An emerging field of research focused on fluctuations in brain signals has provided evidence that the complexity of those signals, as measured by entropy, conveys important information about network dynamics (e.g., local and distributed processing). While much research has focused on how neural complexity differs in populations with different age groups or clinical disorders, substantially less research has focused on the basic understanding of neural complexity in populations with young and healthy brain states. The present study used resting-state fMRI data from the Human Connectome Project (Van Essen et al., 2013) to test the extent that neural complexity in the BOLD signal, as measured by multiscale entropy 1) would differ from random noise, 2) would differ between four major resting-state networks previously associated with higher-order cognition, and 3) would be associated with the strength and extent of functional connectivity—a complementary method of estimating information processing. We found that complexity in the BOLD signal exhibited different patterns of complexity from white, pink, and red noise and that neural complexity was differentially expressed between resting-state networks, including the default mode, cingulo-opercular, left and right frontoparietal networks. Lastly, neural complexity across all networks was negatively associated with functional connectivity at fine scales, but was positively associated with functional connectivity at coarse scales. The present study is the first to characterize neural complexity in BOLD signals at a high temporal resolution and across different networks and might help clarify the inconsistencies between neural complexity and functional connectivity, thus informing the mechanisms underlying neural complexity.

A potential new clinical disorder is arising due to the addiction to cellphones called nomophobia-or feelings of discomfort or anxiety experienced by individuals when they are unable to use their mobile phones or utilize the conveniences these devices provide. However, before being able to officially classify this disorder as clinically relevant, more research needs to be conducted to determine how nomophobia relates to existing disorders. In a sample of 397 undergraduate students, the present study examined the relationship between the Nomophobia Questionnaire (NMP-Q) and the Obsessiveness Content Scale (OBS) of the Minnesota Multiphasic Personality Inventory-2 (the MMPI-2). Confirmatory factor analysis (CFA) was used to test whether the OBS Content Scale would be related to a one-factor NMP-Q solution (Fig. 1) or a four-factor NMP-Q solution (Fig. 2). Convergent and divergent validity were also investigated. The four-factor model was a better fit than the one-factor model as indicated by most fit indices. The findings showed that the OBS latent variable was correlated with all of the four NMP-Q latent variables. Mixed support was found for convergent validity, but high support was found for the divergent validity of the NMP-Q factors. This study contributes to a growing body of literature seeking to better understand the addictive nature of cellphones and takes a new perspective on addiction research and obsessiveness. These findings provide a better understanding between pre-existing assessments of personality disorders (e.g., obsessiveness) that are emerging from the overuse of mobile phones or the excessive fear of losing one's cell phone.

Tissue classification plays a crucial role in the investigation of normal neural development, brain-behavior relationships, and the disease mechanisms of many psychiatric and neurological illnesses. Ensuring the accuracy of tissue classification is important for quality research and, in particular, the translation of imaging biomarkers to clinical practice. Assessment with the human eye is vital to correct various errors inherent to all currently available segmentation algorithms. Manual quality assurance becomes methodologically difficult at a large scale - a problem of increasing importance as the number of data sets is on the rise. To make this process more efficient, we have developed Mindcontrol, an open-source web application for the collaborative quality control of neuroimaging processing outputs. The Mindcontrol platform consists of a dashboard to organize data, descriptive visualizations to explore the data, an imaging viewer, and an in-browser annotation and editing toolbox for data curation and quality control. Mindcontrol is flexible and can be configured for the outputs of any software package in any data organization structure. Example configurations for three large, open-source datasets are presented: the 1000 Functional Connectomes Project (FCP), the Consortium for Reliability and Reproducibility (CoRR), and the Autism Brain Imaging Data Exchange (ABIDE) Collection. These demo applications link descriptive quality control metrics, regional brain volumes, and thickness scalars to a 3D imaging viewer and editing module, resulting in an easy-to-implement quality control protocol that can be scaled for any size and complexity of study.

This study investigated whether the age-related positivity effect strengthens specific event details in autobiographical memory. Participants retrieved past events or imagined future events in response to neutral or emotional cue words. Older adults rated each kind of event more positively than younger adults, demonstrating an age-related positivity effect. We next administered a source memory test. Participants were given the same cue words and tried to retrieve the previously generated event and its source (past or future). Accuracy on this source test should depend on the recollection of specific details about the earlier generated events, providing a more objective measure of those details than subjective ratings. We found that source accuracy was greater for positive than negative future events in both age groups, suggesting that positive future events were more detailed. In contrast, valence did not affect source accuracy for past events in either age group, suggesting that positive and negative past events were equally detailed. Although ageing can bias people to focus on positive aspects of experience, this bias does not appear to strengthen the availability of details for positive relative to negative past events.