A-key-role-for-experimental-task-performance-Effects-of-math-talent,-gender-and-performance-on-the-neural-correlates-of-mental-rotation_2012_Brain.pdf

Brain and Cognition 78 (2012) 14–27

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Brain and Cognition

journal homepage: www.elsevier.com/locate/b&c

A key role for experimental task performance: Effects of math talent, gender

and performance on the neural correlates of mental rotation

Christian Hoppe a , ⇑ , Klaus Fliessbach a , b , Sven Stausberg a , Jelena Stojanovic a , Peter Trautner b ,

Christian E. Elger a , b , Bernd Weber a , b

a Department of Epileptology, University of Bonn Medical Centre, Germany

b Department of NeuroCognition, Life & Brain Centre, Germany

article info

abstract

Article history:

Accepted 18 October 2011

Available online 15 November 2011

The neurophysiological mechanisms underlying superior cognitive performance are a research area of

high interest. The majority of studies on the brain–performance relationship assessed the effects of capa-

bility-related group factors (e.g. talent, gender) on task-related brain activations while only few studies

examined the effect of the inherent experimental task performance factor. In this functional MRI study,

we combined both approaches and simultaneously assessed the effects of three relatively independent

factors on the neurofunctional correlates of mental rotation in same-aged adolescents: math talent

(gifted/controls: 17/17), gender (male/female: 16/18) and experimental task performance (median split

on accuracy; high/low: 17/17). Better experimental task performance of mathematically gifted vs. control

subjects and male vs. female subjects validated the selected paradigm. Activation of the inferior parietal

lobule (IPL) was identiﬁed as a common effect of mathematical giftedness, gender and experimental task

performance. However, multiple linear regression analyses (stepwise) indicated experimental task per-

formance as the only predictor of parietal activations. In conclusion, increased activation of the IPL rep-

resents a positive neural correlate of mental rotation performance, irrespective of but consistent with the

obtained neurocognitive and behavioral effects of math talent and gender. As experimental performance

may strongly affect task-related activations this factor needs to be considered in capability-related group

comparison studies on the brain–performance relationship.

Keywords:

Mental rotation

Mathematical giftedness

Gender effects

Neural correlates of cognitive performance

Inferior parietal lobule

Functional magnetic resonance imaging

1. Introduction

1992 ). Since stimulation tasks which address the speciﬁc knowl-

edge or skills of high-capability subjects are beyond reach for stan-

dard subjects, the applied tasks usually refer to elementary

cognitive abilities that presumably contribute to the respective

capability of interest. However, it is debatable whether a capabil-

ity-related group effect on experimental task performance (i.e.

behavioral performance during scanning) validates the supposed

capability-task relationship or rather confounds the group factor

( Bell, Willson, Wilman, Dave, & Silverstone, 2006; Butler et al.,

2006; Jordan, Wustenberg, Heinze, Peters, & Jancke, 2002; Larson,

Haier, LaCasse, & Hazen, 1995; O’Boyle et al., 2005; Thomsen

et al., 2000; Unterrainer, Wranek, Staffen, Gruber, & Ladurner,

2000; Weiss et al., 2003a,b ). In case of equal experimental task per-

formance, neural correlates of the capability-related group factor

do not represent an NCP of the applied task (according to the above

deﬁnition) but rather indicate unknown group-speciﬁc neurocog-

nitive factors which are irrelevant with regard to experimental task

performance (e.g. stress response).

Alternatively, studies on NCPs may focus more directly on the

effects of behavioral performance in an experimental task on the

brain activations which were elicited by this very task. Task

Interindividual variance of performance in a given task (e.g.

accuracy, speed) is a ubiquitous psychological phenomenon. Any

functional or structural brain property which co-varies with task

performance can be addressed as a neural correlate of performance

(NCP) of the respective task. Searching NCPs is currently a highly

active ﬁeld in neurocognitive research ( Deary, Penke, & Johnson,

2010; Haier, 2009; Neubauer & Fink, 2009; Rypma & Prabhakaran,

2009 ).

