Neuropsychologia 51 (2013) 2251–2260

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Neuropsychologia

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The functional neuroanatomy of multitasking: Combining dual taskingwith a short term memory task

Sabine Deprez a,b,c,n, Mathieu Vandenbulcke c,d,e, Ron Peeters a,b,c, Louise Emsell a,b,c,Frederic Amant f,g, Stefan Sunaert a,b,c

a Department of Radiology, UZ Leuven, Herestraat 49, Leuven, Belgiumb Department of Imaging & Pathology, KU Leuven, Herestraat 49, Leuven, Belgiumc Leuven Research Institute for Neuroscience & Disease (LIND), KU Leuven, Herestraat 49, Leuven, Belgiumd Department of Psychiatry, UZ Leuven, Herestraat 49, Leuven, Belgiume Department of Neurosciences, KU Leuven, Herestraat 49, Leuven, Belgiumf Multidisciplinary Breast Cancer Center, UZ Leuven, Herestraat 49, Leuven, Belgiumg Department of Oncology, KU Leuven, Herestraat 49, Leuven, Belgium

a r t i c l e i n f o

Article history:Received 20 November 2012Received in revised form25 July 2013Accepted 30 July 2013Available online 11 August 2013

Keywords:MRIfMRIExecutive functioningMemoryAttentionMultitaskingDual-tasking

32/$ - see front matter & 2013 Elsevier Ltd. Ax.doi.org/10.1016/j.neuropsychologia.2013.07.0

esponding author at: Department of RadiologUniversity of Leuven, Herestraat 49, B-300016 34 90 70; fax: +32 16 34 37 69.

ail addresses: sabine.deprez@uzleuven.be (S. D.vandenbulcke@uzleuven.be (M. Vandenbulckeeters@uzleuven.be (R. Peeters),msell@med.kuleuven.be (L. Emsell),unaert@uzleuven.be (S. Sunaert).

a b s t r a c t

Insight into the neural architecture of multitasking is crucial when investigating the pathophysiology ofmultitasking deficits in clinical populations. Presently, little is known about how the brain combinesdual-tasking with a concurrent short-term memory task, despite the relevance of this mental operationin daily life and the frequency of complaints related to this process, in disease. In this study we aimed toexamine how the brain responds when a memory task is added to dual-tasking. Thirty-three right-handed healthy volunteers (20 females, mean age 39.975.8) were examined with functional brainimaging (fMRI). The paradigm consisted of two cross-modal single tasks (a visual and auditory temporalsame-different task with short delay), a dual-task combining both single tasks simultaneously and amulti-task condition, combining the dual-task with an additional short-term memory task (temporalsame-different visual task with long delay). Dual-tasking compared to both individual visual andauditory single tasks activated a predominantly right-sided fronto-parietal network and the cerebellum.When adding the additional short-term memory task, a larger and more bilateral frontoparietal networkwas recruited. We found enhanced activity during multitasking in components of the network that werealready involved in dual-tasking, suggesting increased working memory demands, as well as recruitmentof multitask-specific components including areas that are likely to be involved in online holding of visualstimuli in short-term memory such as occipito-temporal cortex. These results confirm concurrent neuralprocessing of a visual short-term memory task during dual-tasking and provide evidence for an effectivefMRI multitasking paradigm.

& 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Doing two things at the same time whilst trying not to forget athird one is a part of everyday life for most of us. However, this abilityto effectively distribute and coordinate attentional resources to per-form multiple tasks can become impaired. Patients with cancer whoreceived chemotherapy (Deprez et al., 2011, 2012; O'Farrell,

ll rights reserved.24

y, University Hospital of theLeuven, Belgium.

eprez),e),

Mackenzie, & Collins, 2013; Ribi, 2012; Wefel & Schagen, 2012),patients with traumatic brain injury (Fortin, Godbout, & Braun,2002; Toyokura, Nishimura, Akutsu, Mizuno, & Watanabe, 2012) andmild cognitive impairment (Makizako et al., 2013) often complainabout subtle cognitive deficits, especially during “multitasking”,despite normal performance on traditional neuropsychological tests.Multitasking deficits have mainly been assessed through neuropsy-chological evaluation. For example by combining executive tasks(Baddeley, Della Sala, Papagno, & Spinnler, 1997), memory tasks(Smith-Conway, Chenery, Angwin, & Copland, 2012), memory andmotor tasks (MacPherson, Parra, Moreno, Lopera, & Della Sala, 2012),everyday tasks involving cooking (Fortin et al., 2002; Frisch, Forstl,Legler, Schope, & Goebel, 2012) and walking and talking (Rochesteret al., 2004), or a combination of tasks in a multitasking framework(Burgess, 2000; Wetherell, Atherton, Grainger, Brosnan, & Scholey,2012). These tasks were mostly assessed using paper-and-pencil or

S. Deprez et al. / Neuropsychologia 51 (2013) 2251–22602252

have been implemented on a computerized platform. Only a limitednumber of studies have used functional Magnetic Resonance Imaging(fMRI) to study multitasking deficits, mostly involving a simple dual-task (Rasmussen et al., 2008; Wu & Hallett, 2008).

The purpose of the present study was to investigate the neuralsubstrates of multitasking in healthy volunteers using fMRI with amultitasking paradigmwe developed, which could later be appliedto study subtle cognitive deficits in specific patient groups.We aimed to develop a multitasking paradigm that combinesdual-tasking (including dividing attention and switching betweentwo types of information, i.e. auditory and visual stimuli) with on-line holding of a third stimulus. These processes are broadlyclassified under the umbrella of working memory, which refersto the cognitive capacity to hold and manipulate information inmemory. Although we have a relatively good understanding of theneural underpinnings of different working memory operationsseparately, it remains largely unknown how these are combined.This study examines the functional neuroanatomy of combiningdual-tasking with an additional short-term memory task.

