Connecting cortex to machines: recent advances in brain interfaces

By John P. Donoghue. Nature Neuroscience, 2002

734 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/d5b837eb7bb4c9682f3cc6008a38afbde305bb18

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

Citations in the corpus

Hand function: peripheral and central constraints on performance. (2004, background): “Design and implementation of neural prostheses (15, 90) that might drive functional electrical stimInvited Review”
A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems (2005, methodology): “…information between the central nervous system (CNS) and computerized artificial instruments, by means of microwire or microelectrode arrays implanted in the brain (Lauer et al., 2000; Nicolelis, 2001; Donoghue, 2002) or in the spinal cord (Prochazka et al., 2001; Alo and Holsheimer, 2002).”
Decoding the visual and subjective contents of the human brain (2005, background): “Further development of such mind-reading approaches may eventually lead to potential applications for non-invasive brain-machine interfac”
Breaking the silence: brain-computer interfaces (BCI) for communication and motor control. (2006, methodology): “Brain – computer interface research received its impetus from an - imal research reconstructing movement from microelectrode - recorded spike trains or synaptic field potentials ( Donoghue , 2002 ; Nicolelis , 2001 ) .”
Brain–machine interfaces to restore motor function and probe neural circuits (2003, background): “Recent review articles discuss this design in greater detai”
Maximum likelihood estimation of cascade point-process neural encoding models (2004, background): “This is interesting especially in the context of neural prosthetic design (Serruya et al 2002, Donoghue 2002), but also more generally in the analysis of neural codes (Rieke et al 1997).”
Statistical models for neural encoding, decoding, and optimal stimulus design. (2007, background): “, can we reconstruct the image that the eye is actually seeing at any given moment, given only a few observed spike trains? What information is discarded in the neural code, and what features are most important? These questions are central both for our basic understanding of neural information proce”
Visual image reconstruction from human brain activity using a combination of multiscale local image decoders. (2008, background): “Thus, the modular decoding approach may greatly improve the ﬂexibility of prediction, which could also expand the capacity of neural prosthetics or brain-machine interfaces (Donoghue, 2002; Wolpaw and McFarland, 2004).”
A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects. (2005, background): “Third, current capabilities to record the simultaneous activity of multiple single neurons (Csicsvari et al. 2003; Donoghue 2002; Nicolelis et al. 2003; Wilson and McNaughton 1993) make it possible to study the extent to which spiking activity in a given neuron is related to concurrent ensemble…”
Neural syntax: cell assemblies, synapsembles and readers (2010, positive): “In this latter approach, it is left to upstream networks to ‘‘figure out’’ the successful, intention-controlled neuronal trajectories, without the need of an experimenterdesigned complex transformation algorithm (Donoghue, 2002; Fetz, 1969, 2007; Kennedy and Bakay, 1998; Legenstein et al., 2010).”
Intention, action planning, and decision making in parietal-frontal circuits. (2009, background): “As such, motor-prosthetics have used this activity to guide the trajectory of a cursor or a robot limb (Schwartz, 2004; Velliste et al., 2008; Nicolelis, 2003; Donoghue, 2002; Hochberg et al., 2006).”
Dynamic Analysis of Neural Encoding by Point Process Adaptive Filtering (2004, background): “Both of these problems are likely to arise with the eventual development of neural prostheses (Donoghue, 2002).”