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Neuropsychologia 48 (2010) 4102–4110

Contents lists available at ScienceDirect

Neuropsychologia

journa l homepage: www.e lsev ier .com/ locate /neuropsychologia

ex differences in sensorimotor mu rhythms during selectivettentional processing

. Popovicha,b,c, C. Dockstadera,b, D. Cheynea,d,e, R. Tannocka,b,f,∗

Neurosciences and Mental Health Program, The Hospital for Sick Children, Toronto, ON, CanadaDept. of Psychiatry, The Hospital for Sick Children, Toronto, ON, CanadaInstitute of Medical Science, University of Toronto, Toronto, ON, CanadaDept. of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, CanadaDept. of Medical Imaging, University of Toronto, Toronto, ON, CanadaHuman Development and Applied Psychology, Ontario Institute for Studies in Education at the University of Toronto,oronto, ON, Canada

r t i c l e i n f o

rticle history:eceived 12 April 2010eceived in revised form7 September 2010ccepted 11 October 2010vailable online 15 October 2010

a b s t r a c t

We used magnetoencephalography to investigate the effect of directed attention on sensorimotor mu(8–12 Hz) response (mu reactivity) to non-painful electrical stimulation of the median nerve in healthyadults. Mu desynchronization in the 10–12 Hz bandwidth is typically observed during higher-order cog-nitive functions including selective attentional processing of sensorimotor information (Pfurtscheller,Neuper, & Krauz, 2000). We found attention-related sex differences in mu reactivity, with females show-ing (i) prolonged mu desynchrony when attending to somatosensory stimuli, (ii) attentional modulation

eywords:u rhythm

ensorimotorttentionex differencesagnetoencephalography

of the mu response based on whether attention was directed towards or away from somatosensorystimuli, which was absent in males, and (iii) a trend for greater neuronal excitability of the primarysomatosensory region suggesting greater physiological responsiveness to sensory stimulation overall.Our findings suggest sex differences in attentional control strategies when processing somatosensorystimuli, whose salience may be greater for females. These sex differences in attention to somatosensorystimuli may help elucidate the well-documented sex biases in pain processing wherein females typically

to ex

omatosensory cortex report greater sensitivity

. Introduction

Behavioural studies have shown that selective attention canromote more efficient information processing, as indexed byaster reaction times, greater performance accuracy, and enhancedensitivity to fine changes made to a stimulus (Womelsdorf &ries, 2007). Human and primate neuroimaging studies haveurther demonstrated that attention can enhance neurophysio-ogical responses in auditory (Jancke, Mirzazade, & Shah, 1999),omatosensory (Hsiao, O’Shaughnessy, & Johnson, 1993), and visualodalities (Motter, 1993). However, although it is well estab-

ished that males and females differ in performance on manyognitive tasks, including self-directed attention to visual stim-li (Neuhaus et al., 2009; Ruytjens et al., 2007; Steffensen et al.,008; Weiss et al., 2003), little is known about sex differences in

∗ Corresponding author at: Neuroscience and Mental Health Program (Room256B), The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario,anada M5G 1X8. Tel.: +1 416 813 7048; fax: +1 416 813 6565.

E-mail address: rosemary.tannock@utoronto.ca (R. Tannock).

028-3932/$ – see front matter © 2010 Elsevier Ltd. All rights reserved.oi:10.1016/j.neuropsychologia.2010.10.016

perimental and clinical pain.© 2010 Elsevier Ltd. All rights reserved.

selective attention to somatosensory stimuli. Studying sex differ-ences is important for clinical research and ultimately might helpexplain why some psychiatric and neurodevelopmental disordersare expressed differently in males and females, or explain poten-tial sources of differential vulnerability in one sex versus the other,such as why females manifest greater pain sensitivity than males.Thus the overall aim of the present study was to determine whethermales and females differ in selective attention to somatosensorystimuli. To do so, we used a non-invasive neuroimaging technique– magnetoencephalography (MEG) – to measure sex differencesin specific oscillatory brain rhythms (mu rhythms) in the pri-mary somatosensory cortex (SI). Prior to summarizing our specificobjectives, hypotheses, and research approach, a comment on murhythms is warranted.

