Thilo van Eimeren

Aug 29, 2024 | biorxiv.org | Elke Smith |Hendrik Theis |Thilo van Eimeren |Kilian Knauth

AbstractDisorders characterised by changes in dopamine (DA) neurotransmission are often linked to changes in the temporal discounting of future rewards. Likewise, pharmacological manipulations of DA neurotransmission in healthy individuals modulates temporal discounting, but there is considerable variability in the directionality of reported pharmacological effects, as enhancements and reductions of DA signalling have been linked to both increases and reductions of temporal discounting.

May 1, 2024 | flipboard.com | Verena Dzialas |Merle C. Hoenig |Stéphane Prange |Gérard N Bischof |Alexander Drzezga |Thilo van Eimeren

Structural underpinnings and long-term effects of resilience in Parkinson’s diseaseResilience in neuroscience generally refers to an individual’s capacity to counteract the adverse effects of a neuropathological condition. While …

Mar 22, 2024 | nature.com | Javier Oltra |Barbara Segura |Thilo van Eimeren |Naroa Ibarretxe-Bilbao |María Díez-Cirarda |Olaia Lucas-Jiménez | +4 more

AbstractClinical, cognitive, and atrophy characteristics depending on sex have been previously reported in Parkinson’s disease (PD). However, though sex differences in cortical gray matter measures in early drug naïve patients have been described, little is known about differences in cortical thickness (CTh) as the disease advances.

Feb 7, 2024 | inria.hal.science | Thilo van Eimeren |Angelo Antonini |Daniela Berg |Nico Bohnen

Article Dans Une Revue Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring Année : 2019 Neuroimaging biomarkers for clinical trials in atypical parkinsonian disorders: Proposal for a Neuroimaging Biomarker Utility System Mots clés Biomarker Trials PSP MSA CBD CBS Neurodegeneration Biomarker Multicentric Multisite Neuroimaging Harmonization PET MRI Biomarker Trials PSP MSA CBD CBS Neurodegeneration Multicentric Multisite Neuroimaging Harmonization PET MRI Fichier principal Alz...

Jan 2, 2024 | jnm.snmjournals.org | Elena Doering |Georgios A. Antonopoulos |Merle C. Hoenig |Thilo van Eimeren

machine learningcognitive impairmentneuroimagingBrain aging entails changes in cognitive performance, brain function, and structural parameters of brain integrity. Brain age can be modeled using machine learning algorithms by estimating a person’s chronologic age from their neuroimaging data. Higher brain age than chronologic age, that is, a positive brain age gap (BAG), is associated with neurodegenerative diseases such as Alzheimer disease (AD).