the ability to suppress irrelevant or interfering stimuli, is a fundamental cognitive function that deteriorates during aging, but little is understood about the bases of decline. Thus, we used event-related functional magnetic resonance imaging (fMRI) to study inhibitory control in healthy adults aged 18 to 78. Activation during "successful inhibition" occurred predominantly in right prefrontal and parietal regions and was more extensive, bilaterally and prefrontally, in the older groups. Presupplementary motor area was also more active in poorer inhibitory performers. Therefore, older adults activate areas that are comparable to those activated by young adults during inhibition, as well as additional regions. The results are consistent with a compensatory interpretation and extend the aging neuroimaging literature into the cognitive domain of inhibition.

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Our understanding of the underlying neurobiology for mood disorders is still limited. We present an integrated model for conceptualizing and understanding mood disorders drawing upon a broad literature pertinent to mood disorders. The integrated model of emotion processing and regulation incorporates the linguistic constructs of the Research Domain Criteria (RDoC) initiative. In particular, we focus on the Positive Valence domain/circuit (PVC), highlighting recent reward research and the Negative Valence domain/circuit (NVC), highlighting rumination. Furthermore, we also illustrate the Cognitive Control and Problem Solving (CCaPS) circuit, which is heavily involved in emotion regulation, as well as the default mode network (DMN) and interactions between circuits. We conclude by proposing methods for addressing challenges in the developmental study of mood disorders including using high-risk design that incorporates risk for many disorders.

Mechanisms and predictors for the successful treatment of anxiety and depression have been elusive, limiting the effectiveness of existing treatments and curtailing the development of new interventions. In this study, we evaluated the utility of three widely used neural probes of emotion (experience, regulation, and perception) in their ability to predict symptom improvement and correlate with symptom change following two first-line treatments-selective serotonin reuptake inhibitors (SSRIs) and cognitive-behavioral therapy (CBT). Fifty-five treatment-seeking adults with anxiety and/or depression were randomized to 12 weeks of SSRI or CBT treatment (ClinicalTrials.gov identifier: NCT01903447). Functional magnetic resonance imaging (fMRI) was used to examine frontolimbic brain function during emotion experience, regulation, and perception, as probed by the Emotion Regulation Task (ERT; emotion experience and regulation) and emotional face assessment task (EFAT; emotion perception). Brain function was then related to anxiety and depression symptom change. Results showed that both SSRI and CBT treatments similarly attenuated insula and amygdala activity during emotion perception, and greater treatment-related decrease in insula and amygdala activity was correlated with greater reduction in anxiety symptoms. Both treatments also reduced amygdala activity during emotion experience but brain change did not correlate with symptom change. Lastly, greater pre-treatment insula and amygdala activity during emotion perception predicted greater anxiety and depression symptom improvement. Thus, limbic activity during emotion perception is reduced by both SSRI and CBT treatments, and predicts anxiety and depression symptom improvement. Critically, neural reactivity during emotion perception may be a non-treatment-specific mechanism for symptom improvement.

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 >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 < .001), shorter session duration (P < .001), and lower accuracy (P < .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.

ClinicalTrials.gov identifier: NCT01903447.

Perturbation-based balance training has shown to induce adaptation of reactive balance responses that can significantly reduce longer-term fall risk in older adults. While specific cortical and subcortical areas in control of posture and locomotion have been identified, little is known about the training-induced plasticity occurring in neural substrates for challenging tasks involving reactive balance control. The purpose of this study was to use functional neuroimaging to examine and determine the neural substrates, if any, involved in inducing adaptation to slip-like perturbations experienced during walking over 3 consecutive training days. We used a mental imagery task to examine the neural changes accompanied by treadmill-slip perturbation training. Ten healthy young adults were exposed to increasing magnitude of displacements during slip-like perturbations while walking, with an acceleration of 6 m/s2 on a motorized treadmill for 3 consecutive days. Brain activity was recorded through MRI while performing imagined slipping and imagined walking tasks before and after the perturbation training. The number of compensatory steps and center of mass state stability at compensatory step touchdown were recorded. As compared with day 1 (first trial), on day 3 (last trial) there was a significant reduction in number of compensatory steps and increase in stability at compensatory step touchdown on the mid and highest perturbation intensities. Before perturbation training, imagined slipping showed increased activity in the SMA, parietal regions, parahippocampal gyrus, and cingulate gyrus compared with rest. After perturbation training, imagined slipping showed increased activation in DLPFC, superior parietal lobule, inferior occipital gyrus, and lingual gyrus. Perturbation training was not associated with decline in activity in any of the brain regions. This study provides evidence for learning-related changes in cortical structures while adapting to slip-like perturbations while walking. The findings reflect that higher-level processing is required for timing and sequencing of movements to execute an effective balance response to perturbations. Specifically, the CNS relies on DLPFC along with motor, parietal, and occipital cortices for adapting to postural tasks posing a significant threat to balance.

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