Edited by: Chad E. Forbes, University of Delaware, USA
Reviewed by: Chad E. Forbes, University of Delaware, USA; Sukhvinder Obhi, Wilfrid Laurier University, Canada
*Correspondence: Joan Y. Chiao, Department of Psychology, Northwestern University, 2029 Sheridan Rd., Evanston, IL 60208, USA. e-mail:
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Both situational (e.g., perceived power) and sustained social factors (e.g., cultural stereotypes) are known to affect how people academically perform, particularly in the domain of mathematics. The ability to compute even simple mathematics, such as addition, relies on distinct neural circuitry within the inferior parietal and inferior frontal lobes, brain regions where magnitude representation and addition are performed. Despite prior behavioral evidence of social influence on academic performance, little is known about whether or not temporarily heightening a person's sense of power may influence the neural bases of math calculation. Here we primed female participants with either high or low power (LP) and then measured neural response while they performed exact and approximate math problems. We found that priming power affected math performance; specifically, females primed with high power (HP) performed better on approximate math calculation compared to females primed with LP. Furthermore, neural response within the left inferior frontal gyrus (IFG), a region previously associated with cognitive interference, was reduced for females in the HP compared to LP group. Taken together, these results indicate that even temporarily heightening a person's sense of social power can increase their math performance, possibly by reducing cognitive interference during math performance.
Priming social power has been shown to affect both social and cognitive processing. People with low power (LP) typically experience heightened uncertainty and increased vigilance of the social environment (for review, see Keltner et al.,
One cognitive mechanism affected by situational power is local-global attentional processing. Because LP individuals attempt to attend to an overabundance of information in the environment, their perception of the big picture or global meaning may be hindered as a result of their attentional focus on many small, local details. When participants' situational power was modulated while completing an attentional scope during a hierarchical attention task, (i.e., Navon figures; Navon,
LP participants' global focus may be impeded by a heightened susceptibility to interference of the local components. Their inability to filter out extraneous information efficiently may be a reflection of depleted executive functioning resources. This idea is supported by behavioral evidence that showed a relatively exaggerated interference effect on a Stroop task and an N-back task, with LP participants making more errors than HP participants on both tasks (Smith et al.,
Mathematical calculation relies on several distinct cognitive and neural mechanisms underlying numerical processing (Dehaene,
Previous research has established a robust number size effect, with increasing size corresponding to lengthier response times and heightened error rate on basic addition and multiplication problems (for review, see Ashcraft,
Here we aimed to investigate the influence of power priming on the neural basis of math calculation. Intact executive functioning may be crucial for some types of mathematical processing. Inefficient executive functioning may impede performance on some types of math calculations, particularly those that require the use of cognitive control mechanisms such as updating, information filtering, and competitive selection processes. For instance, math approximation has been shown to recruit the subregions of the superior parietal lobe, including the intraparietal sulcus (IPS), a region that is also important in magnitude comparisons, such as size and numerosity (Cohen-Kadosh et al.,
Since executive function resources are needed to actively inhibit interfering information, we predicted that priming participants with LP would affect performance on approximation problems. Specifically, we hypothesized that LP participants would demonstrate decreased computational efficiency when solving approximate problems relative to HP participants, because they may be more susceptible to cognitive interference when generating an exact answer and thus, require additional recruitment of cognitive control brain regions to exercise inhibition. On the other hand, we did not expect group performance differences on the exact calculations, since the solutions to these problems are likely automatically retrieved from memory.
Twenty-four right-handed, Caucasian females (
Before participants arrived to the study site, they were randomly assigned to the HP or LP condition. After completing the appropriate fMRI prescreening paperwork, participants were given instructions and completed the two priming tasks and the math task in the experiment.