Neuroimaging research on NCPs has largely focused on the ef-

fects of capability-related group factors (e.g. intelligence, talent,

or expertise) on task-related brain activations ( Grabner, Neubauer,

& Stern, 2006; Lee et al., 2006; Singh & O’Boyle, 2004 ). Capability

effects have been reported since the very beginning of functional

neuroimaging ( Charlot, Tzourio, Zilbovicius, Mazoyer, & Denis,

⇑ Corresponding author. Address: Department of Epileptology, University of Bonn

Medical Centre, Sigmund-Freud-Straße 25, 53105 Bonn, Germany. Fax: +49 228 287

90 16172.

E-mail address: christian.hoppe@ukb.uni-bonn.de (C. Hoppe).

doi: 10.1016/j.bandc.2011.10.008

C. Hoppe et al. / Brain and Cognition 78 (2012) 14–27

performance effects on functional brain activation (and also con-

nectivity) were repeatedly reported and actually challenge any

too simplistic approach to functional brain mapping ( Rypma

et al., 2006; Tagaris et al., 1996b, 1997; Unterrainer et al., 2000,

2005 ). Evidently, this approach makes full use of the available

behavioral and neurophysiological data obtained by functional

neuroimaging. In addition, NCPs of a given task can be assessed

in non-indicated standard subjects, for example by contrasting ret-

rospectively identiﬁed high vs. low experimental task performers

( Rypma et al., 2006 ).

In the present fMRI study, we combined these two research

strategies to allow their evaluation and comparison. Referring to

several previous studies from other groups ( O’Boyle et al., 2005;

Unterrainer et al., 2000, 2004, 2005 ), we simultaneously examined

the effects of math talent, gender and experimental task perfor-

mance on brain activations during mental rotation. Mental rotation

is one of the best studied paradigms in both experimental psychol-

ogy and cognitive neuroscience since its introduction by Shepard

and Metzler (1971) . On a behavioral level, both gender ( Collins &

Kimura, 1997; Kimura, 1996; Linn & Petersen, 1985; Lippa, Collaer,

& Peters, 2010; Lubinski & Humphreys, 1990; Masters & Sanders,

1986, 1993; Moore & Johnson, 2008; Peters, 2008; Quinn & Liben,

2008; Voyer & Hou, 2006; Voyer, Voyer, & Bryden, 1995 ) and math

talent ( Casey, Nuttall, & Benbow, 1995; Hyde, 2005; O’Boyle, Ben-

bow, & Alexander, 1995; Spelke, 2005 ) have shown reliable effects

on mental rotation performance. Mental rotation reliably activates

the posterior parietal cortices (PPC) which also play a key role for

working memory and general intellectual functioning ( Champod

& Petrides, 2007, 2010; Jung & Haier, 2007; Zacks, 2008 ).

Unfolding the idea of speciﬁc neural mechanisms underlying

better cognitive performance of a given task, we tested the follow-

ing hypotheses:

subject recruitment, we additionally aimed at an equal distribution

of male and female subjects in both samples to implement gender

as an independent second capability-related group factor. Due to

technical artifacts in the MRI data, three control subjects had to

be excluded from the ﬁnal analysis. Table 1 lists the characteristics

of the included subjects. All subjects had normal or corrected-to-

normal vision. Subjects were reimbursed for participation (10€/h)

and travel costs. All subjects and their parents gave written in-

formed consent according to the rules of good scientiﬁc practice.

