Abstract

People make faster familiarity decisions for their own face compared with a familiar other. Lesion studies diverge on whether this self-face prioritization (SFP) effect is associated with functional processes isolated in the left or right hemispheres. To assess both decreases (hypo-) and increases (hyper-) in SFP after brain lesion, we asked patients with chronic deficits to perform familiarity judgments to images of their own face, a familiar other, or unfamiliar faces. Of 30 patients, 7 showed hypo- and 6 showed hyper-self-bias effects, comparing responses with their own faces versus responses with a familiar other. Hyper-self-bias correlated with reduced executive control function and, at a neural level, this was associated with lesions to the left prefrontal and superior temporal cortices. In contrast, reduced self-prioritization was associated with damage to the right inferior temporal structures including the hippocampus and extending to the fusiform gyrus. In addition, lesions affecting fibers crossing the right temporal cortex, potentially disconnecting occipital–temporal from frontal regions, diminished the self-bias effect. The data highlight that self-prioritized face processing is linked to regions in the right hemisphere associated with face recognition memory and it also calls on executive processes in the left hemisphere that normally modulate self-prioritized attention.

Introduction

The ability to distinguish ourselves from other people is a core human capacity found in infants as young as 4 months (Rochat and Striano 2002; see also Keenan et al. 2003). An early ability to recognize our own relative to other faces has been argued to act as an index of the development of the self-concept (Gallup 1977) and self-face recognition may serve as a fundamental building block for developing more complex concepts of the self (e.g., Keenan et al. 2001, 2003; Conway et al. 1996). However, the ability to recognize one owns face is itself insufficient for processing to be prioritized. For example, children with autism can recognize themselves in a mirror (Neuman and Hill 1978; Spiker and Ricks 1984; Uddin et al. 2008; Uddin 2011a), but, unlike typically developing children, autistic children pay less rather than more attention to their own image in a mirror (Reddy et al. 2010). On the other hand, increased self-focus over and above basic self-recognition has been associated with the development of depressive symptoms (Grimm et al. 2009). This suggests that the biased processing to the self goes beyond mere recognition processes and taps into deeper self-related processes that may be essential for our wellbeing. Understanding the functional and neural bases of these self-prioritization processes is important to helping our understand both normal self-related processes and abnormalities in self-face processing, and when they occur. This is the aim of our study, which explores the neural correlates of hyper- and hypo-self-biases following brain lesion.

Prioritized processing of our own faces is found in a variety of face processing tasks (Tong and Nakayama 1999; Keenan et al. 2001; Keyes and Brady 2010; Ma and Han 2010). For instance, familiarity decisions (for one's own and other familiar faces vs. the faces of unfamiliar others) are faster and more accurate for one's own face as opposed to the familiar other (Sugiura et al. 2005, 2006, 2008; Sui and Humphreys 2013). Neuroimaging studies have shown that recognizing our own face is associated with increased activation in an extended bilateral network of brain regions, when compared with the faces of personally close others or famous public faces (Uddin et al. 2005; Northoff et al. 2006; Platek et al. 2006). The most consistent finding is for enhanced self-face responses in the inferior, middle, and medial frontal cortices, the inferior parietal cortices, and the inferior temporal cortices including the fusiform and medial temporal cortices, with increased activity most evident in the right hemisphere (for reviews see Platek et al. 2008; Devue and Bredart 2011, but see Kircher et al. 2001). For example, Ma and Han (2012) examined the brain regions related to self-face processing using a procedure in which self, familiar and other faces were morphed together. Focusing on the fusiform face area (FFA), they reported that there was increased activation in the left or right FFA dependent on whether the analysis emphasized processing of the physical features or the identity of the self relative to other faces.

However, one limitation of neuroimaging studies is their correlative nature, preventing an inference on the necessary role of a region for the cognitive process at hand (Price et al. 1999). Another problem is the low temporal resolution of functional magnetic resonance imaging, which makes it difficult to isolate effects of a variable at any one stage of processing. For example, the image of one's own self may not only strongly evokes perceptual memories, but also processes related to heightened attention, retrieval of semantic/autobiographical memory, self-evaluation processes, and so forth. Event-related potential (ERP) studies show that self-faces modulate multiple levels of processing. Viewing one's own face affects the amplitude of the early N170 (the occipito-temporal face-specific component; Keyes et al. 2010), the anterior N2 (the frontal–central saliency component; Sui et al. 2009; Sui, Hong, et al. 2012), the N250 (the temporal familiarity component; Caharel et al. 2002), and finally, the P3 (the posterior attentional component; Sui et al. 2006; Wang et al. 2011).

These limitations can be overcome by investigating how brain lesions impact on self-recognition. For example, after brain damage, the core tendency for prioritizing self-related stimuli may be disrupted, and this may separate from effects on face recognition more generally (e.g., Gallup et al. 2011). Keenan et al. (2001) reported data from 5 patients undergoing hemispheric-specific anesthesia (the WADA test). Participants were required to remember a picture of their own face morphed with a picture of a celebrity and subsequently, to choose whether they had seen the picture of themselves or the celebrity. Right hemisphere anaesthetization was associated with a bias against memory for self-faces relative to the faces of familiar others. On the other hand, Turk et al. (2002) reported a left-hemisphere bias toward self-discrimination when faces were selectively presented to each hemisphere in a split-brain patient. The above studies and others (Sperry et al. 1979; Breen et al. 2001; Feinberg and Roane 2005; Villarego et al. 2011; Van den Stock et al. 2012) provide contrasting results for the lateralization of the self-bias effects. However, it is difficult to draw clear conclusions due to the relatively small sample sizes of patients tested and the differences in methodologies across studies. Furthermore, the majority of the studies have not examined the differential contribution of various structures within each hemisphere to the self-effect. This was done here.

Sui, Chechlacz, et al. (2012) took a somewhat different approach. They explored lesion-symptom mapping of deficits in self-face prioritization (SFP) using voxel-based morphometry (VBM) analysis across the whole brain in a relatively large group of patients. Behavioral measures were based on a task in which patients were presented with 3 faces of the same gender and age: Their own, a familiar other, and an unfamiliar other. Each face was presented oriented toward the left or the right. There were 2 tasks. In the first, patients had to indicate the orientation of the face. In the second, a cross was overlaid on the face and the task was to decide whether the horizontal or the vertical line of the cross was longer. In the first case, the face was the target for the task, while in the second it was irrelevant and a potential distracter. Typically, participants respond faster when judging the orientation of their own face when compared with when the face is of a familiar other person (Sui and Han 2007, Ma and Han 2010), and slower when they need to ignore their own face (in the cross task; Brédart et al. 2006). Sui, Chechlacz, et al. (2012) reported that patients with damage to the left inferior parietal and superior temporal cortices had both a reduced self-face advantage in the orientation judgement task and reduced interference when their own face was a distractor (in the cross task). This finding is consistent with the argument that these brain regions are involved in controlling attention to self and socially relevant stimuli (Saxe and Kanwisher 2003; Sui et al. 2013)—for example, either in guiding attention to appropriate facial features to make the orientation judgement or in signaling the presence of self-related cues in the background (in the cross task). There were also effects selective to each task (orientation judgements or judging the dimensions of the cross). Lesions to the right superior frontal cortex, the right precuneus, and the left anterior temporal cortices selectively impaired the SFP effect for orientation judgements. Lesions to the left superior temporal cortex, the cingulate, and the superior parietal cortex selectively diminished interference effects from the self-face when it was a distractor (in the cross task). The data suggests that while some brain regions (left inferior parietal and superior temporal cortices) support general self-prioritization effects (across tasks where the self-face is a target and when it is a distractor), other brain regions are recruited selectively when self-faces are targets (in the orientation task) or distractors in a task (e.g., in the cross task).