Power was primed using two separate procedures. Participants were first primed with an essay-writing task (adapted from Galinsky et al.,
Inside the scanner, but prior to scanning, participants completed a second power prime consisting of a power analogy task corresponded to their pre-assigned prime condition (Bridge and Chiao, submitted). The power analogy prime consisted of 24 hierarchical social role pairs displayed in an analogical format (e.g., Teacher: Student, see Figure
A total of 20 small addition problems were used in the math task. Ten small addition problems and corresponding approximate (e.g., 6 + 2 = 3 or 9) and exact (e.g., 6 + 2 = 8) answer choices were administered (adapted from Stanescu-Cosson et al.,
We employed a block design that included 5 approximate math, 5 exact math, and 11 gray square control blocks. Participants completed alternating blocks of the approximate and exact math conditions with interleaving blocks of the control task during the fMRI scan. The order of the math blocks was counterbalanced across participants, but each functional run always began and ended with the control task. Each block was comprised of eight response trials that followed the same presentation format. For the math tasks, each trial began with a 200 ms central fixation cross followed by the presentation of an addition problem for 200 ms. Next, a central fixation cross was again displayed for 200 ms, after which two answer choices appeared on the screen for 200 ms. Once the answer choices disappeared from the screen, participants were prompted to make a button press response with their right index or middle finger to select the answer choice on the left or the right, respectively. Participants were allotted 2200 ms to make a response, but they were instructed to respond as quickly as possible without sacrificing speed for accuracy. The format of the gray square control task was identical to the math tasks. Rather than viewing an addition problem and two answer choices, participants instead saw two brief presentations of a gray square centered on the screen. During the allotted response time, participants were prompted to press a button their index finger as quickly as they could. The control blocks served as both a rest period and a baseline to subtract neural activity related to motor preparation and execution. Prior to scanning, participants were given practice trials of each condition in order to gain familiarity with the tasks and the timing of each stimulus presentation.
After scanning, participants completed several behavioral surveys to assess possible individual differences that may affect math calculation, specifically math confidence, explicit math attitudes, and personality traits, such as anxiety (e.g., state-trait anxiety).
Functional brain images were acquired at the Center for Advanced Medical Resonance Imaging (CAMRI) facility located in the Northwestern Medical Hospital in Chicago, IL. Scanning occurred on a 3.0 Tesla Siemens Trio MRI scanner equipped with single-shot, whole-body, echo planar image [repetition time (TR) = 2000 ms; echo time (TE) = 25 ms; flip angle = 70°; FOV = 20 cm, 64 × 64 matrix; 34 slices; voxel size = 3.0 × 3.0 × 4.0 mm], sensitive to BOLD contrast. A high-resolution anatomical T1-weighted image was also acquired [TR = 2300 ms; TE = 2.91 ms; flip angle = 9°; FOV = 256 mm; 256 × 256 matrix; 176 slices; voxel size = 1.0 × 1.0 × 1.0 mm] for each subject. All stimuli were presented using Presentation software (Neurobehavioral Systems, Albany, CA) and projected onto a half-transparent viewing screen located behind the head coil. Subjects viewed the projected stimuli through a mirror.
Functional images were analyzed using SPM5 software (Wellcome Department of Imaging Neuroscience, London, UK) implemented in Matlab (Mathworks, Cherborn, MA, USA). First, all volumes were realigned spatially to the first volume and a mean image was created. After a high-resolution image was coregistered onto the mean image, all volumes were normalized to the MNI (Montreal Neurological Institute) space using a transformation matrix obtained from the normalization process of the high-resolution image of each individual subject to the MNI template. The normalized images were then spatially smoothed with an 8 mm Gaussian kernel.