1.1. Mu Rhythms

Mu rhythms are associated primarily with processing basicsomatosensory information (Pineda, 2005) with source activationtypically greater in the hemisphere contralateral to the involvedbody part (Devos et al., 2006; Nikouline et al., 2000; Salmelin &

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ari, 1994; Stancak & Pfurtscheller, 1996; Stancak et al., 2003).uring somatosensory stimulation and/or during motor prepara-

ion and execution, mu rhythms exhibit a characteristic patternf event-related reactivity that is reliably reproduced (Neuper,ortz, & Pfurtscheller, 2006; Nikouline et al., 2000; Pfurtscheller &

euper, 1994). More specifically, immediately following sensorytimulation mu rhythms are desynchronized (i.e. event-relatedesychronization; ERD) followed by a gradual return to theiraseline state, and are sometimes proceeded by minimal synchro-ization effect (i.e. event-related synchronization; ERS) (Szurhajt al., 2003). ERD and ERS phenomenon refer to increases andecreases in neural activity below (ERD) or above (ERS) baseline

evels, and are believed to reflect sensorimotor activation and inhi-ition, respectively (Lopes da Silva & Pfurtscheller, 1999; SalmelinHari, 1994).Mu rhythms are desynchronized by higher-order attention-

elated demands such as cognitive and affective influences (Pineda,005), action observation (Cheng, Tzeng, Decety, Imada, & Hsieh,006; Cheng, Lee et al., 2008) and imitation (Virji-Babul et al., 2008),timulus expectancy (Babiloni et al., 2004; Babiloni, Brancucci, Delercio et al., 2006; Babiloni, Brancucci, Vecchio, et al., 2006), atten-ional alerting to somatosensory input (Nikouline et al., 2000),nd pain perception (Cheng, Yang, Lin, Lee, & Decety, 2008; Yang,ecety, Lee, Chen, & Cheng, 2009). Two types of attention-relatedu rhythms exist: (i) a somatotopically non-specific lower band

8–10 Hz) elicited during basic cognitive demands when selec-ive attention is not explicitly required, and (ii) a somatotopicallypecific upper band (10–12 Hz) which is elicited during taskshat require highly attentive behaviour (Pfurtscheller, Neuper, &rauz, 2000). It has been proposed that desynchronization of lower

requency mu rhythms reflects general attentional processing,hereas desynchronization of the upper mu bandwidth reflects

elective attention to a motor subsystem (Pfurtscheller et al., 2000).n the present study, we focused our analyses on the 10–12 Hz bando examine sex differences in self-directed attention to somatosen-ory stimuli.

.2. Study aims and hypotheses

The specific aim of this study was to determine whether malesnd females differ in self-directed selective attention to somatosen-ory stimuli, as reflected by the neural dynamics of mu rhythmshen directing attention towards versus away from somatosensory

timuli. We hypothesized that: (i) mu desynchrony in the 10–12 Hzandwidth would be stronger when attending to MNS, compared

o attending away from MNS, as a result of self-directed attentiono somatosensory information; and (ii) there would be attention-elated sex differences in the mu response with females showingreater 10–12 Hz mu desynchrony than males in the Attend to MNSondition.

ig. 1. Predictable MNS pattern. In both attentional conditions, we presented a somatosensattern (ISI: 2 s) wherein a series of four electrical impulses followed by a 4 s MNS break inerve eliciting a small, passive thumb twitch. Participants were required to attend and mr ignore MNS and attend and count specific video incidents (Attend away from MNS).

gia 48 (2010) 4102–4110 4103

2. Materials and methods

2.1. Participants

We studied 20 right-handed healthy control adults (10 females; mean age28.3 (SD = 3.13) years old and 10 males; mean age 27.8 (SD = 4.54) years old). Par-ticipants were recruited using advertisements posted at a university campus ina large metropolitan city. Thus all participants had completed secondary educa-tion and some post-secondary education. Participants were excluded if they woreorthodontic braces, had any non-removable metal, a previous or current diagnosisof psychosis, or a neurological disorder, or were left-handed. Informed consent wasobtained from all subjects using protocols approved by the Institutional ResearchEthics Board.

2.2. MEG recordings

Sensory fields were recorded with a 151-channel whole head MEG system (VSMMedTech Ltd., Vancouver, Canada). MEG signals were digitized at a sampling rate of1250 Hz and an online bandpass filter of 0.3–300 Hz. Prior to recording, each sub-ject was fitted with 3 fiducial localization coils attached to anatomical skin markersplaced at the nasion and bilateral preauricular points. Subjects lay in a supine posi-tion in a magnetically shielded room while head localization measurements weretaken at the beginning and end of each experimental condition to determine headposition relative to the MEG sensors. Structural magnetic resonance images (MRI)were collected using a 1.5 Tesla Signal Advantage system (GE Medical Systems,Milwaukee, USA) in a T1-weighted sequence. Prior to each MR scan radiographicmarkers were matched to the fiducial skin markings so that MEG data could becoregistered with the subject’s MRI images.

