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NeuroImage 34 (2007) 1708–1722
Developmental differences in the neural bases of the faceinversion effect show progressive tuning of face-selectiveregions to the upright orientation

A.M. Passarotti,a,⁎ J. Smith,a M. DeLano,b and J. Huangb

aDepartment of Psychology, Cognitive Science and Neuroscience Program, Michigan State University, Psychology Bld., East Lansing, MI 48824, USAbDepartment of Radiology, Michigan State University, East Lansing, MI 48824, USA

Received 12 October 2005; revised 5 July 2006; accepted 6 July 2006Available online 22 December 2006

Face inversion hinders face processing in adults, while not affectingchildren in the same way. This fMRI study examines the neuralunderpinnings of the behavioral face inversion effect (FIE) fromchildhood to adulthood, and how face-selective regions in the brainmay change with development. Adults, children, and teens performeda facial expression decision on upright and inverted face stimuli. In theright hemisphere (RH) all age groups showed similar profiles of neuralactivation for upright faces, but important developmental differencesoccured for inverted faces. For inverted faces, adults, and to a lesserdegree teens, exhibited decreased levels of activity in the face-selective,right lateral fusiform gyrus (LFG). However, children exhibitedgreater activation for inverted than for upright faces in the sameregion. We found similar, but less robust, developmental trends in theright superior temporal sulcus (STS) and medial fusiform gyrus(MFG). Furthermore, the present study identifies the right LFG as theprimary neural correlate of the behavioral FIE, and therefore of faceprocessing expertise, by showing a significant correlation between thebehavioral FIE and the neural FIE only in this region. Finally, thepresent findings shed some light on at least one of the possiblemechanisms underlying the development of face processing expertise,by suggesting a progressive tuning of face-selective regions in the righthemisphere to the upright orientation, that extends well intoadolescence.© 2006 Elsevier Inc. All rights reserved.

The ability to recognize and discriminate between differentfaces is one of the most important human social skills. Behavioraland neurophysiological research suggests early brain specializationfor face processing (Tzourio-Mazoyer et al., 2002) and newbornpreference for upright faces compared to non-face patterns (DeHaan et al., 2002; Morton and Johnson, 1991) or inverted face-likestimuli (Valenza et al., 1996). Nonetheless, there is also evidencefor steady neural (Passarotti et al., 2003; Aylward et al., 2005;

⁎ Corresponding author. Fax: +574 631 8883.E-mail address: [email protected] (A.M. Passarotti).Available online on ScienceDirect (www.sciencedirect.com).

1053-8119/$ - see front matter © 2006 Elsevier Inc. All rights reserved.doi:10.1016/j.neuroimage.2006.07.045

Gathers et al., 2004) and behavioral (Carey, 1992; Diamond andCarey, 1977; Mondloch et al., 2003; Taylor et al., 2004)development of face processing expertise through the teen years.

While adults are experts at processing upright faces, theirperformance worsens when faces are inverted. This phenomenon iscalled “the face inversion effect” (FIE) (Yin, 1969; Valentine,1988; Moscovitch et al., 1997), and is much more pronounced forfaces than objects (Yovel and Kanwisher, 2004). Awidely acceptedexplanation for the FIE is that adult expertise relies mostly onconfigural processing (i.e., processing of the relationship betweenfacial features, rather than processing of single facial features) andthat configural properties are extracted less efficiently when facesare upside down (Carey, 1992; Diamond and Carey, 1977; Freire etal., 2000; Mondloch et al., 2003; Farah et al., 1995). In fact,experimental evidence suggests that configural information is moresalient than featural information when processing faces. Studiesusing the “composite-face effect” paradigm suggest that recogniz-ing that the top and bottom portions of a face in a compositeactually belong to different faces is harder when the two parts arefused than when they are spatially separated (Young et al., 1987),probably because we are biased to integrate face parts into ameaningful facial configuration. Also, only for faces but not forother objects, it is easier to recognize single face features whenthey are within a whole face, than when the features are isolated(Tanaka and Farah, 1993). Furthermore, people are still fairlyaccurate at identifying blurred faces even when the internalfeatures are not very visible, whereas the opposite is not true.These findings suggest that configural information is more salientthan featural information when we try to identify faces (Sergent,1984; Hayes, 1988).

With regard to hemispheric specialization for face processingrecent neuroimaging evidence suggests that the right hemisphere(RH) is specialized for configural processing (Rossion et al., 2000).Supporting this view, the RH superiority in performance for facesdecreases or disappears with face inversion (Hillger and Koenig,1991). In addition, a MEG study (Watanabe et al., 2003) suggests aRH preference for upright faces since it found that latencies in the

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1709A.M. Passarotti et al. / NeuroImage 34 (2007) 1708–1722

M170 (a face-selective component that possibly originates in thefusiform gyrus) are shorter in the RH for upright faces than forinverted faces. On the other hand, some evidence suggests thatboth configural and featural processing contribute to expert faceprocessing and are affected by face inversion. Recent findings withnormal subjects (Riesenhuber et al., 2004; Yovel and Kanwisher,2004) and subjects with developmental prosopagnosia (Yovel andDuchaine, 2006) suggest that face-selective mechanisms processfaces “holistically”, by extracting both configural and featuralinformation as a whole, and that holistic processing is disrupted byinversion.

Either way, since the FIE is considered an indicator of faceprocessing expertise, understanding whether and how the beha-vioral FIE emerges with age would provide a crucial insight on thedevelopment of face processing expertise. The literature examiningthe behavioral FIE in childhood does not provide clear-cut results,probably because of the use of different paradigms and measures ofperformance (Brace et al., 2001). Some studies suggest aqualitative change in FIE with age, while others suggest onlyquantitative changes or no change at all with age. Carey (Carey,1992; Carey and Diamond, 1977) reported a significant “reversed”behavioral FIE (i.e., better performance for inverted than forupright faces) in children younger than age 10, while Brace et al.(2001) reported this result only in children younger than age 5.These studies would suggest a qualitative switch from featuralprocessing (which is less sensitive to orientation) to configuralprocessing (which is sensitive to orientation) with age. But otherstudies found inversion effects in younger children (Baenninger,1994; Chun and Thomson, 1995; Flin, 1985) and suggest thatduring development either the size of the FIE increases (Mondlochet al., 2002) or remains stable (Young and Bion, 1980; Pascalis etal., 2001). The neural underpinnings of the behavioral FIE havebeen explored almost exclusively in adults. Most fMRI studies oninverted face processing have found a small but significantreduction in activation in the face fusiform area (FFA) (Yoveland Kanwisher, 2004; Gauthier et al., 1999; Haxby et al., 1999;Kanwisher et al., 1998), sometimes accompanied by increasedactivation in inferior temporo-occipital regions that usually processfeatures (Haxby et al., 1999; Kanwisher et al., 1998; Leube et al.,2003). Neuropsychological evidence also suggests that for invertedfaces the FFA may need additional input from object-processingregions (Haxby et al., 1999; Leube et al., 2003; Rossion et al.,2003). In fact, a patient with object agnosia (i.e., with objectprocessing deficits) could process upright faces but showedimpaired processing of objects and inverted faces (Moscovitch etal., 1997), whereas patients with prosopagnosia (i.e., with deficitsin discriminating between faces) usually exhibit the oppositepattern (Farah et al., 1995).

Recent neurophysiological findings suggest that the neuralcorrelates of the behavioral FIE undergo protracted developmentalchanges. The N170 is a face-specific, negative event-relatedpotential (ERP) component, which may have its anatomicalsources in the inferior occipito-temporal areas (Taylor et al.,2004; Bentin et al., 1996). In adults face inversion causes largerN170 latencies and greater amplitudes in the RH (Taylor et al.,2004). The N170 occurs as early as age 4, and even youngerchildren show some evidence of FIE in their N170 profiles (Tayloret al., 1999). Nevertheless, different face processing strategiesexhibit a different developmental timeline. Taylor et al. (2001)found that for featural face processing the N170 reaches adult-likeprofiles by age 11, while configural processing develops more

slowly and improves through adolescence (Taylor et al., 2001,2004). Moreover, different from the findings for featural proces-sing, findings for inverted faces showed that the typical adult N170latencies (with greater right hemisphere amplitudes) emerged onlyin mid-adolescence, suggesting that children did not just usefeature processing with inverted faces, but probably used acombination of both feature and configural processing (Taylor etal., 2001, 2004). The view of gradual, quantitative changes in theneural substrates of face processing (Taylor et al., 2001, 2004) isconfirmed by developmental fMRI studies on upright faceprocessing which found more bilateral activation and widespreadright fusiform activation in children than in adults (Passarotti et al.,2003), with differences in activation until late adolescence(Passarotti et al., 2001), as well as a progressive increase in rightfusiform selectivity for faces compared to objects (Gathers et al.,2004; Aylward et al., 2005).