Mesulam (2000) described working memory as a predomi-nantly attentional function under the control of a fronto-parietalnetwork where the prefrontal and posterior parietal cortex areinvolved in the online maintenance of information, and theprefrontal dorsolateral cortex in controlling the executive aspects(e.g. task ordering and switching between tasks).

Several neuroimaging studies have analyzed the neuroanatomicalcorrelates of cognitive demands in dual-tasking and divided attention(Corbetta, Miezin, Dobmeyer, Shulman, & Petersen, 1991; Dux, Ivanoff,Asplund, & Marois, 2006; Johnson & Zatorre, 2006; Loose, Kaufmann,Auer, & Lange, 2003; Szameitat, Lepsien, von Cramon, Sterr, &Schubert, 2006; Szameitat, Schubert, Muller, & Von Cramon, 2002).They describe the involvement of a fronto-parietal attention networkwith a specific role for the dorsolateral prefrontal cortex in thecoordination of concurrent processes. More specifically, cortical areasalong the inferior frontal sulcus (IFS) (Nebel et al., 2005; Szameitatet al., 2002; Vohn et al., 2007), the middle frontal gyrus (MFG)(Johnson & Zatorre, 2006; Nebel et al., 2005; Szameitat et al., 2002;Vohn et al., 2007) and the intraparietal sulcus (IPS) (Dux et al., 2006;Szameitat et al., 2002; Vohn et al., 2007) have been shown to beinvolved in dual-tasking. Additionally the IFS and MFG are alsoinvolved in task switching (Dove, Pollmann, Schubert, Wiggins, &von Cramon, 2000) and task inhibition (Konishi, Chikazoe, Jimura,Asari, & Miyashita, 2005; Konishi, Nakajima, Uchida, Sekihara, &Miyashita, 1998) suggesting that these areas are implicated in generalcontrol over task coordination. Areas along the IPS have previouslybeen associated with attentional functions, like visual attention andmore multimodal sensory attention (Corbetta & Shulman, 2002;Gillebert et al., 2011; Molenberghs, Mesulam, Peeters, &Vandenberghe, 2007; Vandenberghe et al., 2005). Attentionaldemands are specifically high in dual-task situations where attentionhas to be divided and switched rapidly between tasks and modalities.Both the IPS and dorsolateral prefrontal cortex are part of the dorsalattention network (Corbetta & Shulman, 2002), also termed theexecutive control network (Seeley et al., 2007).

The more demanding the dual-tasks, the more extensive therecruited network is to successfully complete the task. Vohn et al.(2007) studied differences between within-modal (same modality, e.g.visual/visual) and cross-modal (different modality, e.g. visual/auditory)divided attention tasks. Under the cross-modal condition the rightprefrontal–parietal network, that was also active during the within-modal task, was more extensive and more bilateral. Also the activationin the right anterior cingulate cortex and the thalamus was strongerduring the auditory/visual task. This supplementary activation couldreflect an additional demand for the coordination of two ongoingcross-modal cognitive processes when compared to the within-modal tasks.

Very few studies however have examined how the brain com-bines dual-tasking with a memory task, so-called “multitasking”.Findings from lesion studies suggest an association with damage inthe frontal lobe (lateral prefrontal cortex, the anterior cingulate,BA10) and impaired multitasking (Burgess, 2000; Dreher, Koechlin,Tierney, & Grafman, 2008). Santangelo & Macaluso (2013) studiedthe contribution of working memory to divided attention. Theyreported increased activation in the left and right intraparietal sulcusduring object-based divided attention tasks as the number of objectsto be held in working memory increased. This increased activationreflects the recruitment of additional resources to enable dual-taskperformance under conditions of high working memory load andattentional demands. In the remainder of the manuscript, we will usethe term ‘dual-tasking’ to refer to the simultaneous execution of twotasks and ‘multitasking’ to refer to the simultaneous execution ofmore than two tasks.

It is evident that the interdependence of the individual-tasksplays a major role in multitasking paradigms. In other words, theneuro-cognitive architecture of multitasking is critically dependenton the tasks that are performed. In this fMRI study, we address howthe brain combines dual-tasking, consisting of two cross-modalcompeting tasks (a visual and auditory temporal same-different taskwith short delay (TSDS)) with another short-term memory task(a visual temporal same-different task with long delay (TSDL)).

Theoretically, several scenarios with different neural correlatescould occur (Sigman & Dehaene, 2008). In the first scenario, the TSDL

task does not interfere with the execution of the dual-task. This couldimply for example (1) serial processing of the different tasks: encodingof the presented visual stimulus of the TSDL task, execution of thedual-task (DT) and finally retrieval of the visual stimulus and response;or (2) involvement of different neural networks for the distinctivetasks and/or automated processes. In this case we would not observedifferences in brain activation or connectivity between the executionof the DT task in the DT paradigm and the execution of the DT taskwhen combined with our memory task. In the second scenario, theTSDL task actively interferes with the execution of the dual-task. In thiscase, we would observe differences in brain activation and/or con-nectivity between the execution of DT with the memory taskcompared to DT without the memory task. This scenario would showthat the fMRI paradigm that we developed can be used to measurebrain activation linked to multitasking. Differences in activationbetween the dual-task and the multitask condition could be relatedto the extra demands on attentional and coordinating processes aswell as to the process of actively keeping the visual stimuli onlineduring a longer delay. For example, the fronto-parietal brain networkinvolved in the coordination of concurrent processes (Santangelo &Macaluso, 2013; Szameitat et al., 2002), could show enhanced activityduring multitasking when compared to dual-tasking. Additionally,brain regions involved in maintaining memoranda in visual short termmemory (like occipito-temporal cortex) (Song & Jiang, 2006) could berecruited. Alternatively both processes (i.e. the online holding of theencoded stimulus in visual-sort-term memory and the dual-task)could occur in parallel with no enhancement of activity involved in DT.

