پردازش جامع اختلال در پروزوپاگنوزیا مادرزادی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|37904||2011||12 صفحه PDF||سفارش دهید||11714 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Neuropsychologia, Volume 49, Issue 9, July 2011, Pages 2541–2552
Abstract It has long been argued that face processing requires disproportionate reliance on holistic or configural processing, relative to that required for non-face object recognition, and that a disruption of such holistic processing may be causally implicated in prosopagnosia. Previously, we demonstrated that individuals with congenital prosopagnosia (CP) did not show the normal face inversion effect (better performance for upright compared to inverted faces) and evinced a local (rather than the normal global) bias in a compound letter global/local (GL) task, supporting the claim of disrupted holistic processing in prosopagnosia. Here, we investigate further the nature of holistic processing impairments in CP, first by confirming, in a large sample of CP individuals, the absence of the normal face inversion effect and the presence of the local bias on the GL task, and, second, by employing the composite face paradigm, often regarded as the gold standard for measuring holistic face processing. In this last task, we show that, in contrast with controls, the CP group perform equivalently with aligned and misaligned faces and was impervious to (the normal) interference from the task-irrelevant bottom part of faces. Interestingly, the extent of the local bias evident in the composite task is correlated with the abnormality of performance on diagnostic face processing tasks. Furthermore, there is a significant correlation between the magnitude of the local bias in the GL and performance on the composite task. These results provide further evidence for impaired holistic processing in CP and, moreover, corroborate the critical role of this type of processing for intact face recognition.
1. Introduction Face recognition presents one of the most demanding perceptual challenges to the visual system. Not only is a multiplicity of dimensions such as emotional expression and gaze direction conveyed via the face, but the individual identity of each face must be rapidly and accurately established. Despite this apparent complexity, humans are expert at face recognition and the robustness of this ability is further attested to by the fact that recognition remains remarkably accurate even under relatively poor lighting conditions, under changes in view of the face, and with changes in the age and appearance of the face (for example, with changes of facial hair). Surprisingly, however, there are a number of conditions under which normal face recognition is adversely impacted. Common to many, if not all, of these conditions is that there is a disruption of the configural or holistic processing of the face. Consequently, the observer resorts to relying on the featural information rather than on the configural information, in which the relations among the features of the face rather than just the features themselves, are represented (Maurer et al., 2002 and Tanaka and Farah, 1993). 1.1. Configural processing in face recognition Given that all faces share the same local internal components (eyes, nose and mouth), the claim is that deriving a rapid and accurate representation of the face requires disproportionate reliance on the configuration of the features relative to that required for non-face object recognition (Maurer et al., 2002). Any manipulation that disrupts the configuration of the face, then, would be predicted to affect face processing disproportionately. Evidence to support this prediction comes from a number of experimental paradigms. For example, it is now well-known that face processing is adversely affected by changes in orientation: when the face is inverted, recognition is adversely affected to a greater degree, relative to upright, than is true for other classes of objects (Farah et al., 1995, Freire et al., 2000, Leder and Bruce, 1998, Malcolm et al., 2004 and Searcy and Bartlett, 1996). It is also the case that face perception benefits from the presence of the entire face, compared with the presence of just some components of the face and this whole vs. part advantage holds to a greater degree for faces than for other objects (Gauthier and Tarr, 2002 and Tanaka and Farah, 1993). Interestingly, the derivation of the configuration of the face is apparently so automatic that even when instructed to attend selectively to only some parts of a face, normal observers cannot help but be sensitive to the entire face (Amishav & Kimchi, 2010). Data to support this claim comes from a well-established paradigm using composite faces (Boutet et al., 2002, Farah et al., 1998, Gauthier et al., 2003, Le Grand et al., 2004 and Young et al., 1987). In the version of this paradigm used here (Fig. 1), individuals view two consecutively presented composite faces, and make same/different decisions based only on the top part of the face (Le Grand et al., 2004). The bottom part of the face is to be ignored. The two faces are created such that the two top parts could either be the same or different while the bottom part is always different. Additionally, the top and bottom parts of a single face can be either aligned or misaligned. Due to the holistic nature of face processing, even when instructed to judge only the top halves of aligned faces and to ignore the bottom