4 citations · 7 across the 5 of their papers we have counts for
10 papers
Personalized visual encoding model construction with small data
Zijin Gu, Keith Jamison, Mert Sabuncu +1
Encoding models that predict brain response patterns to stimuli are one way to capture this relationship between variability in bottom-up neural systems and individual's behavior o…
NeuroGen: activation optimized image synthesis for discovery neuroscience
Zijin Gu, Keith W. Jamison, Meenakshi Khosla +6
Functional MRI (fMRI) is a powerful technique that has allowed us to characterize visual cortex responses to stimuli, yet such experiments are by nature constructed based on a prio…
Neural encoding with visual attention
Meenakshi Khosla, Gia H. Ngo, Keith Jamison +2
Visual perception is critically influenced by the focus of attention. Due to limited resources, it is well known that neural representations are biased in favor of attended locatio…
From Connectomic to Task-evoked Fingerprints: Individualized Prediction of Task Contrasts from Resting-state Functional Connectivity
Gia H. Ngo, Meenakshi Khosla, Keith Jamison +2
Resting-state functional MRI (rsfMRI) yields functional connectomes that can serve as cognitive fingerprints of individuals. Connectomic fingerprints have proven useful in many mac…
A shared neural encoding model for the prediction of subject-specific fMRI response
Meenakshi Khosla, Gia H. Ngo, Keith Jamison +2
The increasing popularity of naturalistic paradigms in fMRI (such as movie watching) demands novel strategies for multi-subject data analysis, such as use of neural encoding models…
Detecting abnormalities in resting-state dynamics: An unsupervised learning approach
Meenakshi Khosla, Keith Jamison, Amy Kuceyeski +1
Resting-state functional MRI (rs-fMRI) is a rich imaging modality that captures spontaneous brain activity patterns, revealing clues about the connectomic organization of the human…