2.3. Paradigms

Somatosensory stimuli were non-painful, constant-current square wave elec-trical pulses of 0.2 ms duration applied transcutaneously to the right median nerveat a rate of 0.5 Hz (ISI: 2 s between onset of each stimulus), just above each par-ticipant’s motor threshold (eliciting a small, passive, thumb twitch). Median nervestimulation (MNS) was presented in a predictable stimulus pattern with trains offour stimuli followed by a 4 s interval between trains during which no stimuluswas delivered (Fig. 1). Each condition presented identical visual and somatosensorystimuli a silent but engaging cartoon video, “Pingu the Penguin”; somatosensorystimuli consisted of non-painful MNS, and varied only in instructions as to whereparticipants were to direct their attention and which stimulus events to count. Con-ditions were presented in counterbalanced order and consisted of two 6-min trialscomprised approximately 135 stimuli and thirty-five 4 s intervals. Participants wereinstructed to direct attention to a particular sensory modality and mentally countcondition-specific stimulus events. In the Attend to MNS condition, subjects wereinstructed to fixate on the playing video but to attend to the electrical pulses andcount the number of MNS break intervals that occurred throughout the condition.In the Attend away from MNS condition, subjects were instructed to fixate and attendto the video counting the number of times a specific video incident occurred (Pingutrumpets his bill) while ignoring MNS.

2.4. Behavioural measures

2.4.1. Self-report of ‘attentional counts’Following each condition, participants reported the number of events they were

instructed to count (Pingu trumpets or MNS break intervals). Attentional countswere used to ensure that each participant’s attention remained actively engagedthroughout each condition, and that they all successfully complied with conditioninstructions prior to proceeding with the experiment.

ory (MNS) and a visual stimulus (video cartoon). MNS was presented in a predictableterval (no stimulus delivered) was presented transcutaneously to the right median

entally count the number of 4 s MNS break intervals that occurred (Attend to MNS)

4104 C. Popovich et al. / Neuropsychologia 48 (2010) 4102–4110

Fig. 2. An effective paradigm for observing SI attentional effects. Averaged datasets examining neural activity before and after the first electrical stimulus in a train werecreated for both experimental conditions and dipole fits were made on a template head model based on the amplitude peak occurring approximately 20 ms (red line)following the stimulus marker (0 ms). For all participants, source activity was localized to the contralateral (i.e. left) sensorimotor region and both males and females showedtypical pattern of somatosensory activation for each attentional condition with amplitude increases at 20 ms, 40 ms, and 60 ms following MNS. (A) Averaged time-seriesgraph (above) and source localization topoplot (below) for a representative female participant during the Attend to MNS condition. (B) Averaged time-series graph (above)a ring ts Attent MNi to th

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nd source localization topoplot (below) for a representative female participant duource localization topoplot (below) for a representative male participant during theopoplot (below) for a representative male participant during the Attend away fromnterpretation of the references to colour in this figure legend, the reader is referred

.4.2. Self-report of perceived attentional demandOnce all MEG conditions were completed, participants were asked to fill out

wo visual analog scales by ranking each condition to indicate their perception ofhe level of attentional demand that was required for each condition (from least-to-reatest).

.5. Data analyses

.5.1. Beamformer localizationThe synthetic aperture magnetometry (SAM) beamformer (Robinson & Vrba,

998) was used to measure the spatial distribution of mu rhythm activity in theensorimotor cortex during MNS. To ensure the reliability and validity of our results,e followed a well-established methodological approach from recently conducted

tudies in our lab (Dockstader, Gaetz, Cheyne, & Tannock, 2009). Changes in sourceower were computed using the SAM differential power statistic (pseudo t) forhich a baseline time interval (−0.05 s to 0.0 s prior to the onset of the first stimulus

n a train) was subtracted from an active time interval (0.0–0.05 s following onsetf the first stimulus of a train) and bandpass filtered at 1–200 Hz. This computationdentified brain areas of peak activation time-locked to the first MNS event in a train

hat were later used to create ‘virtual sensors’ by passing the single trial MEG signalshrough a spatial filter of 1–30 Hz.