parts, normal observers exhibit significant interference induced by the presence of the task-irrelevant bottom half of the composite face (which is always different). Thus, erroneously, they tend to judge two faces with identical tops as ‘different’ rather than ‘same’ (i.e. make false alarms). This interference from the task-irrelevant bottom of the face is substantially reduced when configural information is disrupted, as in the misaligned condition (Fig. 1, bottom row) (Young et al., 1987) and also when the faces are inverted (Hole, 1994 and Hole et al., 1999). Composite experiment: examples of the stimuli used in the experiment showing the ... Fig. 1. Composite experiment: examples of the stimuli used in the experiment showing the aligned (top row) and misaligned (bottom row) conditions. Figure options 1.2. Disrupted configural processing in prosopagnosia If it is indeed the case that individuals with prosopagnosia are impaired at configural processing, one direct prediction is that their judgments about the top parts of faces will be impervious to the (different) bottom part of faces, even in the especially taxing aligned condition. That is, they will not process the task-irrelevant lower part of the face automatically. Considerable empirical evidence supports the notion that a breakdown in configural processing is related to the impairment in face processing (for review see Barton, 2009 and Rivest et al., 2009). For example, individuals with prosopagnosia were substantially impaired, relative to matched controls, when deciding which of 3 faces was ‘odd’ when the interocular distance or the distance between the nose and mouth were altered (Barton, Press, Keenan, & O’Connor, 2002). Based on these findings, the authors argued that the need to represent the spatial relations between the features (and they note that the distance between the eyes is especially important) is integral to the ability to process faces. Moreover, PS, a well-characterized patient with acquired prosopagnosia but no deficits in other perceptual domains, exhibited abnormal holistic processing on several behavioral tests, including the composite face paradigm (Ramon, Busigny, & Rossion, 2010). This disruption in configural processing skills appears to be true not only of individuals with acquired prosopagnosia (Barton, 2009) but also of individuals with congenital prosopagnosia (CP) (Lobmaier, Bolte, Mast, & Dobel, 2010). CP is an apparently lifelong deficit in face processing that occurs along with intact sensory visual abilities, normal intelligence and adequate opportunity to acquire face recognition skills (Behrmann & Avidan, 2005). Although there is some evidence that CP is related to a difficulty in deriving the configural or holistic relations between the features of a face, this claim is still controversial. On the one hand, CP individuals, similar to individuals with AP (Busigny & Rossion, 2010), are minimally (if at all) affected by face inversion and a few even show better performance for inverted than upright faces (the “inversion” superiority effect) but this latter effect is not very common in either forms of prosopagnosia (Behrmann et al., 2005, Busigny and Rossion, 2010 and Farah et al., 1995) (and see also Table 2 in the present study). Additionally, these same individuals show a bias for local processing of elemental features, even for non-face stimuli. Thus, shown hierarchical, compound Navon stimuli, these individuals are faster at local than global letter identification and, when the letter identities are inconsistent at the two levels, show no interference from global to local letter identification, a pattern markedly discrepant from that of normal observers (Behrmann et al., 2005, Kimchi, 1992 and Navon, 2003) (and see also Table 2, Fig. 2 and Supplementary Fig. 1 in the present study). Finally, along similar lines, Palermo et al. (2011) recently showed reduced holistic processing (i.e. reduced interference indicating atypical configural processing) in a group of 12 individuals with CP on the composite task. Supporting evidence for impaired holistic/configural processing in CP. (a) ... Fig. 2. Supporting evidence for impaired holistic/configural processing in CP. (a) Stimuli used in the compound letter global/local task. (b) Results obtained for the entire group of control participants, age-matched controls and CP participants on the global/local task showing that CPs do not exhibit the expected global advantage and, instead, evince a local advantage and local-to-global interference. Asterisks denote significance level *p < 0.05; **p < 0.005; ***p < 0.0005. Error bars indicate ± standard error of the mean across participants. Figure options This apparent trend towards featural or elemental processing may not be ubiquitous, however. For example, Duchaine (2000) tested a congenital (or ‘developmental’) prosopagnosic on three tests from the Kit of Factor-Referenced Cognitive Tests and showed that this individual performed normally on these gestalt completion tasks. More pertinent perhaps and contrary to our findings, Duchaine, Yovel, and Nakayama (2007) tested a group of 14 developmental prosopagnosia participants on the global/local task and did not find a local processing bias in these individuals. Additionally, Le Grand et al. (2006) employed the composite face task and found abnormal performance in only one out of 8 CP participants. We return to the discrepancies among these studies, as well as others, and offer