonald).

http://dx.doi.org/10.1016/j.neuroimage.2015.03.082 1053-8119/© 2014 Published by Elsevier Inc.

Please cite this article as: Robertson, B.D., et al., Dorsal striatum mediates cognitive control, not cognitive effort per se, in decision-making: An event-related fMRI study, NeuroImage (2014), http://dx.doi.org/10.1016/j.neuroimage.2015.03.082

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Participants

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Sixteen healthy individuals (8 males, 8 females; mean age 23 years; range 19–27) participated in this experiment. Participants were all healthy, right-handed, and each provided written, informed consent according to the Declaration of Helsinki (1991). All participants had completed at least 12 years of education (range 14–21 years). A small monetary compensation was provided to each participant. This project was approved by the Health Sciences Research Ethics Board of the University of Western Ontario.

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Stimuli and design

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In this study, participants completed a number Stroop task with simultaneous measurement of regional BOLD activity using fMRI. During each trial, two numbers, from among the set: 1, 2, 3, 7, 8, or 9, appeared side-by-side, each in Arial font size 40, 55, 70, or 85. Participants were asked to select, as quickly yet accurately as possible, the number that was physically larger in the pair. A single block of 132 randomly ordered trials that included 48 congruent, 48 incongruent, and 36 control trials was performed by each participant (Fig. 1). In the incongruent condition, physical size and numerical magnitude were inconsistent (e.g., 9 1). In the congruent condition, physical size and numerical value were consistent (e.g., 9 1). In the control condition, the numbers in the pair differed only in physical size (e.g., 9 9).

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increased in the incongruent case—where cognitive control as well as cognitive effort demands are greatest (MacLeod, 1991). Varying the magnitude of the physical size difference between number pairs on the relevant dimension creates the condition for investigating the potential role of DS in cognitive effort. It has been shown previously that longer RTs and higher error rates result when selecting between integers that are closer versus more distant in physical size (Cohen Kadosh et al., 2005; Kaufmann et al., 2005). Similarly, RTs and error rates are increased for discriminations of numerical magnitude when number pairs are symbolically closer (e.g., 1 2) relative to more distant (e.g., 1 8) along the number continuum (Moyer and Landauer, 1967). Decreasing the physical size differences of number pairs increases the similarity and hence, the difficulty or cognitive effort required to discriminate between the alternatives. Smaller versus larger differences between pairs in this comparison task do not differ systematically in the need to shift attention away from salient but irrelevant stimuli or to suppress more automatic or habitual responses (i.e., cognitive control; Botvinick et al., 2001; Cools and D’Esposito, 2011; Liu et al., 2004; MacDonald et al., 2000). From a behavioural perspective, we expected RTs to increase during trials with high cognitive control requirements (i.e., the incongruent condition) as well as during trials with high cognitive effort demands (i.e., number pairs with smaller physical size differences). However, if DS mediates cognitive control specifically, DS blood-oxygenationlevel-dependent (BOLD) signal should be greater during incongruent relative to control and/or congruent trials (i.e., Stroop interference), but not for trials with smaller relative to larger physical size differences between number pairs (i.e., the physical size difference effect). Additionally, a negative correlation between DS BOLD signal and Stroop interference scores would indicate a role for DS in cognitive control. Alternatively, if DS merely indexes the cognitive effort required to make decisions, increased DS BOLD signal should correlate positively with RTs during trials that take longer to resolve (i.e., Stroop interference as well as physical size difference effect). In this way, we have devised a means for dissociating the role of DS in cognitive control and cognitive effort, within the same task, using the same data.

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strategies or response sets (Benke et al., 2003; Cameron et al., 2010; Ell et al., 2006; Grahn et al., 2008; Leber et al., 2008; Yehene et al., 2008), in suppressing more automatic responses (Benke et al., 2003; Cameron et al., 2010; MacDonald et al., 2011; White, 2009), and in updating goals (Grahn et al., 2008; Hazy et al., 2006; Vakil et al., 2004). Parkinson’s disease (PD) produces progressive loss of neurons in the substantia nigra—the source of dopamine to DS. Impairments for PD patients in switching attention away from a stimulus (Cools et al., 2003, 2010; Hayes et al., 1998; Shook et al., 2005) or response (Shook et al., 2005; Hood et al., 2007) to another, as well as in selecting between alternatives when there is conflict (MacDonald et al., 2011) also support the notion that DS mediates decisions or selections that require deliberation in the face of competing options or changing circumstances. Concurring with this view, these deficits in PD are redressed by dopamine replacement (Shook et al., 2005; Hood et al., 2007; MacDonald et al., 2011). Finally, many neuroimaging experiments have also shown preferential activity in DS at the time of flexible decision-making and response selection during conflict (Grinband et al., 2006; Monchi et al., 2001; Monchi et al., 2006; Rogers et al., 2000; van Schouwenburg et al., 2010; Ali et al., 2010). A generally unacknowledged problem with the conclusions about DS drawn from these investigations is that as cognitive control demands are heightened, the cognitive effort required to complete the tasks correspondingly increases. Cognitive effort has been defined as the proportion of limited-capacity central processing engaged (Russo and Dosher, 1983), the number of elementary processes enacted (Bettman et al., 1990), or the duration over which cognitive resources are expended (Christensen-Szalanski, 1980). Cognitive effort is experimentally dissociable from cognitive control processes. Tests of elaborative rehearsal, vigilance for targets in single visual or auditory streams (Brand and Jolles, 1987), or item comparisons along a single dimension or feature that vary in similarity and hence discriminatory difficulty (Moyer and Landauer, 1967) manipulate cognitive effort independent of cognitive control. The vast majority of studies confound cognitive effort and cognitive control without recognizing or noting this fact. Despite this, the contention that DS engagement could simply index cognitive effort (Boehler et al., 2011; Krebs et al., 2012; Schmidt et al., 2012) remains a minority position in the literature that has not been critically tested. Addressing this confound and more precisely defining the role of DS in cognition was the aim of the current study. We used a number Stroop task that allowed for independent manipulation of cognitive control and cognitive effort demands. Briefly, in the version of the number Stroop task used here, a number pair was displayed, and participants were asked to select the number in the pair that was physically larger. The numbers could differ in both physical size, the relevant dimension on which participants based their responses, and numerical value, the irrelevant dimension that was always extraneous to enacting the correct response. When the relevant and irrelevant dimensions were incongruent, this provided the means for investigating cognitive control processes. For example, if the physically larger number in a pair is also numerically smaller (e.g., 2 6), a conflict exists between the relevant and irrelevant dimensions with respect to the concept of magnitude. In this example, the participant must resolve this conflict by directing attention to the relevant dimension, where ‘2’ is the physically larger number in the pair, while ignoring the irrelevant dimension in which ‘2’ is the numerically smaller number. Trials with number pairs that differ in physical size, but not numerical magnitude, constituted our control condition (e.g., 2 2). The congruent case arose when the relevant and irrelevant dimensions agreed (e.g., 2 6), in which responding is often faster and less error-prone (Macleod, 1991). Response interference was calculated as the response times (RTs) and error rates in the incongruent condition minus those in the control and congruent conditions. Further, DS activity, assessed using functional magnetic resonance imaging (fMRI) for incongruent compared to control or congruent trials, was contrasted to determine whether DS activity is

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Fig. 1. Number Stroop trial types used in this experiment. Participants were asked to select the physically larger number of the pair. Trials were either: incongruent, in which physically larger numbers are numerically smaller; congruent, where physically larger numbers are numerically larger; or control, in which numbers differ in physical size, but not numerical magnitude. Physical size differences between number pairs were used to manipulate cognitive effort requirements. Trial congruency was used to manipulate cognitive control requirements. Correct responses are shown here in red, but all numbers were black during the experiment.

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Procedure

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Trials were presented on a projection screen inside an MRI machine. The progression of a number Stroop trial is shown in Fig. 2. Trials began with a 500 millisecond (ms) fixation period, during which a small cross appeared in the center of the screen to capture the attention of the participant. A 250 ms blank screen followed this fixation period. Afterward, a number pair was displayed on the screen – one number on the left and one number on the right. This display period lasted until the participant logged their response with their right hand using a button box. Pressing the button under their right index finger signified a selection of the number on the left side of the screen and the button under their middle finger signified a selection of the number on the right side of the screen. Once a selection was made, an inter-trial interval of variable length (525–7000 ms; mean = 2500 ms) occurred before the presentation of the subsequent fixation period.

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Imaging acquisition

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Functional MRI data were collected in a 3 Tesla Siemens Magnetom Trio with Total Imaging Matrix MRI at Robarts Research Institute at the University of Western Ontario. A scout image was obtained for positioning the participant and T1 for anatomical location. There were two runs of T2*-weighted functional acquisitions. The run consisted of one block of 132 trials. All runs lasted an average of 12 minutes with one whole brain image consisting of 43, 2.5-mm-thick slices taken every 2.5 s. The field of view was oriented along the anterior and posterior commissure with a matrix of 88 × 88 pixels, and an isotropic voxel size of 2.5 × 2.5 × 2.5 mm3. The echo time was 30 ms, and the flip angle was 90°.