However, while the results of Sui, Chechlacz, et al. (2012) clarify the roles of some regions involved in self-prioritization in face perception, neither of the tasks they examined directly required self-other discrimination, and at best the tasks indirectly assessed self-face perception. Indeed, it is possible that the brain regions associated with self-face processing in this study reflected control processes recruited either to enhance task performance when the self-face was a target (in the orientation judgement task) or to suppress attention to self-faces as distractors (in the cross-discrimination task).

Moreover, Sui, Chechlacz, et al. (2012) only evaluated decreases in SFP effects and they did not examine cases where self-faces gain increased prioritization—though increased self-prioritization can be detrimental to the individual (Grimm et al. 2009). In developmental research, it has been noted that toddlers can exhibit strong self-biases in their performance—for example, having difficulty in inhibiting their own perspective when they have to make judgments from another viewpoint (e.g., Carlson and Moses 2001). It has been argued that is a result of a failure to exert executive control processes, which leads to an inability to inhibit responses to the self (Moses 2001; Carlson et al. 2004; Sabbagh et al. 2006), though others have hypothesized a failure to develop an adequate theory of mind (Baron-Cohen et al. 1985; Leslie and Frith 1988; Moran et al. 2011). It is also possible that lesions to regions associated with attentional control (e.g., dorsal prefrontal and parietal cortex; Corbetta and Shulman 2002) and/or social cognition (e.g., medial frontal cortex, the temporo-parietal junction, the superior temporal sulcus, and the temporal poles; see Northoff and Bermpohl 2004; Amodio and Frith 2006; Mitchell et al. 2006; Northoff et al. 2006) affect the degree of self-biased behavior, and that damage to these regions may lead to hyper- rather than hypo-self-biases in perception. This would fit with arguments by Kahneman and Klein (2009) and Kahneman (2011) that fast intuitive responses, operating outside of executive control, can be biased toward self-interest. The lesions associated with hyper- and hypo-self-biases were assessed here.

In the current study, we directly tested self-bias effects on face recognition, measuring both hyper- and hypo-self-biases in a group of neurological patients. The task was to discriminate familiar from unfamiliar faces. Two types of familiar faces were presented—the patient's own face and the face of a personally familiar other. For each patient, we measured their SFP effect on recognition by computing the difference between how quickly judgements were made to the individual's own faces compared with the face of a personally familiar other. Importantly, all patients could reliably and easily make accurate familiarity judgments to all 3 faces (their own, the familiar other, and the unfamiliar other) and showed no signs of prosopagnosia. In addition, we measured the same behavior in gender and aged matched healthy controls. The data from the healthy controls were used as a reference to classify the patients into 3 groups: A group with a normal self-bias effect, a hypo-self-bias group (with a pathologically reduced self-bias), and a hyper-self-bias group (with a pathologically increased self-bias effect). We also explored whether performance on other cognitive tasks, such as the ability to exert executive control over behavior, to sustain attention and to perform long-term recognition memory tasks was associated with the self-bias effects. Finally, we used a VBM analysis to directly compare between the 3 groups. Lesions associated with a hypo-self-bias were dissected by measuring reduced gray or white matter evident in the hypo-group compared with the intact and hyper-groups. Lesions associated with a hyper-self-bias were identified by contrasting reduced gray and white matter integrity in the hyper-group compared with the intact and hypo-groups. We asked 3 questions: (1) What lesions are associated hypo-self-bias? (2) what lesions are linked to hyper-self-bias? And (3) are the lesions associated with reduced self-bias in a direct recognition task (the familiarity judgement task used here) the same as those associated with abnormal self-face bias in implicit tasks (as in the orientation and cross-judgement tasks used in Sui, Chechlacz, et al. 2012)?

Materials and Methods

Participants

Patients

The patients were randomly selected from the panel of neuropsychological volunteers at the School of Psychology, University of Birmingham. The patients mainly had acquired brain lesions from stroke, though 1 had suffered herpes simplex encephalitis, 1 had cortico-basal degeneration, and 3 carbon monoxide poisoning. [Excluding the nonstroke patients made little difference to the analysis (see also Chechlacz et al. 2010).] All were at a chronic stage (>12 months postinjury). We conducted a pretest to choose only nonprosopagnosic patients to participate. Patients were presented with central images and required to discriminate their own faces, the faces of familiar others, and those of unfamiliar people. Admission to the study was contingent on patients obtaining 100% discrimination accuracy. Thirty patients were selected who had no contraindications to MRI scanning. No other exclusion criteria were used. The age range was from 36 to 78 years (M = 64.97 ± 10.91 years). All patients provided written informed consent in agreement with ethics protocols at the School of Psychology and Birmingham University Imaging Centre (BUIC). All patients had undertaken the Birmingham Cognitive Screen (BCoS) test battery (Humphreys et al. 2012; www.BCoS.bham.ac.uk) to provide a background neuropsychological profile (for details see Table 1).

Table 1

Patients details: clinical and demographic data

ID Age Gender Handed Etiology TPL SFP deficit 
54 HSE 12 Hypo 
65 Hypo 
74 Hypo 
76 Hypo 
50 Hypo 
69 Hypo 
72 Hypo 
77 Hyper 
73 14 — 
10 69 — 
11 40 CM 12 Hyper 
12 72 CM 12 — 
13 63 0.5 — 
14 64 CBD — 
15 63 — 
16 73 — 
17 57 — 
18 78 — 
19 56 CM Hyper 
20 78 Hyper 
21 63 12 — 
22 77 — 
23 62 15 — 
24 36 Hyper 
25 74 — 
26 74 — 
27 55 — 
28 67 Hyper 
29 54 — 
30 64 — 
ID Age Gender Handed Etiology TPL SFP deficit 
54 HSE 12 Hypo 
65 Hypo 
74 Hypo 
76 Hypo 
50 Hypo 
69 Hypo 
72 Hypo 
77 Hyper 
73 14 — 
10 69 — 
11 40 CM 12 Hyper 
12 72 CM 12 — 
13 63 0.5 — 
14 64 CBD — 
15 63 — 
16 73 — 
17 57 — 
18 78 — 
19 56 CM Hyper 
20 78 Hyper 
21 63 12 — 
22 77 — 
23 62 15 — 
24 36 Hyper 
25 74 — 
26 74 — 
27 55 — 
28 67 Hyper 
29 54 — 
30 64 — 

CBD, cortico-basal degeneration; CM, carbon monoxide poisoning; F, female; HSE, herpes simplex encephalitis; L, left; M, male; R, right; S, stroke; SFP, self-face prioritization; TPL, time post lesion (year).

Healthy Controls for Lesion Identification

For the lesion identification protocol (see below), we acquired T1-weighted images from 100 healthy controls (55 males and 45 females, mean age 54.5 years, range 20–87) with no history of stroke, brain damage, or neurological disorders. These were used to normalize and segment the patients' MR images (see the section on Neuroimaging Data Acquisition and Preprocessing). All the controls provided written informed consent in agreement with ethics protocols at the School of Psychology and BUIC.

