guest ::
| Home > Publications database > Apraxic deficits in Alzheimer’s disease are associated with altered dynamic connectivity in praxis-related networks > print |
| Home > Publications database > Apraxic deficits in Alzheimer’s disease are associated with altered dynamic connectivity in praxis-related networks > print |
| 001 | 1050027 | ||
| 005 | 20251219202235.0 | ||
| 024 | 7 | _ | |a 10.1016/j.neurobiolaging.2025.09.007 |2 doi |
| 024 | 7 | _ | |a 0197-4580 |2 ISSN |
| 024 | 7 | _ | |a 1558-1497 |2 ISSN |
| 024 | 7 | _ | |a 10.34734/FZJ-2025-05741 |2 datacite_doi |
| 037 | _ | _ | |a FZJ-2025-05741 |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Kuzu, Taylan D. |0 0000-0003-2146-2442 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Apraxic deficits in Alzheimer’s disease are associated with altered dynamic connectivity in praxis-related networks |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2026 |b Elsevier Science |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1766155207_16742 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 500 | _ | _ | |a THe DFG funded this study. Project ID 431549029 SFB 1451 and Project ID DR445/9-1.Gereon R. Fink and Oezguer A. Onur were supported by the Marga and Walter Boll-Foundation. |
| 520 | _ | _ | |a Apraxia is a common symptom in Alzheimer's disease (AD) that reduces autonomy and quality of life. However, the neural basis underlying apraxia in AD, for example, reflected by functional connectivity (FC) alterations, remains unexplored. We investigated static and dynamic FC using resting-state functional imaging in 14 patients with biomarker-confirmed AD pathology and 14 matched healthy participants. FC was estimated as average (static) and short-term (dynamic) connectivity strengths between motor- and praxis-related functional networks. Recurring connectivity patterns were clustered into dynamic states to compute temporal connectivity measures. Connectivity measures were used for correlations with apraxic deficits. In AD patients, static connectivity between visual and inferior parietal networks correlated with apraxic imitation (r = 0.762, PFDR = 0.043) and arm/hand gesture deficits (r = 0.848, PFDR = 0.020), while dynamic connectivity between these networks correlated with apraxic imitation deficits (r = 0.851, PFDR = 0.020). Dynamic FC analysis revealed a segregated and integrated state. AD patients spent more time overall (fraction time, PFDR < 0.001) and remained longer without switching (dwell time, PFDR = 0.004) in the segregated state. Both fraction (ρ = -0.858, PFDR = 0.015) and dwell time (ρ = -0.914, PFDR = 0.003) correlated with apraxic imitation deficits. Connectivity strengths between visual and inferior parietal networks and fraction time in the segregated state predicted apraxic imitation deficits (adjusted R2 = 0.782, P < 0.001). We conclude that apraxia in AD patients is associated with altered FC in praxis-related networks, suggesting FC as a potential clinical indicator for predicting motor-cognitive deficits.Keywords: Aging; Alzheimer’s disease; Cologne apraxia screening (KAS); Functional magnetic resonance imaging; Motor system; Praxis; Resting-state. |
| 536 | _ | _ | |a 5251 - Multilevel Brain Organization and Variability (POF4-525) |0 G:(DE-HGF)POF4-5251 |c POF4-525 |f POF IV |x 0 |
| 536 | _ | _ | |a DFG project G:(GEPRIS)431549029 - SFB 1451: Schlüsselmechanismen normaler und krankheitsbedingt gestörter motorischer Kontrolle (431549029) |0 G:(GEPRIS)431549029 |c 431549029 |x 1 |
| 588 | _ | _ | |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de |
| 700 | 1 | _ | |a Brinkmann, Elena |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Bonkhoff, Anna K. |0 P:(DE-Juel1)162183 |b 2 |
| 700 | 1 | _ | |a Wunderle, Veronika |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Bischof, Gérard N. |0 P:(DE-Juel1)166265 |b 4 |
| 700 | 1 | _ | |a Giehl, Kathrin |0 P:(DE-Juel1)178805 |b 5 |u fzj |
| 700 | 1 | _ | |a Schmieschek, Maximilian H. T. |0 P:(DE-HGF)0 |b 6 |
| 700 | 1 | _ | |a Onur, Oezguer A. |0 P:(DE-HGF)0 |b 7 |
| 700 | 1 | _ | |a Jessen, Frank |0 P:(DE-HGF)0 |b 8 |
| 700 | 1 | _ | |a Fink, Gereon R. |0 P:(DE-Juel1)131720 |b 9 |u fzj |
| 700 | 1 | _ | |a Drzezga, Alexander |0 P:(DE-Juel1)177611 |b 10 |u fzj |
| 700 | 1 | _ | |a Weiss-Blankenhorn, Peter |0 P:(DE-Juel1)131748 |b 11 |u fzj |
| 773 | _ | _ | |a 10.1016/j.neurobiolaging.2025.09.007 |g Vol. 157, p. 36 - 47 |0 PERI:(DE-600)1498414-3 |p 36 - 47 |t Neurobiology of aging |v 157 |y 2026 |x 0197-4580 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/1050027/files/1-s2.0-S0197458025001691-main.pdf |y OpenAccess |
| 909 | C | O | |o oai:juser.fz-juelich.de:1050027 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 5 |6 P:(DE-Juel1)178805 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 9 |6 P:(DE-Juel1)131720 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 10 |6 P:(DE-Juel1)177611 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 11 |6 P:(DE-Juel1)131748 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-525 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Decoding Brain Organization and Dysfunction |9 G:(DE-HGF)POF4-5251 |x 0 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2024-12-13 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2024-12-13 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2024-12-13 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2024-12-13 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2024-12-13 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b NEUROBIOL AGING : 2022 |d 2024-12-13 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |d 2024-12-13 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2024-12-13 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2024-12-13 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2024-12-13 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2024-12-13 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2024-12-13 |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
| 915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |d 2024-12-13 |w ger |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2024-12-13 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-3-20090406 |k INM-3 |l Kognitive Neurowissenschaften |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)INM-3-20090406 |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|