After preprocessing, statistical analysis for each individual subject was conducted using the general linear model (Friston et al.,
Random-effect analyses were then conducted with individual subject contrast images (Friston et al.,
To further investigate predicted group interaction effects within specific regions-of-interest (fROIs): independent ROIs were defined via main effect comparisons of Approximate > Control and Exact > Control contrasts and functional ROIs were defined by the interaction of power prime and type of math calculation. Each ROI was defined as a sphere with a 10 mm diameter was drawn around each peak voxel that arose from the random effects analysis with a
We conducted a 2 (
We conducted a 2 (
Reaction time | ||
Exact | 479 (32) | 470 (32) |
Approximate | 567 (28) | 553 (28) |
Accuracy | ||
Exact | 98% (1%) | 99% (1%) |
Approximate | 99% (1%) | 96% (1%) |
Math confidence | 6.83 (0.64) | 6.17 (0.64) |
Math attitudes | 6.67 (0.53) | 4.83 (0.87) |
State-trait anxiety inventory | ||
State anxiety | 1.68 (0.14) | 1.64 (0.09) |
Trait anxiety | 1.93 (0.09) | 1.80 (0.08) |
There was no main effect of power prime on math confidence (
HP prime participants (
There was no main effect of power prime on state or trait anxiety (
For all participants, several subregions within the frontal and parietal lobes showed greater neural response during exact math calculation compared to baseline, including the left angular gyrus and bilateral IFG (Figure
L Angular gyrus | 39 | 474 | −27 | −62 | 39 | 5.96 |
L Cerebellum | 251 | −3 | −80 | −19 | 5.51 | |
R Caudate | 118 | 21 | −5 | 20 | 4.89 | |
R Cerebellum | 78 | 30 | −68 | −19 | 4.75 | |
R Inferior occipital gyrus | 19 | 86 | 42 | −73 | 1 | 4.51 |
L Middle frontal gyrus | 6 | 84 | −27 | 0 | 50 | 4.28 |
L Thalamus | 49 | −15 | −11 | 17 | 3.87 | |
R Inferior frontal gyrus | 9 | 26 | 39 | 10 | 24 | 3.65 |
L Anterior cingulate cortex | 32 | 16 | −6 | 11 | 46 | 3.64 |
R Cerebellum | 509 | 6 | −77 | −16 | 6.07 | |
L Fusiform gyrus | 37 | 134 | −42 | −56 | −10 | 4.95 |
R Cingulate cortex | 24 | 369 | 6 | 4 | 27 | 4.73 |
L Middle frontal gyrus | 6 | 151 | −24 | −3 | 53 | 4.63 |
R Precentral sulcus | 9 | 49 | 39 | 7 | 30 | 4.23 |
R Middle occipital gyrus | 18 | 26 | 33 | −84 | 4 | 4.18 |
R Inferior occipital gyrus | 19 | 42 | 45 | −70 | 1 | 3.84 |
R Precuneus | 7 | 233 | 6 | −68 | 48 | 4.42 |
R Cerebellum | 19 | 9 | −77 | −24 | 3.92 | |
No suprathreshold clusters |
There was no main effect of power prime on neural response. However, compared to HP participants, LP participants showed greater right precentral gyrus during exact and approximate calculation relative to baseline (Table
HP(Approximate + Exact) > LP(Approximate + Exact) | ||||||
No suprathreshold clusters | ||||||
LP(Approximate + Exact) > HP(Approximate + Exact) | ||||||
No suprathreshold clusters | ||||||
HP(Approximate + Exact > Control) > LP(Approximate + Exact > Control) | ||||||
No suprathreshold clusters | ||||||
LP(Approximate + Exact > Control) > HP(Approximate + Exact > Control) | ||||||
Precentral gyrus | 6 | 16 | 42 | −6 | 27 | 4.06 |
HP participants showed greater neural response within right precuneus and left cerebellum compared to LP participants during exact calculation compared to control (Table
HP(Exact > Control) > LP(Exact > Control) | ||||||
R Precuneus/PCC | 31 | 65 | 6 | −60 | 22 | 3.95 |
L Cerebellum | 23 | −27 | −62 | −12 | 2.89 | |
LP(Exact > Control) > HP(Exact > Control) | ||||||
No suprathreshold clusters | ||||||
HP(Approximate > Control) > LP(Approximate > Control) | ||||||
No suprathreshold clusters | ||||||
LP(Approximate > Control) > HP(Approximate > Control) | ||||||
L Inferior frontal gyrus | 47 | 18 | −33 | 26 | −4 | 3.44 |
R Claustrum | 123 | 30 | −19 | 20 | 3.37 | |
R Precentral gyrus | 4 | 30 | 33 | −15 | 45 | 3.25 |
HP(Approximate > Exact) > LP(Approximate > Exact) or LP(Exact > Approximate) > HP(Exact > Approximate) | ||||||
No suprathreshold clusters | ||||||
LP(Approximate > Exact) > HP(Approximate > Exact) or HP(Exact > Approximate) > LP(Exact > Approximate) | ||||||
R Caudate nucleus | 26 | 12 | −2 | 22 | 3.46 | |
In the left IFG [−30 26 −4], we observed an interaction of power prime and type of math calculation,