2.2. Task

The original Shepard–Metzler (SM) paradigm shows a pair of

drawings of quasi-3D-ﬁgures, each of which is constructed out of

10 cubes rendered in two dimensions (‘‘3D ﬁgures’’) and requires

a matching decision (identical vs. mirrored). In contrast, the Van-

denberg–Kuse (VK) paradigm ( Vandenberg & Kuse, 1978 ) which

was applied in the majority of neuroimaging studies ( Zacks,

2008 ) simultaneously shows one Shepard–Metzler ﬁgure as the

target and four additional ﬁgures as probes and requires the sub-

jects to select the one probe which matches the target though

being spatially rotated (i.e. 4-alternatives forced choice; Peters &

Battista, 2008; Peters et al., 1995 ). In this paradigm, identical stim-

uli (i.e. 0 angular disparity condition), scrambled dot patterns de-

rived from the ﬁgures, or black and white bars serve as the control

stimuli.

We propose a modiﬁed preparation rotation paradigm ( Jansen-

Osmann & Heil, 2007 ): (i) To avoid the reportedly high error rates

(>40%) of established paradigms ( O’Boyle et al., 2005; Weiss et al.,

2003a,b ); (ii) to separate mental rotation proper from both the

encoding of the stimulus and the matching test; and (iii) to im-

prove experimental control over the task difﬁculty in terms of both

cognitive load and speed demands for future studies. The modiﬁed

paradigm is shown in Fig. 2 . A two-dimensional rendering of a

three-dimensional stair-like ﬁgure composed of three cubes (i.e.

a fragment of the original Shepard–Metzler items; Fig. 1 ) was used

as the stimulus. Rotations of this object had to be performed at 90

(instead of 15) angles within one of the three spatial planes (hor-

izontal, sagittal, frontal) resulting in 12 possible positions of the

object. At the beginning of each trial, the stimulus was presented

for 2 s in a randomly selected position. Subjects were then

prompted to perform four continuous mental rotations of the ob-

ject starting from the initial position as indicated by four serially

presented arrows (duration: 13 s, i.e. 3.25 s per rotation; each ar-

row presented for 0.813 s). Pilot studies in adolescent control sub-

jects (N = 30) conﬁrmed the appropriateness of these speed

demands. In the task condition, the rotation plane was changed

either for one time or for three times: In Fig. 2 , the task condition

shows three rotation plane changes (upward/sagittal, right/hori-

zontal, clockwise/frontal, downward/sagittal). In the control condi-

tion (active low level task), the arrows indicated back-and-forth

left and right rotating of the object within the horizontal plane

( Fig. 2 ). The subjects were instructed that this condition only re-

quired the maintenance of the ﬁgure in its initial position. Each

trial was completed by a matching decision task presenting the ob-

ject in one of the twelve possible positions as a probe. Subjects

pressed a button to indicate if the probe matched the ﬁgure’s posi-

tion after performing the instructed rotations (response latency:

3 s). A total of 30 control and 30 task trials were presented alter-

nately allowing mental rotation-related brain activations to return

to the baseline. Matching decisions were recorded as correct or

false responses. The individual mental rotation accuracy score,

MRX, was deﬁned by MRX =(1 (number of errors during task tri-

als/number of task trials number of errors during control trials/

number of control trials)) which obtains a positive indicator of

(I) Mathematically gifted vs. control subjects and male vs.

female subjects show better mental rotation performance.

(II) Effect of the experimental task performance factor: Activation

of the PPC is obtained as an NCP, i.e. a positive neural corre-

late of mental rotation performance.

(III) Effects of capability-related factors: Math talent and gender

yield activations of the PPC similar to the effects of experi-

mental task performance as both are associated with better

experimental task performance.

(IV) As the elicited neurocognitive activations are more inher-

ently related to the experimental task, most of the variance

of PPC activations can be explained by the experimental task

performance factor.

2. Materials and methods

This study was approved by the Ethical Review Board of the

Medical Faculty at the University of Bonn (No. 039/06). The study

was carried out in accordance with The Code of Ethics of the World

Medical Association (Declaration of Helsinki)

for experiments

involving humans.