.5.2. SI localizationTo ensure that our paradigm was successful in generating the typical SI response

o MNS, we created datasets for each condition with time windows that only

he Attend away from MNS condition. (C) Averaged time-series graph (above) andd to MNS condition. (D) Averaged time-series graph (above) and source localizationS condition. Source power for MEG time-series graphs are in femto-Tesla (fT). (Fore web version of the article.)

included the neuronal activity elicited before and after the first stimulus in a train.Next, we averaged each dataset to remove any irrelevant neural activity and usedthe EMSE Suite Data Editor Module software (Source Signal Imaging Inc.) to view theoverlaid, evoked response pattern across all MEG sensors. To determine the sourcelocation of the earliest neural response generated for each condition in primarysomatosensory cortex (the N20 response shown to be generated in SI), we used theCTF DipoleFit program to perform a single dipole fit to the amplitude peak occur-ring approximately 20 ms following the first stimulus marker for each dataset. Weexamined SI activation to MNS separately for males and females to ensure that anymodulatory effects observed could not be attributed to sex differences in sourcelocalization (Fig. 2).

2.5.3. Time–frequency analysesTo investigate the time–frequency specificity of the SI neural response we used

the virtual sensor data derived from SAM, and applied a wavelet-based technique(Tallon-Baudry, Bertrand, Delpuech, & Pernier, 1996) that averaged SI source poweractivity across all trials creating time–frequency representation (TFR) plots. Virtualsensor data was passed through a spatial filter of 1–30 Hz and a baseline period

of 0.6 s was used for TFR plots displaying the initial three stimuli events of a train(i.e. −9 s to −8.4 s prior to the onset of the first stimulus), and the 4 s MNS breakinterval (i.e. −1 s to −1.6 s prior to stimuli initiating the subsequent train). TFR plotswere averaged separately across males and females to create sex-specific grand-averaged images of summed data displaying SI source activity for the ascribeddatasets.

C. Popovich et al. / Neuropsychologia 48 (2010) 4102–4110 4105

Fig. 3. Females show prolonged SI activation when attending to MNS. Specific time–frequency boundary boxes of mu activity were defined for the first three stimulusevents of a train (Mu box 1: 10–12 Hz, −6.8 s to 6.4 s; Mu box 2: −4.8 s to −4.4 s; Mu box 3: −2.8 s to −2.4 s). Mean values for each boundary box were computed on eachindividual’s TFR data and averaged for each condition. Grand averaged values were used to compare sex-specific effects of attention modulation in SI. (A) Grand mean TFRf r femf male( −17 tor

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or female participants during the Attend to MNS condition. (B) Grand mean TFR foor male participants during the Attend to MNS condition. (D) Grand mean TFR forred) responses are delineated with square boxes. Source power: (A-m)2 = (−n × 10eader is referred to the web version of the article.)

.5.4. Statistical analyses of the mu responseUsing the same statistical approach as that of our most recent study (Dockstader

t al., 2009), sensorimotor rhythms were first investigated by measuring mu activityERD and/or ERS) values that occurred after the first three stimuli of the train forach experimental condition. Next, we investigated mu responses following the lasttimulus in a train.

.5.5. Bounding boxesFor the contralateral hemisphere, the frequency boundaries for mu reactivity

ere restricted to the 10–12 Hz bandwidth while the temporal boundaries var-ed according to each dataset. Three temporal boundaries of 0.4 s each (−6.8 s to6.4 s, −4.8 s to −4.4 s, −2.8 s to −2.4 s) were chosen for the dataset displaying neural

esponses following the first three stimuli in the train (Fig. 3). One temporal bound-ry of −1.0 s to 0.3 s (total duration of 1.4 s) was chosen for the dataset focusing onhe 4 s break (Fig. 5). These parameters were chosen based on peak neural responsesbserved during the Attend to MNS condition. Next, these time–frequency boundaryox parameters were applied to each individual’s TFR and the pixel values withinhat boundary box were averaged separately for males and females to obtain sex-pecific peak values for mu activity for each condition. All sex-specific mean values

or sensorimotor reactivity were analyzed using the Statistical Package for the Socialciences (SPSS) version 16.0. Prior to conducting statistical analyses, the data werehecked for outliers. Tabachnik and Fidell’s (2007) conservative score-changing pro-edure was used for extreme mu scores (defined as ≥3 standard deviations from theroup mean) on any variable. Deviant mu scores were adjusted to be within one unitway from the next ranked score, thereby retaining its rank order while minimizing

ale participants during the Attend away from MNS condition. (C) Grand mean TFRparticipants during the Attend away from MNS condition. Mu ERD (blue) and ERS+n × 10−17). (For interpretation of the references to colour in this figure legend, the