Cognitive Assessment

Self-Face Prioritization

SFP was measured in a face categorization task in which participants were presented with self-faces, the faces of a gender-matched personally familiar other, and the faces of an unfamiliar person. The task was to classify the face stimuli into 1 of 2 groups, familiar (self-faces and personally familiar other faces) or unfamiliar (unfamiliar other faces). We collected (1) 6 face images for each patient, (2) 6 face images of a gender-matched individual who was highly personally familiar to each patient, and (3) 6 face images of a gender-matched unfamiliar other. The images showed 3 left and 3 right profiles of each face with a neutral facial expression, depicted at angles ranging from 15° to 45° in each direction. The images subtended about 5° × 5° of visual angle at a viewing distance of 60 cm. Each patient completed 2 blocks of 72 trials with equal numbers of images in the self, familiar, and unfamiliar face conditions. Each trial began with the presentation of a white fixation cross at the center of the screen for 500 ms. A face image was then displayed at the center of the screen until the patients made a response. The maximum duration of a face was 3000 ms, and this was followed by feedback for 1000 ms.

We calculated SFP scores based on reaction times—the difference between the familiar other and the self, divided by the sum of the 2 conditions, to take account of overall differences in response latency. Control norms for the SFP scores were based on 25 healthy participants, with no history of neurological disease (9 males and 16 females, age range 20–73). The controls showed self-prioritization effects in the face categorization task, which is consistent with evidence from prior studies in self-face processing (Tong and Nakayama 1999; Keyes and Brady 2010; Sui and Humphreys 2013). The SFP scores for the controls were used to define the SFP impairments for individual patients, which were measured by subtracting the mean for the controls from that of each patient and dividing by the standard deviation for the controls. The cutoff to classify patients as impaired was based on them having a mean level of self-prioritization effect either less or more than 2.5 SDs from the control mean (defining, respectively, a hypo- or a hyper-SFP deficit). (Note that these healthy controls were used to diagnose behavioral deficits in the patients, but they were not included in the imaging analysis where the patients without behavioral SFP deficit served as controls.)

Assessments of Other Cognition Tests

Several other cognitive tasks were also assessed: (1) An executive control task (the Hayling and Brixton tests of executive functions; Burgess and Shallice 1997); (2) immediate and delayed story recognition from the BCoS battery (Humphreys et al. 2012); (3) sustained attention and neglect (from BCoS; Humphreys et al. 2012). These measures were of interest because (respectively): (1) Hyper-self-bias, in particular, may reflect poor executive attentional control; (2) altered self-bias may stem from general impairments in recognition memory; and (3) variations in sustained attention and/or poor attention to the left- or right-facing faces (in patients with neglect) could modulate the effects of the self-face on performance. The story recognition memory required the patients to listen to a story and then to make forced-choice judgements either immediately after the story or after filled delayed of about 10 min. The test of sustained attention required patients to respond to 3 high-frequency, auditorily-presented target words (no, hello, and please) and to ignore (not respond to) 3 high-frequency, related distractors (yes, goodbye, and thanks). Sustained attention was indexed by subtracting the number of correct responses in the last block from those in the first block. Poor sustained attention was shown when performance dropped across test blocks. The test of neglect required patients to cancel a set of complete line drawings of apples while ignoring distractor apples that had a section missing on either the left or right of the object. Targets and distractors were randomly positioned on the page with the proviso that there were equal numbers of each type of item within each of 5 columns across the page. This “Apples” test provides separate measures of “egocentric/spatial neglect” (where items are missed according to their position on the page) and “allocentric/object neglect” (based on false-positive responses to distractors according to whether participants respond incorrectly to distractors with a gap on the left or right of individual stimuli irrespective of the positions of the stimuli on the page; see Chechlacz et al. 2010). Each patient's behavioral performance on these cognitive tasks was classified based on cutoffs drawn from the BCoS and estimated on the dataset from healthy controls (Humphreys et al. 2012).

Neuroimaging Data Acquisition and Preprocessing

Patients and the healthy controls used just for lesion identification (see above) were scanned at BUIC on a 3-T Philips Achieva MRI system with an 8-channel phased-array SENSE head coil. The anatomical scans were acquired using a sagittal T1-weighted sequence (sagittal orientation, time echo/time repetition = 3.8/8.4 ms, voxel size 1 × 1 × 1 mm3).

All T1 scans (both the 30 patients and the100 controls) were first converted and reoriented using MRICro (Chris Rorden, Georgia Tech, Atlanta, GA, USA). The preprocessing of all T1 scans was done using SPM5 (Statistical Parametric Mapping, Welcome Department of Cognitive Neurology, London, UK). All brain scans were transformed into the standard MNI space using the unified-segmentation procedure (Ashburner and Friston 2005). The unified-segmentation procedure involves tissue classification based on the signal intensity in each voxel and on a priori knowledge of the expected location of gray matter (GM), white matter (WM), and cerebrospinal fluid in the brain. Furthermore, to improve tissue classification and spatial normalization of lesioned brains, a modified segmentation procedure was used (see Seghier et al. 2008, for details). The modified approach was used to resolve misclassification of damaged tissue by including an additional prior for an atypical tissue class (an added “extra” class) to account for the “abnormal” voxels within lesions and thus, allowing classification of the outlier voxels.

The segmented images (GM and WM maps) were smoothed with an 8-mm full-width at half-maximum (FWHM) Gaussian filter to accommodate the assumption of random field theory used in the statistical analysis (Worsley 2003). The choice of intermediate smoothing of 8-mm FWHM was previously shown to be optimal for lesion detection and further analysis of segmented images (Seghier et al. 2008; Leff et al. 2009). The preprocessed GM and WM images were used in the analyses to determine voxel-by-voxel relationships between brain damage and SFP deficit.

Voxel-Based Morphometry

To delineate the anatomical structures involved in the SFP effect and to examine contributions of white and gray matter changes, we applied a voxel-wise statistical approach to assess the link between the cognitive deficits in SFP and brain lesions using normalized and smoothed gray and white matter images.

To assess the relationship between brain damage and loss of self-prioritization on a voxel-by-voxel basis, we used a VBM approach (Ashburner and Friston 2000) and conducted parametric statistics within the framework of general linear modeling (Kiebel and Holmes 2003) with SPM5. The analyses for gray and white matter were conducted separately. In the statistical model, we treated the hypo-, hyper-SFP and intact SFP groups as 3 samples. Gender, age, handedness, etiology, and time post lesion (year) were also included as covariates of no interest to control potentially confounding factors. We then used t-contrasts to dissociate individuals with different forms of SFP deficit relative to the other patients (e.g., testing for a change in voxel intensity that was correlated with hypo- or hyper-SFP biases but not with other cognitive deficits).

We report only results showing a significant effect at P < 0.001 cluster-level corrected for multiple comparisons based family wise error correction with the amplitude of voxels surviving at P < 0.005 uncorrected across the whole brain and an extent threshold of 800 mm3 (>200 voxels). The brain coordinates are presented in MNI space. To localize white matter lesions associated with SFP in relation to specific white matter pathways, we used the Johns Hopkins University white matter tractography (Hua et al. 2008), the Mori MRI Atlas of Human White Matter (Mori et al. 2005), and SPM Anatomy Toolbox (Eickhoff et al. 2005).

Results

Behavioral Data

The patients were divided into experimental and control patient groups in terms of their SFP scores in relation to the data of healthy controls. Seven of 30 patients were classified as having a hypo-SFP deficit. Six of these patients had a brain lesion within the right hemisphere and 1 had a bilateral lesion. In contrast, 6 of the 30 patients had a hyper-SFP deficit, with the damage in these cases either being unilateral left hemisphere or bilateral (see Table 2 for further details of individual clinical profiles). Figure 1 shows the SFP effects for the hypo-, hyper-, and control patients (i.e., patients with a SFP effect within the normal range). Notably, there was a significant correlation between the magnitude of the SFP effect in the patients and executive control performance (summed errors on the Hayling and Brixton tests), r = 0.42, P = 0.04: The weaker the executive control performance (the more executive test errors that occurred), the greater the self-advantage (Fig. 2). Also, while the hyper-SFP patients were more likely to have an executive deficit than the other patient groups (the hypo- and control patient groups; χ2 = 7.03, P = 0.008), there were no differences in the incidence of deficits in the other cognitive tests across the patient groups (all P > 0.15).

