Many individuals with major depressive disorder (MDD) experience cognitive dysfunction including impaired cognitive control and negative cognitive styles. Functional connectivity MRI studies of individuals with current MDD have documented altered resting-state connectivity within the default-mode network and across networks. However, no studies to date have evaluated the extent to which impaired connectivity within the cognitive control network (CCN) may be present in remitted MDD (rMDD), nor have studies examined the temporal stability of such attenuation over time. This represents a major gap in understanding stable, trait-like depression risk phenotypes. In the present study, resting-state functional connectivity data were collected from 52 unmedicated young adults with rMDD and 47 demographically-matched healthy controls, using three bilateral seeds in the CCN (dorsolateral prefrontal cortex, inferior parietal lobule, and dorsal anterior cingulate cortex). Mean connectivity within the entire CCN was attenuated among individuals with rMDD, was stable and reliable over time, and was most pronounced from the right dorsolateral prefrontal cortex and right inferior parietal lobule to the three bilateral CCN seeds. Attenuated connectivity in rMDD appeared to be specific to the CCN as opposed to representing attenuated within-network coherence in other networks (e.g., default-mode, salience). In addition, attenuated connectivity within the CCN mediated relationships between rMDD status and cognitive risk factors for depression, including ruminative brooding, pessimistic attributional style, and negative automatic thoughts. Given that these cognitive markers are known predictors of relapse, these results suggest that attenuated connectivity within the CCN could represent a biomarker for trait phenotypes of depression risk.

Objective: To investigate the effects of the BAILAMOSTM dance program on physical activity (PA), cardiorespiratory, and cognitive health. Methods: A parallel, two-armed pilot study was conducted with 57 older Latinos randomized to the BAILAMOSTM dance program ( n = 28) or health education (HE) ( n = 29). We conducted two- and three-way repeated-measures ANOVAs. Results: BAILAMOSTM participants increased participation in leisure moderate-to-vigorous PA (LMVPA) ( F[1,53] = 3.17, p = .048, η2 G = .01) and performance in global cognition relative to HE participants ( F[1,52] = 4.19, p = .045, η2 G = .01). Attendance moderated increases in moderate PA, MVPA, LMVPA, and total PA ( p < .05). Participants of both groups with ≥75% attendance increased participation in PA. Among participants with <75% attendance, BAILAMOSTM participants increased PA relative to HE. Discussion: BAILAMOSTM positively impacted self-reported PA and global cognition in older Latinos. Even smaller doses of dance appear to impact self-reported PA levels.

Aim Impairment in neuropsychological functioning is common in major depressive disorder (MDD), but it is not clear to what degree these deficits are related to risk (e.g., trait), scar, burden, or state effects of MDD. The objective of this study was to use neuropsychological measures, with factor scores in verbal fluency, processing speed, attention, set-shifting, and cognitive control in a unique population of young, remitted, un-medicated, early course individuals with a history of MDD in hopes of identifying putative trait markers of MDD. Methods Youth aged 18-23 in remission from MDD (rMDD; n = 62) and healthy controls (HC; n = 43) were assessed with neuropsychological tests at two time points. These were from four domains of executive functioning, consistent with previous literature as impaired in MDD; verbal fluency and processing speed, conceptual reasoning and set-shifting, processing speed with interference resolution, and cognitive control. Results rMDD youth performed comparably to healthy controls on verbal fluency and processing speed, processing speed with interference resolution, and conceptual reasoning and set-shifting, reliably over time. Individuals with rMDD demonstrated relative decrements in cognitive control at Time 1, with greater stability than HC participants. Conclusion MDD may be characterized by regulatory difficulties that do not pertain specifically to active mood state or fluctuations in symptoms. Deficient cognitive control may represent a trait vulnerability or early course scar of MDD that may prove a viable target for secondary prevention or early remediation

Objective Ubiquitous technologies can be leveraged to construct ecologically relevant metrics that complement traditional psychological assessments. This study aims to determine the feasibility of smartphone-derived real-world keyboard metadata to serve as digital biomarkers of mood. Materials and Methods BiAffect, a real-world observation study based on a freely available iPhone app, allowed the unobtrusive collection of typing metadata through a custom virtual keyboard that replaces the default keyboard. User demographics and self-reports for depression severity (Patient Health Questionnaire-8) were also collected. Using &gt;14 million keypresses from 250 users who reported demographic information and a subset of 147 users who additionally completed at least 1 Patient Health Questionnaire, we employed hierarchical growth curve mixed-effects models to capture the effects of mood, demographics, and time of day on keyboard metadata. Results We analyzed 86 541 typing sessions associated with a total of 543 Patient Health Questionnaires. Results showed that more severe depression relates to more variable typing speed (P &lt; .001), shorter session duration (P &lt; .001), and lower accuracy (P &lt; .05). Additionally, typing speed and variability exhibit a diurnal pattern, being fastest and least variable at midday. Older users exhibit slower and more variable typing, as well as more pronounced slowing in the evening. The effects of aging and time of day did not impact the relationship of mood to typing variables and were recapitulated in the 250-user group. Conclusions Keystroke dynamics, unobtrusively collected in the real world, are significantly associated with mood despite diurnal patterns and effects of age, and thus could serve as a foundation for constructing digital biomarkers.

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