A Standardized Clinical Data Harmonization Pipeline for Scalable AI Application Deployment (FHIR-DHP): Validation and Usability Study.

Background: Increasing digitalization in the medical domain gives rise to large amounts of health care data, which has the potential to expand clinical knowledge and transform patient care if leveraged through artificial intelligence (AI). Yet, big data and AI oftentimes cannot unlock their full potential at scale, owing to nonstandardized data formats, lack of technical and semantic data interoperability, and limited cooperation between stakeholders in the health care system. Despite the existence of standardized data formats for the medical domain, such as Fast Healthcare Interoperability Resources (FHIR), their prevalence and usability for AI remain limited.

Rapid volumetric brain changes after acute psychosocial stress.

Stress is an important trigger for brain plasticity: Acute stress can rapidly affect brain activity and functional connectivity, and chronic or pathological stress has been associated with structural brain changes. Measures of structural magnetic resonance imaging (MRI) can be modified by short-term motor learning or visual stimulation, suggesting that they also capture rapid brain changes. Here, we investigated volumetric brain changes (together with changes in T1 relaxation rate and cerebral blood flow) after acute stress in humans as well as their relation to psychophysiological stress measures.

Anger regulation choice-The role of age and habitual reappraisal.

The ability to choose emotion regulation strategies in accordance to contextual demands, known as emotion regulation flexibility, is key to healthy adaptation. While recent investigations on spontaneous emotion regulation choice tested the effects of emotional intensity and age using standardized negative pictures with no particular emotional quality, we elicited the discrete emotion of anger with personally relevant autobiographical memories in a sample of 52 younger and 41 older adults. In addition, we included habitual reappraisal as a predictor of emotion regulation choice.

A single dose of escitalopram blunts the neural response in the thalamus and caudate during monetary loss.

Background: Selective serotonin reuptake inhibitors (SSRIs) show acute effects on the neural processes associated with negative affective bias in healthy people and people with depression. However, whether and how SSRIs also affect reward and punishment processing on a similarly rapid time scale remains unclear.

Methods: We investigated the effects of an acute and clinically relevant dose (20 mg) of the SSRI escitalopram on brain response during reward and punishment processing in 19 healthy participants.

Positivity in Younger and in Older Age: Associations With Future Time Perspective and Socioemotional Functioning.

Aging has been associated with a motivational shift to positive over negative information (i.e., positivity effect), which is often explained by a limited future time perspective (FTP) within the framework of socioemotional selectivity theory (SST).

Cortical thickness and resting-state cardiac function across the lifespan: A cross-sectional pooled mega-analysis.

Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting-state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT.

Domain-specific cues improve robustness of deep learning-based segmentation of CT volumes.

Machine learning has considerably improved medical image analysis in the past years. Although data-driven approaches are intrinsically adaptive and thus, generic, they often do not perform the same way on data from different imaging modalities. In particular computed tomography (CT) data poses many challenges to medical image segmentation based on convolutional neural networks (CNNs), mostly due to the broad dynamic range of intensities and the varying number of recorded slices of CT volumes.

A functional connectome phenotyping dataset including cognitive state and personality measures.

The dataset enables exploration of higher-order cognitive faculties, self-generated mental experience, and personality features in relation to the intrinsic functional architecture of the brain. We provide multimodal magnetic resonance imaging (MRI) data and a broad set of state and trait phenotypic assessments: mind-wandering, personality traits, and cognitive abilities. Specifically, 194 healthy participants (between 20 and 75 years of age) filled out 31 questionnaires, performed 7 tasks, and reported 4 probes of in-scanner mind-wandering.

A mind-brain-body dataset of MRI, EEG, cognition, emotion, and peripheral physiology in young and old adults.

We present a publicly available dataset of 227 healthy participants comprising a young (N=153, 25.1±3.1 years, range 20-35 years, 45 female) and an elderly group (N=74, 67.

Association of peripheral blood pressure with gray matter volume in 19- to 40-year-old adults.

Objective: To test whether elevated blood pressure (BP) relates to gray matter (GM) volume (GMV) changes in young adults who had not previously been diagnosed with hypertension (systolic BP [SBP]/diastolic BP [DBP] ≥140/90 mm Hg).

Methods: We associated BP with GMV from structural 3T T1-weighted MRI of 423 healthy adults between 19 and 40 years of age (mean age 27.7 ± 5.