2.1. Subjects

The study included 17 adolescent mathematically gifted sub-

jects (MATH) and 20 same-aged control subjects (CON) between

the ages of 15 and 18 without mathematical talent. Mathematical

talent was assigned if the student was matriculated for Mathemat-

ics at the University of Bonn while attending high school (which

relies on the recommendation of their schools) or if a subject re-

cently participated in the ‘Mathematical Olympiad’ at a federal

state level (state of North-Rhine Westphalia; total in 2007:

N = 350 out of 16,000 participants on the community level). During

C. Hoppe et al. / Brain and Cognition 78 (2012) 14–27

Table 1

Subject characteristics and test scores: means (SD) and frequencies.

Math talent

Gender

Talented subjects n = 17

Control subjects n =17 p

Male subjects n = 17

Female subjects n =17 p

1.000 a

Gender m/f

8/9

1.000 a

Math talent yes/no

8/8

9/9

Handedness RH/LH/MH

14/1/2

15/0/2

0.596 a

13/0/3

16/1/1

0.333 a

Handedness Laterality Index c

0.540 b

0.528 b

0.7 (0.6)

0.9 (0.4)

0.8 (0.5)

0.9 (0.5)

0.518 b

0.463 b

Age (years)

16.7 (1.1)

16.5 (0.9)

16.5 (1.0)

16.7 (0.9)

0.001 b

0.940 b

Extracurricular math activities (min/day)

64.1 (49.7)

14.3 (12.2)

52.3 (56.6)

40.9 (34.1)

Math grade d

0.005 b

0.347 b

1.3 (0.6)

2.3 (1.1)

1.6 (1.0)

1.9 (1.0)

Total average grade d

0.085 b

0.772 b

1.9 (0.5)

2.3 (0.5)

2.1 (0.6)

2.1 (0.5)

CFT-20 R (IQ) e

0.106 b

0.772 b

118.2 (13.1)

110.1 (14.5)

115.5 (15.7)

113.0 (13.1)

LPS 7 (C score) f

8.5 (1.2)

7.9 (1.0)

0.160 b

27.4 (4.3)

25.7 (5.2)

0.403 b

0.031 b

0.017 b

Pre-scanning: mental rotation level

7.0 (2.4)

5.5 (1.0)

7.2 (2.4)

5.4 (1.0)

0.018 b

0.030 b

Mental rotation score (MRX)

0.88 (0.09)

0.72 (0.20)

0.86 (0.14)

0.74 (0.18)

Behavioral performance: means (SD).

a Chi-square test.

b Mann–Whitney test.

c Oldﬁeld (1971) .

d German grades: 1 = very good (A grade), 6 = insufﬁcient (F grade).

e Weiß (2006) .

f Horn (1983) , C score: [mean = 5, SD = 2].

Fig. 1. Object for mental rotation. The ﬁgure is constructed out of three small cubes

in contrast to the original Shepard and Metzler (1971) objects which are

constructed out of ten cubes.

mental rotation proper performance controlled for maintenance

performance.

2.3. Adjunctive behavioral measures

Nonverbal intelligence was estimated by the CFT 20-R, part 1

( Weiß, 2006 ), a German measure which is well-established for

individual diagnosis and research on intellectual giftedness. The

test comprises four subtests on visuospatial logical reasoning sim-

ilar to Raven’s progressive matrices (test duration: 14 min.); a self-

developed computerized protocol version showing copies of the

original item sheets were used. Handedness was assessed by the

Edinburgh Handedness Inventory ( Oldﬁeld, 1971 ). Mental rotation

performance was measured using the Letter Rotation subtest LPS

7 from the Leistungs-Prüf-System ( Horn, 1983 ), a well-established

paper–pencil test for mental plane rotation of single letters (test

duration: 2 min). In addition, criteria of math talent, math and

mean school grades (German grades: 1 = very good, 6 = not sufﬁ-

cient), the daily time spent on extracurricular math activities and

other hobbies were documented.

