3 papers
q-bio.QM2023
Sequential Transfer Learning to Decode Heard and Imagined Timbre from fMRI Data
Sean Paulsen, Michael Casey
We present a sequential transfer learning framework for transformers on functional Magnetic Resonance Imaging (fMRI) data and demonstrate its significant benefits for decoding musi…
cs.LG2023
Self-Supervised Pretraining on Paired Sequences of fMRI Data for Transfer Learning to Brain Decoding Tasks
Sean Paulsen, Michael Casey
In this work we introduce a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two…
q-bio.NC2023
Decoding Imagined Auditory Pitch Phenomena with an Autoencoder Based Temporal Convolutional Architecture
Sean Paulsen, Lloyd May, Michael Casey
Stimulus decoding of functional Magnetic Resonance Imaging (fMRI) data with machine learning models has provided new insights about neural representational spaces and task-related…