fMRIPrep: a robust preprocessing pipeline for functional MRI

O Esteban, CJ Markiewicz, RW Blair, CA Moodie… - Nature …, 2019 - nature.com
Preprocessing of functional magnetic resonance imaging (fMRI) involves numerous steps to
clean and standardize the data before statistical analysis. Generally, researchers create ad …

Wearable sweat sensing for prolonged, semicontinuous, and nonobtrusive health monitoring

EJM Moonen, JR Haakma, E Peri, E Pelssers, M Mischi… - View, 2020 - Wiley Online Library
Together with the upcoming market for wearable consumer technologies, noninvasive and
continuous health monitoring has become a new trend in the healthcare landscape. In …

Predictive processing models and affective neuroscience

KM Lee, F Ferreira-Santos, AB Satpute - Neuroscience & Biobehavioral …, 2021 - Elsevier
The neural bases of affective experience remain elusive. Early neuroscience models of
affect searched for specific brain regions that uniquely carried out the computations that …

Fine-grain atlases of functional modes for fMRI analysis

K Dadi, G Varoquaux, A Machlouzarides-Shalit… - NeuroImage, 2020 - Elsevier
Population imaging markedly increased the size of functional-imaging datasets, shedding
new light on the neural basis of inter-individual differences. Analyzing these large data …

Functional PET/MRI reveals active inhibition of neuronal activity during optogenetic activation of the nigrostriatal pathway

S Haas, F Bravo, TM Ionescu… - Science …, 2024 - science.org
The dopaminergic system is a central component of the brain's neurobiological framework,
governing motor control and reward responses and playing an essential role in various …

Test–retest reliability of dynamic functional connectivity in naturalistic paradigm functional magnetic resonance imaging

X Zhang, J Liu, Y Yang, S Zhao, L Guo… - Human brain …, 2022 - Wiley Online Library
Dynamic functional connectivity (dFC) has been increasingly used to characterize the brain
transient temporal functional patterns and their alterations in diseased brains. Meanwhile …

[HTML][HTML] TbCAPs: A toolbox for co-activation pattern analysis

TAW Bolton, C Tuleasca, D Wotruba, G Rey, H Dhanis… - Neuroimage, 2020 - Elsevier
Functional magnetic resonance imaging provides rich spatio-temporal data of human brain
activity during task and rest. Many recent efforts have focussed on characterising dynamics …

Knowing what you know in brain segmentation using Bayesian deep neural networks

P McClure, N Rho, JA Lee, JR Kaczmarzyk… - Frontiers in …, 2019 - frontiersin.org
In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer
segmentations of structural MRI volumes, in minutes rather than hours. The network was …

Adolescents living with HIV, complex needs and resilience in Blantyre, Malawi

BN Kaunda-Khangamwa, P Kapwata, K Malisita… - AIDS Research and …, 2020 - Springer
Background Adolescents living with HIV (ALHIV) in Malawi experience multiple challenges
associated with their illness and various social, environmental, economic and cultural …

Representations of modality-general valence for videos and music derived from fMRI data

J Kim, SV Shinkareva, DH Wedell - NeuroImage, 2017 - Elsevier
This study tested for neural representations of valence that are shared across visual and
auditory modalities referred to as modality-general representations. On a given trial …