Table 2

Demographic and clinical details for patients with a SFP deficit and patient controls entered into the VBM analyses

 Hypo-SFC deficit (n = 7) Hyper-SFP deficit (n = 6) Control patients (N = 17) 
Age in years (SD) 65.71 ± 10.08 59.00 ± 18.15 66.76 ± 7.60 
Gender 2 women, 5 men 6 men 1 woman, 16 men 
Etiology 6 strokes, 1 HSEa 1 CBDb, 1 CMc, 4 strokes 15 strokes, 2 CMc 
Handedness 3 left-handed 1 left-handed 1 left-handed 
Postlesion in years (SD) 4.86 ± 3.72 4.50 ± 4.76 5.32 ± 4.82 
Executive control (%) 29 83 24 
Immediate verbal story recognition deficits 60% (n = 5)d 50% (n = 4) 55% (n = 11) 
Delayed verbal story recognition deficits 40% (n = 5) 50% (n = 4) 39% (n = 11) 
Sustained attention deficit (%) 24 
Spatial neglect (%) 17 29 29 
Object neglect (%) 33 14 35 
 Hypo-SFC deficit (n = 7) Hyper-SFP deficit (n = 6) Control patients (N = 17) 
Age in years (SD) 65.71 ± 10.08 59.00 ± 18.15 66.76 ± 7.60 
Gender 2 women, 5 men 6 men 1 woman, 16 men 
Etiology 6 strokes, 1 HSEa 1 CBDb, 1 CMc, 4 strokes 15 strokes, 2 CMc 
Handedness 3 left-handed 1 left-handed 1 left-handed 
Postlesion in years (SD) 4.86 ± 3.72 4.50 ± 4.76 5.32 ± 4.82 
Executive control (%) 29 83 24 
Immediate verbal story recognition deficits 60% (n = 5)d 50% (n = 4) 55% (n = 11) 
Delayed verbal story recognition deficits 40% (n = 5) 50% (n = 4) 39% (n = 11) 
Sustained attention deficit (%) 24 
Spatial neglect (%) 17 29 29 
Object neglect (%) 33 14 35 

Note: For the cognitive tasks, we report the percentages of patients within each group who were classified as having a clinical deficit relative to age-appropriate control data.

aHerpes simplex encephalitis.

bCortico-basal degeneration.

cCarbon monoxide poisoning. The cognitive profile for the patients was extracted from the scores on the BCoS test (see Humphreys et al. 2012 for detail).

dIt is based on patients who completed cognitive tests. For easier comparison, we present the percentage of patients who have a deficit in any give measure.

Figure 1.

SFP scores for individuals across 3 patient groups and 1 control group: Patients with the hypo-SFP deficit, with the hyper-SFP deficit, without SFP deficit, and healthy controls. SFP scores were measured using reaction time by the difference between the familiar and self-faces divided by the sum of the familiar and self-faces and multiplying 100.

Figure 1.

SFP scores for individuals across 3 patient groups and 1 control group: Patients with the hypo-SFP deficit, with the hyper-SFP deficit, without SFP deficit, and healthy controls. SFP scores were measured using reaction time by the difference between the familiar and self-faces divided by the sum of the familiar and self-faces and multiplying 100.

Figure 2.

The correlation between the magnitude of self-advantage and executive test errors. Patients indicated in white are those classified as having a hyper-SFP effect.

Figure 2.

The correlation between the magnitude of self-advantage and executive test errors. Patients indicated in white are those classified as having a hyper-SFP effect.

Voxel-Based Morphometry

The VBM analysis for the hypo-SFP deficit revealed gray matter damage within the right temporal lobe—there were changes in the inferior temporal region, the hippocampus, and the parahippocampal gyrus partially extending to the fusiform gyrus (Table 3 and Fig. 3A,C). In contrast, the VBM analysis for the hyper-SFP deficit demonstrated that this pattern of performance was associated with damage to the superior frontal gyrus and posterior superior temporal sulcus in the left hemisphere (Table 4 and Fig. 3B,C).

Table 3

Gray matter and white matter lesions associated with a hypo-SFP deficit

Contrast Cluster level Voxel level Coordinates Brain structure 
Size Z-score MNI (x, y, z
Gray matter 4513* 5.38* 36, −12, −22 Right anterior HPCa and PHGb extending to ITGc and FGd 
4.22 46, −6, −32 
4.16 24, 6, −34 
White matter 5166* 4.41 32, −10, −28 Right IFOFe and ILFf 
4.06 34, −22, −10 
3.88 46, −34, −18 
Contrast Cluster level Voxel level Coordinates Brain structure 
Size Z-score MNI (x, y, z
Gray matter 4513* 5.38* 36, −12, −22 Right anterior HPCa and PHGb extending to ITGc and FGd 
4.22 46, −6, −32 
4.16 24, 6, −34 
White matter 5166* 4.41 32, −10, −28 Right IFOFe and ILFf 
4.06 34, −22, −10 
3.88 46, −34, −18 

aHippocampus.

bParahippocampal gyrus.

cInferior temporal gryus.

dFusiform gyrus.

eInferior fronto-occipital fasciculus.

fInferior lateral frontal fasciculus.

*FWE correction at P<0.01.

Table 4

Gray matter lesions associated with a hyper-SFP deficit

Cluster level Voxel level Coordinates Brain structure 
Size Z-Score MNI (x, y, z
242 4.53 −58, −54, −10 Left IOGa/ITGb 
336 3.95 −24, 62 14 Left SFGc 
238 3.58 −40, −80, 28 Left pSTSd 
Cluster level Voxel level Coordinates Brain structure 
Size Z-Score MNI (x, y, z
242 4.53 −58, −54, −10 Left IOGa/ITGb 
336 3.95 −24, 62 14 Left SFGc 
238 3.58 −40, −80, 28 Left pSTSd 

aInferior occipital gyrus.

bInferior temporal gyrus.

cSuperior frontal gyrus.

dPosterior superior temporal sulcus.

Figure 3.

(A) Gray matter damage associated with the hypo-SFP deficit over the right inferior temporal gyrus, hippocampus, and parahippocampal gyrus. (B) Gray matter damage associated with the hyper-SFP deficit in the left superior frontal gyrus and right posterior superior temporal sulcus. (C) The plots illustrate the beta values with 90% confidence interval in the left superior frontal gyrus, right hippocampus, and right FFA. Error bars represent standard errors.

Figure 3.

(A) Gray matter damage associated with the hypo-SFP deficit over the right inferior temporal gyrus, hippocampus, and parahippocampal gyrus. (B) Gray matter damage associated with the hyper-SFP deficit in the left superior frontal gyrus and right posterior superior temporal sulcus. (C) The plots illustrate the beta values with 90% confidence interval in the left superior frontal gyrus, right hippocampus, and right FFA. Error bars represent standard errors.

VBM analyses of white matter damage showed that the hypo-SFP impairments were associated with right inferior temporal lesions along the inferior longitudinal fasciculus (ILF) and the inferior fronto-occipito fasciculus (IFOF) in the white matter adjacent to the right fusiform gyrus and parahippocampal gyrus (Table 3 and Fig. 4). These 2 fasciculi are major tracts that project through the core fusiform region to the anterior temporal and frontal cortices to provide a distributed cortical network that subserves normal face processing (Thomas et al. 2009). White matter damage was not reliably associated with the hyper-SFP deficit.

Figure 4.