Whereas these studies did not examine the neural under-pinnings of the behavioral FIE, the present fMRI study is the first,to our knowledge, to establish the neural segregation andorganization of the neural correlates of the behavioral FIE, fromchildhood to adulthood. We wished to address the crucial questionof whether the effects of inversion on the functioning of face-selective regions may differ with development, and if so, in whatfashion. By using fMRI during processing of upright and invertedfaces we wanted to clearly localize the anatomical underpinningsof the FIE in children and adults. Furthermore, we tested childrenin the 8–11 age range and adolescents to address the existingdebate on whether there is an abrupt, qualitative change in faceprocessing skills around age 10 (Carey, 1992; Carey and Diamond,1977) or whether development of face processing expertise is moregradual and quantitative in nature (Baenninger, 1994; Chun andThomson, 1995; Taylor et al., 2004). With regard to the adultgroup, for inverted face processing we predicted a decrease inperformance accompanied by a decrease in activation of face-selective regions in the right hemisphere, for inverted compared toupright faces (Yovel and Kanwisher, 2004; Leube et al., 2003). Weexpected teens to exhibit similar but somewhat weaker profiles ofactivation in face-selective regions as the adults, since expertconfigural processing is not reached until late adolescence (Tayloret al., 2004). As for the younger children, we predicted that theirfunctional activation in face-selective regions may not differsignificantly for upright and inverted faces, because children mayuse face-specific strategies less efficiently than adults, or they mayuse more general processing strategies that are not as sensitive toorientation (Baenninger, 1994; Taylor et al., 2001).

To test our predictions we collected behavioral and fMRIdata from adults, teens and children during a face-emotion pro-cessing task with inverted and upright face presentations. Faceemotion processing, like face identity processing, relies mostlyon configural or holistic strategies and shows comparable faceinversion effects (Calder et al., 2000; McKelvie, 1995). Weused angry and happy expressions because the ability torecognize them is fully developed by age 6 (Markham andAdams, 1992).

Methods

Participants

Thirteen adults (aged 20–30 years), ten teens (aged 13–17 years), and fourteen children (aged 8–11 years) were recruited

Fig. 1. Example trial and behavioral results. (a) An example of the visualdisplay and trial timeline. Here we present an inverted face trial. Our facepictures were taken from the NimStim Face Stimulus Set. (b) Meanproportion correct for upright and inverted face trials in children (N=10),teens (N=9), and adults (N=10). (c) Mean RT (ms) for performance onupright and inverted face trials in children, teens, and adults. Asteriskindicates significance at p<.05. Error bars in panels b, c represent theSEM.

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from the local community and Michigan State University. Allparticipants were right-handed as assessed by a handednessquestionnaire (Oldfield, 1971) and had normal or corrected tonormal vision. They had no known-neurological or cognitiveimpairment. Adult participants were either volunteering or weregiven class credit. Children and teens received a monetarycompensation ($10) for their 2-h participation. Before testing,adult participants and child parents/guardians signed an informedconsent, while children and teens signed an assent form. Amedical clearance questionnaire was administered to eachparticipant to ensure scanning safety. All our forms and researchprotocols were approved by the Michigan State UniversityCommittee for Research with Human Subjects. fMRI data from2 adults and 1 child were discarded because of technicalproblems, whereas data from 1 adult, 1 teenager, and 2 childrenwere excluded because of low performance levels or excessivemotion. The final fMRI dataset included 10 adults (5 F, 5 M;mean 25.3±4 years), 9 teens (7 F, 2 M; mean 14.9±1.6 years),and 11 children (5 F, 6 M; mean 10±1.6 years). Due to technicaldifficulties with button press recordings, we did not collectbehavioral data from one male child. Therefore our behavioraldataset included 10 children.

Brain imaging procedures

Participants learned the experimental tasks during a trainingsession preceding scanning. In addition, children and teenslistened to audio recordings of scanner noises to become morefamiliar and comfortable with them. Then, the scanning sessionstarted and lasted approximately 40 min. We adopted a standardblock design to maximize signal-to-noise ratio for short imagingsessions. We alternated six 40-s blocks of each task and control in4 min and 8 s. Eight trials (each lasting 5 s) were presented foreach block, for a total of 48 trials in each run. Visual stimuli wereprojected directly on a small MR-compatible LCD screen (viewangle: 12° vertically and 16° horizontally) positioned on the headcoil inside the MRI scanner. Our visual stimuli were presentedthrough the IFIS-SA System (Psychology Software Tools Inc.,Milwaukee, WI). Button presses were performed with a specialmouse, part of the IFIS-SA system, and were recorded at milli-second accuracy.

BOLD images were acquired on a 3 T magnet (G.E. MedicalSystems, Pittsburgh, PA) using a standard GE quadrature headcoil. After an initial coronal localizer and manual shimming, T2*-weighted single-shot gradient-echo planar images (EPI) wereacquired with TR=2 s, TE=40 s, FOV=220 mm, flipangle=80°, 25 contiguous 5.5 mm axial slices, 120 images,64×64 matrix, in-plane resolution, 3.4×3.4×5.5 mm. For eachparticipant, these images were registered to high-resolution T1-weighted structural images (116 sagittal fast SPGR images, FOV256, 1.5 mm slices). We used padding materials to stabilizeparticipants’ heads, and earplugs to attenuate the scanner noise.We showed to children and teens cartoon videos during the initiallocalizer protocols and during anatomical acquisitions, to keepthem relaxed and still.

Behavioral task

During scanning, on each trial participants saw a color pictureof a female face presented centrally on a black background, and,depending on the run, responded selectively to one of two face

emotions (i.e., happy or angry). Each 5-s trial began with a1000 ms fixation cross, followed by central presentation of a facepicture for 2000 ms and a response time of 2000 ms. We decidedto give participants a whole 2 s to process stimuli, to ensure thateven the younger children would perform well. In addition,depending on the run the face stimuli were presented either uprightor upside-down (see Fig. 1a for an example of an inverted facetrial). On each trial of the control task participants gave a simplemotor response (i.e., a key press) when the face stimulus (i.e.,neutral face) appeared. These control trials were blocked and nocognitive decision was required. Order of task conditions(inverted, upright faces) and target emotion (happy, angry) wascounterbalanced across participants.


fMRI image processing

Anatomical and functional images were processed in AFNI(Cox, 1996). To control for initial magnetic field inhomogeneities,

Table 1Significant clusters of activation, their laterality, and their Talairach coordinates (Tachildren (N=11), teens (N=9), and adults (N=10)

Upright faces

x y z BA Hemisphere Region

Adults (N=10) −34 45 −18 20/37 L LFG39 40 −19 20/37 R LFG

−58 55 −12 20/21 L IT gyr63 44 −12 20/21 R IT gyr

−47 −42 17 9 L MF gy−63 −30 3 20/22 L MT gy57 37 0 20/22 R MT gy

−33 84 −7 18/19/37 L IOG58 66 −2 18/19/37 R IOG

−59 60 6 22 L STS64 28 9 22 R STS−9 24 35 20 L MFG11 24 33 20 R MFG

Teens (N=9) −40 −45 −15 37 L LFG38 −41 −13 37 R LFG

−21 36 30 20 L MFG14 31 33 20 R MFG45 43 40 40 R IP lob52 48 7 20/22 R MT gy

−56 32 −15 20/21 L IT gyr58 −16 −20 20/21 R IT gyr

−58 32 −13 20/22 L MT gy−27 −84 −7 18/19/37 L IFG42 −60 −6 18/19/37 R IFG

−42 −43 −4 22 L STS64 −9 11 22 R STS

Children (N=11)−45 41 −9 37 L LFG36 42 −14 37 R LFG−7 54 −3 20 L MFG15 55 4 20 R MFG18 96 −5 18 R Ling.52 −14 45 9 R MF gy22 42 62 7 R SP lob