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fMRI data analyses

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Statistical Parametric Mapping version 5 (SPM5; Wellcome Department of Imaging Neuroscience, London, United Kingdom) and Matrix Laboratory (MATLAB; MathWorks, Inc., Natick, Massachusetts, United States) were used to complete fMRI analysis. Images were slice-time corrected, reoriented for participant motion, spatially normalized to the standard Montreal Neurological Institute (MNI) template, and smoothed with an 8 mm full-width, half-maximum Gaussian kernel. Brain regions mentioned in this paper were defined using the Harvard-Oxford Subcortical and Cortical Atlases in the FMRIB Software Library version 5.0 (FSL v5.0; Analysis Group, FMRIB, Oxford, United Kingdom). All x, y, z values are reported in MNI space. Each participant’s data were modeled using fixed effects analyses in SPM5. Predictor functions were formed by convolving onsets and durations of psychological events of interest with the canonical hemodynamic response function. Trials were organized by both congruency (i.e., congruent, incongruent, or control) and physical size differences

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All analyses were completed using Systat version 13.1 (Systat Software, San Jose, California). RTs were defined as the period from onset of a number pair until the participant made a response using the button box. Two 3 × 2 analyses of variance (ANOVAs) were performed with congruency (incongruent vs. congruent vs. control) and physical size differences (close vs. far) as within-subject variables to examine the effect of these variables on RTs in one ANOVA, and error rates in the other. Post-hoc tests were performed to understand any main effects. Using two 2 × 2 ANOVAs, with congruency (incongruent vs. congruent) and numerical magnitude differences (close vs. far) as within-subject variables, we further investigated whether the numerical magnitude difference between number pairs on the irrelevant dimension affected participant RTs, error rates, or interacted with the congruency effect. The alpha level was set at 0.05 for all comparisons.

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Physical size and numerical magnitude differences between pairs also varied systematically, with possible differences of 15, 30, or 45 font points on the relevant physical size dimension and of 1, 2, 6, or 7 on the to-be-ignored, irrelevant numerical magnitude dimension. Physical size was the relevant dimension because participants were instructed to select the physically larger number of the pair. Numerical magnitude was the irrelevant/distracting dimension because decisions were never based on this information. With respect to the relevant dimension, trials were classified as “close” if the font size difference was 15 points (e.g., font size 40 vs. font size 55) or “far” if the font size difference was 45 points (e.g., font size 40 vs. font size 85). To balance our design and add greater variability to physical size differences between number pairs, trials with an additional, intermediate physical size difference of 30 font points were included in the experiment, but were not considered in our analyses. For numerical magnitude, differences of 1 or 2 between the number pair were considered “close”, whereas differences of 6 or 7 were considered “far”. The physical and numerical difference variables were orthogonal and fully crossed with the congruency variable, allowing for dissociation of their effects. There were 44 trials with font size differences of 15 points (i.e., close trials), 44 trials with font size differences of 30 points, and 44 trials with font size differences of 45 points (i.e., far trials). Additionally, there were 66 trials in which the difference between number pairs on the irrelevant, numerical magnitude dimension was classified as numerically close (i.e., numerical distance of 1 or 2) and 66 trials that the difference between number pairs on the irrelevant numerical magnitude dimension was classified as numerically far (i.e., numerical distances of 6 or 7). The close-far variable on the relevant and irrelevant dimensions was fully balanced, such that there were an equal number of close relevant-close irrelevant, close relevant-far irrelevant, far relevant-close irrelevant, and far relevantfar irrelevant pairings.

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Fig. 2. The progression of a number Stroop trial. a) Trials began with a 500 ms fixation period during which a cross was displayed in the middle of the screen to draw the participant’s attention. b) A 250 ms blank screen was then shown. c) The display period began, lasting until the participant logged his/her response via button press. d) An inter-trial interval of variable duration (525–7000 ms; mean = 2500 ms) occurred.


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Mean RTs and error rates sorted by congruency, physical size differences, and numerical magnitude differences are presented in Table 1. Interference (incongruent – control, incongruent – congruent)

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Table 1 Mean RTs (ms ± SEM) and error rates (% ± SEM) for trials sorted by congruency, physical size difference, and numerical magnitude difference.

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Incongruent

– Close Intermediate Far – – – Close Intermediate Far – – – Close Intermediate Far Close Intermediate Far

– – – – Close Far – – – – Close Far – – – – – – –

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Fig. 3. Stroop interference and facilitation scores. Interference scores are (mean incongruent RT – mean congruent RT, and mean incongruent RT – mean control RT). Facilitation score is (mean congruent RT – mean control RT). Error bars represent ± SEM. Close and far trials of each congruency type (collapsed across numerical magnitude difference) were used. One-sample t-tests (theoretical mean = 0) were completed for each bar. Triple asterisks denote significantly different mean RTs at p b 0.001. A single asterisk denotes significantly different mean RTs at p b 0.05. Cong, congruent; Ctrl, control; Incong, incongruent.

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and facilitation (congruent – control) effects are shown in Fig. 3. Onesample t-tests (theoretical mean = 0) indicate significant response slowing in our interference (incongruent – control, t(15) = 6.319, p b 0.001; incongruent – congruent, t(15) = 8.525, p b 0.001) contrasts and faster responding in our facilitation (congruent – control, t(15) = 2.167, p b 0.05) contrast (Fig. 3). An additional one-sample t-test (theoretical mean = 0) indicates significant response slowing (close – far, t(15) = 4.047, p b 0.005) during trials with close physical size differences compared to trials with far physical size differences (Fig. 4). A one-way ANOVA found no differences in the magnitude of response slowing between our interference (incongruent – control, incongruent – congruent) and close – far contrasts (F(2, 45) = 0.5157, MSE = 1152, p = 0.60). This indicates that an equal amount of cognitive effort was required to respond correctly during incongruent trials and trials with close physical size differences.

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(i.e., close or far) between the number pairs displayed during trials. Again, these effects were orthogonal and fully crossed so each variable could be investigated by collapsing across the other variable. A 3 × 2 fully factorial ANOVA, with congruency (congruent vs. incongruent vs. control) and physical size difference (close vs. far) as within-subject variables was performed on BOLD signal. To match our behavioural analyses, pairwise effects were investigated to better understand any main effects. In addition, to determine whether DS is differentially implicated in cognitive control processes or engaged generally in conditions with high cognitive effort demands, conjunction analyses between Stroop interference and close-far physical distance contrasts were performed at the whole-brain level. Disjunction analyses were also completed to demonstrate that DS is significantly more active in our incongruent – congruent contrast than our close – far contrast. We followed these analyses with region of interest (ROI) analyses conducted using peak MNI coordinates in DS (± 16, − 10, 18) taken from a Stroop interference study by Peterson et al. (1999). In addition to the DS ROIs intended to distinguish engagement in cognitive control versus cognitively effortful processing, we selected an ROI in the anterior cingulate cortex (ACC; ± 11, 1, 50; Ansari et al., 2006). An ACC ROI was used because this brain region is frequently preferentially engaged in tasks that demand significant attention or sustained cognitive effort (Shenhav et al., 2013; Ansari et al., 2006; Kaufmann et al., 2005; MacDonald et al., 2014). Therefore, we supposed that this region might be commonly activated for interference and physical size comparison contrasts. ROIs used in our analyses were 5 mm spheres drawn around the coordinates listed in the studies cited above. Finally, brain-behaviour correlations of BOLD signal with our interference scores due to congruency and physical distance were performed.

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477.75 ± 19.01 553.79 ± 22.23 464.17 ± 18.12 440.56 ± 18.92 468.44 ± 16.79 484.16 ± 23.91 423.24 ± 16.90 450.05 ± 21.25 424.80 ± 17.98 406.17 ± 13.76 423.61 ± 15.96 424.92 ± 17.53 436.69 ± 18.85 477.58 ± 27.68 431.31 ± 15.11 409.60 ± 15.94 487.64 ± 22.10 440.40 ± 17.70 417.65 ± 15.84

Error rates (% ± SEM) 7.55 ± 1.45 11.33 ± 3.34 3.52 ± 0.99 3.52 ± 1.61 5.73 ± 5.67 8.07 ± 8.40 4.56 ± 0.39 3.52 ± 0.98 3.13 ± 0.81 3.13 ± 0.81 3.39 ± 0.57 3.39 ± 0.57 3.65 ± 0.42 2.60 ± 1.00 2.60 ± 1.00 1.56 ± 0.84 7.10 ± 1.19 3.84 ± 0.45 3.69 ± 0.80

Horizontal dashes indicate that trials used to determine RTs and error rates in that row are collapsed across the column variable. With respect to the physical size variable, “Close” denotes a font size difference of 15 points, “Intermediate” denotes a difference of 30 points, and “Far” denotes a difference of 45 points. “Intermediate” physical size trials were not used in our subsequent analyses, but are listed here for the sake of completeness. With respect to the numerical magnitude variable, “Close” denotes numerical magnitude differences of 1 or 2 and “Far” denotes numerical magnitude differences of 6 or 7.

Fig. 4. Response slowing due to physical size differences. Response slowing was determined by subtracting mean RT during far trials from mean RT during close trials. Error bars represent ± SEM. Close and far trials were collapsed across congruency and numerical magnitude difference. A one-sample t-test (theoretical mean = 0) indicated significant response slowing at p b 0.005.