White matter damage linked to the hypo-SFP deficit over the right medial inferior temporal structures and connecting the ILF and the IFOF.

Figure 4.

White matter damage linked to the hypo-SFP deficit over the right medial inferior temporal structures and connecting the ILF and the IFOF.

Discussion

The aim of the current study was to localize the brain region(s) responsible for the behavioral advantage in explicit self-face categorization based on facial familiarity. We used brain-lesioned patients who could recognize both their own and the faces of personally familiar others. The VBM results revealed that damage over the right inferior temporal–occipital subcortical region including the hippocampus and parahippocampus extending to the fusiform gyrus disrupted the behavioral advantage for explicit self-face discrimination (generating a hypo-SFP deficit). The involvement of the right hemisphere in self-prioritization is consistent with previous behavioral (Keenan et al. 1999; Platek and Gallup 2002), patient (Preilowski 1977; Sperry et al. 1979; Keenan et al. 2001), and neuroimaging studies (Platek et al. 2004, 2008; Uddin et al. 2005; Sui and Han 2007). Our data provide the first confirmation of this with a relatively large group of patients. In particular, the VBM analysis also pointed to the involvement of the ILF and IFOF white matter fiber tracts in the right hemisphere as being linked to self-prioritization in face familiarity judgements.

In addition to this, the data also revealed for the first time that lesions in the left superior frontal gyrus and posterior superior temporal sulcus were uniquely associated with an increased self-advantage effect. The magnitude of the self-advantage effect was also correlated with executive dysfunction across the patients, while the hyper-SFP group was reliably more likely to have a deficit in executive dysfunction than the other patient groups. These results are consistent with the argument that, when fewer resources are available, people have difficulty in inhibiting self-related biases (Carlson and Moses 2001; Kahneman and Klein 2009; Kahneman 2011), and this subsequently leads to a “super” self-benefit (Moses 2001; Carlson et al. 2004; Sabbagh et al. 2006). In addition to this, there is evidence that the left superior temporal sulcus moderates attentional responses to self-related cues (e.g., Sui et al. 2013). We propose that damage to this region may impair the ability to implement attentional control signals originating in frontal brain regions (e.g., the superior frontal gyrus), and this makes self-faces more difficult to ignore. The frontal lesions will also be associated with executive deficits, as we observed.

Uddin (2011b) suggested that “an intact corpus callosum enabling interhemispheric transfer is necessary for some, but not all types of self-representation.” Some researchers have reported that, although both the left and right hemispheres are able to recognize the images of the participant's own face (Sperry et al. 1979; Turk et al. 2002), the right hemisphere is dominant (Preilowski 1977; Keenan et al. 2001). Researchers have also reported some cases in which patients with right hemisphere dysfunction fail to recognize their own faces, but retain the ability to recognize the faces of other people (Breen et al. 2001; Villarego et al. 2011; Van den Stock et al. 2012). Consistent with this, behavioral studies with normal participants show an advantage for responding to self-faces when judgments are made using the left hand (Keenan et al. 1999). Other converging evidence comes from patients with delusional misidentification syndrome (DMS), who perceive some alteration in familiar faces. Feinberg and Keenan (2005) reported that the frontal gyrus and the right hemisphere play a crucial role in DMS disorders. For example, they discuss a patient who had undergone surgical removal of a right frontal subdural hematoma and, subsequently, reported that the patient in the bed next to her was her husband (Ruff and Volpe 1981). This fits with evidence that the right prefrontal cortex is crucial for self-awareness (Keenan et al. 2000) and responds to the self-other distinction (Decety and Sommerville 2003). Others have proposed that the sense of self-registered through the right hemisphere is based on an emotion-related response (Devinsky 2000) and on the role of the right hemisphere in self-monitoring (Kaplan and Zaidel 2001). Self-other differences have also been reported in more posterior brain regions. For example, neuroimaging studies show that the right extrastriate body area and the fusiform body area are activated differently by viewing one's own relative to another person's body parts (Vocks et al. 2010). Decety and Chaminade (2003) further propose that connectivity between the right inferior parietal and prefrontal regions plays a crucial function in both self-awareness and in relating the self to others. Our data fit with these findings in showing both the involvement of posterior visually related processing areas as being necessary for SFP (e.g., the temporal–occipital subcortical region—the parahippocampus and hippocampus, extending to the fusiform area) and the critical role of posterior–anterior connectivity (the ILF and IFOF). Our results are also consistent with prior neuroimaging study (Ma and Han 2012), showing that the right fusiform gyrus is engaged in self-identity judgements. Similar evidence comes from an ERP study, demonstrating that the face familiarity “drives” the N250 response in the temporal occipital region (Caharel et al. 2002) and prominently in the right inferior temporal region (Tanaka et al. 2006).

There is evidence indicating that processing of the self-face is special in that configural responses to self-faces are not affected by inversion, while responses to the faces of familiar others are (Keyes 2012). Sui, Chechlacz, et al. (2012) also reported dissociations in self-face recognition relative to the recognition of other faces when self, familiar other, and unfamiliar other faces could be contrasted in a common task (e.g., face orientation judgements), suggesting that self-related processing may recruit brain circuits different to the processes recruited for nonself-related stimuli (see also Sui et al. 2013). The results in the current study further provide evidence that the self is special in face recognition, given that all changes were measured against responses to the face of a highly personably familiar other.

Our data highlight a specific role in self-related familiarity judgements for subcortical structures in the right hemisphere including the hippocampus, the parahippocampus, and related white mater fiber tracts (ILF and IFOF). Although some previous self-recognition studies have reported that self-recognition is associated with greater cortical activation in the right hemisphere, especially around the right temporo-parietal junction (Keenan et al. 2001; Uddin et al. 2005, 2007; Platek et al. 2006; Heinisch et al. 2012), none of them have shown a role for subcortical and white matter fiber tracts. The necessary involvement of these subcortical structures and white matter fiber tracts, shown by our lesion analysis, suggests a network account of self-recognition in self–other face discrimination. In particular, the inferior occipital temporal areas are associated with the recognition of familiar faces and access to stored visual memories, suggesting that the self-advantage arises out of processes sensitive to face memory and their connection to regions within the frontal cortex, which may include supramodal self-representations. Interestingly, the loss of SFP here does not seem to reflect a general loss of familiarity. For example, the patients were generally able to discriminate familiar from unfamiliar faces. Most neuropsychological studies also indicate that it is the most familiar objects that are retained after brain lesion, so that extra familiarity makes representations robust to neural degeneration (e.g., see Snowden et al. 1996). In contrast to this, patients with hypo-SFP have a reduced response to highly familiar stimuli. An alternative is that the SFP process depends on rapid transmission of information from face recognition areas in the right inferior occipital temporal gyrus to frontal lobe regions concerned with self-representation (see Sui et al. 2009; Sui, Hong, et al. 2012, for ERP evidence; Sui et al. (2013) for evidence from brain connectivity analysis). The current evidence indicates that white matter damage, affecting temporal to frontal tracts, is associated with poor self-prioritization—consistent with this argument.

