Four-Week Mentalizing Imagery Therapy for Family Dementia Caregivers: A Randomized Controlled Trial with Neural Circuit Changes.

INTRODUCTION: Family caregivers of patients with dementia suffer a high burden of depression and reduced positive emotions. Mentalizing imagery therapy (MIT) provides mindfulness and guided imagery skills training to improve balanced mentalizing and emotion regulation. OBJECTIVE: Our aims were to test the hypotheses that MIT for family caregivers would reduce depression symptoms and improve positive psychological traits more than a support group (SG), and would increase dorsolateral prefrontal cortex (DLPFC) connectivity and reduce subgenual anterior cingulate cortex (sgACC) connectivity. METHODS: Forty-six caregivers participated in a randomized controlled trial comparing a 4-week MIT group (n = 24) versus an SG (n = 22). Resting state neuroimaging was obtained at baseline and post-group in 28 caregivers, and questionnaires completed by all participants. The primary outcome was change in depression; secondary measures included anxiety, mindfulness, self-compassion, and well-being. Brain networks with participation of DLPFC and sgACC were identified. Connectivity strengths of DLPFC and sgACC with respective networks were determined with dual regression. DLPFC connectivity was correlated with mindfulness and depression outcomes. RESULTS: MIT significantly outperformed SG in improving depression, anxiety, mindfulness, self-compassion, and well-being, with moderate to large effect sizes. Relative to SG, participants in MIT showed significant increases in DLPFC connectivity - exactly replicating pilot study results - but no change in sgACC. DLPFC connectivity change correlated positively with mindfulness and negatively with depression change. CONCLUSIONS: In this trial, MIT was superior to SG for reducing depression and anxiety symptoms and improving positive psychological traits. Neuroimaging results suggested that strengthening DLPFC connectivity with an emotion regulation network might be mechanistically related to MIT effects.

Abnormal Brain Bioenergetics in First-Episode Psychosis.

BACKGROUND: Converging evidence indicates impaired brain energy metabolism in schizophrenia and other psychotic disorders. Creatine kinase (CK) is pivotal in providing adenosine triphosphate in the cell and maintaining its levels when energy demand is increased. However, the activity of CK has not been investigated in patients with first-episode schizophrenia spectrum disorders. METHODS: Using in vivo phosphorus magnetization transfer spectroscopy, we measured CK first-order forward rate constant (k f ) in the frontal lobe, in patients with first-episode psychosis (FEP; n = 16) and healthy controls (n = 34), at rest. RESULTS: CK k f was significantly reduced in FEP compared to healthy controls. There were no differences in other energy metabolism-related measures, including phosphocreatine (PCr) or ATP, between groups. We also found increase in glycerol-3-phosphorylcholine, a putative membrane breakdown product, in patients. CONCLUSIONS: The results of this study indicate that brain bioenergetic abnormalities are already present early in the course of schizophrenia spectrum disorders. Future research is needed to identify the relationship of reduced CK k f with psychotic symptoms and to test treatment alternatives targeting this pathway. Increased glycerol-3-phosphorylcholine is consistent with earlier studies in medication-naïve patients and later studies in first-episode schizophrenia, and suggest enhanced synaptic pruning.

Functional Connectivity-Based Parcellation of the Thalamus: An Unsupervised Clustering Method and Its Validity Investigation.

Node definition or delineating how the brain is parcellated into individual functionally related regions is the first step to accurately map the human connectome. As a result, parcellation of the human brain has drawn considerable attention in the field of neuroscience. The thalamus is known as a relay in the human brain, with its nuclei sending fibers to the cortical and subcortical regions. Functional magnetic resonance imaging techniques offer a way to parcellate the thalamus in vivo based on its connectivity properties. However, the parcellations from previous studies show that both the number and the distribution of thalamic subdivisions vary with different cortical segmentation methods. In this study, we used an unsupervised clustering method that does not rely on a priori information of the cortical segmentation to parcellate the thalamus. Instead, this approach is based on the intrinsic resting-state functional connectivity profiles of the thalamus with the whole brain. A series of cluster solutions were obtained, and an optimal solution was determined. Furthermore, the validity of our parcellation was investigated through the following: (1) identifying specific resting-state connectivity patterns of thalamic parcels with different brain networks and (2) investigating the task activation and psychophysiological interactions of specific thalamic clusters during 8-Hz flashing checkerboard stimulation with simultaneous finger tapping. Together, the current study provides a reliable parcellation of the thalamus and enhances our understating of thalamic. Furthermore, the current study provides a framework for parcellation that could be potentially extended to other subcortical and cortical regions.