{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T19:57:18Z","timestamp":1760385438215},"reference-count":48,"publisher":"Cambridge University Press (CUP)","issue":"6","license":[{"start":{"date-parts":[[2015,7,29]],"date-time":"2015-07-29T00:00:00Z","timestamp":1438128000000},"content-version":"unspecified","delay-in-days":28,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Int Neuropsychol Soc"],"published-print":{"date-parts":[[2015,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A symptom of mild cognitive impairment (MCI) and Alzheimer\u2019s disease\n                    (AD) is a flat learning profile. Learning slope calculation methods vary, and\n                    the optimal method for capturing neuroanatomical changes associated with MCI and\n                    early AD pathology is unclear. This study cross-sectionally compared four\n                    different learning slope measures from the Rey Auditory Verbal Learning Test\n                    (simple slope, regression-based slope, two-slope method, peak slope) to\n                    structural neuroimaging markers of early AD neurodegeneration (hippocampal\n                    volume, cortical thickness in parahippocampal gyrus, precuneus, and lateral\n                    prefrontal cortex) across the cognitive aging spectrum [normal\n                    control (NC); (<jats:italic>n<\/jats:italic>=198;\n                    age=76\u00b15), MCI (<jats:italic>n<\/jats:italic>=370;\n                    age=75\u00b17), and AD (<jats:italic>n<\/jats:italic>=171;\n                    age=76\u00b17)] in ADNI. Within diagnostic group,\n                    general linear models related slope methods individually to neuroimaging\n                    variables, adjusting for age, sex, education, and APOE4 status. Among MCI,\n                    better learning performance on simple slope, regression-based slope, and late\n                    slope (Trial 2\u20135) from the two-slope method related to larger\n                    parahippocampal thickness (all <jats:italic>p<\/jats:italic>-values&lt;.01) and\n                    hippocampal volume (<jats:italic>p<\/jats:italic>&lt;.01). Better regression-based\n                    slope (<jats:italic>p<\/jats:italic>&lt;.01) and late slope\n                    (<jats:italic>p<\/jats:italic>&lt;.01) were related to larger ventrolateral\n                    prefrontal cortex in MCI. No significant associations emerged between any slope\n                    and neuroimaging variables for NC (<jats:italic>p<\/jats:italic>-values \u2265.05) or\n                    AD (<jats:italic>p<\/jats:italic>-values \u2265.02). Better learning performances\n                    related to larger medial temporal lobe (i.e., hippocampal volume,\n                    parahippocampal gyrus thickness) and ventrolateral prefrontal cortex in MCI\n                    only. Regression-based and late slope were most highly correlated with\n                    neuroimaging markers and explained more variance above and beyond other common\n                    memory indices, such as total learning. Simple slope may offer an acceptable\n                    alternative given its ease of calculation. (<jats:italic>JINS<\/jats:italic>, 2015,\n                        <jats:italic>21<\/jats:italic>, 455\u2013467)<\/jats:p>","DOI":"10.1017\/s1355617715000430","type":"journal-article","created":{"date-parts":[[2015,7,29]],"date-time":"2015-07-29T05:06:01Z","timestamp":1438146361000},"page":"455-467","source":"Crossref","is-referenced-by-count":36,"title":["Associations between Verbal Learning Slope and Neuroimaging Markers\n                    across the Cognitive Aging Spectrum"],"prefix":"10.1017","volume":"21","author":[{"given":"Katherine A.","family":"Gifford","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey S.","family":"Phillips","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lauren R.","family":"Samuels","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elizabeth 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Jr. , Jagust W.J. , Trojanowski J.Q. , Shaw L. , & Schmidt M . (2010). The Alzheimer\u2019s disease neuroimaging initiative: Progress report and future plans. 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