Single-neuronal elements of speech production in humans

AR Khanna, W Muñoz, YJ Kim, Y Kfir, AC Paulk… - Nature, 2024 - nature.com
Humans are capable of generating extraordinarily diverse articulatory movement
combinations to produce meaningful speech. This ability to orchestrate specific phonetic …

Time series modeling for heart rate prediction: From arima to transformers

H Ni, S Meng, X Geng, P Li, Z Li, X Chen… - … and Informatics (EEI …, 2024 - ieeexplore.ieee.org
Cardiovascular disease (CVD) is a leading cause of death globally, necessitating precise
forecasting models for monitoring vital signs like heart rate, blood pressure, and ECG …

[HTML][HTML] Large-scale foundation models and generative AI for BigData neuroscience

R Wang, ZS Chen - Neuroscience Research, 2024 - Elsevier
Recent advances in machine learning have led to revolutionary breakthroughs in computer
games, image and natural language understanding, and scientific discovery. Foundation …

Dataset of speech production in intracranial electroencephalography

M Verwoert, MC Ottenhoff, S Goulis, AJ Colon… - Scientific data, 2022 - nature.com
Speech production is an intricate process involving a large number of muscles and cognitive
processes. The neural processes underlying speech production are not completely …

The brain nebula: minimally invasive brain–computer interface by endovascular neural recording and stimulation

Q He, Y Yang, P Ge, S Li, X Chai, Z Luo… - Journal of …, 2024 - jnis.bmj.com
A brain–computer interface (BCI) serves as a direct communication channel between brain
activity and external devices, typically a computer or robotic limb. Advances in technology …

Tokenunify: Scalable autoregressive visual pre-training with mixture token prediction

Y Chen, H Shi, X Liu, T Shi, R Zhang, D Liu… - arxiv preprint arxiv …, 2024 - arxiv.org
Autoregressive next-token prediction is a standard pretraining method for large-scale
language models, but its application to vision tasks is hindered by the non-sequential nature …

[PDF][PDF] Innovative deep learning methods for precancerous lesion detection

Y Gong, H Zhang, R Xu, Z Yu, J Zhang - International Journal of …, 2024 - academia.edu
With the continuous advancement of socioeconomic levels and relentless innovation in
modern medical technologies, there's been a significant increase in the importance people …

Enhance image-to-image generation with llava-generated prompts

Z Ding, P Li, Q Yang, S Li - 2024 5th International Conference …, 2024 - ieeexplore.ieee.org
This paper presents a novel approach to enhance image-to-image generation by leveraging
the multimodal capabilities of the Large Language and Vision Assistant (LLaVA). We …

A neural speech decoding framework leveraging deep learning and speech synthesis

X Chen, R Wang, A Khalilian-Gourtani, L Yu… - Nature Machine …, 2024 - nature.com
Decoding human speech from neural signals is essential for brain–computer interface (BCI)
technologies that aim to restore speech in populations with neurological deficits. However, it …

Subject-agnostic transformer-based neural speech decoding from surface and depth electrode signals

J Chen, X Chen, R Wang, C Le, A Khalilian-Gourtani… - …, 2024 - pmc.ncbi.nlm.nih.gov
Objective: This study investigates speech decoding from neural signals captured by
intracranial electrodes. Most prior works can only work with electrodes on a 2D grid (ie …