{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T18:41:17Z","timestamp":1777920077425,"version":"3.51.4"},"reference-count":69,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,12,6]],"date-time":"2020-12-06T00:00:00Z","timestamp":1607212800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"H2020, ECSEL-04-2015-Smart Health, Advancing Smart Optical Imaging and Sensing for Health (ASTONISH)","award":["692470"],"award-info":[{"award-number":["692470"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Alzheimer\u2019s disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal\/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey\u2013Osterrieth complex figure and Raven\u2019s progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.<\/jats:p>","DOI":"10.3390\/e22121380","type":"journal-article","created":{"date-parts":[[2020,12,6]],"date-time":"2020-12-06T22:27:12Z","timestamp":1607293632000},"page":"1380","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Working Memory Decline in Alzheimer\u2019s Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1903-0501","authenticated-orcid":false,"given":"David","family":"Perpetuini","sequence":"first","affiliation":[{"name":"Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5347-8417","authenticated-orcid":false,"given":"Antonio Maria","family":"Chiarelli","sequence":"additional","affiliation":[{"name":"Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2282-3537","authenticated-orcid":false,"given":"Chiara","family":"Filippini","sequence":"additional","affiliation":[{"name":"Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1506-1995","authenticated-orcid":false,"given":"Daniela","family":"Cardone","sequence":"additional","affiliation":[{"name":"Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7279-3052","authenticated-orcid":false,"given":"Pierpaolo","family":"Croce","sequence":"additional","affiliation":[{"name":"Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"given":"Ludovica","family":"Rotunno","sequence":"additional","affiliation":[{"name":"Department of Medicine and Science of Ageing, University G. D\u2019Annunzio, Via Dei Vestini 31, 66100 Chieti, Italy"}]},{"given":"Nelson","family":"Anzoletti","sequence":"additional","affiliation":[{"name":"Department of Medicine and Science of Ageing, University G. D\u2019Annunzio, Via Dei Vestini 31, 66100 Chieti, Italy"}]},{"given":"Michele","family":"Zito","sequence":"additional","affiliation":[{"name":"Department of Medicine and Science of Ageing, University G. D\u2019Annunzio, Via Dei Vestini 31, 66100 Chieti, Italy"}]},{"given":"Filippo","family":"Zappasodi","sequence":"additional","affiliation":[{"name":"Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]},{"given":"Arcangelo","family":"Merla","sequence":"additional","affiliation":[{"name":"Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D\u2019Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1016\/S1474-4422(07)70178-3","article-title":"Research criteria for the diagnosis of Alzheimer\u2019s disease: Revising the NINCDS\u2013ADRDA criteria","volume":"6","author":"Dubois","year":"2007","journal-title":"Lancet Neurol."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Alsunusi, S., Kumosani, T.A., Glabe, C.G., Huwait, E.A., and Moselhy, S.S. (2020). In vitro study of the mechanism of intraneuronal \u03b2-amyloid aggregation in Alzheimer\u2019s disease. Arch. Physiol. 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