Neurobiology of Risk for Bipolar Disorder

Bipolar disorder (BD) is a chronic mental illness which follows a relapsing and remitting course and requires lifetime treatment. The lack of biological markers for BD is a major difficulty in clinical practice. Exploring multiple endophenotypes to fit in multivariate genetic models for BD is an important element in the process of finding tools to facilitate early diagnosis, early intervention, prevention of new episodes, and follow-up of treatment response in BD. Reviewing of studies on neuroimaging, neurocognition, and biochemical parameters in populations with high genetic risk for the illness can yield an integrative perspective on the neurobiology of risk for BD. The most up-to-date data reveals consistent deficits in executive function, response inhibition, verbal memory/learning, verbal fluency, and processing speed in risk groups for BD. Functional magnetic resonance imaging (fMRI) studies report alterations in the activity of the inferior frontal gyrus, medial prefrontal cortex, and limbic areas, particularly in the amygdala in unaffected first-degree relatives (FDR) of BD compared to healthy controls. Risk groups for BD also present altered immune and neurochemical modulation. Despite inconsistencies, accumulating data reveals cognitive and imaging markers for risk and to a less extent resilience of BD. Findings on neural modulation markers are preliminary and require further studies. Although the knowledge on the neurobiology of risk for BD has been inadequate to provide benefits for clinical practice, further studies on structural and functional changes in the brain, neurocognitive functioning, and neurochemical modulation have a potential to reveal biomarkers for risk and resilience for BD. Multimodal, multicenter, population-based studies with large sample size allowing for homogeneous subgroup analyses will immensely contribute to the elucidation of biological markers for risk for BD in an integrative model

Predicting Science Engagement with Motivation and Teacher Characteristics: a Multilevel Investigation

The purpose of this study was to investigate the student and teacher-level predictors of Turkish middle school students' engagement in science classes. Students' engagement was examined in terms of agentic, behavioral, cognitive, and emotional engagement. The participants of the study were 134 Turkish science teachers and their 3394 grade 7 students. Separate multilevel models were specified for each dimension of students' science engagement. Results of the HLM analyses indicated that dimensions of students' science engagement were significantly predicted mostly by the student-level variables including science self-efficacy, mastery approach and avoidance goals, and performance approach goals. Teacher-level variables were influential only on the cognitive and emotional engagement. There were also cross-level interactions in predicting science engagement. Results were discussed in the light of related literature