the skew it created in the sample. This procedure was applied to a total of two scores(2 mu scores for the Attend to MNS condition derived from two male subjects). Foreach dataset, we examined contralateral mu responses to MNS as a function of stim-ulus condition [2 × 2 repeated measures ANOVAs, with Group (Females, Males) as abetween-subjects factor and Condition (Attend Away from MNS, Attend to MNS) asa within-subjects factor]. Effect sizes were expressed as partial eta squared (partial�2), which is roughly equivalent to R2 in multiple regression. Effect size values mea-sured by R2 or similar indices can be interpreted as follows: values in the range of .01,.09 and .25 are considered small, medium and large effect sizes, respectively (Cohen,1969). Lastly, neuroimaging studies have shown that sex differences in neural activ-ity may be influenced by age (Rubia, Hyde, Halari, Giampietro, & Smith 2010), thusa regression analysis for age and mu power was performed separately for malesand females to investigate whether age influenced 10–12 Hz mu reactivity in eithersex.

3. Results

3.1. Females show greater neural excitability to somatosensorystimuli

For both males and females, the source of peak activationwas localized to the primary somatosensory (SI) region in the

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106 C. Popovich et al. / Neurops

emisphere contralateral to electrical stimulation. Moreover, bothroups showed the characteristic pattern of somatosensory activa-ion in both directed attention conditions: increases in amplitudeower occurring approximately 20 ms, 40 ms, and 60 ms follow-

ng MNS which typically reflects neural activation of SI (seeig. 2). There were no sex differences in the intensity of thelectrical current required to achieve motor thresholds (meanurrent intensity for females = 4.6 �A (micro Amperes) versusales = 4.7 �A).By contrast, examination of the SI response to the first stim-

lus in a train revealed marked sex differences in the magnitudef the N20 response under both directed-attention conditions. The20 is a brief but robust evoked response that can be localized to

he SI regions approximately 20 ms following electrical stimula-ion. SI dipole values were greater in females than in males: meanipole moment = 18.8 nAm (nanoAmpere-meters) for females, and2.4 nAm for males, when attention was directed towards MNS;nd 17.5 nAm for females and 12.4 nAm for males, when atten-ion was directed away from MNS towards the video. However,he observed sex differences did not reach conventional signifi-ance levels in a 2 × 2 repeated measures ANOVA with ConditionAttend to MNS, Attend away from MNS) as the within subjectariable and sex as the between subject variable (main effect forex, F[1,16] = 3.29, p = 0.08, partial �2 = 0.17). Moreover, neither theain effect of condition (F[1,16] = 0.29, p = 0.6, partial �2 = 0.018),

or the condition × sex interaction was significant (F[1,16] = 0.26,= 0.62, partial �2 = 0.02).

.2. Females show prolonged somatosensory activation whenttending to MNS

To investigate sex differences in the SI neural responseuring each directed-attention condition, we averaged specificime–frequency windows of mu reactivity. As hypothesized, the

ost robust sex differences for our attentional paradigm wereound in the 10–12 Hz mu bandwidth, thus we chose to restrict all ofur statistical analysis to this frequency range. Two separate tem-oral windows were chosen to monitor mu reactivity throughouthe entire duration of each condition. We examined mu reactivityo the first three stimuli in a train separately from reactivity follow-ng the forth stimulus to permit more rigorous measurement of thentire extent of the mu response elicited during each attentionalaradigm.

We analyzed mu activity generated 1.2 s after stimulation forhe first three stimulus events in the train (and thus after the betaebound effect, Fig. 3) to test for predicted sex differences in muesponses after each stimulus event prior to the attentional count.ext, we analyzed mu activity following the fourth stimulus in a

rain (Fig. 5) for several reasons: (1) to permit a more precise andomprehensive analysis of mu reactivity, since it was not inter-upted by responses to the next stimulus in a train (Dockstadert al., 2009); and (2) to investigate sex-related mu reactivity dur-ng the attentional count period (i.e., the MNS event-count woulde updated during the 4 s MNS temporal break between trains inhe Attend to MNS condition).

