The Important Role of Motivation and Pleasure Deficits on Social Functioning in Patients With Schizophrenia: A Network Analysis.

Negative symptoms, particularly the motivation and pleasure (MAP) deficits, are associated with impaired social functioning in patients with schizophrenia (SCZ). However, previous studies seldom examined the role of the MAP on social functioning while accounting for the complex interplay between other psychopathology. This network analysis study examined the network structure and interrelationship between negative symptoms (at the "symptom-dimension" and "symptom-item" levels), other psychopathology and social functioning in a sample of 269 patients with SCZ. The psychopathological symptoms were assessed using the Clinical Assessment Interview for Negative Symptoms (CAINS) and the Positive and Negative Syndrome Scale (PANSS). Social functioning was evaluated using the Social and Occupational Functioning Assessment Scale (SOFAS). Centrality indices and relative importance of each node were estimated. The network structures between male and female participants were compared. Our resultant networks at both the "symptom-dimension" and the "symptom-item" levels suggested that the MAP factor/its individual items were closely related to social functioning in SCZ patients, after controlling for the complex interplay between other nodes. Relative importance analysis showed that MAP factor accounted for the largest proportion of variance of social functioning. This study is among the few which used network analysis and the CAINS to examine the interrelationship between negative symptoms and social functioning. Our findings supported the pivotal role of the MAP factor to determine SCZ patients' social functioning, and as a potential intervention target for improving functional outcomes of SCZ.

Validation and extension of the Motivation and Pleasure Scale-Self Report (MAP-SR) across the schizophrenia spectrum in the Chinese context.

BACKGROUND: Developed based on the Clinical Assessment Interview for Negative Symptoms (CAINS), the Motivation and Pleasure Scale-Self Report (MAP-SR) was designed to address the conceptual and psychometric limitations of other instruments assessing negative symptoms. We sought to validate and extend the applicability of the MAP-SR in the Chinese context across the schizophrenia spectrum. METHODS: Three samples, including college students, individuals with social anhedonia and patients with schizophrenia, were recruited. Test-retest reliability, internal consistency, factor structure, and convergent/discriminant validity of the MAP-SR were examined. The group differences between the three participant groups were examined. RESULTS: A four-factor structure of the MAP-SR was found consistently in all three groups of participants. The scale showed convergent/discriminant validity in patients with schizophrenia and individuals with social anhedonia, along with good reliability found in schizophrenia patients. The MAP-SR was also able to distinguish individuals with SocAnh and patients with SZ from matched controls. CONCLUSIONS: The MAP-SR is a valid and reliable instrument in assessing negative symptoms in individuals along the schizophrenia spectrum.

Design and analysis of optimization methods for subdivision surface fitting.

We present a complete framework for computing a subdivision surface to approximate unorganized point sample data, which is a separable nonlinear least squares problem. We study the convergence and stability of three geometrically-motivated optimization schemes and reveal their intrinsic relations with standard methods for constrained nonlinear optimization. A commonly-used method in graphics, called point distance minimization, is shown to use a variant of the gradient descent step and thus has only linear convergence. The second method, called tangent distance minimization, which is well-known in computer vision, is shown to use the Gauss-Newton step, and thus demonstrates near quadratic convergence for zero residual problems but may not converge otherwise. Finally, we show that an optimization scheme called squared distance minimization, recently proposed by Pottmann et al., can be derived from the Newton method. Hence, with proper regularization, tangent distance minimization and squared distance minimization are more efficient than point distance minimization. We also investigate the effects of two step size control methods -- Levenberg-Marquardt regularization and the Armijo rule -- on the convergence stability and efficiency of the above optimization schemes.