Human face recognition ability is specific and highly heritable.
Ontology highlight
ABSTRACT:
SUBMITTER: Wilmer JB
PROVIDER: S-EPMC2841913 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Previous studies have shown that face-specific recognition ability (FRA) is heritable; however, the neural basis of this heritability is unclear. Candidate gene studies have suggested that the catechol-O-methyltransferase (COMT) rs4680 polymorphism is related to face perception. Here, using a partial least squares (PLS) method, we examined the multivariate association between 12 genotypes of 4 COMT polymorphisms (rs6269-rs4633-rs4818-rs4680) and multimodal MRI phenotypes in the human fusiform face area (FFA), which selectively responds to face stimuli, in 338 Han Chinese adults (mean age 20.45 years; 135 males). The MRI phenotypes included gray matter volume (GMV), resting-state fractional amplitude of low-frequency fluctuations (fALFF), and face-selective blood-oxygen-level-dependent (BOLD) responses (FS). We found that the first COMT-variant component (PLS1) was positively associated with the FS but negatively associated with the fALFF in the FFA. Moreover, participants with the COMT heterozygous-HEA-haplotype showed higher PLS1 FFA-MRI scores, which were positively associated with the FRA in an old/new face recognition task, than those with the COMT homozygous HEA haplotype and HEA non-carriers, suggesting that individuals with an appropriate (intermediate) level of dopamine activity in the FFA might have better FRA. In summary, our study provides empirical evidence for the genetic and neural basis for the heritability of face recognition and informs the formation of neural module functional specificity.
| S-EPMC7005682 | biostudies-literature
Project description:Previous work found a small but significant relationship between holistic processing measured with the composite task and face recognition ability measured by the Cambridge Face Memory Test (CFMT; Duchaine & Nakayama, 2006). Surprisingly, recent work using a different measure of holistic processing (Vanderbilt Holistic Face Processing Test [VHPT-F]; Richler, Floyd, & Gauthier, 2014) and a larger sample found no evidence for such a relationship. In Experiment 1 we replicate this unexpected result, finding no relationship between holistic processing (VHPT-F) and face recognition ability (CFMT). A key difference between the VHPT-F and other holistic processing measures is that unique face parts are used on each trial in the VHPT-F, unlike in other tasks where a small set of face parts repeat across the experiment. In Experiment 2, we test the hypothesis that correlations between the CFMT and holistic processing tasks are driven by stimulus repetition that allows for learning during the composite task. Consistent with our predictions, CFMT performance was correlated with holistic processing in the composite task when a small set of face parts repeated over trials, but not when face parts did not repeat. A meta-analysis confirms that relationships between the CFMT and holistic processing depend on stimulus repetition. These results raise important questions about what is being measured by the CFMT, and challenge current assumptions about why faces are processed holistically.
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Project description:Response times (RTs) are commonly used to assess cognitive abilities, though it is unclear whether face processing RTs predict recognition ability beyond accuracy. In the current study, we examined accuracy and RT on a widely used face matching assessment modified to collect meaningful RT data, the computerized Benton Facial Recognition Test (BFRT-c), and measured whether RTs predicted face recognition ability and developmental prosopagnosia (DP) vs. control group membership. 62 controls and 36 DPs performed the BFRT-c as well as validated measures of face recognition ability: the Cambridge Face Memory Test (CFMT) and a Famous Faces Memory Test (FFMT). In controls, BFRT-c accuracy robustly predicted CFMT (r = .49, p < .001), FFMT (r = .43, p < .001), and a CFMT-FFMT composite (r = .54, p < .001), whereas BFRT-c RT was not significantly associated with these measures (all r's .21). We also found that BFRT-c accuracy significantly differed between DPs and controls, but RT failed to differentiate the groups.
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Project description:Developmental prosopagnosia (DP) is characterised by deficits in face identification. However, there is debate about whether these deficits are primarily perceptual, and whether they extend to other face processing tasks (e.g., identifying emotion, age, and gender; detecting faces in scenes). In this study, 30 participants with DP and 75 controls completed a battery of eight tasks assessing four domains of face perception (identity; emotion; age and gender; face detection). The DP group performed worse than the control group on both identity perception tasks, and one task from each other domain. Both identity perception tests uniquely predicted DP/control group membership, and performance on two measures of face memory. These findings suggest that deficits in DP may arise from issues with face perception. Some non-identity tasks also predicted DP/control group membership and face memory, even when face identity perception was accounted for. Gender perception and speed of face detection consistently predicted unique variance in group membership and face memory; several other tasks were only associated with some measures of face recognition ability. These findings indicate that face perception deficits in DP may extend beyond identity perception. However, the associations between tasks may also reflect subtle aspects of task demands or stimuli.
| S-EPMC10951298 | biostudies-literature
Project description:Regions of the occipital and temporal lobes, including a region in the fusiform gyrus (FG), have been proposed to constitute a "core" visual representation system for faces, in part because they show face selectivity and face repetition suppression. But recent fMRI studies of developmental prosopagnosics (DPs) raise questions about whether these measures relate to face processing skills. Although DPs manifest deficient face processing, most studies to date have not shown unequivocal reductions of functional responses in the proposed core regions. We scanned 15 DPs and 15 non-DP control participants with fMRI while employing factor analysis to derive behavioral components related to face identification or other processes. Repetition suppression specific to facial identities in FG or to expression in FG and STS did not show compelling relationships with face identification ability. However, we identified robust relationships between face selectivity and face identification ability in FG across our sample for several convergent measures, including voxel-wise statistical parametric mapping, peak face selectivity in individually defined "fusiform face areas" (FFAs), and anatomical extents (cluster sizes) of those FFAs. None of these measures showed associations with behavioral expression or object recognition ability. As a group, DPs had reduced face-selective responses in bilateral FFA when compared with non-DPs. Individual DPs were also more likely than non-DPs to lack expected face-selective activity in core regions. These findings associate individual differences in face processing ability with selectivity in core face processing regions. This confirms that face selectivity can provide a valid marker for neural mechanisms that contribute to face identification ability.