As shown in Fig. 3, when attention was directed toward theomatosensory events, females showed a sustained mu powerelow baseline (i.e., mu ERD) for the entire duration of the trial,

ndicating prolonged activation of the somatosensory area (Lopesa Silva & Pfurtscheller, 1999; Neuper & Pfurtscheller, 2001). Byontrast, males showed a brief increase in mu power above base-

ine (i.e., mu ERS), reflecting sensorimotor inhibition. However,o sex differences were evident in mu reactivity when directingttention away from somatosensory events and towards a visualtimulus: both showed brief mu desynchrony immediately follow-ng each stimulus event. Statistical analysis revealed a marginally

−2.4 s). We averaged sex-specific values of mu activity following the first 3 stimu-lus events in a train. A marginally significant sex × condition was found (p = 0.057)wherein females (�) expressed greater mu desynchrony (mean mu reactivity = −0.5,se = 0.35) than males (�) (mean mu reactivity = 0.14, se = 0.23) in the Attend to MNS.

significant condition × sex interaction (F[1,18] = 4.125, p = 0.057,partial �2 = 0.19) wherein females expressed greater mu desyn-chrony (mean mu reactivity = −0.5, SE = 0.35) than males (meanmu reactivity = 0.14, SE = 0.23) in the Attend to MNS condition (seeFig. 4). Neither the main effect for condition (F[1,18] = 0.95, p = 0.34,partial �2 = 0.05), or sex (F[1,18] = 1.40, p = 0.25, partial �2 = 0.07)was significant. This pattern of findings suggests that females mayshow a sex-specific neural profile when voluntarily directing theirattention towards somatosensory stimuli.

The most robust sex differences in neural indices of attentionmodulation were found for mu reactivity beginning approximately1 s following the last (i.e., 4th) stimulus in a train (Fig. 5). In theAttend to MNS condition, females showed a strong and continu-ous mu desynchrony that persisted for almost the entire durationof the 4 s MNS break interval. By contrast, there was no evidenceof this attention-related mu modulatory effect in males. How-ever, this sex-specific mu ERD effect did not occur when femalesdirected their attention away from MNS and towards the video.Statistical results showed a significant condition × sex interaction(F[1,18] = 5.54, p = 0.03, partial �2 = 0.24) (Fig. 6). There were no sig-nificant main effects found for condition (F[1,18] = 2.64, p = 0.12,partial �2 = 0.13), or for sex (F[1,18] = 1.34, p = 0.26, partial �2 = 0.07).Post hoc tests indicated sex differences in mu reactivity elicited inthe Attend to MNS condition, with females displaying stronger mudesynchrony (mean = −0.55, SE = 0.28) versus males (mean = 0.16,SE = 0.1), as well as a within-group difference for females based oncondition with Attend to MNS eliciting significantly stronger mudesynchrony (mean = −0.55, SE = 0.28) versus Attend away fromMNS (mean = −0.03, SE = 0.24). Notably, regression analysis usingPearson correlation coefficient confirmed that, in this sample, therewas no correlation between age and mu power (ERS/ERD) formales (Attend to MNS r = −0.06, Attend away from MNS r = −0.17)or females (Attend to MNS r = −0.19, Attend away from MNSr = 0.28).

3.3. No sex differences in behavioural performance

3.3.1. Self-reported count of ‘attended events’Counting errors were computed as a deviation score (differ-

ence between the participant’s count and the confirmed count)and reported as a positive value regardless of whether the countwas an over- or under-estimation. Participants were required to

C. Popovich et al. / Neuropsychologia 48 (2010) 4102–4110 4107

Fig. 5. Sex-specific SI modulation effects of selective attention to the 4 s MNS break interval. TFR plots reflect both the neural activity in response to the fourth stimulusof a train and the requirement to update the count of the 4 s MNS break in the Attend to MNS condition but not the Attend away from MNS condition. Boundary boxesfor mu activity were defined by the Attend to MNS female TFR plot (Mu box: 10–12 Hz, −1.0 s to 0.3 s). Mean values were computed on each individual’s TFR data for bothconditions. Grand averaged values were used to compare sex-specific effects of attention modulation in SI. (A) Grand mean TFR for female participants during the Attend toMNS condition. (B) Grand mean TFR for female participants during the Attend away from MNS condition. (C) Grand mean TFR for male participants during the Attend to MNSc MNSb referea

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ondition. (D) Grand mean TFR for male participants during the Attend away fromoxes. Source power: (A-m)2 = (−n × 10−17 to +n × 10−17). (For interpretation of therticle.)

ount approximately 35 MNS events (Attend to MNS mean errorcore = 0.95, SE = 0.23) and 12 cartoon events (Attend away fromNS mean error score = 0.95, SE = 0.23). A 2 × 2 repeated measures

NOVA with Condition (Attend to MNS, Attend away from MNS)s the within subject variable and Sex as the between subject vari-ble revealed no significant main effects for condition (F[1,18] = 0.0,= 1.0, partial �2 = 0.00), or sex (F[1,18] = 1.49, p = 0.24, partial2 = 0.08), nor was there a significant condition × sex interactionF[1,18] = 1.34, p = 0.26, partial �2 = 0.07).

