Normal aging has been shown to modulate the neural underpinnings of autobiographical memory and emotion processing. Moreover, previous researches have suggested that aging produces a "positivity effect" in autobiographical memory. Although a few imaging studies have investigated the neural mechanism of the positivity effect, the neural substrates underlying the positivity effect in emotional autobiographical memory is unclear. To understand the age-related neural changes in emotional autobiographical memory that underlie the positivity effect, the present functional magnetic resonance imaging (fMRI) study used the independent component analysis (ICA) method to compare brain networks in younger and older adults as they retrieved positive and negative autobiographical events. Compared to their younger counterparts, older adults reported relatively higher positive feelings when retrieving emotional autobiographical events. Imaging data indicated an age-related reversal within the ventromedial prefrontal/anterior cingulate cortex (VMPFC/ACC) and the left amygdala of the brain networks that were engaged in the retrieval of autobiographical events with different valence. The retrieval of negative events compared to positive events induced stronger activity in the VMPFC/ACC and weaker activity in the amygdala for the older adults, whereas the younger adults showed a reversed pattern. Moreover, activity in the VMPFC/ACC within the task-related networks showed a negative correlation with the emotional valence intensity. These results may suggest that the positivity effect in older adults' autobiographical memories is potentially due to age-related changes in controlled emotional processing implemented by the VMPFC/ACC-amygdala circuit.
Pubmed ID: 25177285 RIS Download
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A MATLAB toolbox which implements multiple algorithms for independent component analysis and blind source separation of group (and single subject) functional magnetic resonance imaging data. GIFT works on MATLAB 6.5 and higher. Many ICA algorithms were generously contributed by Dr. Andrzej Cichocki.
View all literature mentionsResearch group based in the Department of Radiology of Wake Forest University School of Medicine devoted to the application of novel image analysis methods to research studies. The ANSIR lab also maintains a fully-automated functional and structural image processing pipeline supporting the image storage and analysis needs of a variety of scientists and imaging studies at Wake Forest. Software packages and toolkits are currently available for download from the ANSIR Laboratory, including: WFU Biological Parametric Mapping Toolbox, WFU_PickAtlas, and Adaptive Staircase Procedure for E-Prime.
View all literature mentionsSoftware package for analysis of brain imaging data sequences. Sequences can be a series of images from different cohorts, or time-series from same subject. Current release is designed for analysis of fMRI, PET, SPECT, EEG and MEG.
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