−64 −16 −15 20/21 L IT gyr56 −9 −20 20/21 R IT gyr

−45 −49 2 20/22 L MT gy45 −48 2 20/22 R MT gy

−20 81 −5 18/19/37 L IOG57 −67 −3 18/19/37 R IOG

−42 −47 −1 22 L STS48 −51 3 22 R STS

The Talairach coordinates (in the x, y, z axes) for our axial images indicate the centeposterior; Z=superior to inferior. Note that in our X coordinates the right (R) hemAbbreviations: lateral fusiform gyrus=LFG; medial fusiform gyrus=MFG; inferoccipital gyrus=IOG; superior temporal sulcus=STS; inferior parietal lobule= IP lofrontal gyrus=MF gyrus; Ligual gyrus=Ling. gyrus; cingulate gyrus=Cing. gyru

the first four time points of all functional runs were discarded apriori. In-plane (slice-wise or 2D) and volumetric (3D) motioncorrection was performed on the dataset using the AFNI programs2dImReg and 3dvolreg, respectively, using the third acquisition as

lairach and Tourneaux, 1988) for the upright and inverted face conditions, in

Inverted faces

x y z BA Hemisphere Region

−44 49 20 37 L LFG35 40 −21 37 R LFG

us −9 24 35 20 L MFGus 11 24 33 20 R MFGrus 56 −16 13 47 R IF gyrusrus −48 10 −28 21 L IT gyrusrus −32 −2 −38 20/22 L MT gyrus

−55 −9 −18 20/22 L MT gyrus4 72 41 7 R Precuneus

−10 87 43 7 L Precuneus55 54 13 22 R ST gyrus

−40 −20 −20 22 L ST gyrus−59 49 −13 20/21 L IT gyrus58 29 −14 20/21 R IT gyrus

−63 −30 3 20/22 L MT gyrus57 37 0 20/22 R MT gyrus

−39 86 −7 18/19/37 L IOG58 60 −2 18/19/37 R IOG

−57 −39 8 22 L STS56 42 9 22 R STS19 38 28 24 R Cing. gyrus

−45 −47 −20 37 L LFG40 −38 −21 37 R LFG

−21 36 30 20 R MFGule 14 31 33 20 L MFGrus −52 −53 −13 20/21 L IT gyrusus 56 −33 −15 20/21 R IT gyrusus −59 −49 −1 20/22 L MT gyrusrus 67 −46 2 20/22 R MT gyrus

−19 −92 −6 18/19/37 L IOG46 73 −8 18/19/37 R IOG

−54 46 −2 22 L STS48 −51 4 22 R STS

−44 44 −11 37 L LFG36 42 −12 37 R LFG−7 54 −3 20 L MFG15 55 4 20 R MFG

−27 −23 −5 47 L IF gyrusgyrus −35 −48 −8 9 L MF gyrusrus −6 49 9 23 L Post. Cing.ule −30 68 58 7 L SP lobuleus −52 43 −13 20/21 L IT gyrusus 56 39 −13 20/21 R IT gyrusrus −47 −8 −35 20/22 L MT gyrusrus 49 25 −14 20/22 R MT gyrus

−29 81 −4 18/19/37 L IOG40 72 −4 18/19/37 R IOG

−51 50 −1 22 L STS47 49 5 22 R STS

r of mass of each significant cluster of activity. X=right to left; Y=anterior toisphere has a positive sign and the left (L) hemisphere has a negative sign.ior temporal gyrus=IT gyrus; middle temporal gyrus=MT gyrus; inferiorbule; superior parietal lobule=SP lobule; inferior frontal gyrus=IFG; middles; posterior cingulate=Post. Cing.


the fiducial volume. The signal was then orthogonalized to theobtained parameters of rigid body rotation and global drift wasremoved on a voxel-wise basis over each functional run. Forvolumetric motion correction, an iterated, weighted linear leastsquares algorithm with Fourier interpolation (Cox and Jesmano-wicz, 1999) was utilized to register all dataset volumes to the thirdacquired T2*-weighted functional volume and time shifted to thefiducial volume in order to account for slice acquisition offset. Weconsidered the algorithm iterations “convergent” when maximummovement was less than .02 voxels and maximum rotation was lessthan .03°. There were no time points at which these constraintswere exceeded; angular and linear drift along and around the x, y,and z axes of the dataset were quantified as vector components andused as regressors in further analyses.

High- and low-bandpass filters were applied to the data (usingthe AFNI program 3dFourier) at .20 Hz and .60 Hz, respectively,in order to suppress predictable pulsatile physiologic noise such ascardiac and respiratory rhythms. Stimulus-related activation wasdetected by examining the time-course correlation of each voxel’ssignal intensity with a family of idealized hemodynamic responsewaveforms (Bandettini et al., 1993). High- and low-bandpassfilters were applied to the data (using the AFNI program3dFourier) at .20 Hz and .60 Hz, respectively, in order tosuppress predictable pulsatile physiologic noise such as cardiacand respiratory rhythms. Stimulus-related activation was detectedby examining the time-course correlation of each voxel’s signalintensity with a family of idealized hemodynamic responsewaveforms (Bandettini et al., 1993). Voxels correlating at acoefficient threshold of .23 (p<.001, uncorrected) were retained.For each individual, statistical maps were then overlaid on the co-registered high-resolution normalized anatomical dataset (Talair-ach and Tourneaux, 1988). Child brain normalization is anaccepted protocol in developmental fMRI studies, since totalbrain size does not increase significantly between ages 9 and 18(Klingberg et al., 2002). Therefore data from 8 to 9 year olds andadults can be effectively transformed into the same stereotacticspace (Schlagger et al., 2002; Kang et al., 2003) with minimal age-related difference. The average motion (roll, pitch, yaw) forchildren was .049°, for adults .020°, and for teens .017°. Theaverage motion for children was .055 mm, for adults .017 mm, andfor teens .022 mm. Student’s t-tests revealed that the child groupdiffered significantly (p< .05) from the other two groups.However, tolerance for motion correction in AFNI was.07 mm×.03° between slices and only subjects in any age cohortwho did not exceeded these tolerance parameters were kept in ouranalyses.

For each subject we obtained mean volume and % signalseparately for upright and inverted face emotion trials using across-correlation analysis (r>.23) in which we identified contig-uous voxels that correlated to a modified waveform with thresholdat p<.01. We followed the same procedure for neutral trials. Ouranalyses focus on upright and inverted face emotion trials, sincethese are the trials that required a cognitive decision and thereforeensured accurate processing. Then, Cluster analyses were carriedout in AFNI. Minimum alpha (confidence) levels were computedusing Monte Carlo noise simulations in the AFNI programAlphaSim (Ward, 1997). In this step, adjacent voxels with pvalues falling below .001 had to form connected regions of at least195 mm3 for significant activation. In addition to individual clusteranalyses, an additional cluster analysis was performed on eachgroup’s statistical maps.

ROI definition

We examined three core regions in extrastriate cortex that havebeen defined as part of a distributed face processing system (Haxbyet al., 2000). Although the functional role of these regions and howthey interact with each other is still not completely understood,several studies suggest that the lateral fusiform gyrus (LFG) is aface-selective region that processes invariant aspects of faces, suchas identity (Haxby et al., 1999; Haxby et al., 2002; Kanwisher etal., 1997), whereas the superior temporal sulcus (STS) processeschangeable aspects of faces, such as gaze orientation or faceexpressions (Hoffman and Haxby, 2000; Puce et al., 1998; Rolls,1984) and may be one of the sources of the N170 (Puce et al.,1998). The inferior occipital gyrus (IOG) processes single facefeatures (Haxby et al., 1999) and may either feed featuralinformation onto the STS and LFG (Hoffman and Haxby, 2000;Haxby et al., 1999), or receive feed-back signals from the LFG toguide fine-grained feature analyses (Rossion et al., 2003). Inaddition, we examined the medial fusiform gyrus region (MFG),which is involved in object processing in adults (Ishai et al., 1999),but has been found to contribute considerably to face processing inchildren (Passarotti et al., 2003). All our participants showedbilateral clusters of activation in these regions (see Table 1).

