Fractionating the Rey Auditory Verbal Learning Test: Distinct roles of large-scale cortical networks in prodromal Alzheimer's disease. (June 2019)

• Record Type: Journal Article
• Authors: Putcha, Deepti; Brickhouse, Michael; Wolk, David A.; Dickerson, Bradford C.
• Is Part Of: Neuropsychologia. Volume 129(2019)
• Page Start: 83
• Page End: 92
• Publication Date: 2019-06
• Subjects: Mild cognitive impairment -- Verbal episodic memory -- Neurodegeneration -- Cortical networks; Neuropsychology -- Periodicals; Neurology -- Periodicals; Psychophysiology -- Periodicals; Neuropsychologie -- Périodiques; Neuropsychology; Periodicals; Electronic journals; 616.8
• DOI: 10.1016/j.neuropsychologia.2019.03.015
• Languages: English
• ISSNs: 0028-3932

Abstract

Abstract: Successful episodic memory calls upon a number of different cognitive processes that are supported by the coordination of several large-scale cortical networks. Previous work from our group has demonstrated dissociable anatomic substrates at different stages of memory in patients with dementia due to Alzheimer's disease (AD). The aim of the current study was to extend the understanding of brain-behavior associations underlying a commonly administered neuropsychological assessment of verbal episodic memory (Rey Auditory Verbal Learning Test; RAVLT) by determining the cortical network contributions to the performance at early vs. late stages of list learning, delayed recall, and retention, in 235 very mild biomarker positive (A+/T+/N+) individuals diagnosed with amnestic mild cognitive impairment (aMCI; MMSE = 27.7). We measured cortical atrophy in four large-scale cortical networks impacted by AD: default mode (DMN), dorsal attention (DAN), frontoparietal (FPN), and language (LN) networks. We also evaluated the role of hippocampal atrophy at each stage of memory performance. Partial correlation analyses controlling for age, sex, and education and corrected for multiple comparisons revealed that early learning was most strongly associated with cortical thickness in the DAN, while late learning was most strongly associated with hippocampal volume, but also related to cortical thickness in the DAN, FPN, DMN, and LN. Delayed recall was associated most strongly with hippocampal volume, but was also related to cortical thickness in the FPN and DMN, while retention was associated only with hippocampal volume. These findings are consistent with prior models of the neural substrates of different stages of verbal list learning and retrieval, provide new insights into the cortical networks undergoing neurodegeneration even at very mild stages of prodromal AD, and inform our thinking about the networks and regions being interrogated by this kind of neuropsychological assessment of episodic memory. Highlights: Early learning is associated with cortical thickness in the dorsal attention network, and not with hippocampal volume. Late learning is associated with hippocampal volume, but also to cortical thickness in the distributed cortical networks. Delayed recall is associated with hippocampal volume and thickness in the frontoparietal and default mode networks. Retention is associated only with hippocampal volume. These findings provide new insights into the cortical networks undergoing neurodegeneration in prodromal AD.