A better understanding of the neural substrates of multitaskingin healthy volunteers will help us with the future evaluation ofpatients with subtle cognitive complaints that score well onclassical neuropsychological tests, but have difficulties with morecomplex tasks like multitasking.

2. Material and methods

2.1. Participants

Thirty-three right-handed healthy volunteers (20 females, mean age 39.975.8)participated in the study. Subjects were recruited through advertisement on localwebsites. All participants had normal or corrected-to-normal vision and were not

S. Deprez et al. / Neuropsychologia 51 (2013) 2251–2260 2253

taking any medication at the time of assessment. None of them had any history ofmental illness or neurological disease. The study was approved by the local ethicalcommission and was conducted in accordance with the Declaration of Helsinki.

2.2. Experimental design and procedure

Visual and auditory stimuli were presented using Presentation 14.8 software(Neurobehavioral Systems, Inc. (NBS), San Francisco, USA). Visual stimuli andinstructions were projected onto a screen that the participants viewed through amirror mounted on the head coil while lying in the scanner. Auditory stimuli werepresented via MR Confon headphones. Participants responded manually during thetasks using response buttons. Subjects were instructed to focus the fixation crossduring the whole experiment.

Participants performed two single tasks (one visual and one auditory TSDS

task), a dual-task combining the two single tasks simultaneously and a multitaskcondition combining a short-term visual memory task and the dual-task. In all fourconditions, auditory and visual stimuli were presented simultaneously.

The only difference was the instruction the participants received. Thereforeobserved changes in brain activity will not be related to physical differences in thestimuli, but rather to the change in attention, working memory load and processingof the tasks.

2.2.1. Single tasksUnder the single task condition, participants were requested to focus their

attention on either the visual or the auditory stimuli, while ignoring the otherstimulus mode. In the visual task (VT), participants were requested to decidewhether the orientation of two sequentially presented grating patterns was thesame or different. In the auditory task (AT), participants were requested to decidewhether the frequency of two sequentially presented monotonal sounds was thesame or different.

Subjects were instructed to press a button twice with the right index fingerwhenever they registered the same orientation (50% chance) or the same frequency(50% chance) or with the right middle finger whenever they registered a differentorientation (VT) or a different frequency (AT).

2.2.2. Dual-taskUnder the dual-task condition, participants were requested to divide attention

between both visual and auditory stimuli and perform both tasks simultaneously.Participants had to decide whether the orientation of the displayed gratings andthe frequency of the presented sounds was the same or different. Responses for thedual-tasks had to be given in a fixed order. The first button press was the responsefor the visual task (right index finger for same orientation, right middle finger fordifferent orientation), the second button press was the response for the auditorytask (right index finger for same frequency, right middle finger for differentfrequency). The four possible combinations each represented 25% chance.

Fig. 1. fMRI multitasking paradigm. (A) Instructions of the tasks in the following order:random order. VT: visual task; AT: auditory task; DT: dual-task; MT: multitask.

2.2.3. MultitaskFor the multitask condition, participants had to first encode two symbols that

were presented before the start of the dual-task. After performing the dual-taskcondition, while keeping the symbols in memory, another 2 symbols weredisplayed. The participants were requested to decide whether the 2 new symbolswere the same as the first 2 symbols. Subjects were instructed to press a buttontwice with the right index finger whenever they recalled the same symbols or withthe right middle finger whenever they decided the symbols were different.

It should be noted that the number of motor responses was the same in allconditions. In accordance with the single task, the dual-task also included twobutton presses in total.

Each trial consisted of 2 gratings and 2 tones presented simultaneously,repeated 8 times. One run consisted of 3 trials of the 4 tasks in random orderalternated with 24 s rest (Fig. 1 and Appendix B: Fig. B.1) The fMRI sessioncomprised 4 runs with a total scan time of about 28 min.

To control for performance differences across tasks and subjects, task difficultylevels were determined by varying the differences in orientation and frequencybetween the two visual and auditory stimuli for each participant during a 1-h trainingsession outside the scanner. Differences in orientation and frequency ranged between101 and 351 and 50 to 300 Hz respectively. These performance measures were thenused to tailor the protocol to each individual so that they would achieve approximately70–80% correct answers in the scanner. The first sound had a random frequencyranging between 1000 and 1800 Hz. The differences defined during the trainingsessionwere used for all tasks during the entire scanning session. With this procedure,the effects of individual differences on the performance of individual-tasks could becontrolled for (Ramsey et al., 2002; Snyder et al., 2011). This will also be of importancewhen we use the paradigm in future clinical studies to compare multitasking brainactivation between groups of patients and controls. The interpretation of fMRI groupdifferences, hyperactivation or hypoactivation, is difficult and tightly linked toparadigm and task-performance (Nagel et al., 2009; Stern et al., 2012).

2.2.4. fMRI data acquisitionAll participants were imaged on a 3 T MR scanner (Intera, Philips, Best, the

Netherlands) with an 8-channel phased-array head coil. The fMRI sequence used was aT2n-weighted gradient echo–echoplanar imaging (GE–EPI) sequence (acquisitionmatrix¼80�94, field of view¼200�240 mm2, in-plane resolution of 2.5�2.5,TR¼3 s, TE¼30 ms, SENSE-reduction factor¼1.7, 48 sagittal slices of 2.5 mm thick-ness). Four functional runs, each consisting of 148 volumes were acquired.