Our ROIs were defined anatomically, using anterior andposterior boundaries as defined in previous studies (Gauthier etal., 1999). Since there is evidence of minimal age-relateddifferences in spatial transformation after age 8 (e.g., Kang et al.,2003; Schlagger et al., 2002) we did not trace the ROIs for eachsubject individually, rather we defined each ROI anatomically on atemplate (Talairach and Tourneaux, 1988), and applied it to thenormalized brains within each group, as several developmentalfMRI studies did (e.g., Nelson et al., 2003; Passarotti et al., 2003).For the LFG ROI we first isolated in each subject a significantcontinuous cluster of activation with center of mass coordinatesthat were similar to the ones given by Grill-Spector and Kanwisher(2005) and Haxby et al. (2002). We then placed an eight-voxelbounding box around the individuals’ cluster center of mass, whichcorresponded to the spatial extent of the FFA given in Rossion etal. (2003) and Kanwisher et al. (1997), and averaged the maskedindividual clusters across subjects within each of the age groups.For each group we had therefore an averaged cluster, which wefound to overlap with the anatomically defined lateral fusiformregion (Haxby et al., 2002; Grill-Spector and Kanwisher, 2005;Rossion et al., 2003). Therefore we adopted the anatomicallydefined LFG as our ROI. The IOG, STS and medial fusiform gyrus(MFG) were also derived from functional clusters and ultimatelyanatomically defined (Talairach and Tourneaux, 1988). SeparateROIs were obtained for the left and the right hemisphere.

Results

Behavioral performance and behavioral FIE

Separate ANOVAs were carried out for Reaction time (RT) andAccuracy data. Incorrect button presses were excluded from the RTanalyses but were included in the Accuracy analyses. Faceorientation (upright, inverted) was the within-subjects factorwhereas Age (children, teens, and adults) was the between-subjectsfactor. When an Age effect was found separate ANOVAs by Agewere also carried out to further examine performance within eachage group.


AccuracyThe Accuracy results are summarized in Fig. 1b. Accuracy

levels were above 90% in each age group. The teens’ accuracy didnot differ from that of children and adults (F values<1), but adultshad a significantly higher accuracy than children [F(1,18)=5.34;p=.03]. In an ANOVA with Age (children, teens, adults) andOrientation (upright, inverted) as factors a significant Faceorientation effect [F(1,26)=5.56; p=.03] demonstrated that overallAccuracy was significantly higher for upright (.97) than forinverted faces (.94). Nevertheless, the interaction of Age×Orienta-tion was not significant (F<1), suggesting that there were norobust age differences in FIE for the accuracy data. SeparateANOVAs by Age confirmed that accuracy for upright and invertedfaces did not differ significantly in either children [F(1,9)=1.95.p=.19], teens [F(1,8)=2.61 p=.14], or adults (F<1).

Since participants had quite a long time to process stimuli andto respond (i.e., 2 s), it is possible that some ceiling effectsoccurred and weakened Age×Orientation effects in the accuracydata. Therefore these data need to be considered with caution. We

Fig. 2. fMRI maps of significant (p<.01, corrected) group cluster activation in chilside) and the inverted face task (right side). See also Table 1. The particular axiaSignificant functional clusters of activation were overlaid on a T1 anatomical imagmm of the axial slices (i.e., according to a superior to inferior axis) from the intercomon the top right side represents the scale of percent signal change increases in the exthe radiological convention [i.e., the left side of the brain picture represents thehemisphere (L)].

turn now our attention to the RT data, which have been found to bemore useful in limiting ceiling effects (Ellis, 1990).

Reaction timeThe RT results are summarized in Fig. 1c. As expected, a

significant main effect of Age indicated that RT improvedsteadily with age for both upright and inverted face presentations[F(2,26)=19.28; p=.00007]. Planned comparisons showed thatthe three groups differed significantly from each other (p<.001).An inspection of the individual data revealed that whereas in 80%of the adults RT was elongated for inverted faces, in children andteens RT was more variable and did not show a consistent costfor face inversion (there was a RT cost for inversion only inabout 40% of children and 44% of teens). The majority ofchildren (60%) exhibited a trend for faster RT with inverted thanwith upright faces. In spite of these trends, the interaction ofAge×Orientation was not significant (F<1).

Separate ANOVAs by Age confirmed that the adult RT wassignificantly higher for inverted faces (858 ms) than for upright

dren (N=11), teens (N=9), and adults (N=10) for the upright face task (leftl slice represented in this figure shows the right and left Fusiform Gyrus.e from one participant. The Z coordinate (Z=−11) indicates the distance inmissural plane (anterior commissure−posterior commissure). The color barperimental tasks compared to the control task. Note that brain images followright hemisphere (R), the right side of the brain picture represents the left

1 To check that our developmental FIE results for the right LFG are notcaused by attentional effects (O’Craven et al., 1999) due to the emotionalcontent of our stimuli, we compared the % signal change for neutral facetrials (which have no emotional content) to that of face emotion trials(which have an emotional content) in an ANOVA with the factors of Age,Type of trials, Hemisphere and Orientation. The interaction of Type oftrial×Hemisphere×Orientation, which would identify FIE patterns for thetwo types of trials, was not significant [F(1,27)= .24, p=.63]. Moreover,the three-way interaction of Age×Type of trial×Orientation was also notsignificant [F(2,27)=1.76, p=.19], suggesting that across all ages the FIEpatterns in LFG did not differ significantly for neutral faces and emotionfaces. No other significant interactions of Type of trial with the other factorswere found.


faces (767 ms) [F(1,9)=7.48, p=.02]. The size of the adultbehavioral FIE (about 12%) is comparable to that found inother studies (Aguirre et al., 1999; Diamond and Carey, 1986;Itier and Taylor, 2004; Valentine, 1988). Conversely, in children[F(1,9)= .11, p=.74] and teens [F(1,8)= .12, p=.74] RT did notdiffer significantly for upright and inverted faces.

ROI analyses and neural FIE

As expected, significant clusters of activity were found in theface-selective region LFG (BA 37), in STS (BA 22), in IOG (BA19), and MFG (BA 20) (see Fig. 2, and Table 1). We report belowpercent signal change analyses separately for each ROI. An initialANOVA was run with Age group (children, teens, adults) as abetween-subjects factor and Hemisphere (left, right) and Orienta-tion (inverse, upright) as within-subjects factors. When the factorof Hemisphere interacted significantly with other factors we carriedout separate analyses by hemisphere.

Lateral fusiform gyrus (LFG) ROIIn an initial ANOVA the three-way interaction of Age×Hemi-

sphere×Orientation was significant [F(2,27)=5.22, p= .01].Planned comparisons on this interaction indicated that onlychildren [F(1,10)=8.83, p=.006] but not adults [F(1,9)=1.92,p=.18] and teens (F<1) demonstrated significant hemisphericdifferences in profiles of activation for upright and inverted faces.Moreover, it was only in the right LFG that the child FIE profilediffered significantly from that of teens [F(1,27)=10.77, p=.003]and adults [F(1,27)=15.71, p=.0005], who did not differ fromeach other (F<1). Given these findings, we proceeded to examineLFG data separately for each hemisphere.

Importantly for our hypotheses, for the right LFG, we founda significant interaction of Age×Face Orientation [F(2,27)=9.19,p<.0009]. Planned comparisons revealed that only for invertedfaces did children show significantly higher percent signal changethan adults [F(1,27)=13.54, p<.001] and teens [F(1,27)=9.59,p<.005], who in turn did not differ from each other (F<1). Nosignificant age differences in levels of activation were found forupright faces (F<1). With regard to the neural FIE (i.e., thedifference between % signal change for upright faces and % signalchange for inverted faces), in accord with the RT data adultsexhibited the expected FIE, with a higher percent signal change forupright (.28%) than for inverted (.09%) faces [F(1,27)=4.81,p<.04]. This adult pattern was similar to the one found in otherstudies (Yovel and Kanwisher, 2004, 2005) and is usually attributedto hindrance of face-specific processes, defined either as configural(Haxby et al., 1999; Leube et al., 2003) or holistic (Yovel andKanwisher, 2004; Riesenhuber et al., 2004) processes. Like inadults, also in teens activation was higher for upright (.26%) thanfor inverted (.15%) faces, although not significantly [F(1,8)=4.81,p<.20]. On the contrary, in children there was a “reversed” neuralFIE, in that children actually showed a higher percent signal(.49%) for processing of inverted faces than of upright faces(.22%) [F(1,10)=11.86, p<.002] (Fig. 3a). The child neural FIEdiffered significantly from that of adults [F(1,27)=15.71,p=.0005] and teens [F(1,27)=10.77, p=.003], who did not differfrom each other (F<1).