Fig. 2. Modiﬁed mental rotation paradigm. Shown are the control condition (no-

rotation or pure maintenance condition) and the task condition (rotation axis

changing). The task condition was announced to the subject each time before the

starting stimulus was presented.

experimental mental rotation task outside of the scanner for

15 min (PC version; Borland Delphi 6.0). The program allowed

the subjects to explore the task, the properties of the stimulus

and the meaning of arrows ( Fig. 2 ). For example, they could ac-

tively rotate the object in the diverse directions by mouse-clicks

to become familiar with the different positions and the effects of

90 rotations on the ﬁgure. The speed demands (i.e. the number

of required mental rotations during the mental rotation phase)

could be controlled to ﬁnd out the maximum speed demand level

which was subjectively experienced as still convenient. For further

exploration, the stimulus was made available as a white cardboard

object (120 120 60 mm 3 ). During familiarization, subjects re-

ceived feedback on the correctness of their responses and the rota-

tion plane was changed three times during one trial, i.e. after each

2.4. Procedure

After the subjects were enrolled in the study, had their person-

related data recorded and handedness surveyed, they practiced the

C. Hoppe et al. / Brain and Cognition 78 (2012) 14–27

single rotation. Subjects were informed about the control condition

and the alternating sequence of true tasks and control tasks ap-

plied during scanning. The total time in the scanner was about

35 min, including the preceding localizer and the subsequent T1-

weighted structural brain scan. The assessment was completed

by applying the CFT-20 R part 1 and the LPS 7 after scanning. The

total duration of the examination was about 75 min.

group factors, we calculated the contrast of the task condition vs.

the control condition (‘‘task effect’’). To identify effects of the group

factors, the task effect was contrasted between the respective

groups (i.e. group task interaction, ‘‘group effects’’).

To exclude potentially confounding effects of error-related pro-

cesses, the correct trials were modeled separately from the error

trials in the ﬁrst-level analysis and the second-level analysis in-

cluded correct trials only. Error trials were modeled as an addi-

tional regressor of no interest. To further control for possible

confounding effects of different amounts of error-related process-

ing, the experimental task performance score was included as a

covariate in all group effects analyses on the a priori group factors,

i.e. math talent and gender. All analyses were conducted with a

threshold of p < .001, uncorrected, and an extent threshold of

k = 10 adjacent voxels. Anatomical labeling of peak activation vox-

els was done by the Masked Contrast Images (mascoi) tool for SPM

(version 2.11; Reimold, Slifstein, Heinz, Mueller-Schauenburg, &

Bares, 2006 ) with a secondary p < .001. Speciﬁc brain regions were

analyzed by the MARSeille Boîte À Région d’Intérêt (MarsBaR)

extension of SPM ( Brett, Anton, Valabregue, & Poline, 2002 ;

www.nitrc.org/projects/marsbar/ ) .

According to the ﬁndings of a meta-analysis of neuroimaging

studies on mental rotation ( Zacks, 2008 ), our main focus was on

the bilateral PPC, i.e. inferior (IPL) and superior parietal lobule

(SPL). With regard to the frontoparietal axis of general intellectual

functioning ( Jung & Haier, 2007 ), we also wanted to examine group

effects on activations in the dorsolateral prefrontal cortices

(DLPFC). Therefore, we deﬁned bilateral prefrontal and parietal

search volumes and extracted individual mean beta values from

all voxels of each search volume as parameter estimates for the

task-related activations in this area. The search volumes were

masked by task effects from the total sample restricting this anal-

ysis to task-related brain regions (Wake Forest University PickAtlas

tool for SPM, release 2.4; Maldjian, Laurienti, & Burdette, 2004;

Maldjian, Laurienti, Kraft, & Burdette, 2003 ). Multivariate analyses

of covariance (MANCOVA) on the activation parameter estimates

were performed with the experimental task performance score,

MRX, as a covariate and math talent, gender and experimental task

performance as the group factors. In addition, correlation and

regression analyses were performed on activation parameter esti-

mates and MRX. To evaluate the relative impact of the three group

factors on task-related brain activations in the selected brain areas,

multiple linear regression analyses (method: stepwise) were per-

formed on the activation parameters from the search volumes.