For anatomical reference a high-resolution 3-D T1-weighted turbo field echo(TFE) sequence covering the entire brain was acquired for each subject (TE/TR, 4.6/9.7 ms; inversion time, 900 ms; slice thickness, 1.2 mm; 256�256 matrix; 182coronal slices; SENSE reduction factor 3).

2.2.5. Statistical analysisTo study differences in behavioral results between the different conditions, we

carried out a one-way ANOVA analysis in SPSS 18.0 (SPSS, Chicago, IL) with the

VT, DT, AT, MT. (B) Illustration of trial design and one run. The task sequence is in

Fig. 2. Behavioral data. Upper panel: average reaction time in ms; lower panel:% average correct answers. For the dual and multitask condition, the reaction timecorresponds to the first button press, which is the answer to the visual task.The error bars represent the standard deviation. VT: visual task; AT: auditory task;DT: dual-task; MT: multitask.

S. Deprez et al. / Neuropsychologia 51 (2013) 2251–22602254

behavioral variable (% correct answers or reaction time) as dependent variable andthe task (VT, AT, DT, MT) as a fixed factor.

For the preprocessing and statistical analyses of the fMRI images, we used thestatistical parametric mapping software package (SPM8, Wellcome Department ofCognitive Neurology, London).

The functional images were realigned to the first volume of the time series tocorrect for head movements, and slice timing was applied to correct for differencesin acquisition time during scanning. After co-registering to the anatomical image,the functional images were spatially normalized to the standard space of theMontreal Neurological Institute brain (MNI-brain). All functional images weresmoothed with a Gaussian kernel of 8 mm full width at half maximum (FWHM).

First-level statistical analysis was done for all subjects in the context of theGeneral Linear Model. Each of the experimental conditions (visual task (VT),auditory task (AT), dual-task (DT), multitask (MT)) and additionally the instruction,rest and response to the short term memory task) were modeled using a train ofdiscrete-time delta functions representing event onsets convolved with a canonicalhemodynamic response function, including all trials. An appropriate high-passfilter of two times the period (294 s) was applied to remove low-frequency drifts.Statistical inference was based on random effects analysis, consisting of two steps.First, the effects of interest for each subject were defined using the followingcontrasts: AT4VT, VT4AT, 2DT4(AT+VT), 2MT4(AT+VT), MT4DT. Second, asecond-level random effects analysis for statistical inference at the group-level,combined the individual contrast images resulting from the first-level analysis in at-test, yielding group statistical t maps for each contrast.

Statistical significance at voxel-level was set to pFWEo0.05 corrected for multiplecomparisons for AT4VT, VT4AT, 2DT4(AT+VT), 2MT4(AT+VT) contrasts. To bemore sensitive to the smaller differences between DT and MT, we used a less stringentvoxel-level threshold of po0.001 uncorrected for multiple comparisons for theMT4DT contrast. For all contrasts, only clusters significant at pFWEo0.05 correctedfor multiple comparisons at cluster level were retained. Plots of contrast estimates(task vs. rest) were generated using the toolbox rfxplot (Glascher, 2009) in a sphere of3 mm around peak coordinates resulting from MT4DT and 2DT4(AT+VT) contrasts.Additionally, a repeated measures ANOVA of the extracted estimates was performedacross tasks in the respective ROI's. Post-hoc analysis included Bonferroni correctionfor multiple comparisons for the number of tasks and number of regions. For displaypurposes, we used a voxel-wise threshold of po0.001 uncorrected for multiplecomparisons with 10 contiguous voxels. All activations were visualized using CARETand projected on the PALS B12 atlas (Van Essen, 2005). When reporting results we usethe term ‘enhanced’ activity to reflect activity in regions involved in both dual andmultitask, which show significantly higher activation during multitasking whencompared to dual-tasking.

Results from the aforementioned analysis raised another research question regard-ing the activation of the cerebellum. We conducted an additional analysis to betterunderstand whether the reported higher activation in the right cerebellum during thedual-task when compared to the single task condition was related to the slightly morecomplex motor response rather than the dual-task condition in itself. Although in ourstudy the number of motor responses is the same for all conditions, there is a smalldifference in motor response during dual-tasking. During both single tasks, subjects hadto respond by pressing the response button twice with the same finger (right indexfinger for same stimuli, right middle finger for different stimuli). For dual-taskinghowever, a correct answer could involve button presses with two different fingers i.e. in50% of the cases we can have same visual stimuli and different auditory stimuli or viceversa, this results in a button press with the right index finger and the right middlefinger. To get more insight whether the cerebellar activation reported in our study couldbe related to this small difference in motor activity, we asked 4 additional new right-handed subjects (mean age 34 yr, sd¼10.9) to perform the fMRI paradigmwith the lefthand. All had normal or corrected-to-normal vision and were medication free. None ofthem had any history of mental illness or neurological disease. If the activation was dueto a difference in motor response, we would expect to see increased left cerebellaractivation. Preprocessing and first-level analysis of the fMRI data of these four subjectswas performed as described before; second-level analysis was done using a fixed-effectsanalysis, given the limited number of subjects.

To explore possible differences in connectivity between active brain regions duringthe multitask and the dual-task condition, we additionally conducted a connectivityanalysis. Functional connectivity was estimated through calculation of partial correla-tions between pairs of brain regions (Marrelec et al., 2006; Vandenberghe et al., inpress). Functional connectivity measures based on partial correlations provide anestimate of the linear conditional dependence between brain regions after removingthe linear influence of other regions (Ryali, Chen, Supekar, & Menon, 2012). First wedefined VOIs as a sphere of 3 mm around significant peak coordinates resulting fromthe MT4DT and 2DT4(AT+VT) group contrast. Second, we extracted averagetimeseries in each VOI for the DT and MT condition respectively. Third, we calculatedpartial correlations as a measure of connectivity between the time series of each pairof VOIs for both conditions. The correlation reflects the relation between the activationin two brain regions while the participant was performing the DT or MT task. Thisyielded two correlation matrices, one for the DT condition and one for the MTcondition. Only significant partial correlations, corrected for the number of connec-tions tested (po0.05/(nr_VOIs� (nr_VOIs-1)/2¼0.0007), are shown. Finally, we con-ducted a 2 sample t-test between the DT and MT connectivity matrices to detectpossible differences in brain connectivity.

