no code implementations • 16 Nov 2023 • Meenakshi Khosla, Alex H. Williams
Common measures of neural representational (dis)similarity are designed to be insensitive to rotations and reflections of the neural activation space.
2 code implementations • 15 May 2021 • Zijin Gu, Keith W. Jamison, Meenakshi Khosla, Emily J. Allen, Yihan Wu, Thomas Naselaris, Kendrick Kay, Mert R. Sabuncu, Amy Kuceyeski
NeuroGen combines an fMRI-trained neural encoding model of human vision with a deep generative network to synthesize images predicted to achieve a target pattern of macro-scale brain activation.
1 code implementation • NeurIPS 2020 • Meenakshi Khosla, Gia H. Ngo, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu
Using concurrent eye-tracking and functional Magnetic Resonance Imaging (fMRI) recordings from a large cohort of human subjects watching movies, we first demonstrate that leveraging gaze information, in the form of attentional masking, can significantly improve brain response prediction accuracy in a neural encoding model.
1 code implementation • 7 Aug 2020 • Gia H. Ngo, Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu
Resting-state functional MRI (rsfMRI) yields functional connectomes that can serve as cognitive fingerprints of individuals.
2 code implementations • 7 Aug 2020 • Gia H. Ngo, Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu
Resting-state functional MRI (rsfMRI) yields functional connectomes that can serve as cognitive fingerprints of individuals.
1 code implementation • 29 Jun 2020 • Meenakshi Khosla, Gia H. Ngo, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu
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.
no code implementations • 16 Aug 2019 • Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu
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 brain.
no code implementations • 30 Dec 2018 • Meenakshi Khosla, Keith Jamison, Gia H. Ngo, Amy Kuceyeski, Mert R. Sabuncu
Here, we present an overview of various unsupervised and supervised machine learning applications to rs-fMRI.
1 code implementation • 11 Sep 2018 • Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu
The specificty and sensitivity of resting state functional MRI (rs-fMRI) measurements depend on pre-processing choices, such as the parcellation scheme used to define regions of interest (ROIs).
no code implementations • 11 Jun 2018 • Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert Sabuncu
Resting-state functional MRI (rs-fMRI) scans hold the potential to serve as a diagnostic or prognostic tool for a wide variety of conditions, such as autism, Alzheimer's disease, and stroke.