a possible, albeit tentative, resolution in Section 4. To explore further whether CP individuals do indeed evince an impairment in holistic processing, here, we conduct 3 experiments, all of which are designed to tap configural processing, in a relatively large group of 14 well-characterized CP individuals. We expect to replicate the lack of an inversion effect and the local bias in the global/local task, both of which we reported previously in smaller groups of participants, and, furthermore, predict that the very same individuals should be less affected by the incongruency effects afforded by the discrepant bottom parts of aligned faces in the composite task. In other words, and counterintuitively, in this last task, CP individuals should perform better than controls and produce fewer false alarms. Finally, a correlation between performance on these tasks would further support an account of abnormal holistic processing in CP. Before reporting our empirical findings, we note that the terms ‘holistic’ and ‘configural’ are used interchangeably in the literature and, indeed, there continues to be heated debate on the differences, if any, that are implied by these two terms (Gauthier & Tarr, 2002). In the context of the present study, we use these terms operationally to refer to the obligatory integrated coding of all the face elements, as has been suggested by others (Farah et al., 1998 and Ramon et al., 2010). Others use the term configural/spacing processing to refer to the coding of the spatial relations and distances between facial (or even non-facial) features, and to the perception of manipulations of second order relations such as the distance between local features, such as the eyes (Barton, 2009, Maurer et al., 2002 and Yovel and Duchaine, 2006). Since the experimental paradigms used here are not diagnostic of the ability to process the spatial relations between facial elements, our results cannot speak directly to the debate regarding the role of holistic vs. spatial relation processing in face perception. Rather, our focus is on characterizing holistic processing in CP individuals and examining the robustness of this finding using three different but converging paradigms.
نتیجه گیری انگلیسی
3. Results 3.1. Diagnostic tests Table 1 and Table 2 display the raw performance and standardized z-scores, as calculated based on performance of control groups, for the diagnostic tasks for all CP participants. 3.1.1. Famous faces Twelve CP individuals were clearly impaired on the famous faces questionnaire. The remaining 2 participants (MT, TZ) still exhibited some mild difficulty with face recognition as evident by their relatively low performance and borderline z-scores. 3.1.2. CFMT, CFPT Of the 12 CP participants who completed the CFMT task, 9 were clearly impaired, two (SI, SW) exhibited low performance and only one participant (BT) was clearly in the normal range. As for the CFPT, of the 11 participants who completed this task, three were clearly impaired, two exhibited relatively low performance and the rest of the participants were in the normal range (see also Supplementary Table 1 for results on the inverted CFPT). 3.1.3. Upright/inverted face discrimination We have previously shown that CP individuals are slower than controls on such a novel face discrimination task and that they do not show the expected decrement in performance for inverted faces (the reader is referred to Behrmann et al., 2005 for detailed analysis and discussion of these original findings). Critically, the results reported in the present study replicate and extend these findings with 6 additional CP participants whose performance on this task has not been reported previously (see Table 2 for details). We start by discussing the results in terms of accuracy and then move to the RT analyses. As is evident in Table 2, accuracy on this task is generally high, likely as a result of the unlimited exposure. Accuracy for upright and inverted faces of all CP participants except for two (IM, BT) was in the normal range. Unsurprisingly, an ANOVA of these data, comparing the performance of the CP group and matched subgroup as the between-subjects factor and orientation (upright, inverted) as the within-subjects factor, revealed a significant main effect of orientation (F(1, 26) = 5.35, p < 0.03) but no effect of group (F < 1) or group × orientation interaction (F < 1). When directly comparing the accuracy for upright and inverted faces in each group, we find a trend for an inversion effect (reduced performance for inverted compared to upright faces) in the matched controls but not in the CP group (planned comparisons for upright vs. inverted faces, controls p = 0.07, CP p = 0.18). Finally, to quantify the extent of the well-documented inversion effect, we calculated an inversion index (separately for accuracy and RT) as follows: View the MathML sourceInversion index=performance(inverted−upright)performance(inverted+upright) Turn MathJax on When examining this index for accuracy, one CP (BT) is outside the normal range due to a dramatic decrease in accuracy for inverted faces (greater reduction than controls). Thus, to summarize, while controls here show a trend towards an inversion effect in terms of accuracy, CPs do not show a similar trend, that is they show equal performance for both upright and inverted faces. As suggested above, this pattern of generally high accuracy for both CP and controls for both orientations likely emerges from