3. Results

3.1. Behavioral performance

The behavioral results are summarized in Fig. 2. ANOVA analysisrevealed significant differences in response time (F(3,128)¼26.6,po0.001) and task performance (F(3,128)¼7.8, po0.001) acrossconditions. Post-hoc comparisons using Bonferroni correctionshowed significant shorter reaction times for both single tasks whencompared to the dual/multi-task, as expected (po0.001). No sig-nificant differences were found in reaction time between the dualand the multitask condition. Furthermore, the level of accuracy in thedual-task (mean 76.2%) did not differ significantly from that in themultitask condition (mean 75.2%) (p40.05). Likewise, the accuracyof the visual task did not differ significantly from the accuracy in thedual-task condition (p40.05). Performance of the visual task how-ever, was significantly better than performance of the multitaskcondition. Similarly, the performance of the auditory task wassignificantly better (po0.05) than of the dual and multi-task condi-tions. Performance on the single tasks was better in the scanner thanthe anticipated 70–80% that we adjusted for during the trainingsession, probably due to a further training effect in the scanner.A correct answer in the dual and multitask condition required both acorrect answer for the visual and the auditory task. When looking atthe visual and auditory task performance separately in those condi-tions, we could also observe separate task accuracies above 80%.

3.2. Neuroimaging results

When contrasting both single tasks, VT4AT and AT4VT, sig-nificant increased activation was found in the visual and auditory

Fig. 3. Single task imaging data. The red significance map shows increased activity during the auditory relative to the visual task. Inversely, the green significance mapcorresponds with higher activity during the visual relative to the auditory task. Both maps are visualized and projected on the PALSB12 atlas using CARET and thresholded atpo0.05 FWE corrected. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Table 1Brain regions with greater activation for the dual task condition as compared to both single tasks condition (2DT4VTAT), threshold set at pFWEo0.05.

H Anatomical Region BA cluster size (in number of voxels) MNI coordinates Cluster pFWE T-statistic

L Middle frontal gyrus BA6 32 �24 �4 50 0.001 6.76L Premotor cortex BA6 119 �26 �6 30 o0.0001 7.15R Middle frontal gyrus, DLPFC, premotor cortex BA6 296 30 0 50 o0.0001 7.92

BA9L IPS, superior parietal lobule, precuneus BA7 94 �10 �70 54 o0.0001 7.17R IPS, superior parietal lobule, precuneus BA7 584 22 �56 42 o0.0001 8.38

BA40BA39

R Cerebellum 1907 34 �60 �36 o0.0001 10.25

H: hemisphere; R: right; L: left; IPS: intraparietal sulcus, DLPFC: dorsolateral prefrontal cortex; pFWE: family wise error correction for multiple comparisons; MNI: Montrealneurological institute.

S. Deprez et al. / Neuropsychologia 51 (2013) 2251–2260 2255

sensory regions respectively, reflecting the selective attention toeither the visual or the auditory task (Fig. 3).

When compared to both visual and auditory single tasks,activation associated with the dual-task paradigm was found inthe intraparietal sulcus, bilaterally, the superior parietal lobe, themiddle and dorsolateral prefrontal cortex including premotorcortex, and the right cerebellum (Table 1 and Fig. 4). It should benoted that the number of voxels that reached our correctedsignificance threshold was considerably higher in the right hemi-sphere compared to the left hemisphere (Table 1). This effect isless clear in Fig. 4 where we used a more liberal threshold(po0.001) for display reasons.

The higher activation in the right cerebellum could not berelated to the slightly more complex motor response during dual-tasking. Brain activation from the four additional subjects per-forming the tasks with the left hand, also revealed significantlyhigher (pFWEo0.0001, T¼10.8) right cerebellar activation duringdual-tasking when compared to both single tasks. See Appendix A(Fig A.1).

During the multitasking condition, the dual-task network wasmore extended, mainly in fronto-parietal areas (Tables 2 and 3,Fig. 4). Additional left-sided homotopic regions also reachedsignificance and showed enhanced activity in part of the inferiorfrontal sulcus and the intraparietal sulcus (Fig. 4). Furthermore, aleft-lateralized MT-specific system including a more anterior partof the inferior frontal sulcus, part of the anterior cingulate cortexand occipitotemporal cortex was additionally recruited. Both theanterior part of the inferior frontal sulcus and anterior cingulatecortex showed significantly higher activation during the MTcondition than all other conditions (Fig. 4). In the occipitotemporalcortex we also found higher activation during the VT condition(Fig. 4).

No significant differences were observed when contrasting thedual-task against the multitask condition.

3.3. Functional connectivity

To explore possible differences in functional connectivityduring the multitask and the dual-task conditions, we calculatedconnectivity matrices in both conditions based on partial correla-tions between pairs of active brain regions. Only significant partialcorrelations corrected for multiple comparisons (po0.0007) areshown in Fig. 5. Two-sample t-tests between the MT and DTconnectivity matrices revealed significant higher (po0.05) func-tional connectivity during MT compared to DT between the leftdorsolateral prefrontal cortex (BA9) and occipito-temporal cortex(Fig. 5). No pairs with significant lower connectivity during MT vs.DT where found.

