Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation
J Wen, E Thibeau-Sutre, M Diaz-Melo… - Medical image …, 2020 - Elsevier
Numerous machine learning (ML) approaches have been proposed for automatic
classification of Alzheimer's disease (AD) from brain imaging data. In particular, over 30 …
classification of Alzheimer's disease (AD) from brain imaging data. In particular, over 30 …
Assessing and tuning brain decoders: cross-validation, caveats, and guidelines
Decoding, ie prediction from brain images or signals, calls for empirical evaluation of its
predictive power. Such evaluation is achieved via cross-validation, a method also used to …
predictive power. Such evaluation is achieved via cross-validation, a method also used to …
fMRIPrep: a robust preprocessing pipeline for functional MRI
Preprocessing of functional magnetic resonance imaging (fMRI) involves numerous steps to
clean and standardize the data before statistical analysis. Generally, researchers create ad …
clean and standardize the data before statistical analysis. Generally, researchers create ad …
Beyond the 30-million-word gap: Children's conversational exposure is associated with language-related brain function
RR Romeo, JA Leonard, ST Robinson… - Psychological …, 2018 - journals.sagepub.com
Children's early language exposure impacts their later linguistic skills, cognitive abilities,
and academic achievement, and large disparities in language exposure are associated with …
and academic achievement, and large disparities in language exposure are associated with …
Flexible reuse of cortico-hippocampal representations during encoding and recall of naturalistic events
ZM Reagh, C Ranganath - Nature Communications, 2023 - nature.com
Although every life event is unique, there are considerable commonalities across events.
However, little is known about whether or how the brain flexibly represents information about …
However, little is known about whether or how the brain flexibly represents information about …
MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites
Quality control of MRI is essential for excluding problematic acquisitions and avoiding bias
in subsequent image processing and analysis. Visual inspection is subjective and …
in subsequent image processing and analysis. Visual inspection is subjective and …
THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior
Understanding object representations requires a broad, comprehensive sampling of the
objects in our visual world with dense measurements of brain activity and behavior. Here …
objects in our visual world with dense measurements of brain activity and behavior. Here …
The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments
The development of magnetic resonance imaging (MRI) techniques has defined modern
neuroimaging. Since its inception, tens of thousands of studies using techniques such as …
neuroimaging. Since its inception, tens of thousands of studies using techniques such as …
QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data
Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for
noninvasively studying the organization of white matter in the human brain. Here we …
noninvasively studying the organization of white matter in the human brain. Here we …
How open science helps researchers succeed
Open access, open data, open source and other open scholarship practices are growing in
popularity and necessity. However, widespread adoption of these practices has not yet been …
popularity and necessity. However, widespread adoption of these practices has not yet been …