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14.36 13.86 10.99 13.58 13.52 13.19 13.03 12.97

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We examined BOLD signal in a 3 × 2 fully factorial model, with congruency (incongruent vs. congruent vs. control) and physical size differences (close vs. far) as within-subject variables. As shown in Table 2, right dorsal putamen (peak coordinates: 27, -7, 1; F(1, 90) = 12.35; cluster size = 3) was significant for main effect of congruency at p b 0.05 with false discovery rate (FDR) correction. All regions differentially modulated by congruency are listed in Table 2. To mirror our behavioural analyses, we investigated brain regions that were preferentially activated by interference (incongruent – control, incongruent – congruent) and the reverse contrasts (control –

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R hippocampus R frontal orbital cortex R amygdala L planum temporale L juxtapositional lobule cortex (ext. into anterior cingulate cortex) L/R occipital pole L insular cortex

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Coordinates (x, y, z)

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R frontal operculum cortex R dorsolateral prefrontal cortex R orbitofrontal cortex R insular cortex R posterior cingulate gyrus R thalamus R white matter L precentral gyrus L temporal fusiform cortex

Cluster size

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Table 2 Regions significant for main effect of congruency.

T

390

We ran a 3 × 2 ANOVA on RTs, with congruency (incongruent vs. congruent vs. control) and physical size difference between number pairs (close vs. far) as within-subject variables to determine the effect of these factors on RTs. Significant main effects of congruency (F(2, 90) = 6.203, MSE = 41589, p b 0.005) and of physical size difference (F(1 90) = 20.33, MSE = 136310, p b 0.001) were observed. There was no significant interaction between congruency and physical size (F(2, 90) = 1.442, MSE = 9670, p = 0.24). Bonferroni-corrected post-hoc t-tests revealed that participants had longer RTs during incongruent trials than during congruent (t(90) = 3.350, p b 0.005) or control (t(90) = 2.618, p b 0.05) trials. However, mean RTs during congruent and control trials did not differ significantly (t(90) = 0.73, p N 0.99). We performed an analogous 3 × 2 ANOVA on error rates, with congruency (incongruent vs. congruent vs. control) and physical size differences between number pairs (close vs. far) as within-subject variables. Main effects of congruency (F(2, 90) = 5.496, MSE = 249.9, p b 0.01) and physical size difference (F(1, 90) = 5.013, MSE = 227.9, p b 0.05) were observed. No significant interaction between congruency and physical size difference (F(2, 90) = 2.972, MSE = 135.1, p = 0.056) was seen on error rates. Bonferroni-corrected post-hoc t-tests revealed that participants made more errors during incongruent trials than during congruent (t(90) = 2.433, p b 0.05) or control (t(90) = 3.167, p = 0.01) trials, but error rates for control and congruent trials did not differ (t(90) = 0.7338, p N 0.99). Further, participants made more errors during close incongruent trials compared to close congruent (t(90) = 3.277, p b 0.005) or close control (t(90) = 3.659, p b 0.005) trials, but error rates for close congruent and close control trials did not differ (t(90) = 0.3823, p N 0.99). There were no differences in error rates for far trials crossing the congruency variable. We next examined whether the numerical magnitude difference between number pairs (i.e., the irrelevant dimension) affected the size of the facilitation or interference effects using a 2 × 2 ANOVA, with congruency (incongruent vs. congruent) and numerical magnitude difference between number pairs (close vs. far) as within-subject factors. A main effect of congruency (F(1, 60) = 9.308, MSE = 63905, p b 0.005), but not of numerical magnitude (F(1, 60) = 0.5071, MSE = 3482, p = 0.48) was observed. Most important, there was no significant interaction between congruency and numerical magnitude difference (F(1, 60) = 0.0754, MSE = 517.7, p = 0.78), suggesting that the size of interference and facilitation effects was not significantly affected by the numerical magnitude difference between number pairs on the irrelevant dimension. A similar 2 × 2 ANOVA, with congruency (incongruent vs. congruent) and numerical magnitude difference (i.e., the irrelevant dimension) between number pairs (close vs. far) as within-subject factors was used to investigate the effects of both factors on error rates. A main effect of congruency (F(1, 60) = 12.86, MSE = 549.3, p b 0.001), but not of numerical magnitude difference (F(1, 60) = 0.0572, MSE = 2.441, p = 0.81) was observed. There was no significant interaction between congruency and numerical magnitude difference (F(1, 60) = 0.2286, MSE = 9.766, p = 0.63), suggesting that error rate was not significantly affected by the difference between number pairs on the irrelevant dimension.

E

338 339

5

All F values listed above were found at p b 0.05 with FDR correction. Coordinates are listed t2:41 in MNI space. ext, extending; L, left; R, right. t2:42

incongruent, congruent – incongruent), as well as contrasts of congruent and control conditions. Table 3 presents brain regions that were significant at p b 0.05 with FDR correction for these pairwise comparisons. In the incongruent – congruent contrast, activations in right dorsal caudate (peak coordinates: 21, 5, 25; t = 3.33; cluster size = 54), left dorsal caudate (peak coordinates: -18, -4, 19; t = 2.85; cluster size = 2), and left dorsal putamen (peak coordinates: -30, -1, 10; t = 2.73; cluster size = 2) all survived FDR correction. The significant activations for these contrasts are shown in Fig. 5. In addition, there were right dorsal caudate (peak coordinates: 27, -7, 1; t = 3.51) and left dorsal caudate (peak coordinates: − 18, − 22, 19; t = 3.10) peaks found as secondary activations within large clusters originating in the right postcentral gyrus and left superior temporal gyrus, respectively. Neither dorsal caudate nor putamen were significantly more active in the remaining pairwise comparisons (i.e., incongruent – control; control – incongruent; congruent – incongruent; congruent – control; control – congruent). However, given that striatum was predicted in our incongruent – control contrast, and because a region of DS was significant at p b 0.05 with FDR correction in our omnibus test of congruency, we further explored striatum in the incongruent – control contrast using p b 0.005 uncorrected for multiple comparisons with a cluster size cutoff of 10 contiguous voxels. BOLD signal in right dorsal putamen (peak coordinates 36, − 1, 4; t = 3.42; cluster size = 48), and left dorsal putamen (peak coordinates − 30, − 1, 13; t = 3.11; cluster size = 13) were significant at this more liberal threshold for the incongruent –


402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426

6 t3:1 t3:2


Table 3 Significant activations in pairwise comparisons of incongruent, congruent, and control trials. Contrast

Anatomical Region


t-stat

Cluster size

t3:4 t3:5 t3:6 t3:7 t3:8 t3:9 t3:10 t3:11 t3:12 t3:13 t3:14 t3:15 t3:16 t3:17 t3:18 t3:19 t3:20 t3:21 t3:22 t3:23 t3:24 t3:25 t3:26 t3:27 t3:28 t3:29 t3:30 t3:31 t3:32 t3:33 t3:34 t3:35 t3:36 t3:37 t3:38 t3:39 t3:40 t3:41 t3:42 t3:43 t3:44 t3:45 t3:46 t3:47 t3:48 t3:49 t3:50 t3:51 t3:52 t3:53 t3:54 t3:55 t3:56 t3:57 t3:58 t3:59 t3:60 t3:61 t3:62 t3:63 t3:64 t3:65 t3:66 t3:67 t3:68 t3:69 t3:70 t3:71 t3:72 t3:73 t3:74

incongruent – congruent

R dorsal caudate L dorsal caudate L dorsal putamen R postcentral gyrus (R dorsal putamen) L superior temporal gyrus (L dorsal caudate) L postcentral gyrus L cerebellum R inferior temporal gyrus

21, 5, 25 −18, −4, 19 −30, −1, 10 66, −7, 13 (27, −7, 1) −60, −4, 1 (−18, −22, 19) −33, −34, 46 −18, −58, −17 60, −58, −11 48, −22, −23 21, −25, −11 18, 32, −17 −12, 5, 46 0, −91, 22 −39, 2, −17 −21, −19, −11 39, 44, 28 30, 29, 10 12, −19, 4 21, −31, 7 −42, −28, −17 39, −13, −23 3, −43, 4 3, −34, 28 −39, 38, 34 −36, −49, 19 −54, −67, −11 48, 50, 13 24, −61, −14 0, −70, 7 30, −82, −20 −36, −76, −23 −18, −31, 4 −15, −46, −5 −45, −52, −5 −12, 17, −11 24, −61, 10 45, 32, 7 12, −88, −11 −24, −40, −29 21, −25, 58 3, −49, 61 – – – – −6, −85, 37 69, −25, 31 −63, −7, −2 18, 32, −17 18, −19, 7 −30, −25, 16 −18, −28, −32 −24, 8, −23 21, 59, −5 27, 47, 40 33, 32, 10 −30, 44, 37 −30, −31, −23 18, −22, −11 −51, 14, −20 −3, 38, −14 63, −37, −11 48, 29, 10 −21, −4, −17 −42, −28, 40 63, −52, −11 42, 50, 13 −27, −7, −23 30, 38, −17

3.33 2.85 2.73 4.76 (3.51) 4.62 (3.10) 4.35 4.32 4.31 3.45 4.17 4.16 3.79 3.79 3.72 3.60 3.54 3.46 3.37 2.78 3.29 2.85 3.13 2.82 3.12 3.07 3.06 3.02 3.02 3.01 3.01 3.00 2.98 2.96 2.95 2.79 2.78 2.78 2.73 2.72 2.71 2.67 – – – – 5.28 4.58 4.56 4.37 3.34 3.21 3.18 3.14 3.10 3.07 3.03 2.93 2.88 2.87 2.85 2.85 2.85 2.84 2.82 2.82 2.72 2.63 2.62 2.61

