Psychobiological factors of resilience and depression in late life.

In contrast to traditional perspectives of resilience as a stable, trait-like characteristic, resilience is now recognized as a multidimentional, dynamic capacity influenced by life-long interactions between internal and environmental resources. We review psychosocial and neurobiological factors associated with resilience to late-life depression (LLD). Recent research has identified both psychosocial characteristics associated with elevated LLD risk (e.g., insecure attachment, neuroticism) and psychosocial processes that may be useful intervention targets (e.g., self-efficacy, sense of purpose, coping behaviors, social support). Psychobiological factors include a variety of endocrine, genetic, inflammatory, metabolic, neural, and cardiovascular processes that bidirectionally interact to affect risk for LLD onset and course of illness. Several resilience-enhancing intervention modalities show promise for the prevention and treatment of LLD, including cognitive/psychological or mind-body (positive psychology; psychotherapy; heart rate variability biofeedback; meditation), movement-based (aerobic exercise; yoga; tai chi), and biological approaches (pharmacotherapy, electroconvulsive therapy). Additional research is needed to further elucidate psychosocial and biological factors that affect risk and course of LLD. In addition, research to identify psychobiological factors predicting differential treatment response to various interventions will be essential to the development of more individualized and effective approaches to the prevention and treatment of LLD

The Neural Mechanisms of Meditative Practices: Novel Approaches for Healthy Aging

ObjectivesMeditation has been shown to have physical, cognitive, and psychological health benefits that can be used to promote healthy aging. However, the common and specific mechanisms of response remain elusive due to the diverse nature of mind-body practices.MethodsIn this review, we aim to compare the neural circuits implicated in focused-attention meditative practices that focus on present-moment awareness to those involved in active-type meditative practices (e.g., yoga) that combine movement, including chanting, with breath practices and meditation.Recent findingsRecent meta-analyses and individual studies demonstrated common brain effects for attention-based meditative practices and active-based meditations in areas involved in reward processing and learning, attention and memory, awareness and sensory integration, and self-referential processing and emotional control, while deactivation was seen in the amygdala, an area implicated in emotion processing. Unique effects for mindfulness practices were found in brain regions involved in body awareness, attention, and the integration of emotion and sensory processing. Effects specific to active-based meditations appeared in brain areas involved in self-control, social cognition, language, speech, tactile stimulation, sensorimotor integration, and motor function.SummaryThis review suggests that mind-body practices can target different brain systems that are involved in the regulation of attention, emotional control, mood, and executive cognition that can be used to treat or prevent mood and cognitive disorders of aging, such as depression and caregiver stress, or serve as "brain fitness" exercise. Benefits may include improving brain functional connectivity in brain systems that generally degenerate with Alzheimer's disease, Parkinson's disease, and other aging-related diseases

Physical Activity and Hippocampal Sub-Region Structure in Older Adults with Memory Complaints.

BackgroundPhysical activity (PA) plays a major role in maintaining cognition in older adults. PA has been shown to be correlated with total hippocampal volume, a memory-critical region within the medial temporal lobe (MTL). However, research on associations between PA and MTL sub-region integrity is limited.ObjectiveTo examine the relationship between PA, MTL thickness, and its sub-regions, and cognitive function in non-demented older adults with memory complaints.MethodsTwenty-nine subjects aged ≥60 years, with memory complaints were recruited for this cross-sectional study. PA was tracked for 7 days using accelerometers, and average number of steps/day determined. Subjects were categorized into two groups: those who walked ≤4000 steps/day (lower PA) and those with >4000 steps/day (higher PA). Subjects received neuropsychological testing and 3T MRI scans. Nonparametric ANCOVAs controlling for age examined differences between the two groups.ResultsTwenty-six subjects aged 72.7(8.1) years completed the study. The higher PA group (n = 13) had thicker fusiform gyrus (median difference = 0.11 mm, effect size (ES) = 1.43, p = 0.001) and parahippocampal cortex (median difference = 0.12 mm, ES = 0.93, p = 0.04) compared to the lower PA group. The higher PA group also exhibited superior performance in attention and information-processing speed (median difference = 0.90, ES = 1.61, p = 0.003) and executive functioning (median difference = 0.97, ES = 1.24, p = 0.05). Memory recall was not significantly different between the two groups.ConclusionOlder non-demented individuals complaining of memory loss who walked >4000 steps each day had thicker MTL sub-regions and better cognitive functioning than those who walked ≤4000 steps. Future studies should include longitudinal analyses and explore mechanisms mediating hippocampal related atrophy

Affective Computing for Late-Life Mood and Cognitive Disorders

Affective computing (also referred to as artificial emotion intelligence or emotion AI) is the study and development of systems and devices that can recognize, interpret, process, and simulate emotion or other affective phenomena. With the rapid growth in the aging population around the world, affective computing has immense potential to benefit the treatment and care of late-life mood and cognitive disorders. For late-life depression, affective computing ranging from vocal biomarkers to facial expressions to social media behavioral analysis can be used to address inadequacies of current screening and diagnostic approaches, mitigate loneliness and isolation, provide more personalized treatment approaches, and detect risk of suicide. Similarly, for Alzheimer\u27s disease, eye movement analysis, vocal biomarkers, and driving and behavior can provide objective biomarkers for early identification and monitoring, allow more comprehensive understanding of daily life and disease fluctuations, and facilitate an understanding of behavioral and psychological symptoms such as agitation. To optimize the utility of affective computing while mitigating potential risks and ensure responsible development, ethical development of affective computing applications for late-life mood and cognitive disorders is needed

Grief, Mindfulness and Neural Predictors of Improvement in Family Dementia Caregivers

Background: Family dementia caregivers often suffer from an immense toll of grief while caring for their loved ones. We sought to identify the clinical relationship between grief, depression and mindfulness and identify neural predictors of symptomatology and improvement.Methods: Twenty three family dementia caregivers were assessed at baseline for grief, mindfulness and depression, of which 17 underwent functional magnetic resonance imaging (fMRI). During fMRI, caregivers were shown faces of either their dementia-stricken relative or that of a stranger, paired with grief-related or neutral words. In nine subjects, post fMRI scans were also obtained after 4 weeks of either guided imagery or relaxation. Robust regression was used to predict changes in symptoms with longitudinal brain activation (BA) changes as the dependent variable.Results: Grief and depression symptoms were correlated (r = 0.50, p = 0.01), and both were negatively correlated with mindfulness (r = −0.70, p = 0.0002; r = −0.52, p = 0.01). Relative to viewing strangers, caregivers showed pictures of their loved ones (picture factor) exhibited increased activation in the dorsal anterior cingulate gyrus and precuneus. Improvement in grief but not mindfulness or depression was predicted by increased relative BA in the precuneus and anterior cingulate (different subregions from baseline). Viewing grief-related vs. neutral words elicited activity in the medial prefrontal cortex and precuneus.Conclusions: Caregiver grief, depression and mindfulness are interrelated but have at least partially nonoverlapping neural mechanisms. Picture and word stimuli related to caregiver grief evoked brain activity in regions previously identified with bereavement grief. These activation foci might be useful as biomarkers of treatment response