With regard to the left LFG, a significant Age effect [F(2,27)=4.02,p<.03] revealed that children exhibited significantly moreactivation than teens (p<.03), and marginally more activationthan adults (p<.06) (Fig. 3b). The interaction of Age×Orienta-

tion was not significant (F<1). Separate ANOVAs by Age showedthat also in the left LFG adults exhibited a higher percent signal forupright (.17%) than for inverted (.07%) faces [F(1,9)=7.89, p=.02],although the size of the FIE in the LH was about half of that in theRH [F(1,9)=6.06, p=.04]. Children and teens exhibited very similaractivation levels for the two conditions (F values<1). Finally, similarto the right LFG results, separate ANOVAs by Orientation showedevidence of age differences in activation only for inverted [F(2,27)=5.07,p<. 013] but not for upright faces [F(1,27)=1.43, = .26]. Plannedcomparisons on the inverted face data revealed that childrenactivated significantly more than adults [F(1,27)=9.01, p=.006]and teens [F(1,27)=5.47, p=.03], who did not differ from eachother (F<1).

Our results suggest that developmental differences in profiles ofneural FIE for our face emotion processing task1 occurredspecifically in the right LFG, but not in left LFG. As an additionalway of representing these findings, we calculated for eachparticipant a score of neural FIE (i.e., % signal for upright faces−% signal for inverted faces). We did this separately for RH and LH.Our Results are reported in Fig. 3c. Similar to findings in our ROIanalyses, an ANOVA on the right LFG scores revealed asignificant Age effect [F(2,27)=7.78, p=.02] such that onlychildren revealed a negative neural FIE score (− .25) (i.e., meangroup activation was higher for inverted faces), whereas teens (.12)and adults (.19) revealed a positive neural FIE score (i.e., higheractivation for upright faces). Planned comparisons revealed that thechildren’s pattern differed significantly from that of adults [F(1,27)=13.14, p=.001] and teens [F(1,27)=8.98, p=.006], who in turn didnot differ (F<1). On the contrary, for the left LFG there were no agedifferences (F<1).

Relation between behavioral and neural FIE in right LFGAs expected our adults, and to a lesser degree teens, showed

greater right LFG activation for upright faces, which suggests a“preference”, or sharper tuning, for upright faces. On the contrary,children exhibited a higher activation for inverted faces, whichaccording to the same rationale would mean a preference for theinverted orientation. But one may also argue that the child datapatterns may result from a general increase in neural and cognitive“effort” in order to extract relevant facial information with anunusual orientation. If this were true, the neural effort resultingfrom inverted face processing would be most likely associated withhigher RT for inverted faces. In order to test the “preference” or“effort” hypotheses for children, we examined the relation betweenthe behavioral FIE (i.e., RT) and the neural FIE for the right LFGin each individual. We were able to identify four different neural/behavioral FIE profiles, and to ascertain that the majority of

Fig. 4. Relation between Behavioral and Neural FIE in the right LFG: agedifferences across four different profiles. The “Upright face preference”profile corresponds to the “typical FIE profile” in our data (i.e., faster RT forupright faces, higher activation for upright faces). The “Inverted face


children did not exhibit an effort profile, rather a preference profilefor inverted faces. Fig. 4 shows the age group distribution for thefour FIE profiles. For our purposes we will focus especially on thetwo “preference” profiles which had overall the highest occurrence(they were present in 2/3 of subjects) and showed a clear agedissociation. In fact, the adult group was characterized by thetypical FIE profile, with a preference for the upright orientation.About 60% of the adults exhibited this pattern, while 33% of theteens and only 10% of children did so. Conversely, the child groupwas mainly characterized by a “reversed FIE profile,” showing apreference for the inverted face orientation. In fact, 60% of the

preference” profile corresponds to the “reversed FIE profile” (i.e., faster RTfor inverted faces, higher activation for inverted faces). The “Upright faceeffort profile” presents higher RTand higher activation for upright faces. The“Inverted face effort profile” presents higher RT and higher activation forinverted faces. The age groups differed significantly in their frequencydistributions across the four categories (see results section). The proportionsare based on 10 children, 9 teens and 10 adults.

children showed this profile, while only 22% of teens, and noadults did so. In addition, there were two minor FIE profiles thatdid not show a preference for upright or inverted faces, rather someeffects of neural and cognitive effort due to orientation. An “Uprightface effort profile” exhibited higher RT and higher activation forupright faces, while an “Inverted face effort profile” exhibited higherRT and higher activation for inverted faces. We found that only 1/3of children, and a little less than 1/2 of the adults and teens fell inthese two categories. A Chi-square (χ2) test revealed that the agegroups differed significantly in their frequency distributions acrossthe four categories [χ2 (6,N=29)=14.44, p=.03]; more specifically,the child and adult frequency distributions for the “reversed” and“typical” FIE patterns differed significantly from each other [Yates’χ2 (1, N=20)=6.41, p=.01].

Superior temporal sulcus (STS) ROIIn a first ANOVA the interaction of Hemisphere×Orientation

was significant [F(1,27)=5.65, p=.02]. Planned comparisonsdemonstrated that overall the left STS had a higher signalchange than the right STS for inverted face trials [F(1,27)=6.79,p=.01], but not for upright face trials (F<1). The Age×Hemi-sphere interaction showed a non-significant trend [F(1,27)=2.78,p=.08] such that children [F(1,27)=3.67, p=.07] and teens

Fig. 3. ROI analyses results for the right and left Lateral fusiform Gyrus.Mean percent signal change for upright and inverted face trials as obtainedfrom the functionally defined LFG ROI in children (N=11), teens (N=9),and adults (N=10). (a) Right LFG. Note that whereas in adults the percentsignal change is greater for upright than inverted faces [F(1,27)=4.81,p<.04] children exhibit significantly more activation for inverted than forupright faces [F(1,10)=11.86, p<.002]. Teens activate more for uprightpresentations, but not significantly so (p<.20). (b) Left LFG. Only in adultspercent signal is significantly higher for upright than inverted faces[F(1,9)=7.89, p=.02], whereas children and teens do not show differencesfor the two conditions (F values<1). Asterisk indicates significance atp<.05. Error bars in panels a, b represent the SEM. (c) Mean upright faceactivation advantage in right and left LFG (Neural FIE). Positive scoresindicate higher selectivity for upright faces than for inverted faces, whereasnegative scores indicate the opposite. Note that for the right LFG there is asignificant Age effect [F(2,27)=7.78, p=.02]. Children differed signifi-cantly from adults [F(1,27)=13.14, p=.001] and teens [F(1,27)=8.98,p=.006], who in turn did not differ (F<1). Asterisk indicates significance atp<.05. Double asterisk indicates significance at p<.001.

Fig. 5. ROI analyses results for the right and left Superior Temporal Gyrus(STS), showing the mean percent signal change obtained for upright andinverted faces from the functionally defined STS ROI in children (N=11),teens (N=9), and adults (N=10). (a) Right STS. Only adults exhibited asignificantly higher percent signal change for upright than for inverted faces[F(1,9)=49.41, p<.00006]. (b) Left STS. No significant results were found(F values<1). Asterisks indicates significance at p<.001. Error bars inpanels a, b represent the SEM.


[F(1,27)=4.39, p=.05] had higher activation in the left STS,while adults had similar activation levels in the two hemispheres(F<1). Next, we analyzed right and left STS data separately ineach age group. In the right STS adults showed a significantneural FIE, with higher percent signal for upright faces (.49%)than for inverted faces (.44%) [F(1,9)=49.41, p< .00006],confirming previous findings of STS preference for the uprightorientation, which has been attributed to its involvement inconfigural processing (Haxby et al., 1999; Leube et al., 2003).Conversely, the right STS in children (F<1) and teens (F<1) didnot show significant orientation preferences (Fig. 5a). For the leftSTS there were no significant results (F values<1) (Fig. 5b). Thepresent findings indicate that similar to the right LFG, the rightSTS increases its sensitivity to the upright face orientation withage. The younger groups engage their left STS more than adultsdo, which suggests that they may rely more on levels of analysesthat are not face-specific.