54 2 2 2368 * 596 * 554 134 157 14 448 42 107 68 18 35 126 20 23 1 14 3 13 4 12 8 10 20 39 14 2 10 10 25 3 3 11 2 1 1 1 2 – – – – 2425 2668 238 42 66 38 20 8 12 15 3 20 7 3 2 10 4 3 5 4 2 2 1 1

t3:75 t3:76

L temporal fusiform cortex

D E T C

E

L middle frontal gyrus L supramarginal gyrus L lateral occipital cortex R ventromedial prefrontal cortex R temporal occipital fusiform cortex L/R lingual gyrus R occipital fusiform gyrus L occipital fusiform gyrus L thalamus L lingual gyrus L inferior temporal gyrus L subcallosal cortex R intracalcarine cortex R inferior frontal gyrus R lingual gyrus L cerebellum R precentral gyrus R precuneus – – – – L cuneus R supramarginal gyrus L superior temporal gyrus R frontal orbital cortex R thalamus L insular cortex L cerebellum L frontal orbital cortex R orbitofrontal cortex R dorsolateral prefrontal cortex R inferior frontal gyrus L dorsolateral prefrontal cortex L temporal fusiform cortex R hippocampus L temporal pole L frontal medial cortex R middle temporal gyrus R inferior frontal gyrus L amygdala L postcentral gyrus R middle temporal gyrus R ventrolateral prefrontal cortex L hippocampus R orbitofrontal cortex

U

N

C

O

R

R

congruent – incongruent incongruent – control control – incongruent congruent – control control – congruent

O

P

R posterior cingulate gyrus

R O

R parahippocampal gyrus R frontal orbital cortex L juxtapositional lobule cortex (ext. into anterior cingulate cortex) L/R occipital pole L insular cortex L hippocampus R dorsolateral prefrontal cortex R frontal operculum cortex R thalamus

F

t3:3

All t values listed above were found at p b 0.05 with FDR correction. Secondary DS activations are listed in parentheses below their primary activations. Coordinates are listed in MNI space. ext, extending; L, left; R, right.


7

T

E

D

P

R O

O

F


433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455

R

R

431 432

N C O

429 430

control contrast. No DS activations were seen at this threshold in the control – incongruent contrast. In our 3 × 2 ANOVA, we found no regions in DS that were significant for main effect of physical size difference at p b 0.05 with FDR correction for multiple comparisons. All regions significantly modulated by physical size difference are shown in Table 4. To be entirely sure that DS was not implicated in this effect, we set a very liberal threshold of p b 0.05 uncorrected for multiple comparisons, with a cluster size cutoff of 10 contiguous voxels. We again found no significant voxels within DS. We then investigated pairwise contrasts of close – far and far – close at p b 0.05 with FDR correction (Table 5). There were no significant activations in DS in either contrast. Using a very liberal threshold of p b 0.05 uncorrected for multiple comparisons, with a cluster-size cutoff of 10 contiguous voxels, there were no significant activations in DS. A single non-significant activation in DS was noted in right dorsal putamen (peak coordinates: 30, 5, 10; t = 1.70; cluster size = 4) that disappeared at a threshold of p b 0.01 uncorrected for multiple comparisons. In the same 3 × 2 ANOVA with the same statistical thresholds listed above, clusters extending into ACC – originating at the border of the left juxtapositional lobule – were observed in our main effect contrasts for both congruency (peak coordinates −12, 5, 46; F(1, 90) = 14.36; cluster size = 9) and physical size difference (peak coordinates − 15, 2, 43; F(1, 90) = 15.22; cluster size = 14). In subsequent pairwise comparisons, both ACC activations were also seen in our incongruent – congruent (peak coordinates −12, 5, 46; t = 3.79; cluster size = 107) and close – far (peak coordinates −15, 2, 43; t = 3.90; cluster size = 66) contrasts. As well, left supramarginal gyrus (peak coordinates − 36, − 49, 19; t = 3.07; cluster size = 8) was significant in our incongruent –

U

427 428

E

C

Fig. 5. Axial slices showing significant activations for our BOLD signal analyses. Activations seen in contrasts of interest are shown in vertical columns for z = 1, 10, and 19. Significant activations (p b 0.05 with FDR correction) in DS are circled in green.

congruent contrast. Right supramarginal gyrus was significant in 456 both the main effect of physical size difference (peak coordinates 457 69, -22, 28; F(1, 90) = 11.21; cluster size = 4) and pairwise 458 t4:1 t4:2

Table 4 Regions significant for main effect of physical size difference. Anatomical Region


F value

Cluster size

R middle temporal gyrus L inferior temporal gyrus R precentral gyrus L precentral gyrus R ventrolateral prefrontal cortex L lateral occipital cortex L superior parietal lobule L cerebellum L posterior cingulate gyrus L juxtapositional lobule cortex (ext. into anterior cingulate cortex) R frontal medial cortex R orbitofrontal cortex R occipital pole R supramarginal gyrus R inferior frontal gyrus R precuneus L precuneus L brain stem L middle frontal gyrus L inferior frontal gyrus L paracingulate gyrus L superior temporal gyrus

54, −55, 11 −45, −55, −8 45, 8, 25 −45, 2, 28 48, 38, 16 −45, −76, 34 −27, −55, 49 −3, −73, −23 −6, −37, 43 −15, 2, 43

36.06 1518 29.68 447 29.64 353 29.41 194 22.91 171 21.25 89 17.98 272 17.70 41 15.94 26 15.22 14

3, 32, −17 21, 47, −14 18, −91, 4 69, −22, 28 57, 17, 7 9, −55, 10 −12, −58, 16 −9, −22, −32 −45, 35, 19 −30, 32, 16 −6, 53, −2 −63, −10, 1

12.54 11.60 11.57 11.21 11.03 10.99 10.68 10.54 10.25 10.02 9.93 9.28

108 4 8 4 12 13 13 1 5 4 5 2

t4:3 t4:4 t4:5 t4:6 t4:7 t4:8 t4:9 t4:10 t4:11 t4:12 t4:13 t4:14 t4:15 t4:16 t4:17 t4:18 t4:19 t4:20 t4:21 t4:22 t4:23 t4:24 t4:25 t4:26

All F values listed above were found at p b 0.05 with FDR correction. Coordinates are listed t4:27 in MNI space. ext, entending; L, left; R, right. t4:28


8 t5:1 t5:2


Table 5 Significant activations for pairwise comparisons of close and far trials.

t6:1 t6:2

Table 6 Conjunction analyses of our interference and close – far contrasts.

t5:3

Contrast

Anatomical Region


t-stat Cluster size

Conjunction

Anatomical Region


t5:4 t5:5 t5:6 t5:7 t5:8 t5:9 t5:10 t5:11 t5:12 t5:13 t5:14 t5:15 t5:16 t5:17 t5:18 t5:19 t5:20 t5:21 t5:22 t5:23 t5:24 t5:25

close – far

R inferior temporal gyrus L inferior temporal gyrus R precentral gyrus L precentral gyrus

54, −55, −11 −45, −55, −8 45, 8, 25 −45, 2, 28 −33, −4, 43 48, 38, 16 −27, −55, 49 −3, −73, −23 −15, 2, 43

6.01 5.45 5.44 5.42 2.82 4.79 4.24 4.21 3.90

1862 729 523 264 6 217 470 81 66

incongruent – congruent ∩ close – far

60, −58, −11 4.31 36, −31, 37 4.06 −12, 2, 43 3.43

21, 47, −14 36, 53, −14 36, 62, 1 36, 44, −17 69, −22, 28 −9, −22, −32 −45, 35, 19 −63, −10, 1 −21, −76, 7 −45, 47, −14 6, −37, 61 −39, −49, −26 60, −22, −2 −36, −4, −29 6, −91, 25 −12, −19, −29 39, −1, −20 12, −70, −14 27, −58, 4 15, 2, 55 21, 8, 25 24, −13, 10 15, 26, 7 18, −31, 1 −24, −70, 28 −27, −73, 25 −66, −25, −5 –

3.41 2.98 2.75 2.73 3.35 3.25 3.20 3.05 2.94 2.92 2.88 2.85

15 3 1 1 11 2 37 11 19 5 4 2

2.85 2.81 2.81 2.81

9 1 1 1

R inferior temporal gyrus R postcentral gyrus L juxtapositional lobule cortex (ext. into anterior cingulate cortex) R precentral gyrus R supramarginal gyrus L postcentral gyrus L supramarginal gyrus R inferior frontal gyrus L lateral occipital cortex L superior temporal gyrus R ventrolateral prefrontal cortex R superior parietal lobule R lateral occipital cortex R dorsolateral prefrontal cortex R inferior temporal gyrus R supramarginal gyrus R angular gyrus R lateral occipital cortex L superior parietal lobule L supramarginal gyrus

