Decoding methods for neural prostheses: where have we reached?
Z Li - Frontiers in systems neuroscience, 2014 - frontiersin.org
This article reviews advances in decoding methods for brain-machine interfaces (BMIs).
Recent work has focused on practical considerations for future clinical deployment of …
Recent work has focused on practical considerations for future clinical deployment of …
The convergence of machine and biological intelligence
To explore the exciting new domain of brain informatics, we invited several well-known
experts to discuss the state of the art, the challenges, the opportunities, and the trends. In" …
experts to discuss the state of the art, the challenges, the opportunities, and the trends. In" …
Task learning over multi-day recording via internally rewarded reinforcement learning based brain machine interfaces
Autonomous brain machine interfaces (BMIs) aim to enable paralyzed people to self-
evaluate their movement intention to control external devices. Previous reinforcement …
evaluate their movement intention to control external devices. Previous reinforcement …
Multi-ganglion ANN based feature learning with application to P300-BCI signal classification
W Gao, J Guan, J Gao, D Zhou - Biomedical Signal Processing and Control, 2015 - Elsevier
The feature extraction of event-related potentials (ERPs) is a significant prerequisite for
many types of P300-BCIs. In this paper, we proposed a multi-ganglion artificial neural …
many types of P300-BCIs. In this paper, we proposed a multi-ganglion artificial neural …
Extracting synchronized neuronal activity from local field potentials based on a marked point process framework
Objective. Brain-machine interfaces (BMIs) translate neural activity into motor commands to
restore motor functions for people with paralysis. Local field potentials (LFPs) are promising …
restore motor functions for people with paralysis. Local field potentials (LFPs) are promising …
Binless kernel machine: Modeling spike train transformation for cognitive neural prostheses
Modeling spike train transformation among brain regions helps in designing a cognitive
neural prosthesis that restores lost cognitive functions. Various methods analyze the …
neural prosthesis that restores lost cognitive functions. Various methods analyze the …
Tracking fast neural adaptation by globally adaptive point process estimation for brain-machine interface
Brain-machine interfaces (BMIs) help the disabled restore body functions by translating
neural activity into digital commands to control external devices. Neural adaptation, where …
neural activity into digital commands to control external devices. Neural adaptation, where …
Distinct neural patterns enable grasp types decoding in monkey dorsal premotor cortex
Objective. Recent studies have shown that dorsal premotor cortex (PMd), a cortical area in
the dorsomedial grasp pathway, is involved in grasp movements. However, the neural …
the dorsomedial grasp pathway, is involved in grasp movements. However, the neural …
Nonlinear modeling of neural interaction for spike prediction using the staged point-process model
Neurons communicate nonlinearly through spike activities. Generalized linear models
(GLMs) describe spike activities with a cascade of a linear combination across inputs, a …
(GLMs) describe spike activities with a cascade of a linear combination across inputs, a …
Tracking neural modulation depth by dual sequential monte carlo estimation on point processes for brain–machine interfaces
Classic brain-machine interface (BMI) approaches decode neural signals from the brain
responsible for achieving specific motor movements, which subsequently command …
responsible for achieving specific motor movements, which subsequently command …