Sowmya Manojna
Sowmya Manojna
Home
Publications
Posters
Projects
Paper Summaries
Blog
Contact
Light
Dark
Automatic
Publications
Type
Conference paper
Journal article
Preprint
Date
2026
2025
2024
2021
Probabilistic Co-Control in Brain-Computer Interfaces: Uncertainty as a Control Signal in Brain-to-Text Decoding
Neural decoders serve as probabilistic interfaces in co-control brain-to-text BCIs …
Jingya Huang
,
Sowmya Manojna Narasimha
,
Aashish N. Patel
,
Ram Dyuthi Sristi
,
Gal Mishne
,
Vikash Gilja
DOI
Compositional decoding of neural activity enhances generalization in handwriting BCIs
State-of-the-art intracortical neuroprostheses currently enable communication …
Sowmya Manojna Narasimha
,
Jingya Huang
,
Ram Dyuthi Sristi
,
Vikash Gilja
,
Gal Mishne
DOI
Coupled Transformer Autoencoder for Disentangling Multi-Region Neural Latent Dynamics
Simultaneous recordings from thousands of neurons across multiple brain areas reveal …
Ram Dyuthi Sristi
,
Sowmya Manojna Narasimha
,
Jingya Huang
,
Alice Despatin
,
Simon Musall
,
Vikash Gilja
,
Gal Mishne
DOI
Word-Level Error Analysis in Decoding Systems: From Speech Recognition to Brain-Computer Interfaces
Brain-to-text (BTT) systems that decode attempted speech from neural activity have achieved 4.2% word error rate (WER). These systems deomnstrate potential for daily …
Jingya Huang
,
Aashish N Patel
,
Sowmya Manojna Narasimha
,
Gal Mishne
,
Vikash Gilja
Cite
Code
Poster
DOI
Understanding flux switching in metabolic networks through an analysis of synthetic lethals
Biological systems are extremely robust and exhibit high levels of redundancy …
Sowmya Manojna Narasimha
,
Tanisha Malpani
,
Omkar S Mohite
,
Saketha Nath
,
Karthik Raman
Cite
Code
Poster
DOI
Guiding Brain-to-Vocalization Decoder Design Using Structured Generalization Error
State-of-the-art intracortical neuroprostheses currently enable communication …
Jingya Huang
,
Pablo Tostado-Marcos
,
Sowmya Manojna Narasimha
,
Aashish N. Patel
,
Ezequiel. M. Arneodo
,
Timothy Q. Gentner
,
Gal Mishne
,
Vikash Gilja
Cite
DOI
Artificial Neurovascular Network (ANVN) to Study the Accuracy Vs. Efficiency trade-off in an Energy Dependent Neural Network
Artificial feedforward neural networks perform a wide variety of classification and function approximation tasks with high accuracy. Unlike their artificial counterparts, …
Bhadra S Kumar
,
Nagavarshini Mayakkannan
,
Sowmya Manojna Narasimha
,
V Srinivasa Chakravarthy
Cite
Project
DOI
Cite
×