Naturalistic stimuli in neuroscience: critically acclaimed

S Sonkusare, M Breakspear, C Guo - Trends in cognitive sciences, 2019 - cell.com
Cognitive neuroscience has traditionally focused on simple tasks, presented sparsely and
using abstract stimuli. While this approach has yielded fundamental insights into functional …

[HTML][HTML] Idiosynchrony: From shared responses to individual differences during naturalistic neuroimaging

ES Finn, E Glerean, AY Khojandi, D Nielson… - NeuroImage, 2020 - Elsevier
Two ongoing movements in human cognitive neuroscience have researchers shifting focus
from group-level inferences to characterizing single subjects, and complementing tightly …

[HTML][HTML] Movie-watching outperforms rest for functional connectivity-based prediction of behavior

ES Finn, PA Bandettini - NeuroImage, 2021 - Elsevier
A major goal of human neuroscience is to relate differences in brain function to differences
in behavior across people. Recent work has established that whole-brain functional …

High-amplitude cofluctuations in cortical activity drive functional connectivity

F Zamani Esfahlani, Y Jo, J Faskowitz… - Proceedings of the …, 2020 - National Acad Sciences
Resting-state functional connectivity is used throughout neuroscience to study brain
organization and to generate biomarkers of development, disease, and cognition. The …

Can brain state be manipulated to emphasize individual differences in functional connectivity?

ES Finn, D Scheinost, DM Finn, X Shen… - Neuroimage, 2017 - Elsevier
While neuroimaging studies typically collapse data from many subjects, brain functional
organization varies between individuals, and characterizing this variability is crucial for …

[PDF][PDF] From maps to multi-dimensional network mechanisms of mental disorders

U Braun, A Schaefer, RF Betzel, H Tost… - Neuron, 2018 - cell.com
The development of advanced neuroimaging techniques and their deployment in large
cohorts has enabled an assessment of functional and structural brain network architecture at …

[HTML][HTML] Classification of children with autism and typical development using eye-tracking data from face-to-face conversations: Machine learning model development …

Z Zhao, H Tang, X Zhang, X Qu, X Hu, J Lu - Journal of Medical Internet …, 2021 - jmir.org
Background Previous studies have shown promising results in identifying individuals with
autism spectrum disorder (ASD) by applying machine learning (ML) to eye-tracking data …

Trait paranoia shapes inter-subject synchrony in brain activity during an ambiguous social narrative

ES Finn, PR Corlett, G Chen, PA Bandettini… - Nature …, 2018 - nature.com
Individuals often interpret the same event in different ways. How do personality traits
modulate brain activity evoked by a complex stimulus? Here we report results from a …

Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis

P Garcés, S Baumeister, L Mason, CH Chatham… - Molecular autism, 2022 - Springer
Background Understanding the development of the neuronal circuitry underlying autism
spectrum disorder (ASD) is critical to shed light into its etiology and for the development of …

ASD validity

L Waterhouse, E London, C Gillberg - Review Journal of Autism and …, 2016 - Springer
ASD research is at an important crossroads. The ASD diagnosis is important for assigning a
child to early behavioral intervention and explaining a child's condition. But ASD research …