2.79 2.77 2.76 2.75 2.74 2.73 2.72 2.71 2.70 2.68 2.67 –

1 1 2 1 2 1 2 1 1 1 1 –

R white matter

R lateral ventricle R thalamus L lateral occipital cortex

far – close

L middle temporal gyrus –

471 472 473 474 475 476 477 478 479 480 481 482

4.00 3.35 3.32 3.22 3.17 2.77

originating in the right postcentral gyrus (peak coordinates 66, −7, 13; t(1, 90) = 4.76; cluster size = 1881) were seen. Additional significant voxels in DS, which fell below our 5-voxel cluster size cutoff are also highlighted in Fig. 7a. These results support the contention that DS is implicated specifically when cognitive control demands increase

R

O

C

N

U

469 470

t6:22 t6:23 t6:25 t6:24 t6:26 t6:27 t6:28 t6:29

F

O

comparison of close – far trials (peak coordinates 69, − 22, 28; t = 3.35; cluster size = 11). Next, we performed conjunction analyses at the whole-brain level between our congruency interference (i.e., incongruent-control and incongruent-congruent) and physical size difference effect (i.e., close – far) contrasts at p b 0.005 uncorrected for multiple comparisons (Table 6; Fig. 6). There were no shared voxels within any region of DS performing conjunctions of either the interference related to congruency or the interference related to within pair physical size difference effect, even with a liberal statistical threshold of p b 0.05 uncorrected for multiple comparisons. Of note, voxels within left ACC were common to both our incongruent – congruent and close – far contrasts, as were voxels within bilateral supramarginal gyrus, supporting our contention that both types of interference were equally cognitively effortful. We next completed a disjunction analysis by applying an exclusive mask of BOLD signal in our close – far contrast (p b 0.005 uncorrected for multiple comparisons) to our incongruent – congruent contrast (p b 0.005 uncorrected for multiple comparisons) to critically test whether DS BOLD signal is significantly increased in our congruency relative to DS BOLD signal in our distance contrast (Table 7; Fig. 7a). A significant activation originating in right thalamus (peak coordinates 18, − 7, 16; t(1, 90) = 3.08; cluster size = 51) that extended into right dorsal caudate and a secondary activation in right dorsal putamen (peak coordinates 27, 7, − 1; t(1, 90) = 3.51) from a larger cluster

467 468

91 114 55 13 52 7

54, −58, −11 42, −34, 31 45, −49, 58 48, −76, −11 −39, −40, 46 −51, −31, 49

R

459 460

465 466

t6:19 t6:20 t6:21

All t values listed above were found at p b 0.005 uncorrected for multiple comparisons. t6:30 Activations with cluster size b 5 are not listed. Coordinates are listed in MNI space. ext, t6:31 extending; L, left; R, right. t6:32

All t values listed above were found at p b 0.05 with FDR correction. Coordinates are listed in MNI space. ext, extending; L, left; R, right.

463 464

R O

P

incongruent – control ∩ close – far

t5:42 t5:43

461 462

15 10 5

D

R planum polare R lingual gyrus

24, −49, 55 3.02 36, −76, −23 3.00 42, 41, 25 2.75

E

t5:30 t5:31 t5:32 t5:33 t5:34 t5:35 t5:36 t5:37 t5:38 t5:39 t5:40 t5:41

30 15 80 26 7 7 14 14

T

t5:26 t5:27 t5:28 t5:29

3.42 3.35 3.21 3.11 3.07 3.06 3.05 3.02

48, 2, 25 69, −22, 28 −36, −37, 43 −51, −31, 49 60, 17, 7 −54, −67, −11 −63, −10, 1 48, 50, 13

C

R supramarginal gyrus L brain stem L middle frontal gyrus L superior temporal gyrus L intracalcarine cortex L orbitofrontal cortex R postcentral gyrus L temporal occipital fusiform cortex R superior temporal gyrus L temporal fusiform cortex R occipital pole L brain stem

t6:3 t6:4 t6:5 t6:7 t6:6 t6:8 t6:9 t6:10 t6:11 t6:12 t6:13 t6:14 t6:15 t6:16 t6:17 t6:18

144 406 9

E

R ventrolateral prefrontal cortex L superior parietal lobule L cerebellum L juxtapositional lobule cortex (ext. into ACC) R orbitofrontal cortex

t-stat Cluster size

Fig. 6. Axial slices showing significant activations from our conjunction analysis. No shared voxels were present in DS. Shared voxels seen within ACC are circled in green at z = 43 (p b 0.005 uncorrected for multiple comparisons).


483 484 485 486 487

B.D. Robertson et al. / NeuroImage xxx (2014) xxx–xxx t7:1 t7:2

9

Table 7 Disjunction analyses of our incongruent – congruent and close – far contrasts. Contrast

Anatomical Region


t-stat

Cluster size

t7:4 t7:5 t7:6 t7:7 t7:8 t7:9 t7:10 t7:11 t7:12 t7:13 t7:14 t7:15 t7:16 t7:17 t7:18 t7:19 t7:20 t7:21 t7:22 t7:23 t7:24 t7:25 t7:26 t7:27 t7:28 t7:29 t7:30 t7:31 t7:32 t7:33 t7:34 t7:35 t7:36 t7:37 t7:38 t7:39 t7:40 t7:41 t7:42 t7:43 t7:44 t7:45 t7:46

incongruent – congruent masked with close – far

R thalamus (ext. into dorsal caudate) R postcentral gyrus (R dorsal putamen) L superior temporal gyrus L postcentral gyrus L lingual gyrus

18, −7, 16 66, −7, 13 27, −7, 1 −60, −4, 1 −33, −34, 46 −18, −58, −17 0, −70, 7 −15, −46, −5 21, −25, −11 18, 32, −17 30, 29, 10 0, −91, 22 −39, 2, −17 −21, −19, −11 −12, −1, 43 39, 44, 28 48, −22, −23 54, −43, −14 12, −19, 4 −42, −28, −17 3, −43, 4 −39, 38, 34 48, −43, 43 −36, −49, 19 24, −61, −14 −18, −31, 4 48, 41, 4 24, −61, 10 51, −58, −14 −45, −55, −8 45, 8, 25 −45, 2, 28 48, 38, 16 −27, −55, 49 −3, −73, −23 −15, 2, 40 21, 47, −14 −45, 35, 19 −45, 47, −14 6, −37, 61 −57, −28, 46 60, −22, −2 15, 26, 7

3.08 4.76 3.51 4.62 4.35 4.32 3.01 2.96 4.17 4.16 3.46 3.79 3.72 3.60 3.56 3.54 3.45 3.05 3.37 3.29 3.13 3.12 3.10 3.07 3.02 2.98 2.97 2.78 5.51 5.45 5.44 5.42 4.79 4.24 4.21 3.82 3.41 3.20 2.92 2.88 2.87 2.85 2.72

51 1881 * 568 427 126 14 25 445 39 20 67 18 34 94 120 14 7 23 14 13 12 6 8 37 10 5 11 1357 778 513 280 212 360 85 60 14 44 5 7 7 9 5

R hippocampus R frontal orbital cortex

R O

R

E

C

T

E

D

close – far masked with incongruent – congruent

P

R thalamus L temporal fusiform cortex R posterior cingulate gyrus L middle frontal gyrus R supramarginal gyrus L supramarginal gyrus R temporal occipital fusiform cortex L thalamus R inferior frontal sulcus R intracalcarine cortex R inferior temporal gyrus L inferior temporal gyrus R precentral gyrus L precentral gyrus R ventrolateral prefrontal cortex L superior parietal lobule L white matter (ext. into lingual gyrus) L juxtapositional lobule R orbitofrontal cortex L middle frontal gyrus L orbitofrontal cortex R postcentral gyrus L supramarginal gyrus R superior temporal gyrus R white matter

O

L/R occipital pole L insular cortex L hippocampus L juxtapositional lobule cortex R dorsolateral prefrontal cortex R inferior temporal gyrus

F

t7:3

Contrasts and exclusive masks were thresholded at p b 0.005 uncorrected for multiple comparisons. Activations of cluster size N 5 that remained after masking are listed above. Coordinates are listed in MNI space. L, left; R, right.

488 489

(i.e., incongruent – congruent) and not merely with enhanced cognitive effort. We repeated this exclusive masking procedure by masking out BOLD signal in our incongruent – congruent contrast (p b 0.005 uncorrected for multiple comparisons) from our close – far contrast (p b 0.005 uncorrected for multiple comparisons). No preferential activity was seen in DS. To further bolster our contention that DS mediates cognitive control and not cognitive effort per se, we repeated our first disjunction analysis by applying an exclusive mask of BOLD signal in our close – far contrast (p b 0.05 uncorrected for multiple comparisons) to our incongruent – congruent contrast (p b 0.05 with FDR correction). Even with these much more stringent statistical thresholds, activations in right dorsal caudate (peak coordinates 18, − 10, 19; t(1, 90) = 2.93; cluster size = 9), left dorsal caudate (peak coordinates − 18, − 4, 19; t(1, 90) = 2.85; cluster size = 2), as well as a secondary activation in right dorsal putamen (peak coordinates 27, −7, 1; t(1, 90) = 3.51) from a larger cluster originating in right postcentral gyrus (peak coordinates 66, − 7, 13; t(1, 90) = 4.76; cluster size = 1351) were seen (Table 8; Fig. 7c). Taken together, the results of our disjunction analyses provide clear evidence that DS is more active due to elevated cognitive control demands and not simply due to the need for more cognitively effortful processing per se. (See Table 9.) We followed with ROI analyses to investigate DS using our incongruent – congruent and close – far contrasts (Fig. 8). In the incongruent –

