Looking beyond the face area: lesion network mapping of prosopagnosia

Abstract

Damage to the right fusiform face area can disrupt the ability to recognize faces, a classic example of how damage to a specialized brain region can disrupt a specialized brain function. However, similar symptoms can arise from damage to other brain regions, and face recognition is now thought to depend on a distributed brain network. The extent of this network and which regions are critical for facial recognition remains unclear. Here, we derive this network empirically based on lesion locations causing clinically significant impairments in facial recognition. Cases of acquired prosopagnosia were identified through a systematic literature search and lesion locations were mapped to a common brain atlas. The network of brain regions connected to each lesion location was identified using resting state functional connectivity from healthy participants (n = 1000), a technique termed lesion network mapping. Lesion networks were overlapped to identify connections common to lesions causing prosopagnosia. Reproducibility was assessed using split-half replication. Specificity was assessed through comparison with non-specific control lesions (n = 135) and with control lesions associated with symptoms other than prosopagnosia (n = 155). Finally, we tested whether our facial recognition network derived from clinically evident cases of prosopagnosia could predict subclinical facial agnosia in an independent lesion cohort (n = 31). Our systematic literature search identified 44 lesions causing prosopagnosia, only 29 of which intersected the right fusiform face area. However, all 44 lesion locations fell within a single brain network defined by connectivity to the right fusiform face area. Less consistent connectivity was found to other face-selective regions. Surprisingly, all 44 lesion locations were also functionally connected, through negative correlation, with regions in the left frontal cortex. This connectivity pattern was highly reproducible and specific to lesions causing prosopagnosia. Positive connectivity to the right fusiform face area and negative connectivity to left frontal regions were independent predictors of prosopagnosia and predicted subclinical facial agnosia in an independent lesion cohort. We conclude that lesions causing prosopagnosia localize to a single functionally connected brain network defined by connectivity to the right fusiform face area and to left frontal regions. Implications of these findings for models of facial recognition deficits are discussed.

Keywords: functional connectivity; lesion network mapping; prosopagnosia; stroke; symptom prediction.

Figure 1

PRISMA flow chart identifying possible lesion locations causing acquired prosopagnosia. We identified patients with acquired prosopagnosia via a PubMed search for ‘prosopagnosia AND stroke’ and by collecting articles referred to by that initial set of papers. Inclusion criteria included description of acquired prosopagnosia from a focal brain lesion and published images of the brain lesion of sufficient quality to allow transfer of the lesion’s location onto a standardized brain atlas. Forty-four subjects across 19 studies met these criteria.

Figure 2

Lesions causing acquired prosopagnosia varied in location. Lesions from 44 patients with acquired prosopagnosia were identified from a systematic literature search or from cases seen by the authors and traced onto a common brain atlas (MNI sixth generation atlas). Twenty-nine lesions intersected an a priori right FFA (A), as shown by four representative lesions (B). Fifteen lesions did not intersect an a priori right FFA (C), demonstrated by four representative lesions (D). In all images, lesion locations are shown in red while the a priori right FFA region is shown as a blue outline.

Figure 3

Lesion network mapping identified consistent regions connected to all lesions causing acquired prosopagnosia. Lesions were traced onto a standardized MNI brain template (A). Brain regions functionally connected to each lesion location were then obtained using a large resting state functional connectivity database (B). Overlap of thresholded functional connectivity maps (t > 9) from each lesion identified brain regions connected to the greatest number of lesion locations (C). Of note, consistent connectivity to the right FFA was still observed from lesion locations that did not intersect the right FFA (D). In all images, the a priori right FFA region is shown as a blue outline.

Figure 4

Split-half replication revealed a consistent pattern of lesion connectivity. A random division of our lesion sample into two independent subsets (A and C) demonstrated high reproducibility for lesion network overlap results. Consistent lesion network mapping regions identified from Subset 1, including the right FFA, the left anterior prefrontal cortex (APFC), the left middle frontal gyrus (MFG), the dorsal anterior cingulate cortex (ACC), and the left superior frontal gyrus (SFG), were also highly correlated with the lesions in Subset 2 (B), and vice versa for regions identified from Subset 2, with lesions from Subset 1 (D). Results are displayed at an overlap threshold of 75% to best illustrate the similarities across the two subsets. In all images, the a priori right FFA region is shown as a blue outline. All correlation distributions are significantly different from zero, P < 0.001. Red lines in box-plots indicate medians while stars indicate means. ROIs = regions of interest.

Figure 5

Connectivity to the right FFA and left frontal cortex is specific to lesions causing acquired prosopagnosia compared to control lesions and lesions causing other syndromes. Using our entire cohort of lesions causing prosopagnosia (n = 44), all lesion locations demonstrated positive and negative correlation to a specific set of locations (A). This pattern of connectivity was specific to lesions causing prosopagnosia compared to a large cohort of control lesions causing non-specific symptoms (B) or to lesions causing specific symptoms other than prosopagnosia (C). The conjunction of our sensitivity and specificity analyses (D) identified five locations including the right FFA, the left anterior prefrontal cortex (APFC), the left middle frontal gyrus (MFG), the dorsal anterior cingulate cortex (ACC), and the left superior frontal gyrus (SFG). In all images, the a priori right FFA region is shown as a blue outline.

Figure 6

Identified left frontal regions overlapped with previously identified frontoparietal control networks. Left frontal regions from the lesion network mapping of acquired prosopagnosia overlap with (A) the frontoparietal control network described in Vincent et al. (2008), (B) functional connectivity based parcellation of the brain into major components (Yeo et al., 2011), and (C) independent component analysis of resting state data (Smith et al., 2009).

Figure 7

Different a priori face-selective regions of interest show different connectivity to lesion locations causing prosopagnosia. Nine regions of interest previously associated with face-selective activity are displayed on transverse brain slices (red regions). The bar height above each region shows the percentage of prosopagnosia lesion locations functionally connected to that region. The right fusiform face area (rFFA) is the only region connected to >95% of acquired prosopagnosia lesions (red line). F-values below each region label reflect the specificity of this connectivity compared to control lesions (post hoc one-way ANOVAs) (Supplementary Fig. 5). Asterisks denote statistical significance of these F-values: ⁺P < 0.05, *P < 0.0001, **P < 1 × 10⁻²⁵, ***P < 1 × 10⁻³⁵. The right FFA is the most sensitive and the most specific connection for prosopagnosia lesions. AMG = amygdala; IFG = inferior frontal gyrus; l = left; OFA = occipital face area; r = right; STS = superior temporal sulcus.

Figure 8

Lesion connectivity with the right FFA and left frontal cortex predicted subclinical facial agnosia. The intersection of positive connectivity with our identified right FFA (red shading) and negative connectivity with our left frontal regions (blue shading) defined a specific network of areas (purple shading) (A) highly likely to cause prosopagnosia if lesioned. Posterior cerebral artery strokes from an independent dataset that were associated with subclinical facial agnosia (B), versus lesions associated with intact facial perception (C), were significantly more likely to intersect this network (D). (**P < 0.01). Red lines in box-plots indicate medians while stars indicate means.