Explainable AI: A review of applications to neuroimaging data
Deep neural networks (DNNs) have transformed the field of computer vision and currently
constitute some of the best models for representations learned via hierarchical processing in …
constitute some of the best models for representations learned via hierarchical processing in …
Decoding task-based fMRI data with graph neural networks, considering individual differences
Task fMRI provides an opportunity to analyze the working mechanisms of the human brain
during specific experimental paradigms. Deep learning models have increasingly been …
during specific experimental paradigms. Deep learning models have increasingly been …
Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis …
Background Brain networks in fMRI are typically identified using spatial independent
component analysis (ICA), yet other mathematical constraints provide alternate biologically …
component analysis (ICA), yet other mathematical constraints provide alternate biologically …
Empathy from dissimilarity: Multivariate pattern analysis of neural activity during observation of somatosensory experience
Empathy seems to rely on our ability to faithfully simulate multiple aspects of others' inferred
experiences, often using brain structures we would use during a similar experience. Much …
experiences, often using brain structures we would use during a similar experience. Much …
Perspective-taking is associated with increased discriminability of affective states in the ventromedial prefrontal cortex
AG Vaccaro, P Heydari… - Social cognitive and …, 2022 - academic.oup.com
Recent work using multivariate-pattern analysis (MVPA) on functional magnetic resonance
imaging (fMRI) data has found that distinct affective states produce correspondingly distinct …
imaging (fMRI) data has found that distinct affective states produce correspondingly distinct …
Distributed patterns of brain activity underlying real-time fMRI neurofeedback training
Neurofeedback (NF) based on real-time functional magnetic resonance imaging (rt-fMRI) is
an exciting neuroimaging application. In most rt-fMRI NF studies, the activity level of a single …
an exciting neuroimaging application. In most rt-fMRI NF studies, the activity level of a single …
Online decoding of object‐based attention using real‐time f MRI
Visual attention is used to selectively filter relevant information depending on current task
demands and goals. Visual attention is called object‐based attention when it is directed to …
demands and goals. Visual attention is called object‐based attention when it is directed to …
The Use of a priori Information in ICA-Based Techniques for Real-Time fMRI: An Evaluation of Static/Dynamic and Spatial/Temporal Characteristics
N Soldati, VD Calhoun, L Bruzzone… - Frontiers in human …, 2013 - frontiersin.org
Real-time brain functional MRI (rt-fMRI) allows in vivo non-invasive monitoring of neural
networks. The use of multivariate data-driven analysis methods such as independent …
networks. The use of multivariate data-driven analysis methods such as independent …
Temporal embedding and spatiotemporal feature selection boost multi-voxel pattern analysis decoding accuracy
Background In fMRI decoding, temporal embedding of spatial features of the brain allows
the incorporation of brain activity dynamics into the multivariate pattern classification …
the incorporation of brain activity dynamics into the multivariate pattern classification …
The Neuroscience of Ambivalent and Ambiguous Feelings
AG Vaccaro - 2023 - search.proquest.com
Mixed feelings or ambivalence, the simultaneous experience of positivity and negativity, are
common and universal experiences. Despite this, there is no research in affective …
common and universal experiences. Despite this, there is no research in affective …