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Pattern recognition approaches to the analysis of neuroimaging data have brought new applications such as the classification of patients and healthy controls within reach. In our view, the reliance on expensive neuroimaging techniques which are not well tolerated by many patient groups and the inability of most current biomarker algorithms to accommodate information about prior class frequencies (such as a disorder's prevalence in the general population) are key factors limiting practical application. To overcome both limitations, we propose a probabilistic pattern recognition approach based on cheap and easy-to-use multi-channel near-infrared spectroscopy (fNIRS) measurements. We show the validity of our method by applying it to data from healthy controls (n = 14) enabling differentiation between the conditions of a visual checkerboard task. Second, we show that high-accuracy single subject classification of patients with schizophrenia (n = 40) and healthy controls (n = 40) is possible based on temporal patterns of fNIRS data measured during a working memory task. For classification, we integrate spatial and temporal information at each channel to estimate overall classification accuracy. This yields an overall accuracy of 76% which is comparable to the highest ever achieved in biomarker-based classification of patients with schizophrenia. In summary, the proposed algorithm in combination with fNIRS measurements enables the analysis of sub-second, multivariate temporal patterns of BOLD responses and high-accuracy predictions based on low-cost, easy-to-use fNIRS patterns. In addition, our approach can easily compensate for variable class priors, which is highly advantageous in making predictions in a wide range of clinical neuroimaging applications. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.
Interpretation bias and dysfunctional social assumptions are proposed to play a pivotal role in the development and maintenance of social phobia (SP), especially in youth. In this study, we aimed to investigate disorder-specific implicit assumptions of rejection and implicit interpretation bias in youth with severe, chronic SP and healthy controls (CG). Twenty-seven youth with SP in inpatient/day-care treatment (M age = 15.6 years, 74% female) and 24 healthy controls (M age = 15.7 years, 54% female) were included. The Implicit Association Test (IAT) and the Affect Misattribution Procedure (AMP) were completed to assess implicit assumptions and interpretation bias related to the processing of social and affective stimuli. No group differences were observed for the IAT controlling for depressive symptoms in the analyses. However, group differences were found regarding interpretation bias (p = .017, η2p = .137). Correlations between implicit scores and explicit questionnaire results were medium to large in the SP group (r =|.28| to |.54|, pall ≤ .05), but lower in the control group (r =|.04| to |.46|, pall ≤ .05). Our results confirm the finding of an interpretation bias in youth SP, especially regarding the implicit processing of faces, whereas implicit dysfunctional social assumptions of being rejected do not seem to be specific for SP. Future research should investigate the causal relationship of assumptions/interpretation bias and SP.
Attention-deficit/hyperactivity disorder (ADHD) is often accompanied by problems in social behaviour, which are sometimes similar to some symptoms of autism-spectrum disorders (ASD). However, neuronal mechanisms of ASD-like deficits in ADHD have rarely been studied. The processing of biological motion–recently discussed as a marker of social cognition–was found to be disrupted in ASD in several studies. Thus in the present study we tested if biological motion processing is disrupted in ADHD. We used 64-channel EEG and spatio-temporal source analysis to assess event-related potentials associated with human motion processing in 21 children and adolescents with ADHD and 21 matched typically developing controls. On the behavioural level, all subjects were able to differentiate between human and scrambled motion. But in response to both scrambled and biological motion, the N200 amplitude was decreased in subjects with ADHD. After a spatio-temporal dipole analysis, a human motion specific activation was observable in occipital-temporal regions with a reduced and more diffuse activation in ADHD subjects. These results point towards neuronal determined alterations in the processing of biological motion in ADHD.
