Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

What can be expected from a semi-distributed multi-model approach for streamflow forecasting? Tailoring the structure and size of a super-ensemble on the Rhône basin - Cyril Thébault; Charles Perrin; Sébastien Legrand; Vazken Andréassian; Guillaume Thirel; Olivier Delaigue (Journal of Hydrology, 2025)

Nitrogen fixation in Arctic lichens and mosses: A survey across circumpolar subzones - Perrin Hagge; Elizabeth King-Doonan; François Lutzoni; Jolanta Miadlikowska; Blanka Aguero; Hannah Whitby; Charles Umbanhowar; Claudia Colesie; A. Elizabeth Arnold; Eric Yitong; Nicolas Cassar (Science of The Total Environment, 2025)

Extra constraint on actual evaporation in a semi-distributed conceptual model to improve model physical realism - Shu-Chen Hsu; Alban de Lavenne; Charles Perrin; Vazken Andréassian (Hydrological Sciences Journal, 2025)

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Lead-time-dependent calibration of a flood forecasting model - Paul C. Astagneau; François Bourgin; Vazken Andréassian; Charles Perrin (Journal of Hydrology, 2024)

Impact of suspicious streamflow data on the efficiency and parameter estimates of rainfall–runoff models - Cyril Thébault; Charles Perrin; Vazken Andréassian; Guillaume Thirel; Sébastien Legrand; Olivier Delaigue (Hydrological Sciences Journal, 2023)

When does a parsimonious model fail to simulate floods? Learning from the seasonality of model bias - Paul C. Astagneau; François Bourgin; Vazken Andréassian; Charles Perrin (Hydrological Sciences Journal, 2021)

Streamflow naturalization methods: a review - Morgane Terrier; Charles Perrin; Alban de Lavenne; Vazken Andréassian; Julien Lerat; Jai Vaze (Hydrological Sciences Journal, 2021)

Twenty-three unsolved problems in hydrology (UPH) – a community perspective - Günter Blöschl; Marc F.P. Bierkens; Antonio Chambel; Christophe Cudennec; Georgia Destouni; Aldo Fiori; James W. Kirchner; Jeffrey J. McDonnell; Hubert H.G. Savenije; Murugesu Sivapalan; Christine Stumpp; Elena Toth; et al. (Hydrological Sciences Journal, 2019)

The Quantile Solidarity approach for the parsimonious regionalization of flow duration curves - Carine Poncelet; Vazken Andréassian; Ludovic Oudin; Charles Perrin (Hydrological Sciences Journal, 2017)

Hydrological response characteristics of Mediterranean catchments at different time scales: a meta-analysis - Mohammad Merheb; Roger Moussa; Chadi Abdallah; François Colin; Charles Perrin; Nicolas Baghdadi (Hydrological Sciences Journal, 2016)

Impact of microbiological samples in the hospital management of community-acquired, nursing home-acquired and hospital-acquired pneumonia in older patients - A. Putot; J. Tetu; S. Perrin; H. Bailly; L. Piroth; J.-F. Besancenot; B. Bonnotte; P. Chavanet; P. d’Athis; P.-E. Charles; H. Sordet-Guépet; P. Manckoundia (European Journal of Clinical Microbiology & Infectious Diseases, 2016)

On the need to test hydrological models under changing conditions - Guillaume Thirel; Vazken Andréassian; Charles Perrin (Hydrological Sciences Journal, 2015)

Graphical tools based on Turc-Budyko plots to detect changes in catchment behaviour - Laurent Coron; Vazken Andréassian; Charles Perrin; Nicolas Le Moine (Hydrological Sciences Journal, 2015)

Comparing expert judgement and numerical criteria for hydrograph evaluation - Louise Crochemore; Charles Perrin; Vazken Andréassian; Uwe Ehret; Simon P. Seibert; Salvatore Grimaldi; Hoshin Gupta; Jean-Emmanuel Paturel (Hydrological Sciences Journal, 2015)

Resurrection of Mesoplodon hotaula Deraniyagala 1963: A new species of beaked whale in the tropical Indo‐Pacific - Merel L. Dalebout; C. Scott Baker; Debbie Steel; Kirsten Thompson; Kelly M. Robertson; Susan J. Chivers; William F. Perrin; Manori Goonatilake; R. Charles Anderson; James G. Mead; Charles W. Potter; Lisa Thompson; et al. (Marine Mammal Science, 2014)
We present genetic and morphological evidence supporting the recognition of a previously synonymized species of Mesoplodon beaked whale in the tropical Indo‐Pacific, Mesoplodon hotaula . Although the new species is closely‐related to the rare ginkgo‐toothed beaked whale M. ginkgodens, we show that these two lineages can be differentiated by maternally (mitochondrial DNA ), biparentally (autosomal), and paternally (Y chromosome) inherited DNA sequences, as well as by morphological features. The reciprocal monophyly of the mt DNA genealogies and the largely parapatric distribution of these lineages is consistent with reproductive isolation. The new lineage is currently known from at least seven specimens: Sri Lanka (1), Gilbert Islands, Republic of Kiribati (1+), Palmyra Atoll, Northern Line Islands, U.S.A. (3), Maldives (1), and Seychelles (1). The type specimen (Sri Lanka) was described as a new species, M. hotaula , in 1963, but later synonymized with M. ginkgodens . This discovery brings the total number of Mesoplodon species to 15, making it, by far, the most speciose yet least known genus of cetaceans.

How significant are quadratic criteria? Part 2. On the relative contribution of large flood events to the value of a quadratic criterion - Lionel Berthet; Vazken Andréassian; Charles Perrin; Cecile Loumagne (Hydrological Sciences Journal, 2010)

Regionalization of precipitation and air temperature over high-altitude catchments – learning from outliers - Audrey Valéry; Vazken Andréassian; Charles Perrin (Hydrological Sciences Journal, 2010)

How significant are quadratic criteria? Part 1. How many years are necessary to ensure the data-independence of a quadratic criterion value? - Lionel Berthet; Vazken Andréassian; Charles Perrin; Cecile Loumagne (Hydrological Sciences Journal, 2010)

The Court of Miracles of Hydrology: can failure stories contribute to hydrological science? - Vazken Andréassian; Charles Perrin; Eric Parent; Andras Bárdossy (Hydrological Sciences Journal, 2010)

Optimizing carbon sequestration in commercial forests by integrating carbon management objectives in wood supply modeling - Charles P.-A. Bourque; Eric T. Neilson; Chris Gruenwald; Samantha F. Perrin; Jason C. Hiltz; Yvon A. Blin; Geoffrey V. Horsman; Matthew S. Parker; Christie B. Thorburn; Michael M. Corey; Fan-rui Meng; D. Edwin Swift (Mitigation and Adaptation Strategies for Global Change, 2007)