10 citations · 20 across the 4 of their papers we have counts for
4 papers
Learning Personal Representations from fMRIby Predicting Neurofeedback Performance
Jhonathan Osin, Lior Wolf, Guy Gurevitch +5
We present a deep neural network method for learning a personal representation for individuals that are performing a self neuromodulation task, guided by functional MRI (fMRI). Thi…
fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits
Rotem Leibovitz, Jhonathan Osin, Lior Wolf +2
We obtain a personal signature of a person's learning progress in a self-neuromodulation task, guided by functional MRI (fMRI). The signature is based on predicting the activity of…
Self-Supervised Transformers for fMRI representation
Itzik Malkiel, Gony Rosenman, Lior Wolf +1
We present TFF, which is a Transformer framework for the analysis of functional Magnetic Resonance Imaging (fMRI) data. TFF employs a two-phase training approach. First, self-super…
Deep driven fMRI decoding of visual categories
Michele Svanera, Sergio Benini, Gal Raz +3
Deep neural networks have been developed drawing inspiration from the brain visual pathway, implementing an end-to-end approach: from image data to video object classes. However bu…