22 citations · 52 across the 11 of their papers we have counts for
12 papers
Consumer-friendly EEG-based Emotion Recognition System: A Multi-scale Convolutional Neural Network Approach
Tri Duc Ly, Gia H. Ngo
EEG is a non-invasive, safe, and low-risk method to record electrophysiological signals inside the brain. Especially with recent technology developments like dry electrodes, consum…
Zero-shot Learning of Individualized Task Contrast Prediction from Resting-state Functional Connectomes
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-s…
GLACIAL: Granger and Learning-based Causality Analysis for Longitudinal Imaging Studies
Minh Nguyen, Gia H. Ngo, Mert R. Sabuncu
The Granger framework is useful for discovering causal relations in time-varying signals. However, most Granger causality (GC) methods are developed for densely sampled timeseries…
A Transformer-based Neural Language Model that Synthesizes Brain Activation Maps from Free-Form Text Queries
Gia H. Ngo, Minh Nguyen, Nancy F. Chen +1
Neuroimaging studies are often limited by the number of subjects and cognitive processes that can be feasibly interrogated. However, a rapidly growing number of neuroscientific stu…
Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query
Gia H. Ngo, Minh Nguyen, Nancy F. Chen +1
Most neuroimaging experiments are under-powered, limited by the number of subjects and cognitive processes that an individual study can investigate. Nonetheless, over decades of re…
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…
Domain-shift Conditioning using Adaptable Filtering via Hierarchical Embeddings for Robust Chinese Spell Check
Minh Nguyen, Gia H. Ngo, Nancy F. Chen
Spell check is a useful application which processes noisy human-generated text. Spell check for Chinese poses unresolved problems due to the large number of characters, the sparse…
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…
Hierarchical Character Embeddings: Learning Phonological and Semantic Representations in Languages of Logographic Origin using Recursive Neural Networks
Minh Nguyen, Gia H. Ngo, Nancy F. Chen
Logographs (Chinese characters) have recursive structures (i.e. hierarchies of sub-units in logographs) that contain phonological and semantic information, as developmental psychol…
Machine learning in resting-state fMRI analysis
Meenakshi Khosla, Keith Jamison, Gia H. Ngo +2
Machine learning techniques have gained prominence for the analysis of resting-state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview of various u…
Phonology-Augmented Statistical Framework for Machine Transliteration using Limited Linguistic Resources
Gia H. Ngo, Minh Nguyen, Nancy F. Chen
Transliteration converts words in a source language (e.g., English) into words in a target language (e.g., Vietnamese). This conversion considers the phonological structure of the…