4. Discussion

We investigated how the brain combines two competingtasks (dual-tasking) with an additional short-term memory task(multitasking). We found widespread activation in a predominantlyright-sided fronto-parietal network and the cerebellum during thedual-tasking when compared to both visual and auditory singletasks. When adding the TSDL task, this fronto-parietal network wasfurther extended and additional left sided homotopic regions alsoreached significance, with enhanced activity in part of the inferiorfrontal sulcus and the intraparietal sulcus. Furthermore, MT-specificleft-lateralized neural components including a more anterior part ofthe inferior frontal sulcus, part of the anterior cingulate cortex andoccipitotemporal cortex were recruited.

Fig. 4. Dual and multitask imaging data. Dual and multitasking brain activations are visualized and projected on the PALS B12 atlas using CARET (for display, all T-mapsthresholded at po0.001). Green: significance map indicating higher activity during dual-task compared to both single tasks (2 DT4(VT+AT)); red: higher activation duringmultitask compared to both single tasks (2MT4(VT+AT)); blue: higher activation during multitask compared to dual-task (MT4DT). The upper and lower barchartsillustrate contrast estimates (AU) for the different conditions in the corresponding brain areas. The error bars represent the standard error of the mean (SEM). n Indicates asignificant difference between contrast estimates of the respective tasks, resulting from post-hoc repeated measures ANOVA analysis with Bonferroni correction acrossnumber of tasks and number of ROI's. VT: visual task; AT: auditory task; DT: dual-task; MT: multitask. R: right; L: left; IPS: intra-parietal sulcus; PMC: premotor cortex;ACC: anterior cingulate cortex; OT: occipito-temporal; IFSa: activation in more anterior part of inferior frontal sulcus; IFSp: activation in more posterior part of inferior frontalsulcus.

Table 2Brain regions with greater activation for the multi-task condition as compared to both single task conditions (2MT4VTAT), threshold set at pFWEo0.05.

H Anatomical region BA Cluster size (in number of voxels) MNI coordinates Cluster pFWE T-statistic

L Inferior frontal sulcus BA9 248 �40 2 30 o0.0001 8.37BA6

L Middle frontal gyrus BA6 325 �34 �2 62 o0.0001 8.03L Middle frontal gyrus BA46 32 �50 22 32 0.002 7.13L Medial frontal gyrus, SMA BA6 50 �6 12 52 0.002 7.19

BA32BA8

R Middle frontal gyrus BA6 285 34 2 50 o0.0001 8.20R Middle frontal gyrus, DLPFC BA46 75 48 30 26 o0.0001 7.87L IPS, superior parietal lobule, precuneus BA7 998 �8�72 54 o0.0001 9.31

BA40R IPS, superior parietal lobule, precuneus BA7 1125 14 �72 54 o0.0001 9.05

BA40BA39

R Cerebellum 2668 32 �60 �36 o0.0001 12.84R Cerebellum 41 26 �74 �50 0.003 7.05

H: Hemisphere; R: Right; L: Left; IPS: intraparietal sulcus; DLPFC: dorsolateral prefrontal cortex; SMA: supplementary motor area; pFWE: family wise error correction formultiple comparisons; MNI: Montreal neurological institute.

S. Deprez et al. / Neuropsychologia 51 (2013) 2251–22602256

Table 3Brain regions with greater activation for the multitask condition as compared to the dual task condition (MT4DT), threshold set at po0.001.

H Region BA Cluster size (in number of voxels) MNI coordinates Cluster pFWE T-statistic

L Inferior frontal sulcus, middle frontal gyrus BA46 877 �50 38 16 o0.001 5.47BA9BA10

L IPS, superior parietal lobule, precuneus BA40 1184 �36 �78 8 o0.001 5.18BA7BA39

L Occipito-temporal cortex BA37 434 �46 �60 �12 o0.001 5.64BA20BA19

L Cingulate cortex BA32 302 �4 22 44 0.001 4.97

H: hemisphere; R: right; L: left; IPS: intraparietal sulcus, pFWE: family wise error correction for multiple comparisons; MNI: Montreal neurological institute.

Fig. 5. Functional connectivity data. Partial correlation matrices in the DT (left) and MT (right) condition respectively, representing functional connectivity between VOIsdefined as a sphere of 3 mm around significant peak coordinates resulting from the MT4DT and 2DT4AT+VT group contrasts. The color represents the mean partialcorrelation coefficient across all subjects between the VOIs. Only partial correlations significant at po0.05 corrected for multiple comparisons are represented. * Indicateswhere the partial correlation coefficient is significantly higher (po0.05) during the MT task condition when compared to the DT condition. (For interpretation of thereferences to color in this figure legend, the reader is referred to the web version of this article.)

S. Deprez et al. / Neuropsychologia 51 (2013) 2251–2260 2257

Firstly, these findings confirm that the neural mechanismsunderlying our DT-task and our MT-task (DT plus memory task)are different. This suggests that multi-tasking represents a seriesof multiple co-occurring mental events processed simultaneously,rather than serially. Secondly, we found extended and enhancedactivity in frontal and parietal regions that were already involvedin dual-tasking, as well as the recruitment of additional neuralresources. The former suggests that our multi-tasking paradigmputs extra demands on central coordinating processes (such astask ordering and attentional shifting) during the execution ofmultiple tasks, whereas the latter points to activation of additionalbrain areas involved in maintaining memoranda in visual shortterm memory. It should be noted, however, that strictly speaking,our paradigm does not allow to disentangle central coordinatingprocesses from short-term memory-related processes. Indeed,further experiments such as correlations between regional brainactivity during MT and neuropsychological test scores reflectingdifferent cognitive processes in patients groups, are needed to gainbetter insight into the functional contribution of these differentareas.