Analyses including brain activation parameters were also per-

formed by SPSS (Version 17.0.1., German release).

2.5. Magnetic resonance image acquisition

Magnetic resonance image scanning was performed on a 1.5T

MRI Scanner (Siemens Avanto, Erlangen, Germany) using a TIM

8-channel standard head coil. We acquired 500 T2 -weighted, gra-

dient echo planar imaging (EPI) scans including three initial dum-

my scans that were discarded in order to achieve steady-state

magnetization with the following parameters: slice-thick-

ness = 3 mm; interslice gap = .3 mm; matrix size = 64 64; ﬁeld

of view = 192 192 mm 2 ; echo time (TE) = 40 ms; repetition time

(TR) = 2910 ms. Thirty-ﬁve transversal slices were acquired which

covered the whole cerebral cortex but only the upper part of the

cerebellum. In addition, we obtained a sagittal T1-weighted 3D-

mprage sequence with 160 slices.

Scanning was comprised of 30 trials in the control condition

and 30 trials in the task condition. The inter-block interval was jit-

tered and varied randomly between 1.5 and 2.5 s. The scanning

procedure always followed the sequence: localizer (1 min), mental

rotation (60 22 s = 22 min), MPRAGE (8 min). The task was pre-

sented via video goggles (Nordic NeuroLab, Bergen, Norway) using

Presentation software (NeuroBehavioural Systems Inc., Albany/

California, USA; monitor resolution: 1024 768 pixels). Subjects

indicated their answers with the help of response grips (Nordic-

NeuroLab, Bergen, Norway).

2.6. Behavioral data analysis

The effects of math talent and gender on MRX were tested using

a bifactorial ANOVA and post hoc T-tests for independent samples.

Nonparametric tests (Mann–Whitney U-test, v 2 -test) were used to

test group differences of non-normally distributed adjunctive mea-

sures (e.g. school grades). Correlations of MRX, other performance-

related parameters and brain activation parameter estimates were

analyzed by Pearson’s product-moment correlation. The signiﬁ-

cance level was set to a = .05. Behavioral data were analyzed by

SPSS (Version 17.0.1., German release).

2.7. Neuroimaging data analysis

The preprocessing was performed by FSL software version 4.1.2

(FMRIB’s Software Library, www.fmrib.ox.ac.uk/fsl ) . Preprocessing

included realignment with unwarping; slice timing correction

using Fourier-space time-series phase-shifting; motion correction

using MCFLIRT; grand-mean intensity normalization of the entire

4D dataset by a single multiplicative factor; registration to stan-

dard space an EPI-template (resampled voxel size after registra-

tion: 3 3 3mm 3 ); and smoothing with a 8-mm Gaussian

kernel. The fMRI statistical analysis was done using Statistical

Parametric Mapping 5 (SPM5, www.ﬁl.ion.ucl.ac.uk/spm/ ) . The

hemodynamic response to each block was modeled by a canonical

hemodynamic response function. The onset was deﬁned by the

occurrence of the starting stimulus and the modeled block com-

prised the entire mental rotation phase, except for the ﬁnal test

(duration: 17 s). For each subject, parameter images for the con-

trasts of each condition were generated and subjected to a sec-

ond-level group effects analysis using a one-way ANOVA (within

subject) with group membership as a between subject factor. In or-

der to identify mental rotation related activation irrespective of the

3. Results

3.1. Performance

As shown in Table 1 , math talent and gender were stochastically

independent. In addition, both group factors showed no effect on

age, handedness distribution, nonverbal intelligence (CFT-20 R)

and two-dimensional mental letter rotation performance (LPS 7).

MATH spent signiﬁcantly more time per day on extracurricular

mathematical activities (Mann–Whitney U-test, p < .001), had bet-

ter math grades (p < .005), and a tendency towards better total

average grades (non-signiﬁcant trend, p < .085). No gender effects

on adjunctive behavioral measures were obtained.