The present results show some contrasts with our own previous reported data using a VBM analysis with a similar patient population, separating conditions where self-face information would be beneficial or detrimental to performance (according to whether the faces were targets or distractors; Sui, Chechlacz, et al. 2012). In that study, right frontal damage was associated with a reduced SFP effect when faces were targets (and self-faces were beneficial), while left-hemisphere lesions were associated with a reduced ability for patients to ignore their own face as a distractor (when the self-face was detrimental to the task). The latter result could reflect control structures in the left hemisphere involved in inhibiting salient distractors (see Mevorach et al. 2010, for evidence), rather than self-face processing itself. The prior effect of right frontal damage can be understood if performance previously was dependent on participants setting-up “templates” for the self-face when judging face orientations. For example, the right frontal regions linked to poor self-prioritization in Sui, Chechlacz, et al. (2012) have been previously associated with participants holding templates of stimuli in working memory (Soto et al. 2008). Such templates may have been more important for orientation judgements than for direct familiarity judgements, as required here. The current task, requiring speeded familiarity judgements, may depend less on explicit templates for stimuli and more on directly generated familiarity responses to stimuli (Talyor et al. 2009; Seger et al. 2011; Immordino-Yang and Singh 2013). The critical brain regions in our study, involving inferior occipito-temporal cortex, the hippocampus, and parahippocampus, may support just such familiarity-based responses; weakening such responses, through brain lesion, disrupts the usual advantage for self-faces even when explicit face recognition still takes place.

Conclusions

There has been little prior evidence on the brain regions necessary for SFP in explicit face discrimination tasks. The present evidence points to cortical and subcortical structures in the right hemisphere, and their connections to frontal lobe regions, as being critical to show an advantage to self-faces, with damage to these regions leading to a hypo-SFP effect due to less efficient access to face memory. In contrast, damage to the left superior frontal gyrus and posterior superior temporal sulcus were associated with hyper-SFP effects, which we attribute to poor executive control and the modulation of social attention to self-faces.

Funding

This work was supported by a Royal Society Newton Fellowship to J.S., an ESRC grant to J.S. and G.W.H. (ES/J001597/1), and a Stroke Association grant and an ERC Advanced Grant (323883) to G.W.H.

Notes

Conflict of Interest: None declared.

References

Amodio
DM
Frith
CD
Meeting of minds: the medial frontal cortex and social cognition
Nat Rev Neurosci
 , 
2006
, vol. 
7
 (pg. 
268
-
277
)
Ashburner
J
Friston
KJ
Unified segmentation
NeuroImage
 , 
2005
, vol. 
26
 (pg. 
839
-
851
)
Ashburner
J
Friston
KJ
Voxel-based morphometry—the methods
Neuroimage
 , 
2000
, vol. 
11
 (pg. 
805
-
821
)
Baron-Cohen
S
Leslie
AM
Frith
U
Does the autistic child have a “theory of mind”?
Cognition
 , 
1985
, vol. 
21
 (pg. 
37
-
46
)
Brédart
S
Delchambre
M
Laureys
S
One's own face is hard to ignore
Q J Exp Psychol
 , 
2006
, vol. 
59
 (pg. 
46
-
52
)
Breen
N
Caine
D
Coltheart
M
Mirrored-self misidentification: two cases of focal onset dementia
Neurocase
 , 
2001
, vol. 
7
 (pg. 
239
-
254
)
Burgess
P
Shallice
T
The Hayling and Brixton Tests. Test manual
 , 
1997
Bury St Edmunds, UK
Thames Valley Test Company
Caharel
S
Poiroux
S
Bernard
C
Thibaut
F
Lalonde
R
Rebai
M
ERPs associated with familiarity and degrees of familiarity during face recognition
Int J Neurosci
 , 
2002
, vol. 
112
 (pg. 
1499
-
1512
)
Carlson
SM
Moses
LJ
Individual differences in inhibitory control and children's theory of mind
Child Dev
 , 
2001
, vol. 
72
 (pg. 
1032
-
1053
)
Carlson
SM
Moses
LJ
Claxton
LJ
Individual differences in executive functioning and theory of mind: an investigation of inhibitory control and planning ability
J Exp Child Psychol
 , 
2004
, vol. 
87
 (pg. 
299
-
319
)
Chechlacz
M
Rotshtein
P
Bickerton
WL
Hansen
PC
Deb
S
Humphreys
GW
Separating neural correlates of allocentric and egocentric neglect: distinct cortical sites and common white matter disconnections
Cogn Neuropsychol
 , 
2010
, vol. 
27
 (pg. 
277
-
303
)
Conway
MA
Collins
AF
Gathercole
SE
Anderson
SJ
Recollections of true and false autobiographical memories
J Exp Psychol Gen
 , 
1996
, vol. 
125
 (pg. 
69
-
95
)
Corbetta
M
Shulman
GL
Control of goal-directed and stimulus-driven attention in the brain
Nat Rev Neurosci
 , 
2002
, vol. 
3
 (pg. 
201
-
215
)
Decety
J
Chaminade
T
When the self represents the other: a new cognitive neuroscience view on psychological identification
Conscious Cogn
 , 
2003
, vol. 
12
 (pg. 
577
-
596
)
Decety
J
Sommerville
JA
Shared representations between self and others: a social cognitive neuroscience view
Trends Cogn Sci
 , 
2003
, vol. 
7
 (pg. 
527
-
533
)
Devinsky
O
Right cerebral hemisphere dominance for a sense of corporeal and emotional self
Epilepsy Behav
 , 
2000
, vol. 
1
 (pg. 
60
-
73
)
Devue
C
Bredart
S
The neural correlates of visual self-recognition
Conscious Cogn
 , 
2011
, vol. 
20
 (pg. 
40
-
51
)
Eickhoff
SB
Stephan
KE
Mohlberg
H
Grefkes
C
Fink
GR
Amunts
K
Zilles
K
A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data
Neuroimage
 , 
2005
, vol. 
25
 (pg. 
1325
-
1335
)
Feinberg
TE
Keenan
JP
Where in the brain is the self?
Conscious Cogn
 , 
2005
, vol. 
14
 (pg. 
661
-
678
)
Feinberg
TE
Roane
DM
Delusional misidentification
Psychiatr Clin N Am
 , 
2005
, vol. 
28
 (pg. 
665
-
683
)
Gallup
GG
Jr
Self-recognition in primates: a comparative approach to the bidirectional properties of consciousness
Am Psychol
 , 
1977
, vol. 
32
 (pg. 
329
-
338
)
Gallup
GG
Anderson
JR
Platek
SM
Gallagher
S
Self-recognition
The oxford handbook of the self
 , 
2011
New York
Oxford University Press Inc
(pg. 
82
-
108
)
Grimm
S
Jutta
E
Boesiger
P
Schuepbach
D
Daniel
H
Boeker
H
Northoff
G
Increased self-focusing major depressive disorder is related to neural abnormalities in subcortical–cortical midline structures
Hum Brain Mapp
 , 
2009
, vol. 
30
 (pg. 
2617
-
2627
)
Heinisch
C
Krüger
MC
Brüne
M
Repetitive transcranial magnetic stimulation over the temporoparietal junction influences distinction of self from famous but not unfamiliar others
Behav Neurosci
 , 
2012
, vol. 
126
 (pg. 
792
-
796
)
Hua
K
Zhang
J
Wakana
S
Jiang
H
Li
X
Reich
DS
Calabresi
PA
Pekar
JJ
van Zijl
PC
Mori
S
Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification
Neuroimage
 , 
2008
, vol. 
39
 (pg. 
336
-
347
)
Humphreys
GW
Bickerton
WL
Samson
D
Riddoch
MJ
The Birmingham Cognitive Screen (BCoS)
 , 
2012
London
Psychology Press
Immordino-Yang
MH
Singh
V
Hippocampal contributions to the processing of social emotions
Hum Brain Mapp
 , 
2013
, vol. 
34
 (pg. 
945
-
955
)
Kahneman
D
Thinking, fast and slow
 , 
2011
New York
Farrar, Straus and Giroux
Kahneman
D
Klein
G
Conditions for intuitive expertise: a failure to disagree
Am Psychol
 , 
2009
, vol. 
64
 (pg. 
515
-
526
)
Kaplan
JT
Zaidel
E
Error monitoring in the hemispheres: the effect of lateralized feedback on lexical decision
Cognition
 , 
2001
, vol. 
82
 (pg. 
157
-
178
)
Keenan
JP
Gallup
GG
Falk
D
The face in the mirror: the search for the origins of consciousness
 , 
2003
New York
Harper Collins
Keenan
JP
McCutcheon
B
Sanders
G
Freund
S
Gallup
GG
Pascual-Leone
A
Left hand advantage in a self-face recognition task
Neuropsychologia
 , 
1999
, vol. 
37
 (pg. 
1421
-
1425
)
Keenan
JP
Nelson
AM
O'Connor
M
Pascual-Leone
A
Self-recognition and the right hemisphere
Nature
 , 
2001
, vol. 
409
 pg. 
305
 