494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 Q8 509 510

N C O

492 493

U

490 491

R

t7:47 t7:48

congruent contrast, we found significant mean signal change in right DS (t = 3.07; p = 0.005). For our close – far contrast, no significant activations were noted in the DS ROIs (left: t = 1.38; p = 0.30; right: t = 1.63; p = 0.20). The magnitude of mean signal change in right DS in our incongruent – congruent and close – far contrasts did not differ significantly (t = 0.38; p = 0.49) using a paired t-test, however. We subsequently found significant, common bilateral mean signal change in the ACC ROI for the interference contrast (left: t = 3.71; p b 0.01 right: t = 2.98; p = 0.001) as well as left ACC in the close – far contrast (left: t = 2.36; p b 0.05). Finally, brain-behaviour correlations of BOLD signal with Stroop interference (i.e., incongruent – congruent; incongruent – control) as well as with close – far physical size difference scores were performed at p b 0.005 uncorrected for multiple comparisons (Table 8). We found that dorsal caudate BOLD signal was negatively correlated with interference scores in both our interference contrasts (i.e., incongruent - congruent; incongruent – control), demonstrating its role in cognitive control (Fig. 9). We found no correlation between DS BOLD signal and difference scores for our close – far contrast, even at p b 0.05 uncorrected for multiple comparisons, a very liberal criterion. We also found no correlation between ACC BOLD signal and RTs in any of our contrasts. Left supramarginal gyrus BOLD signal was positively correlated with interference scores for both our interference contrasts.


511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533


R

E

C

T

E

D

P

R O

O

F

10

C

O

R

Fig. 7. Axial slices showing significant activations for disjunction analyses. Column a) shows significant voxels in our incongruent – congruent contrast (p b 0.005 uncorrected for multiple comparisons) after masking out activations in our close – far contrast (p b 0.005 uncorrected for multiple comparisons). Column b) shows significant voxels in our close – far contrast (p b 0.005 uncorrected for multiple comparisons) after masking out activations in our incongruent – congruent contrast (p b 0.005 uncorrected for multiple comparisons). Column c) shows significant voxels in our incongruent – congruent contrast (p b 0.05 with FDR correction) after masking out activations in our close – far contrast (p b 0.05 uncorrected for multiple comparisons). This more stringent disjunction analysis was performed to further bolster our contention that DS mediates cognitive control and not cognitive effort per se. Significant activations in DS for each disjunction analysis are circled in green.

Discussion

535 536

We examined whether DS mediates cognitive control processes specifically or cognitive effort generally, using a number Stroop task with simultaneous fMRI. The physical size difference between number pairs on the relevant dimension and the numerical magnitude difference between number pairs on the irrelevant dimension were fully crossed with congruency, such that these effects were entirely orthogonal. In this way, we were able to examine the effect of congruency and physical size difference effects on RTs, error rates, and fMRI BOLD signal within the same data set. We hypothesized that our congruency manipulation (incongruent vs. congruent and control) stresses cognitive control processes as well as increases cognitive effort. In contrast, the physical distance effect (i.e., close 15 point font differences vs. far 45 point font differences) enhances cognitive effort to enact the comparison, but not cognitive control demands. Participants took longer to respond and had higher error rates during incongruent relative to control and congruent trials, and for close relative to far physical size difference trials. Participants responded

539 540 541 542 543 544 545 546 547 548 549 550 551

U

537 538

N

534

faster during congruent trials relative to control trials. These findings are consistent with a very large literature (Dyer, 1973; Jensen and Rohwer, 1966; Macleod, 1991; MacLeod and MacDonald, 2000; Holloway and Ansari, 2010; Kaufmann et al., 2005). Congruency, physical size, and numerical magnitude difference variables did not interact. Analogous to our behavioural analyses, we investigated the effects of congruency (incongruent vs. congruent vs. control) and physical size differences (close vs. far) on BOLD signal. We found that DS activity was modulated by our congruency variable. Pairwise comparisons revealed greater DS activation for incongruent trials—during which conflicting information on the irrelevant dimension needed to be suppressed—compared to the congruent case. At a slightly more liberal criterion (p b 0.005 uncorrected for multiple comparisons), these same DS regions were also significantly more active for incongruent compared to control trials. No striatal regions were preferentially more active for control or congruent trials relative to the incongruent case. Of greater significance, given our aims, preferential DS activation did not occur for close relative to far physical size difference comparisons or the reverse contrast. Even using a very liberal criterion of p b 0.05,


552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570

B.D. Robertson et al. / NeuroImage xxx (2014) xxx–xxx Table 8 Additional stringent disjunction analysis of our incongruent – congruent masked with our close – far contrast.

R dorsal caudate L dorsal caudate R postcentral gyrus (R dorsal putamen)

t8:47 t8:48 t8:49 t8:50 t8:51 t8:52 t8:53 t8:54 t8:55 t8:56 t8:57 t8:58

T

C

E

t8:40 t8:41 t8:42 t8:43 t8:44 t8:45 t8:46

R

t8:35 t8:36 t8:37 t8:38 t8:39

R

t8:30 t8:31 t8:32 t8:33 t8:34

N C O

t8:29

18, −10, 19 2.93 9 −18, −4, 19 2.85 2 66, −7, 13 4.76 1351 (27, −7, 1) (3.51) * 33, −28, 40 3.91 11 54, −22, 58 2.72 1 L lingual gyrus −18, −58, −17 4.32 81 −15, −46, −5 2.96 24 L postcentral gyrus −42, −25, 40 4.24 91 −36, −28, 58 3.01 13 R hippocampus 21, −25, −11 4.17 421 R orbitofrontal cortex 18, 32, −17 4.16 11 30, 38, −17 3.43 5 L central opercular cortex −57, −1, 4 3.97 507 L/R cuneal cortex 0, −88, 25 3.77 43 L insular cortex −39, 2, −17 3.72 17 L posterior cingulate −15, −25, 34 3.68 120 gyrus L hippocampus −21, −19, −11 3.60 35 R inferior temporal gyrus 48, −22, −23 3.45 14 54, −40, −14 2.82 2 R dorsolateral prefrontal 27, 47, 37 3.43 75 cortex R posterior cingulate 15, −31, 37 3.42 134 gyrus 6, −43, 4 2.94 4 3, −34, 28 2.82 4 R thalamus 12, −16, 4 3.33 19 21, −31, 7 2.78 1 L temporal fusiform −42, −28, −17 3.29 14 cortex L anterior cingulate gyrus −9, −1, 40 3.27 64 R inferior frontal gyrus 33, 29, 10 3.24 2 R supramarginal gyrus 69, −34, 31 3.22 2 L middle frontal gyrus −39, 38, 34 3.12 12 L juxtapositional lobule −15, 5, 49 3.11 4 cortex L supramarginal gyrus −36, −49, 19 3.07 8 −51, −37, 43 2.82 2 −51, −31, 34 2.75 3 L/R lingual gyrus 0, −70, 7 3.01 9 L thalamus −18, −31, 4 2.98 10 −18, −22, 16 2.64 1 R temporal fusiform 39, −13, −23 2.85 3 cortex R precuneus cortex 12, −79, 43 2.84 4 3, −49, 61 2.67 2 18, −67, 43 2.64 1 L subcallosal cortex −12, 17, −11 2.79 3 R intracalcarine cortex 24, −61, 10 2.78 6 R lingual gyrus 6, −73, −8 2.77 3 12, −88, −11 2.73 1 R temporal occipital 24, −61, −11 2.72 1 fusiform cortex R precentral gyrus 21, −25, 58 2.71 1 R occipital fusiform gyrus 24, −67, −14 2.67 3 L lateral occipital cortex −57, −67, −2 2.67 1

U

t8:25 t8:26 t8:27 t8:28

Cluster size

t8:59 t8:60 t8:61 t8:62

Incongruent – congruent contrast was thresholded at p b 0.05 with FDR correction and an exclusive mask of our close – far contrast at p b 0.05 uncorrected for multiple comparisons was applied. Activations that remained after masking are listed above. Coordinates are listed in MNI space. L, left; R, right.

