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09/2011; , ISBN: 978-953-307-738-3
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ABSTRACT: Congenital prosopagnosia is a selective deficit in face identification that is present from birth. Previously, behavioral deficits in face recognition and differences in the neuroanatomical structure and functional activation of face processing areas have been documented mostly in separate studies. Here, we propose a neural network model of congenital prosopagnosia which relates behavioral and neuropsychological studies of prosopagnosia to theoretical models of information processing. In this study we trained a neural network with two different algorithms to represent face images. First, we introduced a predisposition towards a decreased network connectivity implemented as a temporal independent component analysis (ICA). This predisposition induced a featural representation of faces in terms of isolated face parts. Second, we trained the network for optimal information encoding using spatial ICA, which led to holistic representations of faces. The network model was then tested empirically in an experiment with ten prosopagnosic and twenty age-matched controls. Participants had to discriminate between faces that were changed either according to the prosopagnosic model of featural representation or to the control model of holistic representation. Compared to controls prosopagnosic participants were impaired only in discriminating holistic changes of faces but showed no impairment in detecting featural changes. In summary, the proposed model presents an empirically testable account of congenital prosopagnosia that links the critical features--a lack of holistic processing at the computational level and a sparse structural connectivity at the implementation level. More generally, our results point to structural differences in the network connectivity as the cause of the face processing deficit in congenital prosopagnosia.
Neural networks: the official journal of the International Neural Network Society 03/2011; 24(6):652-64. · 1.88 Impact Factor
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ABSTRACT: The study investigates long-term recognition memory in congenital prosopagnosia (CP), a lifelong impairment in face identification that is present from birth. Previous investigations of processing deficits in CP have mostly relied on short-term recognition tests to estimate the scope and severity of individual deficits. We firstly report on a controlled test of long-term (one year) recognition memory for faces and objects conducted with a large group of participants with CP. Long-term recognition memory is significantly impaired in eight CP participants (CPs). In all but one case, this deficit was selective to faces and didn't extend to intra-class recognition of object stimuli. In a test of famous face recognition, long-term recognition deficits were less pronounced, even after accounting for differences in media consumption between controls and CPs. Secondly, we combined test results on long-term and short-term recognition of faces and objects, and found a large heterogeneity in severity and scope of individual deficits. Analysis of the observed heterogeneity revealed a dissociation of CP into subtypes with a homogeneous phenotypical profile. Thirdly, we found that among CPs self-assessment of real-life difficulties, based on a standardized questionnaire, and experimentally assessed face recognition deficits are strongly correlated. Our results demonstrate that controlled tests of long-term recognition memory are needed to fully assess face recognition deficits in CP. Based on controlled and comprehensive experimental testing, CP can be dissociated into subtypes with a homogeneous phenotypical profile. The CP subtypes identified align with those found in prosopagnosia caused by cortical lesions; they can be interpreted with respect to a hierarchical neural system for face perception.
PLoS ONE 01/2011; 6(1):e15702. · 4.09 Impact Factor
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ABSTRACT: Prosopagnosia is a selective deficit in facial identification which can be either acquired, (e.g., after brain damage), or present from birth (congenital). The face recognition deficit in prosopagnosia is characterized by worse accuracy, longer reaction times, more dispersed gaze behavior and a strong reliance on featural processing.
We introduce a conceptual model of an apperceptive/associative type of congenital prosopagnosia where a deficit in holistic processing is compensated by a serial inspection of isolated, informative features. Based on the model proposed we investigated performance differences in different face and shoe identification tasks between a group of 16 participants with congenital prosopagnosia and a group of 36 age-matched controls. Given enough training and unlimited stimulus presentation prosopagnosics achieved normal face identification accuracy evincing longer reaction times. The latter increase was paralleled by an equally-sized increase in stimulus presentation times needed achieve an accuracy of 80%. When the inspection time of stimuli was limited (50 ms to 750 ms), prosopagnosics only showed worse accuracy but no difference in reaction time. Tested for the ability to generalize from frontal to rotated views, prosopagnosics performed worse than controls across all rotation angles but the magnitude of the deficit didn't change with increasing rotation. All group differences in accuracy, reaction or presentation times were selective to face stimuli and didn't extend to shoes.
Our study provides a characterization of congenital prosopagnosia in terms of early processing differences. More specifically, compensatory processing in congenital prosopagnosia requires an inspection of faces that is sufficiently long to allow for sequential focusing on informative features. This characterization of dysfunctional processing in prosopagnosia further emphasizes fast and holistic information encoding as two defining characteristics of normal face processing.
PLoS ONE 01/2010; 5(7):e11482. · 4.09 Impact Factor
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ABSTRACT: Congenital prosopagnosia (CP) is defined by a lifelong impairment in face recognition that is present from birth. Subjects with congenital prosopagnosia (CP) show pro-nounced and selective deficits in facial identification but perform normal in different facial categorization tasks (e.g. recognition of facial expressions). We investigated whether the selectivity of this deficit can be explained by structural ("congenital") differences in the representation and the processing of facial information. Based on a single-layer neural network model, independ-ent component analysis (ICA) was used to represent the information contained in face images in two different ways. In temporal ICA, a sparseness assumption on the network connectivity leads to distributed face representa-tions in terms of local features. In spatial ICA, sparseness assumptions on output activations produced a factorial face code based on globally dispersed, holistic features. An experimental comparison of both ICA representations was conducted with a group of 13 CP subjects and 23 age-matched controls. Participants had to judge similarity between an average face and a set of test face images manipulated according to one of the two ICA representa-tions. In comparison to control subjects, participants with CP showed clear deficits in discerning manipulations according to spatial ICA but no significant differences with respect to temporal ICA manipulations. Based on an ICA model of face representation, our results point to structural differences in the network connectivity as the cause of the face-processing deficit in CP. This hypothesis is supported by a recent imaging study which reveals reduced structural connectivity between ventral regions of the visual cortex in CP subjects [1]. Moreover, a computational study Draper et al. [2] compared the per-formance of both ICA architectures and observed worse identity discrimination but better emotion discrimination for temporal ICA. Thus, sparse connectivity can selectively reduce facial information diagnostic for identity discrimi-nation.
