Turbulent dynamics and in silico perturbation-based measures are disrupted across biological stages of Alzheimers disease
- 1Pompeu Fabra University
Abstract
According to the AT(N) framework, Alzheimers disease (AD) can be biologically characterised by amyloid deposition, tau pathology, and neurodegeneration, yet how these processes relate to whole-brain dynamics remains unclear. Here, we investigated these relationships and the link between whole-brain dynamics and cognitive dysfunction using multimodal neuroimaging from 145 ADNI3 participants. We combined multiscale measures of turbulent dynamics with responses to in silico perturbations obtained from whole-brain models. AD progression was characterised by a scale-dependent reorganisation of turbulent dynamics where information flow showed the strongest contribution to the dynamics-related variance in cognitive performance. Large-scale turbulence was associated with all three AT(N) components. Model-based information capability and susceptibility measures progressively decreased across AD stages and were associated with amyloid burden and regional tau deposition. Model-free features discriminated comparisons involving AD dementia, whereas adding model-based measures produced modest, metric-dependent changes in classification performance. Exploratory analyses showed spatial alignment between large-scale turbulence alterations and AD-risk gene-expression gradients, with APOE among the strongest associations in both disease-stage contrasts examined. Lastly, we found a progressive decoupling between turbulent dynamics and the E:I balance across AD stages. Together, these findings link model-based and model-free measures of whole-brain dynamics to proteinopathy, neurodegeneration, and cognitive impairment, supporting their complementary value for characterising AD progression.
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BibTeX
@misc{martinezmolina2026turbulent,
title = {{Turbulent dynamics and in silico perturbation-based measures are disrupted across biological stages of Alzheimers disease}},
author = {N. Martinez-Molina and D. Aquilue-Llorens and L. Rass and G. Montana-Valverde and G. Patow and A. Escrichs and Y. Sanz-Perl and M. L. Kringelbach and S. Palva and F. de Maestu and G. Deco},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.12.26365318},
url = {https://www.medrxiv.org/content/10.64898/2026.10.12.26365318v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Turbulent dynamics and in silico perturbation-based measures are disrupted across biological stages of Alzheimers disease
AU - N. Martinez-Molina
AU - D. Aquilue-Llorens
AU - L. Rass
AU - G. Montana-Valverde
AU - G. Patow
AU - A. Escrichs
AU - Y. Sanz-Perl
AU - M. L. Kringelbach
AU - S. Palva
AU - F. de Maestu
AU - G. Deco
PY - 2026
DA - 2026/10/12
PB - medRxiv
DO - 10.64898/2026.10.12.26365318
UR - https://www.medrxiv.org/content/10.64898/2026.10.12.26365318v1
AB - According to the AT(N) framework, Alzheimers disease (AD) can be biologically characterised by amyloid deposition, tau pathology, and neurodegeneration, yet how these processes relate to whole-brain dynamics remains unclear. Here, we investigated these relationships and the link between whole-brain dynamics and cognitive dysfunction using multimodal neuroimaging from 145 ADNI3 participants. We combined multiscale measures of turbulent dynamics with responses to in silico perturbations obtained from whole-brain models. AD progression was characterised by a scale-dependent reorganisation of turbulent dynamics where information flow showed the strongest contribution to the dynamics-related variance in cognitive performance. Large-scale turbulence was associated with all three AT(N) components. Model-based information capability and susceptibility measures progressively decreased across AD stages and were associated with amyloid burden and regional tau deposition. Model-free features discriminated comparisons involving AD dementia, whereas adding model-based measures produced modest, metric-dependent changes in classification performance. Exploratory analyses showed spatial alignment between large-scale turbulence alterations and AD-risk gene-expression gradients, with APOE among the strongest associations in both disease-stage contrasts examined. Lastly, we found a progressive decoupling between turbulent dynamics and the E:I balance across AD stages. Together, these findings link model-based and model-free measures of whole-brain dynamics to proteinopathy, neurodegeneration, and cognitive impairment, supporting their complementary value for characterising AD progression.
ER -