Medicine (RMH Academic Centre) - Research Publications

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Author: van Rheenen, Tamsyn × End date: 2017 × Start date: 2017 × Type: Journal Article ×

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    Configural and Featural Face Processing Influences on Emotion Recognition in Schizophrenia and Bipolar Disorder
    Van Rheenen, TE ; Joshua, N ; Castle, DJ ; Rossell, SL (CAMBRIDGE UNIV PRESS, 2017-03)
    OBJECTIVES: Emotion recognition impairments have been demonstrated in schizophrenia (Sz), but are less consistent and lesser in magnitude in bipolar disorder (BD). This may be related to the extent to which different face processing strategies are engaged during emotion recognition in each of these disorders. We recently showed that Sz patients had impairments in the use of both featural and configural face processing strategies, whereas BD patients were impaired only in the use of the latter. Here we examine the influence that these impairments have on facial emotion recognition in these cohorts. METHODS: Twenty-eight individuals with Sz, 28 individuals with BD, and 28 healthy controls completed a facial emotion labeling task with two conditions designed to separate the use of featural and configural face processing strategies; part-based and whole-face emotion recognition. RESULTS: Sz patients performed worse than controls on both conditions, and worse than BD patients on the whole-face condition. BD patients performed worse than controls on the whole-face condition only. CONCLUSIONS: Configural processing deficits appear to influence the recognition of facial emotions in BD, whereas both configural and featural processing abnormalities impair emotion recognition in Sz. This may explain discrepancies in the profiles of emotion recognition between the disorders. (JINS, 2017, 23, 287-291).
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    Characterizing cognitive heterogeneity on the schizophrenia-bipolar disorder spectrum
    Van Rheenen, TE ; Lewandowski, KE ; Tan, EJ ; Ospina, LH ; Ongur, D ; Neill, E ; Gurvich, C ; Pantelis, C ; Malhotra, AK ; Rossell, SL ; Burdick, KE (CAMBRIDGE UNIV PRESS, 2017-07)
    BACKGROUND: Current group-average analysis suggests quantitative but not qualitative cognitive differences between schizophrenia (SZ) and bipolar disorder (BD). There is increasing recognition that cognitive within-group heterogeneity exists in both disorders, but it remains unclear as to whether between-group comparisons of performance in cognitive subgroups emerging from within each of these nosological categories uphold group-average findings. We addressed this by identifying cognitive subgroups in large samples of SZ and BD patients independently, and comparing their cognitive profiles. The utility of a cross-diagnostic clustering approach to understanding cognitive heterogeneity in these patients was also explored. METHOD: Hierarchical clustering analyses were conducted using cognitive data from 1541 participants (SZ n = 564, BD n = 402, healthy control n = 575). RESULTS: Three qualitatively and quantitatively similar clusters emerged within each clinical group: a severely impaired cluster, a mild-moderately impaired cluster and a relatively intact cognitive cluster. A cross-diagnostic clustering solution also resulted in three subgroups and was superior in reducing cognitive heterogeneity compared with disorder clustering independently. CONCLUSIONS: Quantitative SZ-BD cognitive differences commonly seen using group averages did not hold when cognitive heterogeneity was factored into our sample. Members of each corresponding subgroup, irrespective of diagnosis, might be manifesting the outcome of differences in shared cognitive risk factors.