Keenan
JP
Wheeler
MA
Gallup
GG
Pascual-Leone
A
Self recognition and the right prefrontal cortex
Trends Cogn Sci
 , 
2000
, vol. 
4
 (pg. 
338
-
344
)
Keyes
H
Categorical perception effects for facial identity in robustly represented familiar and self-faces: the role of configural and featural information
Q J Exp Psychol
 , 
2012
, vol. 
65
 (pg. 
760
-
772
)
Keyes
H
Brady
N
Self-face recognition is characterized by “bilateral gain” and by faster, more accurate performance which persists when faces are inverted
Q J Exp Psychol
 , 
2010
, vol. 
63
 (pg. 
840
-
847
)
Keyes
H
Brady
N
Reilly
RB
Foxe
JJ
My face or yours? Event-related potential correlates of self-face processing
Brain Cogn
 , 
2010
, vol. 
72
 (pg. 
244
-
254
)
Kiebel
S
Holmes
A
Frackowiak
RSJ
Friston
KJ
Frith
C
Dolan
R
Price
CJ
Zeki
S
Shburner
J
Penny
WD
The general linear model
Human brain function
 , 
2003
2nd ed
London
Academic Press
(pg. 
725
-
760
)
Kircher
T
Senior
C
Phillips
M
Rabe-Hesketh
S
Benson
P
Bullmore
E
Brammer
M
Simmons
A
Bartels
M
David
A
Recognizing one's own face
Cognition
 , 
2001
, vol. 
78
 (pg. 
B1
-
B15
)
Leff
AP
Schofield
TM
Crinion
JT
Seghier
ML
Grogan
A
Green
DW
Price
CJ
The left superior temporal gyrus is a shared substrate for auditory short-term memory and speech comprehension: evidence from 210 patients with stroke
Brain
 , 
2009
, vol. 
132
 (pg. 
3401
-
3410
)
Leslie
AM
Frith
U
Autistic children's understanding of seeing, knowing and believing
B J Develop Psychol
 , 
1988
, vol. 
6
 (pg. 
315
-
324
)
Ma
Y
Han
S
Why respond faster to the self than others? An implicit positive association theory of self advantage during implicit face recognition
J Exp Psychol Human
 , 
2010
, vol. 
36
 (pg. 
619
-
633
)
Ma
Y
Han
S
Functional dissociation of the left and right fusiform gyrus in self-face recognition
Hum Brain Mapp
 , 
2012
, vol. 
33
 (pg. 
2255
-
2267
)
Mevorach
C
Hodsoll
J
Allen
HA
Shalev
L
Humphreys
GW
Ignoring the elephant in the room: a neural circuit to down-regulate salience
J Neurosci
 , 
2010
, vol. 
30
 (pg. 
6072
-
6079
)
Mitchell
JP
Macrae
CN
Banaji
MR
Dissociable medial prefrontal contributions to judgments of similar and dissimilar others
Neuron
 , 
2006
, vol. 
50
 (pg. 
655
-
663
)
Moran
JM
Young
L
Saxe
R
Lee
SM
O'Young
D
Mavros
P
Gabrieli
J
Impaired theory of mind for moral judgement in high-functioning autism
Proc Natl Acad Sci USA
 , 
2011
, vol. 
108
 (pg. 
2688
-
2692
)
Mori
S
Wakana
S
Nagae-Poetscher
LM
van Zijl
PCM
MRI atlas of human white matter
 , 
2005
Amsterdam
Elsevier
Moses
LJ
Executive accounts of theory-of-mind development
Child Dev
 , 
2001
, vol. 
72
 (pg. 
688
-
690
)
Neuman
C
Hill
S
Self-recognition and stimulus preference in autistic children
Dev Psychobiol
 , 
1978
, vol. 
11
 (pg. 
571
-
578
)
Northoff
G
Bermpohl
F
Cortical midline structures and the self
Trends Cogn Sci
 , 
2004
, vol. 
8
 (pg. 
102
-
107
)
Northoff
G
Heinzel
A
de Greck
M
Bermpohl
F
Dobrowolny
H
Panksepp
J
Self-referential processing in our brain—a meta-analysis of imaging studies on the self
Neuroimage
 , 
2006
, vol. 
31
 (pg. 
440
-
457
)
Platek
SM
Gallup
GG
Jr
Self-face recognition is affected by schizotypal personality traits
Schizophr Res
 , 
2002
, vol. 
57
 (pg. 
311
-
315
)
Platek
SM
Keenan
JP
Gallup
GG
Jr
Where am I? The neurological correlates of self and other
Cogn Brain Res
 , 
2004
, vol. 
19
 (pg. 
114
-
122
)
Platek
SM
Loughead
JW
Gur
RC
Busch
S
Ruparel
K
Phend
N
Panyavin
IS
Langleben
DD
Neural substrates for functionally discriminating self-face from personally familiar faces
Hum Brain Mapp
 , 
2006
, vol. 
27
 (pg. 
91
-
98
)
Platek
SM
Wathne
K
Tierney
NG
Thomson
JW
Neural correlates of self-face recognition: an effect-location meta-analysis
Brain Res
 , 
2008
, vol. 
1232
 (pg. 
173
-
184
)
Preilowski
B
Self-recognition as a test of consciousness in left and right hemisphere of “split-brain” patients
Act Nerv Super (Praha)
 , 
1977
, vol. 
19
 