571 572

uncorrected for multiple comparisons at the whole-brain level, no DS peaks of 10 contiguous voxels or greater were detected for our close – far contrast. In contrast, ACC was significant in our main effect analyses of both congruency and physical size differences, as well as during subsequent pairwise comparisons of incongruent – congruent and close – far trials. The supramarginal gyrus was significant for the main effect of physical size difference and pairwise comparisons of incongruent – congruent and close – far contrasts. These activations confirm that our aim of

573 574 575 576 577 578 579

DS in cognitive control or cognitive effort

640

F

incongruent – congruent masked with close – far

t-stat

O

t8:5 t8:6 t8:9 t8:7 t8:10 t8:8 t8:11 t8:12 t8:13 t8:14 t8:15 t8:16 t8:17 t8:18 t8:19 t8:20 t8:21 t8:22 t8:23 t8:24


R O

Anatomical Region

P

Contrast

580 581

D

t8:4

modulating cognitive effort using both congruency and physical size difference manipulations was achieved. Conjunction analyses – completed using a slightly more liberal criterion (p b 0.005 uncorrected for multiple comparisons) – between our congruency interference (i.e., incongruent – congruent, incongruent – control) contrasts yielded shared voxels within DS. In contrast, our congruency-related interference and physical size (i.e., close-far) conjunction analyses revealed no shared voxels in DS. However, left ACC activation was shared between our incongruent – congruent and close – far contrasts, and bilateral supramarginal gyrus activation was common for incongruent – congruent or incongruent – control and our close – far contrast. This supports the claim that we succeeded in creating conditions that were equally effortful using congruency and physical size difference manipulations. Disjunction analysis – performed by masking out all voxels arising in our close – far contrast (p b 0.005 uncorrected for multiple comparisons) from our incongruent – congruent contrast (p b 0.005 uncorrected for multiple comparisons) – yielded significant voxels in right dorsal caudate and a secondary activation in right dorsal putamen. Repeating this analysis with much more stringent thresholds (incongruent – congruent contrast at p b 0.05 with FDR correction masked with close – far contrast at p b 0.05 uncorrected for multiple comparisons) yielded significant bilateral dorsal caudate activations as well as a secondary activation in right dorsal putamen. These results provide direct evidence that DS is significantly more active for interference contrasts related to elevated cognitive control demands than for interference occurring due to closer physical size comparisons. Disjunction analysis, completed by masking out all voxels arising in our incongruent – congruent contrast (p b 0.005 uncorrected for multiple comparisons) from our close – far contrast (p b 0.005 uncorrected for multiple comparisons) yielded no significant voxels in DS, lending further credence to our contention that DS mediates cognitive control and not cognitive effort per se. ROI analyses yielded results consistent with our whole-brain analyses. Significant mean signal change was found in right DS in our incongruent – congruent contrast, but no mean signal change was found within our DS ROIs for the close – far contrast. The difference in the magnitude of signal change in right DS in our incongruent – congruent and close – far contrasts did not reach significance; however, despite this finding, our disjunction analyses surveying the whole brain – and reported above – did uncover preferentially more bilateral DS activity in the congruency relative to distance contrasts. No voxels in DS were significantly more active for the physical size distance effect compared to the congruency effect. As expected, and proof of our success in matching the effort required by our congruency and distance manipulations, significant mean signal changes were seen in our ACC ROIs for both interference and close – far contrasts. Finally, brain-behaviour investigations – completed using a slightly more liberal criterion (p b 0.005 uncorrected for multiple comparisons) – revealed that DS BOLD signal was negatively correlated with Stroop interference scores, but close – far physical difference scores did not correlate with DS BOLD signal in any manner. That is, higher BOLD signal in DS was associated with less interference from the distracting dimension, as would be expected for a brain region that is implicated in cognitive control functions. ACC BOLD signal was not correlated with RTs in any of our contrasts though left supramarginal gyrus BOLD was positively correlated with interference and difference scores in both our interference and distance contrasts, respectively. Taken together, we conclude that DS plays a role specifically in cognitive control and not in cognitively effortful processing per se.

E

t8:1 t8:2 t8:3

11

582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639

Preferential DS activation for incongruent relative to congruent and 641 control Stroop trials has been noted previously (Ali et al., 2010; Ansari 642 Q9 et al., 2006; Liu et al., 2006; Tang et al., 2009; Peterson et al., 1999, 643


12 t9:1 t9:2


Table 9 Positive and negative correlations between BOLD signals and RTs in our interference and close – far contrasts. Correlation

Type

Anatomical region


t-stat

Cluster size

t9:4 t9:5 t9:6 t9:7 t9:8 t9:9 t9:10 t9:11 t9:12 t9:13 t9:14 t9:15 t9:16 t9:17 t9:18 t9:19 t9:20 t9:21 t9:22 t9:23 t9:24 t9:25 t9:26 t9:27 t9:28 t9:29 t9:30 t9:31 t9:32 t9:33 t9:34 t9:35 t9:36

incongruent – congruent

positive

R insular cortex L supramarginal gyrus R inferior frontal gyrus

36, 2, 1 −57, −43, 49 48, 23, 4 57, 17, 10 60, −43, 13 39, 50, 31 −18, −7, 22 6, −4, 19 −6, −25, 19 0, −64, 31 −57, −13, −17 27, −13, −11 18, −16, 13 39, 14, −26 −45, −16, −26 −39, 32, −14 39, 50, 31 −39, −40, 58 −27, −58, 52 60, 23, 10 −51, 26, −5 −54, −43, 49 −42, 8, 40 27, −85, 1 18, −13, 25 24, −13, −11 0, −28, 13 −12, −43, 46 −30, −85, 25 −39, −7, 34 −60, −13, 13 −27, −58, 58 −15, 47, 31

4.46 4.02 3.89 3.74 3.35 3.33 3.85 6.44 4.16 5.04 4.36 4.29 4.18 4.15 3.98 3.35 3.95 3.95 3.52 3.94 3.64 3.57 3.51 3.20 3.37 4.75 4.24 4.41 4.34 4.15 3.50 3.38 3.72

11 5 23 6 5 5 7 33 10 43 14 25 5 17 5 8 6 16 24 9 9 7 18 5 10 21 14 18 102 8 6 7 13

positive

R inferior frontal gyrus L frontal orbital cortex L supramarginal gyrus L middle frontal gyrus R lateral occipital cortex R dorsal caudate R amygdala L/R white matter (ext. to thalamus) L precuneus L lateral occipital cortex L precentral gyrus L central opercular cortex L superior parietal cortex L dorsolateral prefrontal cortex

negative

close – far

E

D

positive

negative

O

incongruent – control

L/R precuneus L middle temporal gyrus R amygdala R thalamus R temporal pole L inferior temporal gyrus L frontal orbital cortex R dorsolateral prefrontal cortex L superior parietal lobule

R O

negative

P

R middle temporal gyrus R dorsolateral prefrontal cortex L dorsal caudate R thalamus

F

t9:3

All t values listed above were found at p b 0.005 uncorrected for multiple comparisons. Activations with cluster size b 5 are not listed. Coordinates are listed in MNI space. ext, extending; L, left; R, right.

644

2002; Pardo et al., 1990). Similarly, DS is preferentially active in shifting

C

T

t9:37 t9:38

E

645 Q10 from one goal to another (Grahn et al., 2008; Hazy et al., 2006; Vakil 646 et al., 2004), in resolving incongruent stimulus-stimulus associations 647 648

U

N

C

O

R

R

that conflict across consecutive trials (MacDonald et al., 2011), as well as in switching among decision strategies (Benke et al., 2003: 649 Q11 Cameron et al., 2010; Ell et al., 2006; Grahn et al., 2008; Leber et al.,

Fig. 8. Mean signal change for regions of interest in our incongruent – congruent and close – far contrasts. A Single asterisk denotes significant mean signal change at p b 0.05. Double asterisks denote significant mean signal change at p b 0.01. Triple asterisks denote mean signal change at p b 0.001. ACC, anterior cingulate cortex; Cong, congruent; DS, dorsal striatum; Incong, incongruent; L, left; R, right.

2008; Yehene et al., 2008). These findings, and ours reported here, can be interpreted as evidence for DS’ role in cognitive control processes because correct responding requires suppressing competing responses, shifting attention from salient but irrelevant stimulus dimensions to target dimensions, or overcoming previously established associations. Keeping in mind that cognitive effort has been defined as the proportion of engaged, limited-capacity central processing (Russo and Dosher, 1983), the number of elementary processes enacted (Bettman et al., 1990), or the duration over which cognitive resources are expended (Christensen-Szalanski, 1980), these condition that stress cognitive control mechanisms are also more cognitively effortful than their comparison conditions. This introduces an alternative explanation for increased DS BOLD signal in these conditions. To differentiate cognitive control from cognitive effort, in the current experiment, we also investigated the effect of physical size differences between number pairs using the same data set. In line with a number of similar studies, RTs were longer for close relative to far physical size differences between number pairs, which is consistent with the view that these trials are more cognitively effortful (Cohen Kadosh et al., 2005; Kaufmann et al., 2005, 2006; MacDonald et al., 2014; Pinel et al., 2001). However, varying the physical size differences between number pairs does not alter cognitive control demands. That is, close and far trials do not differ in their requirement to shift attention from one stimulus dimension to another, or override more automatic or habitual response tendencies (Botvinick et al., 2001; Cools and D’Esposito, 2011; Liu et al., 2004; MacDonald et al., 2000). DS activity did not correlate with the behavioural slow-down in responding for number pairs that had smaller physical size differences compared to those with larger differences, even when a liberal statistical threshold was employed. We interpret these findings as support for the notion that DS does not merely mediate cognitive effort, but rather is specifically engaged in decisions that require greater deliberation or cognitive control. The


