Shan Gao | 高珊
@shangao.bsky.social
PhD student @UChicago studying world models in brain and machine, during online processing and across cultural evolution.
shaangao.github.io
shaangao.github.io
(7/x) The fNIRS-fMRI signal prediction model generalized across stimuli. A model trained on Run 1 of Sherlock significantly predicted fMRI activity when watching Friday Night Lights in 66 ROIs, while a model trained on both runs significantly predicted fMRI activity in 84 ROIs.
May 7, 2025 at 1:52 PM
(7/x) The fNIRS-fMRI signal prediction model generalized across stimuli. A model trained on Run 1 of Sherlock significantly predicted fMRI activity when watching Friday Night Lights in 66 ROIs, while a model trained on both runs significantly predicted fMRI activity in 84 ROIs.
(6/x) Do predicted neural dynamics retain moment-to-moment semantic information in the movie? To test it, we built an encoding model from time-resolve embeddings of movie annotations. Out of the 66 ROIs, 12 exhibited above-chance accuracy, including dmPFC and the language network (dlPFC and LTC).
May 7, 2025 at 1:52 PM
(6/x) Do predicted neural dynamics retain moment-to-moment semantic information in the movie? To test it, we built an encoding model from time-resolve embeddings of movie annotations. Out of the 66 ROIs, 12 exhibited above-chance accuracy, including dmPFC and the language network (dlPFC and LTC).
(5/x) The predicted whole-brain neural dynamics also recapitulated ground-truth intersubject functional connectivity (ISFC) patterns.
May 7, 2025 at 1:52 PM
(5/x) The predicted whole-brain neural dynamics also recapitulated ground-truth intersubject functional connectivity (ISFC) patterns.
(4/x) Our model significantly predicted the neural dynamics in 66 out of 122 ROIs, including more than 80% of ROIs in the default mode network and the control network, and including areas that were anatomically inaccessible by fNIRS, such as the precuneus and basal ganglia.
May 7, 2025 at 1:52 PM
(4/x) Our model significantly predicted the neural dynamics in 66 out of 122 ROIs, including more than 80% of ROIs in the default mode network and the control network, and including areas that were anatomically inaccessible by fNIRS, such as the precuneus and basal ganglia.
(3/x) In light of prior research on functional connectivity and linear mapping between fNIRS and fMRI signals, we adapted principal component regression (aPCR) to predict whole-brain fMRI signals from PFC fNIRS signals.
May 7, 2025 at 1:52 PM
(3/x) In light of prior research on functional connectivity and linear mapping between fNIRS and fMRI signals, we adapted principal component regression (aPCR) to predict whole-brain fMRI signals from PFC fNIRS signals.
(6/x) Do the predicted neural dynamics retain moment-to-moment semantic information in the movie? To test it, we built an encoding model from time-resolve embeddings of movie annotations. Out of the 66 ROIs, 12 exhibited above-chance accuracy, including dmPFC and the language network (dlPFC and LTC)
November 21, 2024 at 8:50 PM
(6/x) Do the predicted neural dynamics retain moment-to-moment semantic information in the movie? To test it, we built an encoding model from time-resolve embeddings of movie annotations. Out of the 66 ROIs, 12 exhibited above-chance accuracy, including dmPFC and the language network (dlPFC and LTC)
(5/x) The predicted whole-brain neural dynamics also recapitulated ground-truth intersubject functional connectivity (ISFC) patterns.
November 21, 2024 at 8:50 PM
(5/x) The predicted whole-brain neural dynamics also recapitulated ground-truth intersubject functional connectivity (ISFC) patterns.
(4/x) Our model significantly predicted the neural dynamics in 66 out of 122 ROIs, including more than 80% of ROIs in the default mode network and the control network, and including areas that were anatomically inaccessible by fNIRS, such as the precuneus and basal ganglia.
November 21, 2024 at 8:50 PM
(4/x) Our model significantly predicted the neural dynamics in 66 out of 122 ROIs, including more than 80% of ROIs in the default mode network and the control network, and including areas that were anatomically inaccessible by fNIRS, such as the precuneus and basal ganglia.
(3/x) In light of prior research on functional connectivity and linear mapping between fNIRS and fMRI signals, we adapted principal component regression (aPCR) to predict whole-brain fMRI signals from PFC fNIRS signals.
November 21, 2024 at 8:50 PM
(3/x) In light of prior research on functional connectivity and linear mapping between fNIRS and fMRI signals, we adapted principal component regression (aPCR) to predict whole-brain fMRI signals from PFC fNIRS signals.