{"686611":{"#nid":"686611","#data":{"type":"event","title":"MS Proposal by Liam Hart","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EName: Liam Hart\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EMaster\u2019s Thesis Proposal Meeting\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EData:\u003C\/strong\u003E\u0026nbsp;\u003Cstrong\u003EWednesday, December 10th, 2025\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETime:\u003C\/strong\u003E\u0026nbsp;12:00PM \u2013 2:00PM\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Virtual, Meeting link\u0026nbsp;\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/96679673444?pwd=k8onYs7nbdPcbFjICxS04A7LvQL9Sx.1\u0022 title=\u0022https:\/\/gatech.zoom.us\/j\/96679673444?pwd=k8onYs7nbdPcbFjICxS04A7LvQL9Sx.1\u0022\u003Eclick here\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EThesis Chair\/Advisor\u003C\/strong\u003E:\u003Cbr\u003EHsiao-Wen Liao, Ph.D. (Georgia Tech)\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EThesis Committee Members:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ESashank Varma, Ph.D. (Georgia Tech)\u003C\/p\u003E\u003Cp\u003EAudrey Leroux, Ph.D. (Georgia Tech)\u003C\/p\u003E\u003Cp\u003E\u003Cbr\u003E\u003Cstrong\u003ETitle:\u0026nbsp;Gist-Based Compensation for Age-Related Episodic Decline in Emotional Autobiographical Memory: A Natural Language Analysis of Life\u2019s Highs and Lows\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;Age-related reductions in the episodic specificity of autobiographical memory are well established, whereas gist-based representations and semantic processing remain comparatively preserved in old age. Emerging evidence suggests that older adults may leverage intact semantic memory to compensate for diminished episodic retrieval, drawing on a broader range of semantic knowledge to facilitate detailed recall. Yet it remains unclear whether this compensatory mechanism extends to emotional memories. Socioemotional aging research consistently demonstrates an age-related positivity effect\u2014older adults show a relative preference for positive over negative information, reflecting motivational priorities to maintain a positive emotional state. Theoretical accounts suggest that positive memories often rely more on relational, gist-based processing. Since detailed recall of positive memories align with these emotional goals, this compensatory semantic scaffolding may be especially prominent during the recall of positive events compared to negative ones. The proposed secondary data analysis study evaluates this possibility by analyzing high and low points in the life stories of older adults and testing whether the association between breadth of semantic content and episodic detail is moderated by valence. Topic modeling will be used to quantify semantic breadth, and a validated language model fine-tuned on Autobiographical Interview\u2013scored narratives will provide automated estimates of episodic details. Multilevel models will assess the hypothesized compensatory relationship between semantic breadth and episodic detail, and whether this effect is moderated by memory valence. By integrating cognitive aging and socioemotional selectivity perspectives, this study aims to clarify how preserved semantic memory and emotional goals jointly shape detailed autobiographical remembering in old age.\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EGist-Based Compensation for Age-Related Episodic Decline in Emotional Autobiographical Memory: A Natural Language Analysis of Life\u2019s Highs and Lows\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Gist-Based Compensation for Age-Related Episodic Decline in Emotional Autobiographical Memory: A Natural Language Analysis of Life\u2019s Highs and Lows "}],"uid":"27707","created_gmt":"2025-11-24 19:18:35","changed_gmt":"2025-11-24 19:19:18","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2025-12-10T12:00:00-05:00","event_time_end":"2025-12-10T14:00:01-05:00","event_time_end_last":"2025-12-10T14:00:01-05:00","gmt_time_start":"2025-12-10 17:00:00","gmt_time_end":"2025-12-10 19:00:01","gmt_time_end_last":"2025-12-10 19:00:01","rrule":null,"timezone":"America\/New_York"},"location":"Virtual","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"166866","name":"MS Proposal"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}