.3.2. Ratings of perceived attentional demandWe analyzed participants’ scores on a 10 cm visual analog scale

or each condition to assess if their perceived level of attentionalemand varied by condition (as predicted) or sex, or both factors.onsistent with our predictions, there was a significant main effectf condition (F[1,18] = 44.44, p = 0.000, partial �2 = 0.71) with Attendo MNS condition being rated as more demanding of attention than

he Attend away from MNS condition (Attend to MNS mean = 6.35,E = 0.54, Attend away from MNS = 1.94, SE = 0.36). Neither the mainffect for sex (F[1,18] = 0.04, p = 0.84, �2 = 0.00) nor the interactionetween condition and sex was significant, (F[1,18] = 1.81, p = 0.20,artial �2 = 0.09).

condition. Mu ERD (blue) and ERS (red) responses are delineated with rectangularnces to colour in this figure legend, the reader is referred to the web version of the

4. Discussion

This study investigated the effect of attention directed towardsand away from somatosensory stimuli on mu rhythms in the con-tralateral primary somatosensory cortex of healthy adults. Ourresults were consistent with the hypothesized sex differencesspecifically in the 10–12 Hz mu bandwidth, and provide the firstdemonstration of sex differences in selective attentional process-ing of somatosensory information. Findings included (i) greatermu desynchrony in females compared to males when selectivelyattending to somatosensory stimuli; (ii) attentional modulation ofthe mu response elicited only in females; and (iii) an enhanced(although statistically non-significant) physiological response toMNS elicited in females, that could not be attributed to age dif-ferences in this sample. However, contrary to our hypothesis,10–12 Hz mu desynchrony was not greater in the Attend to MNSversus the Attend away from MNS condition overall. As noted pre-

viously, this was due to the lack of attention-related modulation ofmu rhythms in males. No sex differences were found in behaviouralperformance as indicated by the counts of stimulus events or inthe perceived level of attentional demand of the two experimentalconditions.

4108 C. Popovich et al. / Neuropsychol

Fig. 6. Grand-averaged sex-specific mu reactivity values from attending to the 4 sMNS break interval (10–12 Hz, −1.0 s to 0.3 s). We averaged sex-specific values of muactivity following the fourth stimulus in a train when an attentional count updatewas required for the Attend to MNS condition, but not for the Attend away fromMNS condition. There was a significant condition × sex interaction for mu activity(ias

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p = 0.03). Simple t-tests revealed a between group difference with females (�) elic-ting stronger mu ERD versus males (�) for the Attend to MNS condition, as well aswithin-group effect in females between conditions with Attend to MNS eliciting

tronger mu ERD than the Attend away from MNS condition.

We report a non-significant trend in the neurophysiologicalesponse to non-painful MNS with females showing a greater neu-al response overall. This finding is consistent with previous studieseporting greater neural sensitivity in females during both restingtates (Barry et al., 2005; Barry, Clarke, McCarthy, & Seligowitz,006) and physiological stimulation (Kakigi & Shibasaki, 1992).owever, whether females reliably show greater neural excitabil-

ty during MNS remains controversial. For example, Huttunen,ikstrom, Salonen, and Ilmoniemi (1999) found that age, but not

ex, showed a significant positive correlation with the strength ofhe N20 response elicited with MNS, while another study reportedsignificantly lower M20 cortical response in females than males

Zappasodi et al., 2006). Contrary to these findings, the non-painfultimuli used in our study elicited a greater SI response in femaleselative to males regardless of condition. Notably, the prolonged0–12 Hz mu desynchrony was observed in females only during thettend to MNS attentional count period. Collectively, these findingsuggest that females do not show greater sensitivity to MNS pere, but rather are more attentive to and show prolonged process-ng of basic somatosensory information. If females tend to perceiveomatosensory stimuli to be more salient and thereby attend androcess such stimuli more intensely than do males, this process-

ng bias may help explain why females typically show greaterensitivity for most pain modalities (Fillingim & Maixnerm, 1995;affiuletti, Herrero, Jubeau, Impellizzeri, & Bizzini, 2008) and areore prone to chronic pain disorders (Fillingim, 2000; Greenspan

t al., 2007).There are several possible explanations for the observed sex dif-

erences in self-directed attention to somatosensory stimuli. Oneossibility is that males and females may use different cognitivetrategies while processing sensory stimuli (Clements-Stephens,imrodt, & Cutting, 2009; Jordan, Wustenberg, Heinze, Peters, &

