Data-driven modelling of neurodegenerative disease progression: thinking outside the black box
Data-driven disease progression models are an emerging set of computational tools that
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …
A synergetic turn in cognitive neuroscience of brain diseases
Despite significant improvements in our understanding of brain diseases, many barriers
remain. Cognitive neuroscience faces four major challenges: complex structure–function …
remain. Cognitive neuroscience faces four major challenges: complex structure–function …
The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds
Abstract The Latin American Brain Health Institute (BrainLat) has released a unique
multimodal neuroimaging dataset of 780 participants from Latin American. The dataset …
multimodal neuroimaging dataset of 780 participants from Latin American. The dataset …
Heterogeneous factors influence social cognition across diverse settings in brain health and age-related diseases
Aging diminishes social cognition, and changes in this capacity can indicate brain diseases.
However, the relative contribution of age, diagnosis and brain reserve to social cognition …
However, the relative contribution of age, diagnosis and brain reserve to social cognition …
[HTML][HTML] Gaming expertise induces meso‑scale brain plasticity and efficiency mechanisms as revealed by whole-brain modeling
Video games are a valuable tool for studying the effects of training and neural plasticity on
the brain. However, the underlying mechanisms related to plasticity-associated brain …
the brain. However, the underlying mechanisms related to plasticity-associated brain …
Neural geometrodynamics, complexity, and plasticity: a psychedelics perspective
We explore the intersection of neural dynamics and the effects of psychedelics in light of
distinct timescales in a framework integrating concepts from dynamics, complexity, and …
distinct timescales in a framework integrating concepts from dynamics, complexity, and …
Alzheimer's Disease: Insights from Large-Scale Brain Dynamics Models
L Yang, J Lu, D Li, J Xiang, T Yan, J Sun, B Wang - Brain Sciences, 2023 - mdpi.com
Alzheimer's disease (AD) is a degenerative brain disease, and the condition is difficult to
assess. In the past, numerous brain dynamics models have made remarkable contributions …
assess. In the past, numerous brain dynamics models have made remarkable contributions …
Visual deep learning of unprocessed neuroimaging characterises dementia subtypes and generalises across non-stereotypic samples
Background Dementia's diagnostic protocols are mostly based on standardised
neuroimaging data collected in the Global North from homogeneous samples. In other non …
neuroimaging data collected in the Global North from homogeneous samples. In other non …
Biophysical models applied to dementia patients reveal links between geographical origin, gender, disease duration, and loss of neural inhibition
Background The hypothesis of decreased neural inhibition in dementia has been sparsely
studied in functional magnetic resonance imaging (fMRI) data across patients with different …
studied in functional magnetic resonance imaging (fMRI) data across patients with different …
Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole‐brain modeling
C Coronel‐Oliveros, RG Gómez… - Alzheimer's & …, 2024 - Wiley Online Library
INTRODUCTION Alzheimer's disease (AD) and behavioral variant frontotemporal dementia
(bvFTD) lack mechanistic biophysical modeling in diverse, underrepresented populations …
(bvFTD) lack mechanistic biophysical modeling in diverse, underrepresented populations …