Spend time outdoors for your brain - an in-depth longitudinal MRI study.

OBJECTIVES: The effects of nature on physical and mental health are an emerging topic in empirical research with increasing influence on practical health recommendations. Here we set out to investigate the association between spending time outdoors and brain structural plasticity in conjunctions with self-reported affect. METHODS: We established the Day2day study, which includes an unprecedented in-depth assessment of variability of brain structure in a serial sequence of 40-50 structural magnetic resonance imaging (MRI) acquisitions of each of six young healthy participants for 6-8 months (n = 281 MRI scans in total). RESULTS: A whole-brain analysis revealed that time spent outdoors was positively associated with grey matter volume in the right dorsolateral prefrontal cortex and positive affect, also after controlling for physical activity, fluid intake, free time, and hours of sunshine. CONCLUSIONS: Results indicate remarkable and potentially behaviorally relevant plasticity of cerebral structure within a short time frame driven by the daily time spent outdoors. This is compatible with anecdotal evidence of the health and mood-promoting effects of going for a walk. The study may provide the first evidence for underlying cerebral mechanisms of so-called green prescriptions with possible consequences for future interventions in mental disorders.

Day2day: investigating daily variability of magnetic resonance imaging measures over half a year.

BACKGROUND: Most studies of brain structure and function, and their relationships to cognitive ability, have relied on inter-individual variability in magnetic resonance (MR) images. Intra-individual variability is often ignored or implicitly assumed to be equivalent to the former. Testing this assumption empirically by collecting enough data on single individuals is cumbersome and costly. We collected a dataset of multiple MR sequences and behavioural covariates to quantify and characterize intra-individual variability in MR images for multiple individuals. METHODS AND DESIGN: Eight participants volunteered to undergo brain scanning 40-50 times over the course of 6 months. Six participants completed the full set of sessions. T1-weighted, T2*-weighted during rest, T2-weighted high-resolution hippocampus, diffusion-tensor imaging (DTI), and proton magnetic resonance spectroscopy sequences were collected, along with a rich set of stable and time-varying physical, behavioural and physiological variables. Participants did not change their lifestyle or participated in any training programs during the period of data collection. CONCLUSION: This imaging dataset provides a large number of MRI scans in different modalities for six participants. It enables the analysis of the time course and correlates of intra-individual variability in structural, chemical, and functional aspects of the human brain.

Resting-state fMRI correlations: From link-wise unreliability to whole brain stability.

The functional architecture of spontaneous BOLD fluctuations has been characterized in detail by numerous studies, demonstrating its potential relevance as a biomarker. However, the systematic investigation of its consistency is still in its infancy. Here, we analyze within- and between-subject variability and test-retest reliability of resting-state functional connectivity (FC) in a unique data set comprising multiple fMRI scans (42) from 5 subjects, and 50 single scans from 50 subjects. We adopt a statistical framework that enables us to identify different sources of variability in FC. We show that the low reliability of single links can be significantly improved by using multiple scans per subject. Moreover, in contrast to earlier studies, we show that spatial heterogeneity in FC reliability is not significant. Finally, we demonstrate that despite the low reliability of individual links, the information carried by the whole-brain FC matrix is robust and can be used as a functional fingerprint to identify individual subjects from the population.