The impact of ultra-high field MRI on cognitive and computational neuroimaging

F De Martino, E Yacoub, V Kemper, M Moerel… - Neuroimage, 2018 - Elsevier
The ability to measure functional brain responses non-invasively with ultra high field MRI (7
T and above) represents a unique opportunity in advancing our understanding of the human …

The use of machine learning and deep learning algorithms in functional magnetic resonance imaging—a systematic review

M Rashid, H Singh, V Goyal - Expert Systems, 2020 - Wiley Online Library
Abstract Functional Magnetic Resonance Imaging (fMRI) is presently one of the most
popular techniques for analysing the dynamic states in brain images using various kinds of …

Decoding actions at different levels of abstraction

MF Wurm, A Lingnau - Journal of Neuroscience, 2015 - jneurosci.org
Brain regions that mediate action understanding must contain representations that are
action specific and at the same time tolerate a wide range of perceptual variance. Whereas …

Use of common average reference and large-Laplacian spatial-filters enhances EEG signal-to-noise ratios in intrinsic sensorimotor activity

S Tsuchimoto, S Shibusawa, S Iwama… - Journal of neuroscience …, 2021 - Elsevier
Background Oscillations in the resting-state scalp electroencephalogram (EEG) represent
various intrinsic brain activities. One of the characteristic EEG oscillations is the …

The dorsal attention network reflects both encoding load and top–down control during working memory

S Majerus, F Péters, M Bouffier, N Cowan… - Journal of Cognitive …, 2018 - direct.mit.edu
The dorsal attention network is consistently involved in verbal and visual working memory
(WM) tasks and has been associated with task-related, top–down control of attention. At the …

Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors

K Yoo, MD Rosenberg, S Noble, D Scheinost… - NeuroImage, 2019 - Elsevier
Abstracts Brain functional connectivity features can predict cognition and behavior at the
level of the individual. Most studies measure univariate signals, correlating timecourses from …

Identity prediction errors in the human midbrain update reward-identity expectations in the orbitofrontal cortex

JD Howard, T Kahnt - Nature communications, 2018 - nature.com
There is general consensus that dopaminergic midbrain neurons signal reward prediction
errors, computed as the difference between expected and received reward value. However …

Learning about safety: Conditioned inhibition as a novel approach to fear reduction targeting the develo** brain

P Odriozola, DG Gee - American Journal of Psychiatry, 2021 - psychiatryonline.org
Adolescence is a peak time for the onset of psychiatric disorders, with anxiety disorders
being the most common and affecting as many as 30% of youths. A core feature of anxiety …

Tools of the Trade Multivoxel pattern analysis in fMRI: a practical introduction for social and affective neuroscientists

ME Weaverdyck, MD Lieberman… - Social Cognitive and …, 2020 - academic.oup.com
The family of neuroimaging analytical techniques known as multivoxel pattern analysis
(MVPA) has dramatically increased in popularity over the past decade, particularly in social …

Individualized prediction of reading comprehension ability using gray matter volume

Z Cui, M Su, L Li, H Shu, G Gong - Cerebral Cortex, 2018 - academic.oup.com
Reading comprehension is a crucial reading skill for learning and putatively contains 2 key
components: reading decoding and linguistic comprehension. Current understanding of the …