the unlimited exposure duration and under such conditions, RT is considered the more telling dependent variable. We first describe the RT results on the upright face discrimination condition alone. Ten of the 14 CPs fell outside the normal range with significantly longer RT for upright faces. One participant exhibited relatively slower performance compared to controls (JT) and one participant, BT, exhibited normal performance in terms of RT but was substantially impaired in accuracy, thus exhibiting a clear speed-accuracy trade-off (notably no other participant showed such a trade-off). Three additional participants (TD, BT, SI) exhibited normal RT for upright faces, but as will be evident below, these participants showed a trend towards faster RT for inverted compared to upright faces and hence exhibited overall abnormal performance in this task. Thus, most, if not all, CP individuals exhibit difficulty not only with recognition of famous faces but also with perceptual tasks involving novel faces both here and on the CFMT (for related results see (Behrmann et al., 2005, Bowles et al., 2009 and Dobel et al., 2007). Importantly, when directly comparing CP to their matched control group (between subjects) with orientation as the within-subjects factor, CP participants showed no RT difference between inverted and upright faces, while controls exhibited significantly faster RT for upright over inverted faces (significant group × orientation interaction F(1,26) = 5.59, p < 0.026, planned comparison for upright vs. inverted faces, controls: p < 0.007; CP: p = 0.63). Interestingly, a t-test comparing the CP and matched control data on inverted faces reveals no group difference (p = 0.4) but controls were significantly faster than CP on upright faces. Thus, at the group level, CPs do not show the typical advantage for upright compared to inverted faces in terms of RT. To explore the inversion effect (or lack thereof) at an individual level, we calculated an index for each participant, as we did for accuracy above. Interestingly, 6 CPs exhibited decreased RT for inverted compared to upright faces, as evident by their inversion index (5 who are more than 1 SD away from controls and 1 who is more than 3 SD away from controls). Thus, some CP individuals show evidence for inversion superiority in terms of RT. The lack of an inversion effect at the group level and the tendency towards inversion superiority exhibited by some CP individuals, provide further evidence for the disrupted holistic perception in CP. These results in themselves replicate our previous report of this finding and set the stage for the detailed discussion regarding holistic processing as directly tested by the two experimental tasks below. 3.2. Experimental tasks 3.2.1. Global/local task Fig. 2b shows the data from the hierarchical global/local letter experiment for the large control group (n = 38), for the subgroup of age-matched controls (n = 13) and for the 13 CP participants (one CP, IT, did not complete this task). We first describe the performance of our control groups (whole group and age-matched subgroup), to confirm that we have replicated the standard findings, i.e. global advantage and global-to-local interference, and then we compare the CP group with the matched controls. 18.104.22.168. Control groups The results for the large, as well as matched control groups are presented in Fig. 2. A two-way ANOVA of consistency (consistent, inconsistent) × task (global, local) for the large control group (n = 38) revealed a significant consistency × task interaction (F(1,37 = 8.3), p < 0.007), main effect of consistency (F(1,37) = 28.6, p < 0.000005) and a trend towards main effect of task (F(1,37) = 3.3, p = 0.08) with RTs for local slower than for global trials. Similarly, for the matched controls (n = 13), there is a two-way interaction (F(1,12 = 7.9), p < 0.02), as well as main effects of task (F(1,12 = 8), p < 0.015) and consistency (F(1,12 = 18.8), p < 0.001). Thus, both control groups show the same pattern with performance faster on the global than local trials and faster on the consistent than the inconsistent condition. There is also, however, disproportionate slowing on local inconsistent trials, relative to global inconsistent trials, reflecting the global-to-local interference. 22.214.171.124. CP We first perform a similar analysis on the data from the CP group alone, with task and consistency as within-subject variables (Fig. 2). Note that the performance of the CP group is qualitatively different from that of controls in that they are slower in the global than local task. This is confirmed by a main effect of task (F(1,12 = 15.13), p < 0.002). Similarly to controls, CP also exhibited a main effect of consistency (F(1,12 = 8.9), p < 0.01) (for more details see Fig. 2b and see Supplementary Fig. 1 for raw data of individual CPs on this task). There is also an interaction between task and consistency, (F(1,12 = 8.2), p < 0.015), that arises because the global inconsistent condition is even slower than global consistent, relative to the local conditions. To directly evaluate the pattern of CP performance relative to the age-matched controls, we performed an ANOVA that revealed a three-way interaction of group (CP, matched controls) × consistency (consistent, inconsistent) × task (global, local) (F(1,24) = 14.97, p < 0.0007). This analysis also revealed a robust task × group interaction (F(1,24) = 22.88, p < 0.00007) but no consistency × group interaction (F < 1). Interestingly, there was no main effect of group (F(1,24) = 1.34, p = 0.26), indicating that it is not the case that CP were simply slower compared to controls on this task. Rather, both the significant local advantage and the local-to-global interference in the CP group clearly diverge from the matched and large control groups, suggesting that the differences between the CP and control groups are robust and replicable. 