Finally, like the right LFG, the right STS also exhibited agedifferences in the upright activation advantage [F(2,27)=10.30,p=.005], while the left STS did not (F<1). For the right STSplanned comparisons revealed that adults (.05%) and teens (.006%)exhibited a positive upright orientation advantage, but this patternwas significant only in adults [F(2,27)= , p=.008]. Adults alsodiffered from children [F(2,27)=20.47, p=.0001] who exhibited anon-significant preference (F<1) for the inverted orientation(− .24).

Inferior occipital gyrus (IOG) ROIAn initial ANOVA revealed a significant interaction of

Age×Hemisphere [F(2,27)=6.72, p=.004] and Hemisphere×Or-ientation [F(1,27)=5.84, p=.02]. Therefore we analyzed our dataseparately by hemisphere. For the right IOG no significant effectswere found (Fig. 6a). For the left IOG a main effect of Age wassignificant [F(2,27)= .004], in that children (.55) and teens (.53)exhibited greater activation (p<.05) than adults (.45) for bothorientations. No interaction of Age×Orientation was found (Fig.6b). Separate ANOVAs by Age demonstrated a significant inte-raction of Hemisphere×Orientation both in children [F(1,10)=5.6,p=.04] and in teens [F(1,8)=8.03, p=.02]. Planned compar-isons on the child data showed no orientation effects in the left[F(1,10)=1.13, p=.31] or right IOG (F values<1). Plannedcomparisons on the teen data revealed that the left IOGactivated more for upright faces (.55%) than inverted ones(.51%) [F(1,8)=5.01, p=.05], whereas the right IOG did notshow significant orientation effects (F<1). Moreover, plannedcomparisons on the child data showed that activation washigher in the left (.56%) than in the right IOG (.53%) only forupright faces [F(1,10)=5.09, p=.047]. The teens showed a similarbut non-significant trend [F(1,8)=4.03, p=.08]. Adults exhibitedsignificantly more activation in the right IOG (.51%) than the leftIOG (.46%) [F(1,9)=13.95, p=.005], but no other effects orinteractions were significant for this group (F<1). Finally, when wecompared each group with one another the only significant findingwas that children (.56%) [F(1,27)=12.7, p=.002] and teens (.51%)[F(1,27)=8.13, p=.008] exhibited higher activation than adultsonly in the left IOG.

Medial fusiform gyrus (MFG) ROIIn an initial ANOVA Age effects were significant in this region

[F(1,27)=7.30, p=.003], in that percent signal was significantlyhigher in children (.53%) than in adults (.18%) [F(1,27)=11.79,

p=.002] and teens (.21%) [F(1,27)=9.46, p=.005], who did notdiffer from each other (F<1). Although children showed a trendfor more activation with inverted faces, and adults showed a trendfor more activation with upright faces, the interaction ofAge×Orientation did not reach significance [F(2,27)=2.20,p=.13] (Fig. 7). Different from the other ROIs, the factor ofHemisphere did not interact with other factors in MFG. Finally,separate ANOVAs by Orientation revealed a significant Age effectonly for inverted faces [F(2,27)=6.34, p<.006] in that for thesetrials the percent signal in MFG was significantly higher inchildren (.53%) than in adults (.18%) [F(1,27)=10.02, p=.004]and teens (.21%) [F(1,27)=7.58, p=.01], who did not differ fromeach other (F<1).


Comparison between LFG and MFG levels of activationFinally, wewished to examine whether the present fMRI data may

show a developmental shift in neural engagement for face processingfrom medial fusiform regions to face-selective lateral fusiformregions. We performed an ANOVAwith Age as the between-subjectsfactor and ROI (MFG, LFG), Hemisphere and Orientation asthe within-subjects factors. A significant four-way interaction[F(2,27)=5.12, p<.01] revealed that for upright faces, in the RHnone of the groups showed a difference between levels of activation inLFG andMFG. The age groups did not differ in right LFG activation(F values<1), but children’s levels of activation in the rightMFGweremarginally higher than those of the other two groups [F(1,27)=3.18,p=.08]. For upright faces, in the LH only children showed higherpercent signal change for MFG than LFG [F(1,27)=37.8, p=.0001].

Fig. 7. Results for MFG ROI analyses. We present our results collapsedacross Hemisphere since we did not obtain significant hemisphericdifferences. These results show the mean percent signal change obtainedfor children (N=11), teens (N=9), and adults (N=10), for upright andinverted face Age was significant [F(1,27)=7.30, p=.003], indicating thatchildren activated significantly more than adults [F(1,27)=11.79, p=.002]and teens [F(1,27)=9.46, p=.005]. Error bars represent the SEM.

Fig. 6. ROI analyses results for the right and left inferior occipital gyrus(IOG), showing the mean percent signal change obtained from thefunctionally defined IOG ROI in children (N=11), teens (N=9), and adults(N=10) for the upright and inverted faces. (a) Right IOG. No significanteffects of orientation were found. (b) Left IOG. A main effect of Age wassignificant [F(2,27)= .004], in that children and teens activated significantlymore (p<.05) than adults for both orientations. Error bars in panels a, brepresent the SEM.

Finally,with inverted faces, in both hemispheres only children showedhigher percent signal for MFG than LFG (in RH: [F(1,27)=4.71,p=.04]; in LH [F(1,27)=22.23, p=.0007]), while the other twogroups did not show this difference (F values<1). In summary, robustage differences were found only for inverted faces; only childrenengagedmore their medial fusiform regions than their lateral fusiformregions in both hemispheres with inverted faces.

Correlation between Age and Neural FIE

We performed Pearson correlation analyses (2-tailed) to furtherexamine the relationship between Age and the upright faceprocessing advantage in each of our ROIs. Confirming our resultsfrom the ROI analyses, only for the right LFG there was asignificant positive correlation between neural FIE and Age(r=.60, p=.001). This correlation was not significant for the leftLFG (r=− .10, p=.62), the left IOG (r=− .11, p=.56), the rightIOG (r=.14, p=.46), and the left STS (r=.09, p=.45). Moreover,we found a correlation trend for the right STS (r=.32, p=.09),which did show a significant increase in preference for uprightorientation with age in the ROI analyses, and for the MFG (LH andRH combined; r=.33, p=.08), which had also shown a similartrend in the ROI analyses, though not significant.

Correlation between Behavioral FIE and Neural FIE

Finally, we carried out correlation analyses across all ourparticipants to examine the relationship between the behavioral FIE(inverted face RT−upright face RT) and the neural FIE (% signalfor upright faces−% signal for inverted faces). We did this for eachof our ROIs to identify which one (s) may be the closest neuralcorrelate(s) of the behavioral FIE. We found that only for the rightLFG (r=.39, p=.04) there was a significant positive correlationbetween the behavioral and the neural FIE patterns. That is,participants who exhibited faster RT for upright faces than for


inverted faces also exhibited higher activation for upright than forinverted faces in the right LFG, and vice versa. This was trueacross all ages, but as we reported above while the majority ofadults exhibited a preference for the upright orientation only 33%of teens and 10% of children did so. Fig. 8 shows a scatter plot onthe correlation between the neural FIE and behavioral FIE for theright LFG in each age group.

No significant correlations were found for the left LFG (p=.47),the left STS (p=.83), the right IOG (p=.55), the left IOG (p=.47),and for the MFG (LH and RH combined; p=.48), which confirmsthat these regions provide a level of analysis that is not face-specific(Haxby et al., 1999; Ishai et al., 1999). Therefore, in accord with thecurrent ROI findings, and similar to a study with adults by Yovel andKanwisher (2005) the correlation analyses indicate that the rightLFG may be the closest neural correlate of the behavioral FIE.Interestingly, we found a marginally significant correlation alsobetween the neural FIE and the behavioral FIE in the right STS(r=.36, p=.053). Moreover, the right LFG and the right STS FIEpatterns correlated significantly with each other (r=.51, p=.005),but not with any other ROI, which confirms that these two regionsinteract closely during face processing and exhibit similar neural FIEpatterns. Therefore the right STS may be a secondary correlate forthe behavioral FIE when, like in our study, the task taps specificallyonto STS functions by requiring processing of facial expressions(Puce et al., 1998; Winston et al., 2004).

