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• Higher visual areas act like domain-general filters with strong selectivity and functional specialization
• Privileged representational axes in biological and artificial neural networks
• Soft Matching Distance: A metric on neural representations that captures single-neuron tuning
• Using artificial neural networks to ask ‘why’questions of minds and brains
• Characterizing the ventral visual stream with response-optimized neural encoding models
• A highly selective response to food in human visual cortex revealed by hypothesis-free voxel decomposition
• Predicting individual task contrasts from resting‐state functional connectivity using a surface‐based convolutional network
• NeuroGen: Activation optimized image synthesis for discovery neuroscience
• Cortical response to naturalistic stimuli is largely predictable with deep neural networks
• Neural encoding with visual attention
• A shared neural encoding model for the prediction of subject-specific fMRI response
• From connectomic to task-evoked fingerprints: Individualized prediction of task contrasts from resting-state functional connectivity
• Machine learning in resting-state fMRI analysis
• Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction
• 3D convolutional neural networks for classification of functional connectomes
• Detecting abnormalities in resting-state dynamics: An unsupervised learning approach