no code implementations • 21 Oct 2023 • Minh Nguyen, Gia H. Ngo, Mert R. Sabuncu
Given sufficient pairs of resting-state and task-evoked fMRI scans from subjects, it is possible to train ML models to predict subject-specific task-evoked activity using resting-state functional MRI (rsfMRI) scans.
no code implementations • 13 Oct 2022 • Minh Nguyen, Gia H. Ngo, Mert R. Sabuncu
We call our approach GLACIAL, which stands for "Granger and LeArning-based CausalIty Analysis for Longitudinal studies."
no code implementations • 24 Jul 2022 • Gia H. Ngo, Minh Nguyen, Nancy F. Chen, Mert R. Sabuncu
In this paper, we present Text2Brain, an easy to use tool for synthesizing brain activation maps from open-ended text queries.
2 code implementations • 28 Sep 2021 • Gia H. Ngo, Minh Nguyen, Nancy F. Chen, Mert R. Sabuncu
In this work, we propose Text2Brain, a neural network approach for coordinate-based meta-analysis of neuroimaging studies to synthesize brain activation maps from open-ended text queries.
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 • 27 Aug 2020 • Minh Nguyen, Gia H. Ngo, Nancy F. Chen
Spell check is a useful application which processes noisy human-generated text.
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.
1 code implementation • 20 Dec 2019 • Minh Nguyen, Gia H. Ngo, Nancy F. Chen
Using recursive neural network imposes a prior on the mapping from logographs to embeddings since the network must read in the sub-units in logographs according to the order specified by the recursive structures.
no code implementations • WS 2019 • Minh Nguyen, Gia H. Ngo, Nancy Chen
Finding that explicitly modeling structures leads to better generalization, we consider the task of predicting Cantonese pronunciations of logographs (Chinese characters) using logographs{'} recursive structures.
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.
no code implementations • 7 Oct 2018 • Gia H. Ngo, Minh Nguyen, Nancy F. Chen
The problem is compounded by the limited linguistic resources available when converting foreign words to transliterated words in the target language.
1 code implementation • EMNLP 2018 • Minh Nguyen, Gia H. Ngo, Nancy F. Chen
Graphemes of most languages encode pronunciation, though some are more explicit than others.
no code implementations • WS 2018 • Snigdha Singhania, Minh Nguyen, Gia H. Ngo, Nancy Chen
This paper reports the results of our trans-literation experiments conducted on NEWS 2018 Shared Task dataset.