| S-EPMC3322334 | biostudies-literature
Project description:BackgroundAlthough face recognition is now well studied, few researchers have considered the nature of forgetting over longer time periods. Here, I investigated how newly learned faces were recognised over the course of one week. In addition, I considered whether self-reported face recognition ability, as well as Big Five personality dimensions, were able to predict actual performance in a recognition task.MethodsIn this experiment (N = 570), faces were learned through short video interviews, and these identities were later presented in a recognition test (using previously unseen images) after no delay, six hours, twelve hours, one day, or seven days.ResultsThe majority of forgetting took place within the first 24 hours, with no significant decrease after that timepoint. Further, self-reported face recognition abilities were moderately predictive of performance, while extraversion showed a small, negative association with performance. In both cases, these associations remained consistent across delay conditions.DiscussionThe current work begins to address important questions regarding face recognition using longitudinal, real-world time intervals, focussing on participant insight into their own abilities, and the process of forgetting more generally.
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Project description:The present study proposes a cognitive prosthesis device for face memory impairment as a proof-of-concept for the domain-specific cognitive prosthesis. Healthy subjects (n = 6) and a patient with poor face memory were enrolled. An acquaintance face recognition test with and without the use of cognitive prosthesis for face memory impairment, face recognition tests, quality of life, neuropsychological assessments, and machine learning performance of the cognitive prosthesis were followed-up throughout four weeks of real-world device use by the patient. The healthy subjects had an accuracy of 92.38 ± 4.41% and reaction time of 1.27 ± 0.12 s in the initial attempt of the acquaintance face recognition test, which changed to 80.48 ± 6.23% (p = 0.06) and 2.11 ± 0.20 s (p < 0.01) with prosthesis use. The patient had an accuracy of 74.29% and a reaction time of 6.65 s, which improved to 94.29% and 3.28 s with prosthesis use. After four weeks, the patient's unassisted accuracy and reaction time improved to 100% and 1.23 s. Functional MRI study revealed activation of the left superior temporal lobe during face recognition task without prosthesis use and activation of the right precentral motor area with prosthesis use. The prosthesis could improve the patient's performance by bypassing the brain area inefficient for facial recognition and employing the area more efficiently for the cognitive task.
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Project description:Face recognition is widely used for security and access control. Its performance is limited when working with highly pigmented skin tones due to training bias caused by the under-representation of darker-skinned individuals in existing datasets and the fact that darker skin absorbs more light and therefore reflects less discernible detail in the visible spectrum. To improve performance, this work incorporated the infrared (IR) spectrum, which is perceived by electronic sensors. We augmented existing datasets with images of highly pigmented individuals captured using the visible, IR, and full spectra and fine-tuned existing face recognition systems to compare the performance of these three. We found a marked improvement in accuracy and AUC values of the receiver operating characteristic (ROC) curves when including the IR spectrum, increasing performance from 97.5% to 99.0% for highly pigmented faces. Different facial orientations and narrow cropping also improved performance, and the nose region was the most important feature for recognition.
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Project description:The ability to recognize people by their voice is an important social behavior. Individuals differ in how they pronounce words, and listeners may take advantage of language-specific knowledge of speech phonology to facilitate recognizing voices. Impaired phonological processing is characteristic of dyslexia and thought to be a basis for difficulty in learning to read. We tested voice-recognition abilities of dyslexic and control listeners for voices speaking listeners' native language or an unfamiliar language. Individuals with dyslexia exhibited impaired voice-recognition abilities compared with controls only for voices speaking their native language. These results demonstrate the importance of linguistic representations for voice recognition. Humans appear to identify voices by making comparisons between talkers' pronunciations of words and listeners' stored abstract representations of the sounds in those words.
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Project description:Why are some individuals better at recognizing faces? Uncovering the neural mechanisms supporting face recognition ability has proven elusive. To tackle this challenge, we used a multimodal data-driven approach combining neuroimaging, computational modeling, and behavioral tests. We recorded the high-density electroencephalographic brain activity of individuals with extraordinary face recognition abilities-super-recognizers-and typical recognizers in response to diverse visual stimuli. Using multivariate pattern analyses, we decoded face recognition abilities from 1 s of brain activity with up to 80% accuracy. To better understand the mechanisms subtending this decoding, we compared representations in the brains of our participants with those in artificial neural network models of vision and semantics, as well as with those involved in human judgments of shape and meaning similarity. Compared to typical recognizers, we found stronger associations between early brain representations of super-recognizers and midlevel representations of vision models as well as shape similarity judgments. Moreover, we found stronger associations between late brain representations of super-recognizers and representations of the artificial semantic model as well as meaning similarity judgments. Overall, these results indicate that important individual variations in brain processing, including neural computations extending beyond purely visual processes, support differences in face recognition abilities. They provide the first empirical evidence for an association between semantic computations and face recognition abilities. We believe that such multimodal data-driven approaches will likely play a critical role in further revealing the complex nature of idiosyncratic face recognition in the human brain.
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