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Updated: Jun 9, 2025

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
Published on: February 14, 2014
Depressive symptoms are linked to age-specific neuroanatomical and cognitive variations
Eyal Bergmann1, Daniel Harlev2, Noham Wolpe3
1Department of Psychiatry, Rambam Health Care Campus, Haifa, Israel; Department of Neuroscience, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States of America.
Abstract:
Depression is a heterogeneous disorder, both in terms of patient symptomatology and in patient sociodemographic factors. Here, we examine the contribution of age to this heterogeneity, by characterizing the associations of depressive symptoms with cognitive performance and brain structure across the lifespan. We analyzed data from the Cambridge Centre for Aging Neuroscience (Cam-CAN) cohort (N = 2591, age 18-99). A subset of this cohort (N = 647) underwent structural MRI. Depressive symptoms were measured using the Hospital Anxiety and Depression Scale. Cognitive assessments were performed using The Addenbrooke's Cognitive Examination Revised. Generalized linear models were employed to examine the relationship between depressive symptoms and cognitive performance. Statistical parametric mapping explored age-dependent associations between depressive symptoms and grey matter volume. Cognitive performance was associated with a significant age by depression by cognitive domain interaction, indicating that older individuals with more depressive symptoms had a lower cognitive performance, particularly in the fluency domain. Structural MRI revealed preferential depression-related reduction in grey matter volume in the left and right hippocampi in older adults. By contrast, in younger adults, depressive symptoms were more strongly associated with grey matter volume reduction in the left superior frontal gyrus and left middle frontal gyrus. Collectively, these findings indicate that the associations of depression with cognitive performance and brain structure are age-dependent, suggesting that the pathophysiological mechanisms underlying depression may differ between young and older adults. Recognizing these differences will support the development of better diagnostic tools and therapeutic interventions for depression across the lifespan.
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