126.96.36.199. Global/local index To evaluate the extent of the local bias for the individual CP participants, we calculated a global bias index for each CP and each control [RT(local inconsistent − global inconsistent) − RT(local consistent − global consistent)] and this index along with its normalized z-score relative to the large control group is presented in Table 3. This index is a reflection of the graphic depiction of the results ( Fig. 2 and Supplementary Fig. 1), and shows the magnitude of the inconsistency interference and the global or local bias—a positive index indicates a global bias while a negative index indicates a local bias. The mean index for the controls (aggregated across all controls) is 38 ms, reflecting the global bias while the mean index for the CPs is −92.4 ms. Nine of the 13 CP participants exhibited a bias towards local advantage as evident by their global bias index (see Table 3). Thus, the local bias in this task is at both the group level and the individual subject level in many of the CPs. 3.2.2. Composite face experiment Previous reports using the composite manipulation (Le Grand et al., 2004 and Young et al., 1987) have demonstrated that the signature finding obtained with normal observers is an interference effect, in which there is a reduction in accuracy and/or increase in RT during the ‘same top’ trials of the aligned condition compared to the misaligned condition. For example, Le Grand et al. (2004) reported that control participants have a mean accuracy and RT of 63% and 780 ms for the same/aligned condition relative to the 91% and 616 ms in the same/misaligned condition. This reduced performance in the same/aligned condition compared with the same/misaligned is attributed to the automaticity of the holistic nature of face processing. The question here is whether CP participants also show a reduced interference effect compared to the controls. We first describe the performance of our control groups (whole group and age-matched subgroup), showing that we have replicated the predicted composite effect, and then examine the performance of the CP group in relation to that of control. Following other studies which show that the alignment manipulation is only effective during the “same top” condition (Le Grand et al., 2004, Michel et al., 2006 and Ramon et al., 2010), we focus only on this condition when examining the composite effect and use the performance on these trials as a measure of holistic perception (for raw data of these conditions for each CP see Table 3). 188.8.131.52. Control groups We first establish that our control participants exhibit the well-documented composite effect (Fig. 3). As described in the Methods section, we used a large control group (n = 50) to ensure that we can replicate the standard results and we also sampled a subgroup of 14 age-matched controls to permit direct statistical comparison between CP and controls. Composite experiment: mean accuracy (a) and reaction time (b) on the composite ... Fig. 3. Composite experiment: mean accuracy (a) and reaction time (b) on the composite face experiment for the entire group of control participants, age-matched controls and CP participants on the ‘same top’ trials. Note the lack of interference effect in the CP group in accuracy and in RT, indicating that CPs are not affected by the experimental manipulation. Asterisks denote significance level *p < 0.05; ***p < 0.0005. # indicates p value that is marginally significant (p = 0.06 in top graph and p = 0.07 in the lower graph). Error bars indicate ± standard error of the mean across participants. Figure options A one-way ANOVA comparing aligned and misaligned performance (only ‘same top’ trials) on the data from the large control group revealed, as expected, a significant influence of alignment on both accuracy, (F(1,49) = 46.9, p < 0.0001), and RT, (F(1,49) = 8.9, p < 0.005) (see Fig. 3). Thus, overall, the large control group exhibits the expected interference effect during ‘same top’ trials. The same analyses conducted with the age-matched control group replicated these findings (alignment effect accuracy: (F(1,13) = 17.7, p < 0.001); RT: F(1,13) = 8.9, p < 0.01) and assured us that even the smaller subset of matched controls evince the predicted effects (see Fig. 3). 