Lastly, we performed separate correlations by Age, to obtainsome insight on whether the neural correlates of the behavioral FIEmay change with age. Although our results were not significant,(possibly due to our small samples) they were suggestive of adevelopmental trend, such that, in adults there was a marginalcorrelation between the behavioral FIE and the neural FIE in rightLFG (r=.56, p=.08), whereas teens did not show any significantresults (p>.05), and children showed a marginal correlation only inright MFG (r=.55, p=.09) but not in right LFG (p=.15) (see Fig. 8).

Discussion

The main goal of the present study was to establish the neuralcorrelates of the behavioral FIE from childhood to adulthood. Our

Fig. 8. This scatterplot shows the correlation between the neural FIE in rightLFG (% change for upright faces−% change for inverted faces) and thebehavioral FIE (RT for inverted faces−RT for upright faces) in each agegroup. Note that positive numbers in neural and behavioral FIE indicate apreference for upright faces, whereas negative numbers indicate a preferencefor inverted faces.

findings provide one of the first pieces of evidence that links thedevelopment of the neural bases of the behavioral FIE to specificface-selective regions in the right hemisphere. Moreover, theyshow evidence of progressive tuning of these regions to the uprightorientation with development.

Starting with the behavioral FIE results, performance for allgroups showed accuracies well above 90%. While previousdevelopmental studies provided contrasting results in terms ofwhether FIE increases with age (Mondloch et al., 2003) or not(Young and Bion, 1980; Pascalis et al., 2001), the present RTresults are suggestive of developmental changes in FIE profiles,because it is not until adulthood that we see a consistent cost in RTwith face inversion. Moreover, similar to other developmentalstudies (Chun and Thomson, 1995; Flin, 1985; Taylor et al., 2004)even our teens did not exhibit an adult-like FIE, which indicatesthat changes in face processing strategies continue well beyond theage of 10, as was initially proposed (Carey, 1992; Carey andDiamond, 1977).

With regard to our fMRI results, we found developmentaldifferences in the neural bases of the FIE, and these differenceswere specifically for the right LFG, which has been found to bespecialized for whole-based face processing (an indicator of faceprocessing expertise), but not the left LFG, which seems to bemore involved in part-based face processing (Rossion et al., 2000).In general, while overall children showed higher profiles offunctional activation than teens and adults (see also Passarotti etal., 2003; Gathers et al., 2004), significant age differences in ac-tivation were found only for inverted faces. Our analyses revealedthat adults exhibited the expected pattern of neural FIE (i.e., apreference for the upright orientation), with higher percent signalchange for upright than for inverted faces. Also teens exhibitedhigher activation for upright than for inverted faces in the rightLFG, but not significantly so, which is indicative of prolongedneural and functional development of this face-selective regionwell beyond childhood. Importantly for our study, youngerchildren exhibited a different neural FIE pattern than adults andteens in the right LFG. In fact, they showed evidence of a“reversed” neural FIE, in that their percent signal change in rightLFG was actually significantly higher for inverted than for uprightfaces. This dramatic difference was somewhat unexpected, giventhat children did not exhibit significant orientation effects in thebehavioral performance. But an inspection of the individual RTdata revealed that also for the behavioral performance childrenexhibited a trend for an inverted orientation preference (i.e., fasterRT for inverted than for upright faces), although not significantlyso. It is noteworthy that a number of developmental studies(Schlagger et al., 2002; Passarotti et al., 2003) have also foundsignificant age differences in neural activation in the absence ofsignificant behavioral differences. This suggests that developingbrain systems are somewhat immature or inefficient in children,and may require more functional activity or a different profile offunctional activity compared to adults, to reach similar levels ofbehavioral performance (Nelson et al., 2003).

We will now briefly report FIE contributions of additional areasin the distributed face processing system (Haxby et al., 2000). Ofthese regions, only the face-selective, right STS showed adevelopmental shift from a trend for higher activation with theinverted orientation in children to a significant upright facepreference in adults. Children exhibited more bilateral activationand relied more than adults on the left STS, which suggests thatthey were relying on processing strategies that are not face-specific


(Rossion et al., 2000) more than adults. Furthermore, in accordwith previous findings (Leube et al., 2003; Yovel and Kanwisher,2005), we did not find an orientation effect in IOG at any age,confirming that this region does not engage in face-specificprocesses (Ishai et al., 1999) and therefore does not undergo robustdevelopmental FIE changes. Similar to what we found for theLFG, the MFG data revealed less robust, non-significant trends forhigher activation with inverted faces in children and teens, andhigher activation for upright faces in adults. Lastly, while forupright faces none of the age groups exhibited differences betweenright MFG and LFG levels of activity, with inverted faces only inchildren MFG activation was higher than that in LFG, suggestingthat with inverted faces children may rely more on this region,which does not use face-specific processing strategies (Ishai et al.,1999).

Turning to our main developmental FIE finding, one possibleexplanation for the higher right LFG activity with inverted faces inchildren could be that it is caused by a general increase in neuraleffort in order to extract relevant information from faces that are inan unusual and unfamiliar orientation. That is, since children arestill developing their face processing skills (Taylor et al., 2004;Baenninger, 1994) they may not be able to adjust their strategiesefficiently depending on face orientation. If this were true, theneural effort resulting from inverted face processing would be mostlikely associated with higher RT. On the contrary, this is not thecase in the current data, because most children were actuallysomewhat faster with inverted than with upright faces, while stillexhibiting high accuracies for both orientations. When weexamined the relation between behavioral and neural FIE in theindividual data for the right LFG we found two FIE profiles thatwere represented either mostly by adults or mostly by children.Specifically, the majority of adults (60%) exhibited the “typicalFIE profile”, with a preference for the upright orientation (i.e.,faster RT and higher activation for upright faces), while only 10%of children and 33% of teens did so. Most children (60%) actuallyexhibited a “reverse FIE profile” (i.e., faster RT and higheractivation for inverted faces), while no adults and only 22% of theteens did so. Clearly then, the “general effort” explanation for thechildren data does not hold, because the majority of children didnot exhibit the “effort profile”, rather they exhibited a relativepreference for inverted faces in RT and a significant preference forinverted faces in the fMRI data.

Further research with larger samples and more differentiatedage groups will be necessary to gain a deeper understanding ofthese intriguing developmental results. At this point we can onlyspeculate on the mechanisms that underlie this relative preferencefor the inverted face orientation in children, and the neural andcognitive changes that lead to adult expertise in face processing.Some studies suggest that developmental changes in holistic andconfigural processing (Baenninger, 1994; Taylor et al., 2004;Gathers et al., 2004, Aylward et al., 2005). Whatever these changesare, our results provide some clues on at least one possiblemechanism that may lead to the adult expertise, that is aprogressive selectivity of face-selective regions to the uprightorientation.

While it is clear that in adults a behavioral preference forupright faces is associated with face processing expertise(Valentine, 1988), there is growing neurophysiological evidencethat also the neural bases of face processing favor the upright faceorientation, at least in adults. Yovel and Kanwisher (2005) foundsharper FFA tuning to upright than to inverted faces by using an

fMRI-adaptation paradigm with adults. In addition, a recent studyby Tsao et al. (2004), that combined fMRI and single-unitrecordings, identified for the first time a whole cortical region inthe infero-temporal cortex of the macaque brain consisting entirelyof face-selective cells, which also showed an inversion effect.Moreover, both neuropsychological studies with brain-damagedpatients (Moscovitch et al., 1997; Farah et al., 1995) and a recentbehavioral study that examined after-effects for upright andinverted face pictures (Rhodes et al., 2004), suggest that differentmechanisms may be responsible for processing of upright andinverted faces. We still do not know whether within the middlefusiform gyrus there is only one population of neurons thatresponds preferentially to upright faces, or whether there aredifferent populations that respond preferentially either to theupright or the inverted orientation (see also Yovel and Kanwisher,2005 for a discussion of this issue). Based on the current results,we can only speculate that if there is one neural population in rightinfero-temporal regions that is selective to faces in the uprightorientation, this level of selectivity may progressively increaseduring development. A progressive shift in orientation preferencemay be one of the mechanisms that enable acquisition of faceprocessing expertise with age. Alternatively, if there are indeeddistinct neural populations that prefer either one orientation or theother, or have no preference, we could hypothesize that youngerchildren may engage relatively more the neural populations thatrely on non-face specific processing levels (which are moreefficient for inverted than for upright faces). These neuralpopulations may also interact more with medial and posteriorfusiform regions, with which they may share similar processingstrategies (i.e., featural or part-based processing). With age andprogressive specialization the neural circuitry that favors theupright orientation may develop more efficient face-selectiveprocesses, and eventually become the elected circuitry for expertface processing.