ancke, 2002). For example, it has been proposed that females use aore effortful approach, involving continual “online” processing of

alient stimuli in order to keep track of relevant information (Gron,

underlich, Spitzer, Tomczak, & Riepe, 2000). By contrast, males

end to apply principles, based on grouping or categorizing multi-le geometric cues (Gron et al., 2000; Jordan et al., 2002). Thus, inhe present study, it is possible that the enhanced and prolonged

u desynchrony observed in females during the “attend to MNS

ogia 48 (2010) 4102–4110

condition” reflects an effortful and vigilant top–down approach. Incontrast, the evidence of mu synchronization after every stimu-lus event (indicative of sensorimotor inactivation) in males mayindicate their reliance on automatic categorization or grouping ofthe sensory stimuli. This approach would permit rapids shifts ofattention away from the video to update the count of the specifiedsomatosensory event (interval between stimulus trains) followedby rapid disengagement and shift of attention back to the videoclip. However, we acknowledge that a direct comparison betweensex-specific cognitive strategies used to perform highly complexvisuospatial manipulations cannot be applied directly to sex differ-ences in the processing of basic somatosensory information. Thus,we are not suggesting here that there is a causal relation betweenthe sex differences in mu reactivity and sex-specific attentionalstrategies that may have been used to perform either condition.Rather, we propose that the theory of sex differences in cognitivestrategies may be used as a contextual reference with respect tothe sex differences found in this study.

Sex differences in stimulus bias or modality preference mightalso account for the observed sex differences. For example, maleshave been found to respond faster to visual stimuli than females(Spierer, Petersen, Duffy, Corcoran, Rawls-Martin, 2010) and spendmore time playing videogames compared to females (Jackson, Zhao,Kolenic, Fitzgerald, Harold, & Von Eye, 2008). Thus, the observedsex-differences in the present study may be driven primarily byour choice of a video clip (i.e., visual stimuli) rather than auditorystimuli, which appear to be differentially preferred by males andfemales respectively (Jackson et al., 2008).

We also cannot discount several limitations of this study includ-ing: (i) MNS is a non-natural type of somatosensory stimulationthat may be susceptible to sex differences in the perceived levelof somatosensory discomfort, (ii) the attentional conditions werenot adequately equated for stimuli frequency (i.e. predictable MNSevents paired with unpredictable video events) or occurrence (i.e.fewer video incidents versus MNS events to count), (iii) the experi-mental manipulation of attend to MNS while fixating on a videoplaying requires rapid shifting of attention, rather than exclu-sively and consistently attending to MNS, and (iv) we did notcontrol for the gonadal hormones (i.e. females were not matchedfor menstrual cycle phase) which may have may have affectedsomatosensory sensitivity and/or brain reactivity (Tu et al., 2009).However, it has been suggested that gonadal hormones do not influ-ence somatosensory sensitivity (Klatzkin, Mechlin, & Girdler, 2009).Future directions will examine mu rhythms using a paradigm thatequally balances the attentional conditions, increases attentionaldemands, and thoroughly investigates perceived levels of tactilediscomfort and attentional strategies used for behavioural perfor-mance.

Notwithstanding the limitations, our findings suggest that sexdifferences exist in the 10–12 Hz mu rhythm when self-directingattention to non-painful somatosensory information. These resultsare informative for interpreting previous attention-related stud-ies that have failed to consider sex differences and highlightthe importance of powering studies to permit investigation ofpotential sex differences in self-directed allocation of attention tosensory processing. Also, sex differences in top–down control ofattention suggest critical ramifications for understanding the well-documented sex bias in pain processing, as well as for psychiatricand neurological illnesses associated with attentional deficits suchas Attention Deficit Hyperactivity Disorder.

Acknowledgments

This research was supported by funds from operating grantsfrom the Canadian Institutes of Health Research (CIHR #64279; DC),

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he Hospital for Sick Children Psychiatry Endowment Fund (CD, DC,T), the Canadian Research Chairs Program (RT), as well as by theniversity of Toronto Open Fellowship Award and the Hospital forick Children Research Training Centre Graduate Fellowship AwardCP)

Dr. Tannock has received funding as an advisory board memberr consultant for Eli Lilly, and Janssen-Cilag. No funding was pro-ided by any of these parties for the current study. Ms. Popovich,rs. Dockstader and Cheyne report no biomedical financial inter-sts or potential conflicts of interest

ppendix A. Supplementary data

Supplementary data associated with this article can be found, inhe online version, at doi:10.1016/j.neuropsychologia.2010.10.016.

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