Fig. 3 shows the group effects on the mental rotation perfor-

mance score, MRX. Bifactorial univariate ANOVA conﬁrmed main

effects of the factors math talent [F(1, 30) = 10.57, p < .003,

g 2 = 0.22] and gender [F(1, 30) = 6.72, p < .015, g 2 = 0.14] with no

interaction effect [F(1, 30) = 1.22, p = .279] indicating that MATH

C. Hoppe et al. / Brain and Cognition 78 (2012) 14–27

shows a superposition of these effects (for anatomic labels of peak

activation voxels see Table 2 ). Behaviorally superior subjects (i.e.

MATH, male subjects, and high performers) consistently showed

higher activations in the left IPL (SMG, not AG) when compared

to behaviorally inferior subjects. In addition, mathematically gifted

subjects showed increased activation in the left SPL and the right

postcentral gyrus. Additionally, male subjects showed activations

in the left precuneus, left precentral and right postcentral gyrus.

High performers also showed activations in the right IPL and the

right middle frontal gyrus. In contrast, behaviorally inferior as

compared to superior groups showed more diverse patterns of rel-

atively increased activations either in left frontal (math talent, gen-

der) or temporoparietal (experimental task performance) regions.

3.4. Activation parameters [ Fig. 6 and 7 ]

Fig. 3. Experimental task performance score, MRX (group means, bars in graph are

SEs of the mean). Bifactorial univariate ANOVA obtained main effects of math talent

[F(1, 30) = 10.57, p < .003, g 2 = 0.22] and gender [F(1, 30) = 6.7, p < .015, g 2 = 0.14]

indicating higher accuracy in the talented subjects and in the male subjects; no

‘math talent gender’ interaction effect was obtained, F(1, 30) = 1.22, p < .279.

Individual task-related activation parameter estimates (beta

values) were extracted from the following frontal and parietal

search volumes: left DLPFC corresponding to BA 9 (L.DLPFC, 60

voxels); right DLPFC (R.DLPFC, 29 voxels); left IPL (L.IPL, 383 vox-

els); right IPL (R.IPL, 217 voxels); left SPL (L.SPL, 199 voxels); and

right SPL (R.SPL, 171 voxels). The shown voxel numbers refer to

the search volumes after masking by the task effect.

Activations in the left and right prefrontal search volumes

showed no group effects [math talent: L.DLPFC: T(32) = 1.471,

p = .151; R.DLPFC: T(32) = 0.739; p = .465; gender: L.DLPFC:

T(32) = 0.953, p = .348; R.DLPFC: T(32) = 0.640, p = .527; experi-

mental

vs. CON and male vs. female subjects showed better mental rota-

tion performance. Regarding the control task condition, the bifac-

torial univariate ANOVA obtained a main effect for math talent

[F(1, 30) = 5.16, p < .030, g 2 = 0.15] indicating higher accuracy of

MATH during the maintenance condition; no main effect of gender

(p = .836) and no ‘‘talent gender’’ interaction effect (p = .653)

were revealed. MRX was correlated with the pre-scanning self-esti-

mate of maximum mental rotation speed (r = 0.41, p < .017), men-

tal letter rotation performance (r = 0.41, p < .016), math grades

(r = 0.57, p < .001), and, in a non-signiﬁcant trend, nonverbal

intelligence (r = 0.32, p = .062).

The stimulation task performance factor was retrospectively de-

ﬁned by a median split of the total sample based on MRX (cut-

off = 0.85, high/low performers: 17/17). The performance factor

was signiﬁcantly correlated with math talent [ v 2 (1) = 5.765,

p < .016] (5/17 MATH were low performers, 5/17 CON were high

performers) but not with gender [ v 2 (1) = 1.889, p = .169] (6/16

male subjects were low performers, 7/18 female subjects were

high performers).

