Alain Goriely

This study models oscillatory and steady streaming flow of cerebrospinal fluid in the cranial subarachnoid space using a lubrication-based framework, showing that oscillatory forcing enhances solute transport.

The paper introduces a dynamical ATN model to simulate and predict the spatiotemporal progression of Aβ, tau, and neurodegeneration in Alzheimer's disease using multimodal imaging data.

The paper identifies a cellular tipping point between aggregate accumulation and removal as a universal feature of neurodegeneration, validated through live-cell assays and super-resolution imaging.

The paper develops a mechanistic model of tau protein dynamics using PET data to predict regional tau accumulation and disease progression stages in Alzheimer's patients.

This study shows that sleep deprivation reduces brain clearance rates but preserves their spatial pattern, affecting tau propagation differently in a computational model.

This paper introduces a framework to quantify irreversibility in brain network dynamics across multiple levels and identifies higher-order organizational patterns in human brain interactions.

The paper uses a computational model to show neuronal activity and amyloid-beta drive tau seeding in the entorhinal cortex, linking these factors to early Alzheimer's disease pathology.

This paper uses neural networks to discover two-stage tau aggregation dynamics from PET data, revealing a more accurate model than traditional reaction-diffusion approaches.

This paper develops a physics-based model of the elephant trunk to predict its motion from muscle activation, revealing how specific muscle contractions enable task-specific movements.

The paper studies how neuronal activity influences the spread of toxic proteins in neurodegenerative diseases through a multi-timescale model of spreading on adaptive networks.

The paper uses a whole-brain model to show glioma patients have altered neuronal dynamics compared to healthy controls, with changes in interregional coupling and excitability.

This paper develops a mathematical model to study how brain clearance mechanisms interact with toxic protein progression and aging in neurodegenerative diseases like Alzheimer's.

This study develops a microscopic model to understand the rheological behavior of axons under stretch, showing viscoelastic properties at moderate velocities and failure at higher velocities due to damage.

This paper models the spread of amyloid-β and tau in the human brain to explain Alzheimer's disease-related neuronal hyperactivation, frequency slowing, and hypoactivation.

The paper models axon bundle migration in response to rigidity gradients using optic ray theory, showing behavior analogous to Snell's law and demonstrating guidance by stiffness variations.

The paper introduces a method using braid diagrams to analyze staging patterns in neurodegenerative diseases and shows how model choices affect staging outcomes.

The paper develops a coupled network-based model to study interactions between amyloid-beta and tau proteins in neurodegenerative diseases, revealing their cooperative role in disease propagation.

The paper models the spread of misfolded protein aggregates in the brain using nucleation-aggregation-fragmentation dynamics and network transport mechanisms.

This paper models prion-like spreading of Alzheimer's disease by integrating misfolding kinetics with a brain connectivity network derived from the Human Connectome Project, showing accurate predictions of neuropathology and simulating therapeutic strategies.