Heart rate variability alterations in late life depression: A meta-analysis.

OBJECTIVE: There is strong evidence for a bi-directional relationship between heart-health and depression in later life, but the physiological mechanisms underlying this relationship remain unclear. Heart rate variability is one promising factor that might help explain this relationship. We present results of a meta-analysis that considers heart rate variability alterations in older adults with depression. METHODS: Literature search of Embase, PsychInfo and Medline revealed five clinical studies and six observational studies that examined the relationship between heart rate variability and depression in adults with a mean age over 60. These studies were included in this meta-analysis. RESULTS: Heart rate variability was reduced among older adults with clinical depression (N = 550), relative to healthy controls (Hedges' g = -0.334, 95%CI [-0.579, -0.090], p = .007). When high-frequency and low-frequency heart rate variability were investigated separately, only low-frequency heart rate variability was significantly reduced in depressed patients (Hedges' g = -0.626, 95%CI [-1.083, -0.169], p = .007). A similar but weaker pattern of results was found in the observational studies. Most findings remained significant among unmedicated depressed older adults. LIMITATIONS: Evidence of effect-size heterogeneity was found in the clinical studies, indicating the need for more well-designed research in the area. CONCLUSION: Heart rate variability is reduced among older adults with depression, and this effect is not fully attributable to antidepressant medication use. Specifically, low-frequency heart rate variability may be reduced in depressed older adults. Heart rate variability warrants further attention, as it could help inform research into the prevention and treatment of depression in later life.

Drosophila learn efficient paths to a food source.

Elucidating the genetic, and neuronal bases for learned behavior is a central problem in neuroscience. A leading system for neurogenetic discovery is the vinegar fly Drosophila melanogaster; fly memory research has identified genes and circuits that mediate aversive and appetitive learning. However, methods to study adaptive food-seeking behavior in this animal have lagged decades behind rodent feeding analysis, largely due to the challenges presented by their small scale. There is currently no method to dynamically control flies' access to food. In rodents, protocols that use dynamic food delivery are a central element of experimental paradigms that date back to the influential work of Skinner. This method is still commonly used in the analysis of learning, memory, addiction, feeding, and many other subjects in experimental psychology. The difficulty of microscale food delivery means this is not a technique used in fly behavior. In the present manuscript we describe a microfluidic chip integrated with machine vision and automation to dynamically control defined liquid food presentations and sensory stimuli. Strikingly, repeated presentations of food at a fixed location produced improvements in path efficiency during food approach. This shows that improved path choice is a learned behavior. Active control of food availability using this microfluidic system is a valuable addition to the methods currently available for the analysis of learned feeding behavior in flies.