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Drawing from theories regarding the role of awareness in behavioral self-regulation, this research was designed to examine the role of mindfulness as a moderator between implicit motivation and the motivation for day-to-day behavior. We hypothesized that dispositional mindfulness (Brown and Ryan, J Pers Soc Psychol, 84, 822–848, 2003) would act to modify the expression of implicit autonomy orientation in daily behavioral motivation. Using the Implicit Association Test (Greenwald et al. J Pers Soc Psychol, 74, 1464–1480, 1998), Study 1 provided evidence for the reliability and validity of a new measure of implicit autonomy orientation. Using an experience-sampling strategy, Study 2 showed the hypothesized moderating effect, such that implicit autonomy orientation predicted day-to-day motivation only for those lower in dispositional mindfulness. Those higher in mindfulness showed more autonomously motivated behavior regardless of implicit orientation toward autonomy or heteronomy. It also showed that this moderating effect of awareness was specific to mindfulness and was primarily manifest in spontaneous behavior. Discussion focuses on the implications of these findings for dual process theory and research.

Human beings can be proactive and engaged or, alternatively, passive and alienated, largely as a function of the social conditions in which they develop and function. Accordingly, research guided by self-determination theory has focused on the social–contextual conditions that facilitate versus forestall the natural processes of self-motivation and healthy psychological development. Specifically, factors have been examined that enhance versus undermine intrinsic motivation, self-regulation, and well-being. The findings have led to the postulate of three innate psychological needs—competence, autonomy, and relatedness—which when satisfied yield enhanced self-motivation and mental health and when thwarted lead to diminished motivation and well-being. Also considered is the significance of these psychological needs and processes within domains such as health care, education, work, sport, religion, and psychotherapy.

The tensor-based morphometry (TBM) has been widely used in characterizing tissue volume difference between populations at voxel level. We present a novel computational framework for investigating the white matter connectivity using TBM. Unlike other diffusion tensor imaging (DTI) based white matter connectivity studies, we do not use DTI but only T1-weighted magnetic resonance imaging (MRI). To construct brain network graphs, we have developed a new data-driven approach called the e-neighbor method that does not need any predetermined parcellation. The proposed pipeline is applied in detecting the topological alteration of the white matter connectivity in maltreated children.
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