output
20042026
most citedAssessing and tuning brain decoders: cross-validation, caveats, and guidelines

887 citations

Showing 2018Show all

13 papers · 1 filter

q-bio.NC2018★ 38 cited

Neural correlates of episodic memory in the Memento cohort

Stéphane Epelbaum, Vincent Bouteloup, Jean Mangin +22

IntroductionThe free and cued selective reminding test is used to identify memory deficits in mild cognitive impairment and demented patients. It allows assessing three processes:…

q-bio.NC2018★ 4 cited

COGEVIS: A New Scale to Evaluate Cognition in Patients with Visual Deficiency

Claire Meyniel, Dalila Samri, Farah Stefano +9

We evaluated the cognitive status of visually impaired patients referred to low vision rehabilitation (LVR) based on a standard cognitive battery and a new evaluation tool, named t…

q-bio.NC2018★ 32 cited

Disrupted core-periphery structure of multimodal brain networks in Alzheimer's Disease

Jeremy Guillon, Mario Chavez, Federico Battiston +7

In Alzheimer's disease (AD), the progressive atrophy leads to aberrant network reconfigurations both at structural and functional levels. In such network reorganization, the core a…

q-bio.QM2018★ 26 cited

Ordinal Synchronization: Using ordinal patterns to capture interdependencies between time series

Ignacio Echegoyen, Victor Vera-Ávila, Ricardo Sevilla-Escoboza +2

We introduce Ordinal Synchronization () as a new measure to quantify synchronization between dynamical systems. is calculated from the extraction of the ordinal patterns r…

physics.data-an2018★ 50 cited

Detection of time reversibility in time series by ordinal patterns analysis

Johann H. Martínez, José L. Herrera-Diestra, Mario Chavez

Time irreversibility is a common signature of nonlinear processes, and a fundamental property of non-equilibrium systems driven by non-conservative forces. A time series is said to…

cs.LG2018★ 181 cited

Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data

Jorge Samper-González, Ninon Burgos, Simona Bottani +13

A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of AD. However, they are difficult to reproduce because…