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. 2025 Feb 24;17(1):e70091.
doi: 10.1002/dad2.70091. eCollection 2025 Jan-Mar.

A network perspective on cognition in individuals with Parkinson's disease

Daniel Scharfenberg  1 , Elke Kalbe  1 , Monika Balzer-Geldsetzer  2 , Daniela Berg  3 , Rüdiger Hilker-Roggendorf  4   5 , Jan Kassubek  6 , Inga Liepelt-Scarfone  7   8 , Brit Mollenhauer  9   10 , Kathrin Reetz  11   12 , Oliver Riedel  13 , Sandra Roeske  14 , Jörg B Schulz  11   12 , Alexander Storch  15 , Claudia Trenkwalder  9   10 , Karsten Witt  16   17   18 , Hans-Ulrich Wittchen  19 , Richard Dodel  20 , Anja Ophey  1
Affiliations

A network perspective on cognition in individuals with Parkinson's disease

Daniel Scharfenberg et al. Alzheimers Dement (Amst). .

Abstract

Introduction: In neuropsychological diagnostics, the assignment of cognitive tests to domains is usually not empirically based. Hence, we aimed to assess the dimensionality structure of cognition in individuals with Parkinson's disease (PD) and conceptually replicate the findings in cognitively healthy individuals (CHIs).

Methods: We performed Exploratory Graph Analysis (EGA) for dimensionality analysis of cognitive test scores in N = 698 individuals with PD from the DEMPARK/LANDSCAPE study. Redundancy was reduced based on Unique Variable Analysis (UVA) before re-performing EGA. CHI data (N = 60,398) served as a conceptual replication base.

Results: EGA identified five dimensions. After removing redundancy identified by UVA, EGA identified a unidimensional structure of cognitive test scores. The findings were conceptually replicated in CHIs.

Discussion: The findings imply the need to re-evaluate the composition of cognitive test batteries to reduce redundancy and improve the validity of cognitive diagnostics. Cognition may be better described as a network of interrelated cognitive functions rather than a factorial structure of latent cognitive domains.

Highlights: Cognitive test scores of the same paradigm were strongly associated with each other.This finding indicates redundancy in the cognitive test battery.After removing redundancy, scores were best represented by unidimensional structures.The findings in Parkinson's disease were conceptually replicated in healthy controls.The results suggest that cognition should be viewed as a complex "network" of interrelated functions.

Keywords: Parkinson's disease; cognitive decline; cognitive domains; dimensionality analysis; mutualism hypothesis; network analysis; network neuropsychology.

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Conflict of interest statement

D.S., M.B.G., D.B., R.H.R., B.M., K.R., O.R., S.R., J.B.S., A.S., C.T., H.U.W., R.D., and A.O. have no competing interests to declare. E.K. received grants from the German Ministry of Education and Research, the Joint Federal Committee, and The German Parkinson Foundation, all outside the submitted work. E.K. received honoraria from the companies EISAI GmbH, Germany, memodio GmbH, Germany, Desitin GmbH, Germany, and Prolog GmbH, Germany, all outside the submitted work. J.K. is a consultant and speaker for AbbVie, Bial, Biogen, Desitin, Esteve, Novartis, Roche, STADA, UCB Pharma, and Zambon; in addition, he is Specialty Chief Editor for Frontiers in Neurology (section Applied Neuroimaging) and Associate Editor (Neurology) for Therapeutic Advances in Chronic Disease. I.L.S. reports funding from Bayer AG and travel grants from Desitin and the German Society for Neurology outside the submitted work. K.W. receives funding from the Deutsche Forschungsgemeinschaft (German Research Association) and STADAPHARM GmbH outside the present study. He has received honoraria for presentations/advisory boards/consultations from BIAL, Indorsia, Boston Scientific and STADAPHARM GmbH, outside the present study. He has received royalties from Thieme Press and Elsevier Press. He serves as an editorial board member of Wiley's Parkinson's Disease, Behavioural Neurology, and PLOS One. Author disclosures are available in the Supporting Information.

Figures

FIGURE 1
FIGURE 1
Network and dimensionality structure of cognitive functioning in individuals with PD (A) before and (B) after UVA. Green (solid) edges indicate positive pairwise conditional associations; red (dashed) edges indicate negative conditional associations. Node colors indicate assignment to dimensions as empirically derived by EGA. Values near edges indicate wTO, with wTO >0.20 indicating small‐to‐moderate redundancy, wTO >0.25 indicating moderate‐to‐large redundancy, and wTO >0.30 indicating large‐to‐very‐large redundancy. Values marked in bold indicate wTO is larger than the cutoff of wTO >0.25 for removal of redundant variables. BNT, Boston Naming Test; BTA, Brief Test of Attention; CScat, Modified Wisconsin Card Sorting Test categories; CSnpe, Modified Wisconsin Card Sorting Test non‐perservative errors; CSpe, Modified Wisconsin Card Sorting Test perservative errors; DSbw, Digit Span backwards; DSfw, Digit Span forward; EGA, exploratory graph analysis; FigC, Figures Copying; FigR, Figures Recall; LPS7, Leistungsprüfsystem 7; LPS9, Leistungsprüfsystem 9; PhoWF, phonematic Word Fluency; SemWF, semantic Word Fluency; StrC, Stroop color naming; StrI, Stroop interference; StrW, Stroop word reading; TB/A, Trail Making Test B/A; UVA, unique variable analysis; VbL, Verbal Learning; VbR, Verbal Recall; wTO, weighted topological overlap.
FIGURE 2
FIGURE 2
Network and dimensionality structure of cognitive functioning in CHIs (A) before and (B) after UVA. Green (solid) edges indicate positive pairwise conditional associations; red (dashed) edges indicate negative conditional associations. Node colors indicate assignment to dimensions as empirically derived by EGA. Values near edges indicate wTO, with wTO >0.20 indicating small‐to‐moderate redundancy, wTO >0.25 indicating moderate‐to‐large redundancy, and wTO >0.30 indicating large‐to‐very‐large redundancy. Values marked in bold indicate a wTO larger than the cutoff of wTO >0.25 for removal of redundant variables. BNT, Boston Naming Test; CHIs, cognitively healthy individuals; COD, Coding; DSB, Digit Span backwards; DSF, Digit Span forward; EGA, exploratory graph analysis; LF, Letter fluency; SF, Semantic Fluency; SR‐DR, Story Recall direct recall; SR‐IR, Story Recall immediate recall; TMTA, Trail Making Test part A; TMTB, Trail Making Test part B; UVA, unique variable analysis; VLT‐DR, Auditory Verbal Learning Test delayed recall; VLT‐TR, Auditory Verbal Learning Test total recall; wTO, weighted topological overlap.
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