For the total sample, error rates from the active control condi-

tion were signiﬁcantly lower than from the task condition

(Mean ± SD: baseline = 0.06 ± 0.07; task = 0.26 ± 0.19)

[T(33) = 6.85, P < .001]. As a non-signiﬁcant trend, mean error

rates from task trials with one change of the rotation axis were

lower than for trials with three changes of the rotation axis

[T(33) = 1.977, p = .056] thus indicating that the modiﬁed mental

rotation paradigm allows the manipulation of task difﬁculty in

terms of cognitive load.

task performance:

L.DLPFC:

T(32) = 0.736, p = .467;

R.DLPFC: T(32) = 1.426, p = .163].

Fig. 6 shows the group means of the parameter estimates ex-

tracted from the parietal cortical search volumes for MATH and

CON (panel A), male and female subjects (B), and high and low

mental rotation performers (C). Repeated measures MANOVA

including the a priori group factors, math talent and gender, and

the four parietal activation parameter estimates (L.IPL, R.IPL,

L.SPL, R.SPL) as dependent variables obtained no multivariate main

or interaction effects (p > .196 for all effects). Post hoc univariate

testing yielded a main effect of math talent on L.IPL activa-

tion [F(1, 30) = 5.518, p < .026, g 2 = 0.14] and near-signiﬁcant

trends towards main effects of math talent on L.SPL activa-

tion [F(1, 30) = 3.469, p = .072, g 2 = 0.092] and of gender on L.IPL

[F(1, 30) = 3.999, p = .055, g 2 = .101] and L.SPL activation

[F(1, 30) = 4.126, p = .051, g 2 = 0.109]; no interaction effect was

indicated. The univariate effects of talent and gender were omitted

if MRX was included as a covariate into the model (p > .130 for all

effects). In contrast to the a priori group factors, the task perfor-

mance group factor yielded a multivariate main effect on the pari-

etal activation parameters [Wilks lambda = 0.702, F(4, 29) = 3.079,

p < .031]. In addition, post hoc univariate testing obtained effects

of the performance factor on activation parameter estimates from

each included parietal search volume [L.IPL: F(1, 32) = 8.398,

p < .007, g 2 = .021; R.IPL: F(1, 32) = 9.742, p < .004, g 2 = 0.23; L.SPL:

F(1, 32) = 4.362, p < .045, g 2 = 0.12; R.SPL: F(1, 32) = 5.084, p < .031,

g 2 = 0.14].

MRX showed positive correlations with the activation parame-

ter estimates from the parietal search volumes (L.IPL: r = 0.41,

p < .016; R.IPL: r = 0.40, p < .018; R.SPL: r = 0.39, p < .023) except

for L.SPL the activation of which showed a near-signiﬁcant trend

(r = 0.34, p = .051). The scatter plots in Fig. 7 show the correlation

of MRX and task-related activations of the bilateral IPL; math talent

and gender are also indicated. L.IPL activation was also positively

correlated with the pre-scanning self-estimate of mental rotation

speed (r = 0.363, p < .035).

To evaluate the relative contributions of the three performance

factors to task-related brain activation, we performed stepwise

multiple linear regression analyses on the activation parameters

3.2. Task effects

Mental rotation activated widespread parietal and frontal re-

gions in the cerebral hemispheres, midbrain and also cerebellum

( Table 2 ). The peak activation for the ‘‘task vs. control condition’’

contrast was in the left IPL (Montreal Neurological Institute

[MNI] template coordinates for the peak activation voxel:

X = 42; Y = +39; Z = +42). More speciﬁcally, the activated inferior

parietal region comprised the supramarginal gyrus (SMG, Brod-

mann area/BA 40/7) but not the angular gyrus (AG, BA 39).

3.3. Group effects

The effects of the two capability-related group factors, math tal-

ent and gender, and the retrospectively deﬁned task performance

factor on task-related brain activations are shown in Fig. 4 ; Fig. 5

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