Another important goal of the present study was to identifywhich region is the closest neural correlate of the behavioral FIE(hence of face processing expertise). We were able to identify theright LFG as the closest neural correlate, by showing a significantpositive correlation between the behavioral FIE and the neural FIEonly in this ROI. Yovel and Kanwisher (2005) found similar resultsfor adults in the FFA, although they did not find hemisphericdifferences. Our paradigm was able to further segregate the neuralbases of the behavioral FIE to the right hemisphere, which isspecialized for configural face processing (Haxby et al., 1999;Kanwisher et al., 1997) or holistic processing (Yovel andKanwisher, 2004). In addition, our results indicate that althoughthe typical FIE profile was present much more in adults than inteens and children, across ages those individuals who exhibited aRT advantage for upright faces also exhibited a preference forupright orientation in the right LFG activity, and vice versa. Thisfinding indicates that across development, there is a link between apreference for upright orientation and efficiency of face processing.We also found that the neural FIE in STS presented a marginallysignificant correlation with the behavioral FIE, and also correlatedwith the FIE in the right LFG, which confirms that these two-faceselective regions in the right hemisphere interact closely duringface processing. In addition, this finding suggests that the STS maybe a secondary correlate of the behavioral FIE if the experimentaltask taps specifically onto STS function such as processing offacial expressions (Puce et al., 1998). In fact, Yovel and Kanwisher(2005) did not find a significant correlation with the behavioral FIE


for STS, because their face identification task did not relyspecifically on STS processing (Puce et al., 1998; Winston et al.,2004).

Having identified the correlates of the behavioral FIE, the nextcrucial developmental question is whether they may change withage. In fact, previous fMRI studies (Gathers et al., 2004; Passarottiet al., 2003) found that younger children engaged not only theLFG but also other medial and posterior fusiform regions toprocess faces. Although we cannot draw any strong conclusionsfrom our marginally significant results, our findings hint at adevelopmental change of the direct neural correlate for the beha-vioral FIE, in that while adults exhibited a marginally significantcorrelation between behavioral FIE and right LFG, teens showedno significant results, and in children it was actually the rightMFG, but not the right LFG, that showed a marginally significantcorrelation. This is an interesting result, since our ROI analysesdid find that for upright faces children activated their right MFGmore than the other two groups (although not significantly so), andfor inverted faces they activated more their right MFG than theright LFG. While larger samples are needed to further clarify thesetrends, the present findings suggest that different from the adultprofile, the child “behavioral preference” for inverted orientationmay be associated with relatively more engagement of the rightMFG, a region that employs non-face-specific processingstrategies (Ishai et al., 1999).

Turning now our attention to a more general issue, one may askwhether we can generalize our developmental findings to faceprocessing that does not involve emotions. We can reasonablyexclude that our developmental FIE results were driven by theemotional content of our face stimuli, or by attentional effects dueto the emotional content, for the following reasons. First, there isevidence that the right LFG response to faces is not affected by thetype of face processing employed, as long as the stimuli employedare perceived as faces (Kanwisher et al., 1997). Second, althoughsome attentional modulation of the FFA has been found whenattentional shifts from one attribute of a composite object toanother were required (O’Craven et al., 1999), other studiesinvolving a face emotion processing paradigm found FIE patternsthat were comparable to those for face-identity tasks that did nothave emotional information and therefore should not have anyattentional confound (Calder et al., 2000; McKelvie, 1995).Moreover, the current adult and teen fMRI FIE profiles closelyreplicate findings from other adult studies that used a face-identitytask instead of our face-emotion task (Yovel and Kanwisher, 2004;Haxby et al., 1999; Kanwisher et al., 1998). Even our child data forupright faces are very similar to findings from a face-matching taskthat did not involve facial emotions (Passarotti et al., 2003; Gatherset al., 2004). Third, a recent fMRI-adaptation study (Winston et al.,2004) found a neuro-anatomical dissociation for processing of faceidentity in LFG, and face expressions in STS; therefore our FIEresults in LFG should not be affected by facial emotions.Moreover, any general attentional effects in our data would bepresent both for upright and inverted face trials, and therefore whencomparing functional activation for upright and inverted faces anyattentional effect would be canceled out. Similarly, when wecompared our FIE patterns for emotional face trials (which have anemotional content) and neutral face trials (with no emotionalcontent) we did not find any significant differences (see Footnote1).

It is important to note that while the present study providesevidence on the development of the neural correlates of the

behavioral FIE, it also presents some limitations and leaves openquestions that call for more research. For instance, this studycannot tell us whether the developmental inversion effects that wefound in right LFG and STS are specific to faces, or may reflectmore general mechanisms, in which case our FIE results wouldextend to other non-face stimuli in children. Moreover, it will beimportant that future studies clarify the changes in processingstrategies (e.g., improvements in configural and holistic proces-sing) that contribute to the progressive neural tuning to uprightorientation with age. In the meantime, useful insights come from adevelopmental fMRI study that indeed contrasted neural activityfor upright faces and objects in children, and found that while 5 to8 year olds exhibited selectivity for upright faces versus objectsoutside of the fusiform gyrus, by age 9–11 selective fusiformactivation for faces versus objects emerged (Gathers et al., 2004).Similarly, Aylward et al. (2005) found that the selective fusiformengagement for faces versus houses increased up to adolescence.These results suggest that the right fusiform gyrus undergoesprolonged development before it becomes more engaged forupright faces than objects, and that the emergence of thispreference is possibly associated with improvements in face-specific processes (Gathers et al., 2004; Aylward et al., 2005;Taylor et al., 2004).

Finally, these important changes in the brain circuitry for faceprocessing are most likely the result of an interaction betweenneural maturation and experience. Studies with infants indicatevery precocious preference for faces over objects (Morton andJohnson, 1991) and very early engagement of right hemisphereregions for face processing (Tzourio-Mazoyer et al., 2002). At thesame time, specific early visual input during critical periods ofdevelopment is necessary for the right hemisphere to fully developface processing expertise later in life 8. In fact, a developmentalstudy by LeGrand et al. (2003) found that children whose righthemisphere was deprived of any visual input because of congenitalunilateral cataract, exhibited impairment in face configuralprocessing (but not featural processing) even years after thecataracts were removed. Moreover, maturation, myelination,synapse overproduction and pruning continue until mid-adoles-cence (Luna et al., 2004) and contribute to a progressivelocalization of cognitive functions (Gathers et al., 2004; Passarottiet al., 2003) and improvements in processing speed and efficiency(Mondloch et al., 2003; Taylor et al., 2004). At the same time,these neurophysiological changes are also enabled and guided byexperience (Stiles et al., 2003). An example of fusiform gyrusplasticity to experience and learning is provided by Gauthier’sfindings that in adults the right lateral fusiform gyrus may showincreased sensitivity to non-face stimuli for which an individualhas acquired processing expertise (Gauthier et al., 1999) (but seeMcKone and Kanwisher, 2005 for an alternative explanation ofGauthier’s results). Altogether these findings suggest that devel-opment and fine tuning of the cortical regions that will later enableface processing expertise require an orchestrated interaction ofneural maturation and experience.

Conclusions

The present developmental fMRI study established the func-tional and anatomical organization of the neural FIE in childrenand teenagers. In addition, it identified the right LFG, and to alesser degree the right STS, as the closest neural correlate of thebehavioral FIE, while also providing some initial clues that FIE


correlates may change with age. Finally, in agreement withbehavioral (Baenninger, 1994, Chun and Thomson, 1995) and ERPstudies (Taylor et al., 2001, 2004), our current findings suggest thatthere is a gradual, progressive tuning of face-selective regions inthe right hemisphere to the upright orientation until lateadolescence.

Acknowledgments

We wish to thank the children and families who participated inour study and the Department of Radiology at Michigan StateUniversity for providing the scanning facilities. Many thanks toLauren Harris and Marie Banich for helpful comments on previousdrafts of this paper. Face stimuli were taken from the NimStim FaceStimulus Set. Development of the MacBrain Face stimulus set wasoverseen by Nim Tottenham and supported by the JD and CTMacArthur Foundation Research Network on Early Experienceand Brain Development.

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