非周期图
萧条(经济学)
心理学
精神科
医学
数学
组合数学
经济
宏观经济学
作者
Carl D. Hacker,Madaline Mocchi,Jiayang Xiao,Brian Metzger,Joshua M. Adkinson,Bailey Pascuzzi,Raissa Mathura,Denise Oswalt,Andrew J. Watrous,Eleonora Bartoli,Anusha Allawala,Victoria Pirtle,Xiaoxu Fan,Isabel A. Danstrom,Ben Shofty,Garrett P. Banks,Yue Zhang,Michelle Armenta-Salas,Koorosh Mirpour,Nicole Provenza
标识
DOI:10.1016/j.bpsc.2024.10.019
摘要
BACKGROUND: A reliable physiological biomarker for major depressive disorder is essential for developing and optimizing neuromodulatory treatment paradigms. In this study, we investigated a passive electrophysiologic biomarker that tracks changes in depressive symptom severity on the order of minutes to hours. METHODS: = 2). This surgical setting allowed for precise temporal and spatial sensitivity in the ventromedial prefrontal cortex, a challenging area to measure. We focused on the aperiodic slope of the power spectral density, a metric that reflects the balance of activity across all frequency bands and may serve as a proxy for excitatory/inhibitory balance in the brain. RESULTS: Our findings demonstrated that shifts in aperiodic slope correlated with depression severity, with flatter (less negative) slopes indicating reduced depression severity. This significant correlation was observed in all 5 participants, particularly in the ventromedial prefrontal cortex. CONCLUSIONS: This biomarker offers a new way to track patient responses to major depressive disorder treatment, thus paving the way for individualized therapies in both intracranial and noninvasive monitoring contexts.
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