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To link electrophysiological features to the underlying neurobiology of AD, we prioritized studies that integrated EEG\/MEG with other data modalities, such as positron emission tomography (PET) imaging and\/or fluid biomarkers (cerebrospinal fluid [CSF] or blood\/plasma) of amyloid beta (A\u03b2) and tau. Our analysis contextualizes these findings within current mechanistic hypotheses of AD pathophysiology. A key highlight of the present review is that electrophysiological changes along the AD disease progression may follow a non\u2010monotonic trajectory, underscoring a need for caution when developing biomarkers for early detection or staging the disease with non\u2010invasive electrophysiology. We also discuss outstanding challenges in the interplay between AD pathology and electrophysiological dynamics. This review highlights the potential of multimodal approaches to refining our understanding of AD and improving its early diagnosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>A systematic review of electrophysiological signatures of AD in multimodal studies.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Existing findings are contextualized with AD pathophysiology and neurobiology.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Electrophysiological signatures of AD evolve in a dynamic, non\u2010linear fashion.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>oscillations show a non\u2010monotonous behavior in different stages of AD progression.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>EEG\/MEG biomarkers hold significant promise for the early detection\/monitoring of AD.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.70835","type":"journal-article","created":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T11:17:06Z","timestamp":1762859826000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Tracking electrophysiological signatures of Alzheimer's disease: a systematic review of multimodal studies"],"prefix":"10.1002","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5442-9177","authenticated-orcid":false,"given":"Abbas","family":"Sohrabpour","sequence":"first","affiliation":[{"name":"Athinoula A. 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