184.108.40.206. CP A simple effect analysis of accuracy and RT revealed no effect of alignment [accuracy: F(1,13) = 1.4, p = 0.3; RT F < 1], thus dramatically diverging from the results obtained with controls ( Fig. 3). To directly evaluate the pattern of CP performance relative the matched control group, we conducted an ANOVA with group (CP, matched controls) as the between-subject measure, and performance in terms of accuracy or RT on the experimental conditions (‘same top’: misaligned, aligned) as a within-subject repeated measure. The analysis for accuracy revealed a significant group × alignment interaction (F(1,26) = 8.9, p < 0.006), as well as a significant main effect of alignment (F(1,26) = 17.6, p < 0.0003) with no main effect of group (F < 1). Importantly the group × alignment interaction stems from a difference in the ‘same top’ aligned condition (p = 0.06) while no such difference was found in the “same top” misaligned condition (see Fig. 3a). A similar analysis for RT comparing the CPs to the matched control group revealed a trend of alignment × group interaction (F(1,26) = 3.8, p = 0.06) with no main effects for alignment or group (F < 1). Interestingly, as can be seen in Fig. 3, while controls showed a trend towards RT increase for aligned compared to misaligned faces (p = 0.07), no such effect was found for CP. The qualitative similarity of the findings when comparing the results of the CP to either of the control groups ( Fig. 3) is reassuring and attests to the robustness of the dramatic difference in performance obtained in the CPs relative to controls. 220.127.116.11. Interference index To examine further the response pattern of individual CP participants, we calculated an interference index which directly compares the performance, in accuracy or RT (see Table 3), on the misaligned vs. aligned conditions during ‘same top’ trials. The index was calculated separately for each CP and then was transformed to a z-score by normalizing the index by the mean index of the large group. We multiplied the results by 100 to obtain % index: View the MathML sourceInterference index=performance(misaligned−aligned)performance(misaligned+aligned)×100% Turn MathJax on As can be seen in Table 3, at the individual subject level, half of the CPs exhibited an index that was one SD greater than that of controls, either for accuracy (three CPs), RT (three CPs) or both (one CP, BT—see below). It is important to note, however, that, for all CPs except for one (MT), the z-score based on accuracy was negative indicating a trend towards reduced interference compared to controls. Along similar lines, eight CPs had a positive z-score for RT, indicating faster RT for aligned compared to misaligned faces, a pattern that is the reverse from controls. As noted above, CP participant (BT) exhibited a pattern that may reflect a speed-accuracy trade off—with greater accuracy for aligned compared to misaligned faces accompanied by an RT increase for aligned faces that is greater than controls. Thus, while it is not possible to show the reduced interference effect at the individual subject level for every participant, and, in this sense this task is not perfectly sensitive, the group effect described above is robust and informative regarding the nature of face processing in CP (for more discussion of this issue see Section 4). 3.2.3. Correlation between different experimental measures Finally, in order to explore further the nature of the face processing deficit in the CP individuals and to explore possible relationships between the different experimental measures used here, we looked for correlations between performance in the different diagnostic and experimental tasks. Interestingly, this analysis revealed a significant correlation between performance in the composite face task and two of the diagnostic tests. Specifically, we find a negative correlation between the famous faces questionnaire and the RT index of the composite task (r = −0.61, p < 0.021) such that participants with low recognition scores exhibited a more positive index, indicating less interference (more abnormal performance) in the composite task. A significant negative correlation was also found between the same composite index and the CFMT z-scores, such that lower z-scores (more negative) were correlated with a more positive index (r = −0.72, p < 0.009). Importantly, performance on the CFMT and famous face questionnaire was not correlated (p = 0.32) and hence could not mediate the correlations described above. Such correlations between the performance on the composite task and the diagnostic tests are very important as they reveal that the local bias exhibited by CPs in the composite task is related to the way they process both familiar and unfamiliar faces. Moreover, these correlations suggest that even though the reduced composite effect cannot be shown significantly for each CP participant, this measure is still related to the general face processing skills of each CP. Finally, it is very interesting to note that the local bias index calculated from the global/local experiment and the composite interference index based on accuracy level, calculated across the CP participants, are positively correlated (r = 0.52, p = 0.06): a more negative index (increased local processing) in the global/local task is associated with a smaller interference index (less holistic or configural processing) in the composite task. This correlation provides support for the claim that, at least, in these individuals with face processing deficits, there may be an association between the impairments in holistic processing of faces (composite task) and non-face stimuli (global-local task). We note however, that this association may not be universally true; for example in the acquired prosopagnosic patient PS, there was a clear dissociation between impaired performance on the composite task and intact performance in the Navon task ( Busigny & Rossion, 2011), indicating that these two tasks do not necessarily tap onto the same perceptual skills. We consider this further in the Discussion below. None of the other correlation between the tasks and measures was significant (see Supplemenatary Table 2 for details).