[HTML][HTML] AM/EEG-fMRI fusion primer: resolving human brain responses in space and time
Any cognitive function is mediated by a network of many cortical sites whose activity is
orchestrated through complex temporal dynamics. To understand cognition, we need to …
orchestrated through complex temporal dynamics. To understand cognition, we need to …
Multi-scale neural decoding and analysis
Objective. Complex spatiotemporal neural activity encodes rich information related to
behavior and cognition. Conventional research has focused on neural activity acquired …
behavior and cognition. Conventional research has focused on neural activity acquired …
THINGSvision: A Python Toolbox for Streamlining the Extraction of Activations From Deep Neural Networks
L Muttenthaler, MN Hebart - Frontiers in Neuroinformatics, 2021 - frontiersin.org
Over the past decade, deep neural network (DNN) models have received a lot of attention
due to their near-human object classification performance and their excellent prediction of …
due to their near-human object classification performance and their excellent prediction of …
The perceptual neural trace of memorable unseen scenes
Some scenes are more memorable than others: they cement in minds with consistencies
across observers and time scales. While memory mechanisms are traditionally associated …
across observers and time scales. While memory mechanisms are traditionally associated …
Recurrent connectivity supports higher-level visual and semantic object representations in the brain
Visual object recognition has been traditionally conceptualised as a predominantly
feedforward process through the ventral visual pathway. While feedforward artificial neural …
feedforward process through the ventral visual pathway. While feedforward artificial neural …
Reconstructing feedback representations in the ventral visual pathway with a generative adversarial autoencoder
H Al-Tahan, Y Mohsenzadeh - PLoS Computational Biology, 2021 - journals.plos.org
While vision evokes a dense network of feedforward and feedback neural processes in the
brain, visual processes are primarily modeled with feedforward hierarchical neural networks …
brain, visual processes are primarily modeled with feedforward hierarchical neural networks …
[HTML][HTML] Recent advances in understanding object recognition in the human brain: deep neural networks, temporal dynamics, and context
Object recognition is the ability to identify an object or category based on the combination of
visual features observed. It is a remarkable feat of the human brain, given that the patterns of …
visual features observed. It is a remarkable feat of the human brain, given that the patterns of …
Emergence of visual center-periphery spatial organization in deep convolutional neural networks
Research at the intersection of computer vision and neuroscience has revealed hierarchical
correspondence between layers of deep convolutional neural networks (DCNNs) and …
correspondence between layers of deep convolutional neural networks (DCNNs) and …
Visual perception of highly memorable images is mediated by a distributed network of ventral visual regions that enable a late memorability response
Behavioral and neuroscience studies in humans and primates have shown that
memorability is an intrinsic property of an image that predicts its strength of encoding into …
memorability is an intrinsic property of an image that predicts its strength of encoding into …
[HTML][HTML] img2fmri: a python package for predicting group-level fMRI responses to visual stimuli using deep neural networks
M Bennett, C Baldassano - Aperture neuro, 2023 - ncbi.nlm.nih.gov
Here we introduce a new python package, img2fmri, to predict group-level fMRI responses
to individual images. This prediction model uses an artificial deep neural network (DNN), as …
to individual images. This prediction model uses an artificial deep neural network (DNN), as …