Suppl 2
(pg. 
343
-
344
)
Price
CJ
Mummery
CJ
Moore
CJ
Frakowiak
RS
Friston
KJ
Delineating necessary and sufficient neural systems with functional imaging studies of neuropsychological patients
J Cogn Neurosci
 , 
1999
, vol. 
11
 (pg. 
371
-
382
)
Reddy
V
Williams
E
Costantini
C
Lan
B
Engaging with the self: mirror behaviour in autism, Down syndrome and typical development
Autism
 , 
2010
, vol. 
14
 (pg. 
531
-
546
)
Rochat
P
Striano
T
Who's in the mirror? Self-other discrimination in specular images by four- and nine-month-old infants
Child Dev
 , 
2002
, vol. 
73
 (pg. 
35
-
46
)
Ruff
RL
Volpe
BT
Environmental reduplication associated with right frontal and parietal lobe injury
Neurol Neurosurg Psychiatry
 , 
1981
, vol. 
44
 (pg. 
382
-
386
)
Sabbagh
MA
Xu
F
Carlson
SM
Moses
LJ
Lee
K
The development of executive functioning and theory of mind: a comparison of Chinese and US preschoolers
. Psychol Sci
 , 
2006
, vol. 
17
 (pg. 
74
-
81
)
Saxe
R
Kanwisher
N
People thinking about thinking people. The role of the temporo-parietal junction in “theory of mind”
Neuroimage
 , 
2003
, vol. 
19
 (pg. 
1835
-
1842
)
Seger
CA
Dennison
CS
Lopez-Paniagua
D
Peterson
EJ
Roark
AA
Dissociating hippocampal and basal ganglia contributions to category learning using stimulus novelty and subjective judgments
Neuroimage
 , 
2011
, vol. 
55
 (pg. 
1739
-
1753
)
Seghier
ML
Ramlackhansingh
A
Crinion
J
Leff
AP
Price
CJ
Lesion identification using unified segmentation-normalisation models and fuzzy clustering
Neuroimage
 , 
2008
, vol. 
41
 (pg. 
1253
-
1266
)
Snowden
JS
Griffiths
HL
Neary
D
Semantic-episodic memory interactions in semantic dementia: implications for retrograde memory function
Cogn Neuropsychol
 , 
1996
, vol. 
13
 (pg. 
1101
-
1137
)
Soto
D
Hodsoll
J
Rotshtein
P
Humphreys
GW
Automatic guidance of attention from working memory
Trends Cogn Sci
 , 
2008
, vol. 
23
 (pg. 
342
-
348
)
Sperry
RW
Zaidel
E
Zaidel
D
Self recognition and social awareness in the deconnected minor hemisphere
Neuropsychologia
 , 
1979
, vol. 
17
 (pg. 
153
-
166
)
Spiker
D
Ricks
M
Visual self-recognition in autistic children: developmental relationships
Child Dev
 , 
1984
, vol. 
55
 (pg. 
214
-
225
)
Sugiura
M
Sassa
Y
Jeong
H
Horie
K
Sato
S
Kawashima
R
Face-specific and domain-general characteristics of cortical responses during self-recognition
Neuroimage
 , 
2008
, vol. 
42
 (pg. 
414
-
422
)
Sugiura
M
Sassa
Y
Jeongb
H
Miurab
N
Akitsukib
Y
Horied
K
Satod
S
Kawashima
R
Multiple brain networks for visual self-recognition with different sensitivity for motion and body part
Neuroimage
 , 
2006
, vol. 
32
 (pg. 
1905
-
1917
)
Sugiura
M
Watanabe
J
Maeda
Y
Matsue
Y
Fukuda
H
Kawashima
R
Cortical mechanisms of visual self-recognition
Neuroimage. 2
 , 
2005
, vol. 
4
 (pg. 
143
-
149
)
Sui
J
Chechlacz
M
Humphreys
GW
Dividing the self: distinct neural substrates of task-based and automatic self-prioritization after brain damage
Cognition
 , 
2012
, vol. 
122
 (pg. 
150
-
162
)
Sui
J
Han
S
Self-construal priming modulates neural substrates of self-awareness
Psychol Sci
 , 
2007
, vol. 
18
 (pg. 
861
-
866
)
Sui
J
Hong
Y-Y
Liu
CH
Humphreys
GW
Han
S
Dynamic cultural modulation of neural responses to one's own and friend's faces
Soc Cogn Affect Neurosci
 , 
2012
, vol. 
8
 (pg. 
326
-
332
)
Sui
J
Humphreys
GW
The boundaries of self-face perception: response time distributions, perceptual categories and decision weighting
Vis Cogn
 , 
2013
, vol. 
21
 (pg. 
415
-
445
)
Sui
J
Liu
CH
Han
S
Cultural difference in neural mechanisms of self-recognition
Soc Neurosci
 , 
2009
, vol. 
4
 (pg. 
402
-
411
)
Sui
J
Rotshtein
P
Humphreys
GW
Coupling social attention to the self forms a network for personal significance
Proc Natl Acad Sci USA
 , 
2013
, vol. 
110
 (pg. 
7607
-
7612
)
Sui
J
Zhu
Y
Han
S
Self-face recognition in attended and unattended conditions: an ERP study
NeuroReport
 , 
2006
, vol. 
17
 (pg. 
423
-
427
)
Talyor
MJ
Arsalidou
M
Bayless
SJ
Morris
D
Evans
JW
Barbeau
EJ
Neural correlates of personally familiar faces: parents, partner and own faces
Hum Brain Mapp
 , 
2009
, vol. 
30
 (pg. 
2008
-
2020
)
Tanaka
JW
Curran
T
Porterfield
AL
Collins
D
Activation of preexisting and acquired face representations: the N250 event-related potential as an index of face familiarity
J Cogn Neurosci
 , 
2006
, vol. 
18
 (pg. 
1488
-
1497
)
Thomas
C
Avidan
G
Humphreys
K
Jung
KJ
Gao
F
Behrmann
M
Reduced structural connectivity in ventral visual cortex in congenital prosopagnosia
Nat Neurosci
 , 
2009
, vol. 
12
 (pg. 
29
-
31
)
Tong
F
Nakayama
K
Robust representations for faces: evidence from visual search
J Exp Psychol Human
 , 
1999
, vol. 
25
 (pg. 
1016
-
1035
)
Turk
DJ
Heartherton
TF
Kelley
WM
Funnell
MG
Gazzaniga
MS
Macrae
CN
Mike or me? Self-recognition in a split-brain patient
Nat Neurosci
 , 
2002
, vol. 
5
 (pg. 
841
-
842
)
Uddin
LQ
Brain connectivity and the self: The case of cerebral disconnection
Conscious Cogn
 , 
2011b
, vol. 
20
 (pg. 
94
-
98
)
Uddin
LQ
The self in autism: an emerging view from neuroimaging
Neurocase
 , 
2011a
, vol. 
17
 (pg. 
201
-
208
)
Uddin
LQ
Davies
MS
Scott
AA
Zaidel
E
Bookheimer
SY
Lacoboni
M
Dapretto
M
Neural basis of self and other representation in autism: an fMRI study of self-face recognition
PLoS One
 , 
2008
, vol. 
3
 pg. 
e3526
 
Uddin
LQ
Kaplan
JT
Molnar-Szakacs
I
Zaidel
E
Iacoboni
M
Self-face recognition activates a frontoparietal ‘mirror’ network in the right hemisphere: an event-related fMRI study
Neuroimage
 , 
2005
, vol. 
25
 (pg. 
926
-
935
)
Uddin
LQ
Lacoboni
M
Lange
C
Keenan
JP
The self and social cognition: the role of cortical midline structures and mirror neurons
Trends Cogn Sci
 , 
2007
, vol. 
11
 (pg. 
153
-
157
)
Van den Stock
J
de Gelder
B
De Winter
FL
Van Laere
K
Vandenbulcke
M
A strange face in the mirror. Face-selective self-misidentification in a patient with right lateralized occipito-temporal hypo-metabolism
Cortex
 , 
2012
, vol. 
48
 (pg. 
1088
-
1090
)
Villarego
A
Martin
VP
Moreno-Ramos
T
Camacho-Salas
A
Porta-Etessam
J
Bermejo-Pareja
F
Mirrored-self misidentification in a patient without dementia: evidence for right hemispheric and bifrontal damage
Neurocase
 , 
2011
, vol. 
17
 (pg. 
276
-
284
)
Vocks
S
Busch
M
Gronemeyer
D
Schulte
D
Herpertz
S
Suchan
B
Differential neuronal responses to the self and others in the extrastriate body area and the fusiform body area
Cogn Affect Behav Neurosci
 , 
2010
, vol. 
10
 (pg. 
422
-
429
)
Wang
J
Kitayama
S
Han
S
Sex difference in the processing of task-relevant and task-irrelevant social information: an event-related potential study of familiar face recognition
Brain Res
 , 
2011
, vol. 
1408
 (pg. 
41
-
51
)
Worsley
KJ
Frackowiak
RSJ
Friston
KJ
Frith
C
Developments in random field theory
Human brain function
 , 
2003
Cambridge
Academic Press
(pg. 
881
-
886
)