Finally, there was also a significant effect of individual differences in math confidence,
Within IFG, there was a significant power prime and type of math calculation interaction,
To determine the extent to which social and personality factors predict neural response within bilateral IFG, we conducted a multiple linear regression with state-trait anxiety, math confidence, math attitudes and power prime as predictor variables. Results show that power prime β = 0.04,
Here we show for the first time that temporarily heightening a person's social power decreases neural response within regions previously associated with cognitive interference and improves math ability, particularly for approximate math calculation, even when controlling for individual differences in trait anxiety and math confidence. Specifically, people who are primed with LP are more likely to recruit left IFG when solving math problems, providing evidence that heightened cognitive interference during approximate math calculation may explain why math performance is decreased when people are in situations of LP. Furthermore, we speculate that power priming affects the neural processing during approximate compared to exact math calculation, due to incongruency with cognitive styles of math calculation. Our findings are consistent with prior behavioral studies demonstrating reduced executive functioning (Smith et al.,
Notably, we also show that power priming increases females' recruitment of the left IFG during math calculation, irrespective of type of math calculation. Prior research has shown that when females are reminded of negative stereotypes about female's performance in math, they show increased recruitment of the ventral anterior cingulate cortex (vACC) during math calculation (Krendl et al.,
Finally, we demonstrate that a novel power prime, specifically completing analogies that test knowledge of social power roles, in addition to writing a power prime essay, are effective at temporarily modulating both neural and behavioral responses during math calculation. Our findings have implications for interventions and procedures that may be implemented in educational studies and environments to improve math performance in social groups who are known to encounter negative cultural stereotypes about their groups' math ability. Recent evidence suggests that the human ability to perform numerical approximation is a foundational stepping stone for achieving more complex mathematical abilities. For instance, Halberda et al. (
On a national scale, social status influences students' learning and future academic success. For instance, a substantially smaller proportion of high school seniors from low socioeconomic status (SES) households (50.8%) anticipate attaining post-secondary and graduate-level degrees in comparison to students from middle- and high-income households (66.4 and 86.6%, respectively) (US Department of Education,
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We thank L. Waters, J. Scimeca, and A. Gurnani for assistance with stimuli preparation and data collection. This work is supported by NSF grants BCS-0720312 and BCS-0722326 to Joan Y. Chiao.
Inexperienced
A leader
Studious
Silly
Sleepy
Dependent
Ordinary
Powerful
Athletic
Compliant
Influential
Lighthearted
Clean
Compliant
Demanding
Hungry
Fascinating
Materialistic
Authoritative
Submissive
Gullible
Intimidating
Focused
Thorough
Destitute
Indecisive
Sincere
Pompous
Vulnerable
Compulsive
Have Leverage
Unpopular
Artistic
Esteemed
Submissive
Scientific
Subordinate
Adept
Lighthearted
Troubled
Superior
Gentle
Subservient
Withdrawn
Authoritative
Helpless
Musical
Dull
Submissive
Meditative
Patronizing
Environmentally Conscious
Ashamed
Passive
Influential
Lonely
Powerless
Whimsical
Controlling
Precise
Forgetful
Important
Sensitive
Subordinate
Controlling
A Daydreamer
Helpless
Sensitive
Fashionable
Inferior
Superior
Theatrical
Adventurous
Ethical
Prestigious
Subservient
Accomplished
Comical
Conservative
Subordinate
Knowledgeable
Fashionable
Impressionable
Clean
Commanding
Cooperative
Impractical
Social
Moral
Submissive
Disorganized
Dominant
Accomplished
Unskilled
Forgetful
Frivolous