650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681


13

N C O

R

R

E

C

T

E

D

P

R O

O

F

Statistical equivalence between conditions could arise due to unsuccessful implementation of the critical experimental manipulation or due to insufficient power to detect true differences between the contrasted conditions. To mitigate this criticism of our main analyses, however, we found significant differences in the DS BOLD response for the incongruent - congruent contrast relative to the close – far contrast using exclusive masking. That is, DS activations in the former contrast were unique and significantly greater than for the latter and consequently our conclusions about differential DS involvement in congruency versus distance effects do not rest solely on a null result. It should be noted that the pairwise comparisons of beta values in our caudate ROI between congruency and distance contrasts did not, however, reach significance. Finally, the converse disjunction analysis – completed using more lenient statistical thresholds – revealed no significant DS BOLD signal for the close – far contrast relative to the incongruent – control comparison. Additional considerations further mollify concerns about interpreting the null effect in the main close – far distance analyses. A number of findings suggest that we succeeded in critically testing DS’ role in cognitive effort. Though we failed to find differential DS BOLD signal between number pairs with smaller versus larger physical size differences, the predicted behavioural differences arose and the pattern of cortical activations associated with variation in physical size differences in the current study was coherent with the existing literature (e.g., ACC, supramarginal gyrus extending to the intraparietal sulcus, left superior parietal lobule, bilateral precuneus, left posterior cingulate gyrus; Ansari et al., 2005; Cohen Kadosh et al., 2005; Kaufmann et al., 2005, 2006; MacDonald et al., 2014; Pinel et al., 2001, 2004). Further, the behavioural interference effects from our congruency manipulation (i.e., incongruent – control, incongruent – congruent) and our physical size difference effect (i.e., close minus far physical size difference number pairs) were not significantly different at p b 0.05. The interference effects for incongruent – control was 53.59 ± 8.48 (ms ± SEM) and incongruent – congruent was 68.57 ± 8.04 (ms ± SEM). These values were comparable to the interference achieved for close – far physical size difference trials, 67.98 ± 16.80 (ms ± SEM). This is important because it suggests that at the behavioural level, our congruency and size manipulations were equally robust, and the cognitive effort required was comparable for both experimental conditions relative to their respective baseline conditions. In line with this finding, the activations seen at the border of the juxtapositional lobule cortex and ACC were present during pairwise comparisons and conjunction analyses of interference and physical size contrasts, in line with ACC’s role in attentional and effortful processing (Shenhav et al., 2013; Ansari et al., 2006; Bench et al., 1993; Botvinick et al., 2001; Carter et al., 1995; but see Kaufmann et al., 2005; Tang et al., 2009 for notable negative examples). These ACC activations are also known to vary both in the location of their local maxima and cluster sizes between studies (Egner and Hirsch, 2005). Common activation for interference and physical size distance effects in supramarginal gyrus was also expected and previously noted, given this region’s role in stimulus-level attention and number comparison and processing (Kaufmann et al., 2005). In summary, this pattern of results suggests that we properly enacted our distance manipulation, and equated our Stroop and distance effects in terms of potency and required effort based on both behavioural and neural data. Our findings are therefore quite compelling and credible in refuting claims that DS merely mediates cognitive effort (Boehler et al., 2011; Krebs et al., 2012; Schmidt et al., 2012), converging with a larger literature using other methodologies that bear brief interpretation respecting DS and cognitive effort below. The behavioural indices of increased cognitive effort are increased RTs and error rates studied in both humans (e.g., Moyer and Landauer, 1967) and animals (Dehaene et al., 1998). Our finding that preferential DS activity does not result for discriminations of more similar relative to more dissimilar stimuli has been found by others in both adults (Cohen Kadosh et al., 2005; MacDonald et al., 2014; Pinel et al., 2001, 2004; Tang et al., 2009) and children (Kaufmann et al., 2006). Also in line with our

Fig. 9. Axial slices showing significant activations for negative BOLD-Stroop Interference correlations. Significant activations (p b 0.005 uncorrected for multiple comparisons) in DS are circled in green.

682 683

689

Weaknesses and alternative interpretations of the current study addressed

690

An inherent difficulty in our approach is that to refute the possibility that DS mediates cognitive effort requires accepting a null hypothesis in our main analyses. In a well-designed study, rejecting the null hypothesis warrants confidence that differences between conditions arose due to manipulation of the experimental variable. Conclusions drawn from failing to reject the null hypothesis are fraught with greater difficulty.

684 685 686 687

691 692 693 694 695

U

688

fact that DS BOLD signal was negatively correlated with the magnitude of the Stroop interference effect further suggests its role in cognitive control, though this was only significant at p b 0.005 uncorrected for multiple comparisons. When DS BOLD signal was reduced, the irrelevant and distracting dimension interfered more with responding. Conversely, When DS BOLD signal was increased, responding was more focused and less susceptible to distraction.


696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761


771 772 773 774 775 776 777 778 779 780 781 782 783 784

Our findings cohere with mounting evidence from our lab (Hiebert 788 et al., 2014a, 2014b; Vo et al., 2014), as well as a larger literature Q13789 Q12 (e.g., Cools, 2006a; Cools, 2010; Grahn et al., 2008; Hughes et al., 790 2013). DS dysfunction in both humans and non-human primates results 791 in deficits in shifting attention between stimuli, especially away from 792 more salient ones (Benke et al., 2003; Cools et al., 2003, 2010; Thoma 793 et al., 2008), flexibly altering decision-making strategies or response 794 Q14 sets (Benke et al., 2003: Cameron et al., 2010; Ell et al., 2006; Grahn 795 et al., 2008; Leber et al., 2008; Yehene et al., 2008), suppressing more 796 automatic responses (Benke et al., 2003; Cameron et al., 2010; 797 Q15 MacDonald et al., 2011; White, 2009), and updating goals (Grahn 798 et al., 2008; Hazy et al., 2006; Vakil et al., 2004). In Thoma et al. 799 (2008), patients with basal ganglia lesions showed increased RTs and 800 error rates during the classical colour-word Stroop task. In PD patients, 801 shifting attention to more salient stimuli is accomplished more easily 802 (Cools et al., 2010; MacDonald et al., 2011), whereas shifting attention 803 to less salient stimuli yields more impairment compared to controls 804 (Cameron et al., 2010; Cools et al., 2006b, 2010; Hood et al., 2007; 805 MacDonald et al., 2011). In healthy volunteers, DS activation occurs 806 when participants are required to suppress competing motor responses, 807 as in the incongruent condition of the Stroop task (Ali et al., 2010; Leung 808 et al., 2000; Pardo et al., 1990; Pinel et al., 2004; Peterson et al., 1999, 809 2002). Taken together, these results suggest that DS is implicated in 810 decision making when deliberation and cognitive control are required.

832 Q16

Alexander et al., 1986 Cowan and Wilson, 1994 Dalley et al Di Martino et al., 2008 Kincaid et al., 1998 Leh et al., 2008 Postuma and Dagher, 2006 Zhang et al., 2009 Zheng and Wilson, 2002

C

E

R

R

O

C

N

U

811

Conclusion

812

We used a simple number Stroop task to address a pervasive confound in the study of cognitive abilities mediated by DS. Cognitive effort usually increases proportionally with cognitive control demands. The number Stroop task allowed us to independently manipulate cognitive control and cognitive effort to investigate DS BOLD signal in relation to each of these separate cognitive effects. We found that increasing cognitive control requirements by introducing distracting, conflicting information (i.e., the incongruent case) increased participant RTs, error rates, and was associated with increased DS BOLD signal. Further, the magnitude of the DS BOLD signal was inversely correlated with the size of the Stroop effect, supporting its role in cognitive control. Enhancing cognitive effort demands by decreasing the difference in physical

813 814 815 816 817 818 819 820 821 822 823

826 827 828 829 830 831

833 834

Acknowledgments

835 836 837 838 839 840 841 842

This study was supported by a Canada Excellence Research Chair award to Dr. Adrian Owen, and by start-up funds and an Opportunity Grant from the Academic Medical Organization of Southwestern Ontario awarded to Dr. Penny MacDonald.

843 844

References

847

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size between number pairs increased participant RTs, but was not associated with preferential DS activation, even using liberal statistical criteria. Our results support claims that DS specifically mediates cognitive control, and not cognitive effort per se, in decision-making. Increasingly, cognitive functions are ascribed to the striatum. Understanding these specific cognitive functions is important in anticipating cognitive and behavioural deficits of patients with neurological and psychiatric illnesses that implicate the striatum.

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findings, Zamarian et al. (2006) demonstrated that PD patients without dementia perform as well as healthy controls during tasks that involve working with analog magnitude scales (1–100), verbal counting, or single-digit magnitude comparisons, all tasks that vary cognitive effort leaving cognitive control processes invariant. Further, in MacDonald et al. (2014), PD patients and healthy controls were instructed to select the numerically larger or smaller written integer from a pair (e.g., one vs. eight) based on a simultaneously presented cue. All participants revealed a symbolic distance effect, whereby responses to number pairs that were closer (e.g., one vs. two) relative to farther (e.g., one vs. six) in numerical value were slower and more error prone. Of crucial importance, the symbolic distance effect for PD patients did not differ from that of healthy age-matched controls. Further, the symbolic distance effect was not affected by dopaminergic medication status (OFF vs. ON) of PD patients. This is inconsistent with a role for DS in mediating these effects, given that off medication in PD, DS function is compromised, whereas it is improved with dopamine replacement (Cools, 2006a; Shook et al., 2005; Hood et al., 2007; MacDonald et al., 2011). In similar fashion, numerous single-case studies of patients with basal ganglia lesions show no deficits in their ability to judge magnitude in the absence of conflict (Benke et al., 2003; Dehaene and Cohen, 1997; Delazer et al., 2004; Hittmair-Delazer et al., 1994). Taken together, converging evidence suggests that DS does not mediate cognitively effortful judgment or decisions per se.

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Examining dorsal striatum in cognitive effort using Parkinson's disease and fMRI.

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