Behaviorally, our fMRI multitasking paradigm was conceived toequalize correct answers across tasks and subjects to minimizeeffects related to effort and to avoid confounds related to differencein performance in future clinical applications. Reaction times duringdual-tasking however, were significantly longer than reaction times

during single tasks, as expected. This reflects a concurrence cost ofperforming simultaneously both single tasks. The process of coor-dinating and executing two tasks at once is in itself a resource-demanding task (Ruthruff, Johnston, & Remington, 2009). Dual-taskinterference (Pashler, 1994) is thought to reflect an attentionalbottleneck at a central/amodal decision-making stage that pre-cludes efficient processing of both tasks (Dux et al., 2006). Impor-tantly, the DT and MT condition did not differ significantly in termsof accuracy and reaction time. This suggests that the increasedneural activation during multitask compared to dual-task can beattributed to MT-related cognitive processes such as attentionalcontrol and short term memory.

4.1. From single task to dual-tasking

Visual and auditory stimuli were presented simultaneouslyin all conditions.

Focusing attention on only one modality during the visual orauditory single task increased the activation in the correspondingsensory area. Divided attention during the dual-task condition didnot lead to a global increase in sensory cortex activity, but didrecruit additional amodal brain regions. Other groups havereported increased sensory activation while focusing attentionon one modality only and increased activation in amodal brainregions (in the absence of increased sensory activation), when

S. Deprez et al. / Neuropsychologia 51 (2013) 2251–22602258

dividing attention across two modalities (Johnson & Zatorre, 2006;Loose et al., 2003). In accordance with other studies, we foundincreased activation during DT (divided attention) in the intraparietalsulcus, the inferior frontal sulcus and the middle frontal gyrus as partof the dorsolateral prefrontal cortex (Johnson & Zatorre, 2006; Looseet al., 2003; Stelzel, Schumacher, Schubert, & D'Esposito, 2006;Szameitat et al., 2002). Increased dorsolateral prefrontal cortexactivity during divided attention represents increased executivefunctioning that involves both enhanced top-down attentional andworking memory control (Nebel et al., 2005).

We additionally reported increased activation mainly in the rightcerebellum during the dual-task condition. The interested reader isreferred to Appendix A for a discussion on the cerebellar activity.

4.2. From dual-task to multitasking

From previous studies we know that more demanding dual-task conditions recruit a more extended fronto-parietal network(Nebel et al., 2005; Stelzel et al., 2006; Szameitat et al., 2006; Vohnet al., 2007). Easier conditions begin with mainly right-sidedactivity within the attention network. As conditions become moredemanding, in addition to an enhanced right-sided activitation,left-lateralized homotopic regions activate (Nebel et al., 2005).This reflects higher need for information processing requirements,i.e. executive control of attention and/or working memory. Thiswas for example the case when comparing cross-modal dual-tasking to within-modal dual-tasking (Vohn et al., 2007). Stelzelet al. described increased left IFS activation associated withincreased dual-task costs. Also Szameitat et al. reported increasedactivation with increased dual-task requirements in the left IFSwhen comparing different-order trials with same-order trials. Thisoccurred in combination with increased right MFG and right IPSactivation (Szameitat et al., 2006).

Consistent with these findings, we found a more extendedfronto-parietal activation with left-sided homotopic regions dur-ing our more demanding multitask condition (when compared todual-tasking). Adding a TSDL task to the dual-task conditionimplies increased cognitive requirements and extra demands incoordinating interfering processes of attention and working memory.This encoding and holding a stimulus in working memory interfereswith the deployment of top-down attention (Scalf, Dux, & Marois,2011) needed for executing the dual-task condition.

Additionally, we identified the recruitment of more MT-specificregions, including the anterior part of the inferior frontal sulcus,part of the anterior cingulate cortex and occipitotemporal cortex.

4.2.1. Prefrontal cortexWe observed an increase in neural activity in cortical regions

surrounding the left IFS. Schubert & Szameitat, 2003 reported thatthe left IFS has been related to executive processes of managinginterfering information in order to determine appropriate action.Considering the enhanced working memory load during themultitask condition (i.e. encode and online holding of the visualsymbols during a longer delay in order to make a response at theend of the trial), the activity along the IFS might reflect higherdemands on both, adequate allocation of attention and executiveprocesses of working memory.

More specifically we can distinguish 2 zones in the frontalcluster along the IFS (resulting from the MT4DT contrast): an areacovering part of BA9, already active during the dual-task condition,now showing enhanced activation and a more anterior MT-specificprefrontal area covering part of BA10 and BA46. Also Koechlin,Basso, Pietrini, Panzer, and Grafman (1999) described activation inpart of the middle frontal gyrus BA9 during a divided attentiontask. When combining this divided attention task with another

independent task involving cognitive branching, they describedadditional activation in a more anterior prefrontal area BA10 inline with our findings.

The middle frontal gyrus is known to be involved in theallocation of attention and monitoring, updating and manipulationof information. According to Petrides model (Petrides, 2000) theDLPFC has a role in manipulating information in working memory.Our findings relate to this model as the enhanced activation in BA9can reflect the additional demands on handling information inworking memory during multitasking. Also D'Esposito et al.(1995), described engagement of the DLPFC in delayed-responsetrials.

Additionally, lesion studies have found associated damage inthe frontal lobe (lateral prefrontal cortex, BA10) with impairedmultitasking (Burgess, 2000; Dreher et al., 2008).

