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Record W4407986124 · doi:10.1101/2025.02.25.25322663

Unveiling paths to Alzheimer’s disease: excitation-inhibition ratio shapes hierarchical dynamics

2025· preprint· en· W4407986124 on OpenAlexaff
Francesca Saviola, A. Ferrari, Daniele Corbo, Michela Pievani, Silvia Saglia, Annamaria Cattaneo, Ilari D’Aprile, Giulia Quattrini, Valentina Cantoni, Enrico Premi, Barbara Borroni, Roberto Gasparotti

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsDynamics (music)ExcitationDiseaseNeuroscienceComputer scienceMedicinePsychologyPhysicsInternal medicineAcoustics

Abstract

fetched live from OpenAlex

Abstract Alzheimer’s disease is marked by cognitive and memory impairment, with early disruptions in the balance between excitatory and inhibitory neurotransmission, thought to be closely linked to co-occurrent brain changes. The posterior-to-anterior hypothesis posits that functional neurodegeneration begins in critical areas of the default mode network, particularly the hippocampus and posterior cingulate cortex, before extending to more anterior brain regions. This study seeks to evaluate how cortical hierarchy, measured with functional connectivity proxies for excitation/inhibition equilibrium, shapes across the continuum from cognitively unimpaired individuals to symptomatic Alzheimer’s disease. We include 97 participants: 28 patients (including 20 carriers of the Apolipoprotein E allele, ɛ4+), 35 at-risk individuals (ɛ4+), and 34 controls (ɛ4-). Resting-state functional MRI and T1-weighted imaging were collected for all subjects, with a subset of Alzheimer’s patients also undergoing GABA-edited magnetic resonance spectroscopy in posterior cingulate cortex to provide a multimodal description of pathology-related excitation/inhibition disruptions’ impact on cortical hierarchical dynamics. To probe the validity of excitation/inhibition proxies, we (i) investigated the relationship between in-vivo measurements and cognitive profile in Alzheimer’s; (ii) compared default mode network temporal dynamics across groups; (iii) tested its multivariate association with cognitive profile and genetic interactions; (iv) and quantified subject fingerprints related to both pathology presence and genetic risk factors. The in-vivo excitation/inhibition ratio significantly related to cognitive deficits in Alzheimer’s patients, indicating that lower inhibition corresponds to poorer cognitive performance. A voxel-wise analysis demonstrated a positive association between neurometabolism in the posterior cingulate and temporal dynamics across default mode network regions, which can effectively differentiate between patients and controls. Furthermore, network fluctuations showed significant links to cognitive performance metrics, particularly among at-risk individuals. The study identified distinct functional fingerprints based on cortical temporal dynamics, emphasizing the interplay between genetic predisposition and the presence of Alzheimer’s disease. This investigation provides compelling evidence for the clinical importance of functional connectivity proxies related to excitation/inhibition, particularly within the default mode network. Neurodegeneration induces both a temporal and neurometabolic functional regression in higher-order cortical areas, resulting in a loss of specialized function. Consequently, the hierarchical continuum of cortical functions is disrupted, leading to a homogenization of brain activity. Excitation/inhibition proxies can expand our ability to recognize brain fingerprints of at-risk pre-symptomatic and pre-clinical subjects, opening pathways for potential disease-modifying treatments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.329
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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