4.2.2. The intra-parietal sulcusIn the present study, the multitask condition not only showed

enhanced activity in the prefrontal cortex, but also in parietalareas. These activations were located mainly along the IPS. The IPSis known to be implicated in visual attention as well as in visualshort-term memory processes (Gillebert et al., 2012; Logan& Gordon, 2001). A meta-analysis on working memory literaturefound evidence that prefrontal, but also parietal cortex activityincreases with increasing executive demands (Wager & Smith,2003). The enhanced parietal activity accompanies enhancedprefrontal activity during multitasking performance, pointingtowards a fronto-parietal network, as central-coordinator of morecomplex cognitive processes (Corbetta & Shulman, 2002).

A study from Magen, Emmanouil, McMains, Kastner, & Treisman(2009) suggests that higher activity along IPS may reflect theattentional demands of visual short-term memory rehearsal pro-cesses. Also in our multitasking paradigm rehearsal is needed to keepthe visual stimuli presented at the beginning of the trial online duringthe execution of the simultaneous visual and auditory tasks in orderto be able to provide an answer at the end of the trial. The increasedactivity along the IPS might hence reflect additional attentionalresources needed for this rehearsal process. Also work of Majeruset al. highlight the importance of the left IPS as an attentionalmodulator in a variety of short-term memory task (Majerus et al.,2006, 2007). Molenberghs et al. (2007) studied the role of theposterior parietal cortex in the context of remapping attentionalpriorities in more detail. They described involvement of the IPS in thecompilation of an attentional priority map, allowing to resolve thecompetition between simultaneously presented stimuli and shiftingattention accordingly (Bundesen & Habekost, 2008). As already noted,the design of our paradigm does not allow us to distinguish whetheror not the observed enhanced activation in the IPS is related to thehigher attentional demands, processes involved in visual short-termmemory or a combination of both.

4.2.3. Occipito-temporal cortexDuring multitasking, additional MT-specific activity was observed

in left-lateralized neural components including part of the occipito-temporal cortex. This area is involved in visual information proces-sing and visual short term memory (Song & Jiang, 2006; Tallon-Baudry, Bertrand, Peronnet, & Pernier, 1998). The additional onlineholding of visual stimuli during the multitasking process representshigher demands on visual short-term memory when compared todual-tasking. The neural activity in the occipito-temporal cortexmight be explained by these demands.

The process of generating mental images from memorydepends primarily upon structures in the left hemisphere (Farah,1989) also involving occipito-temporal regions. The observedleft-lateralized activation in those regions in our study can be

S. Deprez et al. / Neuropsychologia 51 (2013) 2251–2260 2259

related to the process of keeping the presented visual stimuliinvolving mental imagery online (Lambert, Sampaio, Mauss, &Scheiber, 2004) while simultaneously executing the auditory andvisual tasks. Not surprisingly, occipitotemporal cortex also showedincreased activity during the single VT task related to modality-specific attentional processing.

Interestingly, we observed a statistically significant increase infunctional connectivity during multitasking between the occipito-temporal cortex and the left DLPFC (BA9) when compared with dual-tasking. de Borst et al. (2012) have described a role for frontal regionsto orchestrate remote occipito-temporal regions to encode detailedrepresentations of objects during visual imagery. Also, a MEG studyinvestigating the attentional blink, reported neural synchronizationbetween frontal and occipital/temporal regions (Gross et al., 2004).Higher levels of synchronization between these brain regions in themultitask condition may reflect higher demand for executive controland top-down attentional processes controlling the online holding ofvisual symbols in working memory and the continuous execution ofthe simultaneous auditory and visual tasks.

4.2.4. Anterior cingulate cortexAdditional MT-specific activity was also observed in the left

anterior cingulate cortex when compared to DT. This confirmsfindings of Burgess (2000) who reported that the regions mostimplicated in multitasking are the anterior cingulate and thedorsolateral prefrontal cortex.

The cingulate gyrus plays an important role in attentional proces-sing (Posner & Rothbart, 1998), and is known to be involved in theexecution of cross-modal tasks (Banati, Goerres, Tjoa, Aggleton, &Grasby, 2000; Vohn et al., 2007) and more specifically in task switch-ing (Hyafil, Summerfield, & Koechlin, 2009). Increased task difficultyadditionally relates to increased activity in the cingulate cortex (Banatiet al., 2000; Laurienti et al., 2003). The above findings could relate tothe observed activity in the anterior cingulate in our study. Ourmultitask condition indeed involves higher attentional demands tocontrol the simultaneous processing of tasks (i.e. executing the visualand auditory tasks in combination with online holding of visualstimuli). Interestingly, studies in rhesus monkeys investigating theinnervation between the ACC and BA46/BA10 suggest that the ACCplays a role to direct attention to new tasks while temporarily holdingin memory another task (Medalla & Barbas, 2010).

5. Conclusion

In this study, we investigated how the brain combines twocompeting tasks (dual-tasking) with an additional short-term mem-ory task (multitasking). A fronto-parietal network already activeduring dual-tasking, showed enhanced and more extensive activa-tion bilaterally during multi-tasking, suggesting increased workingmemory demands. We additionally reported supplementary activa-tion in the occipito-temporal cortex likely to be involved in onlineholding of visual stimuli in short termmemory during a longer delay.These observations allow us to conclude that the paradigm that wedeveloped effectively registers brain activation linked to multitask-ing, validating our paradigm. ‘Since multitasking is sensitive to theeffect of ageing, any inferences should be restricted to the agesegment that we studied, i.e. between 35 and 50 years old.’

A better understanding of the neural substrates of multitaskingin healthy volunteers is of special interest in future clinicalneuropsychological examination of patients with subtle cognitivecomplaints that score well on classical neuropsychological tests,but have difficulties with more complex tasks like multitasking.

Appendix A. Supplementary materials

Supplementary data associated with this article can be found inthe online version at http://dx.doi.org/10.1016/j.neuropsychologia.2013.07.024.

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