Cognitive control signals for neural prosthetics.

Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature (2012) 7.87

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Direct control of paralysed muscles by cortical neurons. Nature (2008) 4.30

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Quadcopter control in three-dimensional space using a noninvasive motor imagery-based brain-computer interface. J Neural Eng (2013) 1.85

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Emulation of computer mouse control with a noninvasive brain-computer interface. J Neural Eng (2008) 1.70

Incorporating feedback from multiple sensory modalities enhances brain-machine interface control. J Neurosci (2010) 1.68

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Definitions of state variables and state space for brain-computer interface : Part 1. Multiple hierarchical levels of brain function. Cogn Neurodyn (2006) 1.57

Continuous three-dimensional control of a virtual helicopter using a motor imagery based brain-computer interface. PLoS One (2011) 1.56

Continuous neuronal ensemble control of simulated arm reaching by a human with tetraplegia. J Neural Eng (2011) 1.55

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Dissociable effects of the implicit and explicit memory systems on learning control of reaching. Exp Brain Res (2006) 1.51

Detecting neural-state transitions using hidden Markov models for motor cortical prostheses. J Neurophysiol (2008) 1.50

A closed-loop human simulator for investigating the role of feedback control in brain-machine interfaces. J Neurophysiol (2010) 1.46

Selectivity for grasp in local field potential and single neuron activity recorded simultaneously from M1 and F5 in the awake macaque monkey. J Neurosci (2008) 1.43

Asynchronous decoding of dexterous finger movements using M1 neurons. IEEE Trans Neural Syst Rehabil Eng (2008) 1.36

Volitional control of single cortical neurons in a brain-machine interface. J Neural Eng (2011) 1.29

Human neocortical electrical activity recorded on nonpenetrating microwire arrays: applicability for neuroprostheses. Neurosurg Focus (2009) 1.27

Behavioral and neural correlates of visuomotor adaptation observed through a brain-computer interface in primary motor cortex. J Neurophysiol (2012) 1.27

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Bias, optimal linear estimation, and the differences between open-loop simulation and closed-loop performance of spiking-based brain-computer interface algorithms. Neural Netw (2009) 1.25

Factor-analysis methods for higher-performance neural prostheses. J Neurophysiol (2009) 1.25

Neuronal Reward and Decision Signals: From Theories to Data. Physiol Rev (2015) 1.24

Brain control of movement execution onset using local field potentials in posterior parietal cortex. J Neurosci (2009) 1.23

A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task. J Neurosci (2010) 1.19

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Cognitive neural prosthetics. Annu Rev Psychol (2010) 1.17

Are muscle synergies useful for neural control? Front Comput Neurosci (2013) 1.17

Sensing with the motor cortex. Neuron (2011) 1.14

Cognitive signals for brain-machine interfaces in posterior parietal cortex include continuous 3D trajectory commands. Proc Natl Acad Sci U S A (2012) 1.11

Adaptive decoding for brain-machine interfaces through Bayesian parameter updates. Neural Comput (2011) 1.10

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Spike train decoding without spike sorting. Neural Comput (2008) 1.08

Simultaneous modeling of visual saliency and value computation improves predictions of economic choice. Proc Natl Acad Sci U S A (2013) 1.05

A cognitive neuroprosthetic that uses cortical stimulation for somatosensory feedback. J Neural Eng (2014) 1.05

A real-time brain-machine interface combining motor target and trajectory intent using an optimal feedback control design. PLoS One (2013) 1.05

Goal selection versus process control in a brain-computer interface based on sensorimotor rhythms. J Neural Eng (2009) 1.04

Autonomous head-mounted electrophysiology systems for freely behaving primates. Curr Opin Neurobiol (2010) 1.04

Statistical Signal Processing and the Motor Cortex. Proc IEEE Inst Electr Electron Eng (2007) 1.03

A dynamical systems view of motor preparation: implications for neural prosthetic system design. Prog Brain Res (2011) 1.03

Responses of amygdala neurons to positive reward-predicting stimuli depend on background reward (contingency) rather than stimulus-reward pairing (contiguity). J Neurophysiol (2009) 1.02

Speeded near infrared spectroscopy (NIRS) response detection. PLoS One (2010) 1.01

Sensors and decoding for intracortical brain computer interfaces. Annu Rev Biomed Eng (2013) 1.01

EEG control of a virtual helicopter in 3-dimensional space using intelligent control strategies. IEEE Trans Neural Syst Rehabil Eng (2010) 1.01

Advances in neuroprosthetic learning and control. PLoS Biol (2013) 0.99

High accuracy decoding of movement target direction in non-human primates based on common spatial patterns of local field potentials. PLoS One (2010) 0.97

Toward optimal target placement for neural prosthetic devices. J Neurophysiol (2008) 0.97

Observation-based learning for brain-machine interfaces. Curr Opin Neurobiol (2008) 0.96

Volitional control of neural activity relies on the natural motor repertoire. Curr Biol (2013) 0.96

The utility of multichannel local field potentials for brain-machine interfaces. J Neural Eng (2013) 0.96

Human posterior parietal cortex plans where to reach and what to avoid. J Neurosci (2010) 0.96

Reward-based decision signals in parietal cortex are partially embodied. J Neurosci (2015) 0.96

Neural interfaces at the nanoscale. Nanomedicine (Lond) (2008) 0.95

A cortical-spinal prosthesis for targeted limb movement in paralysed primate avatars. Nat Commun (2014) 0.95

Optic ataxia: from Balint's syndrome to the parietal reach region. Neuron (2014) 0.95

Probability-based prediction of activity in multiple arm muscles: implications for functional electrical stimulation. J Neurophysiol (2008) 0.94

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Toward more versatile and intuitive cortical brain-machine interfaces. Curr Biol (2014) 0.93

Restoration of motor function following spinal cord injury via optimal control of intraspinal microstimulation: toward a next generation closed-loop neural prosthesis. Front Neurosci (2014) 0.93

How many neurons can we see with current spike sorting algorithms? J Neurosci Methods (2012) 0.93

Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic. IEEE Trans Neural Syst Rehabil Eng (2013) 0.92

Operant conditioning of primate prefrontal neurons. J Neurophysiol (2010) 0.92

Shaping the dynamics of a bidirectional neural interface. PLoS Comput Biol (2012) 0.92

Single trial prediction of self-paced reaching directions from EEG signals. Front Neurosci (2014) 0.92

Efficient universal computing architectures for decoding neural activity. PLoS One (2012) 0.92

Reprogramming movements: extraction of motor intentions from cortical ensemble activity when movement goals change. Front Neuroeng (2012) 0.92

Design and validation of a real-time spiking-neural-network decoder for brain-machine interfaces. J Neural Eng (2013) 0.92

Neural population partitioning and a concurrent brain-machine interface for sequential motor function. Nat Neurosci (2012) 0.91

The parietal reach region is limb specific and not involved in eye-hand coordination. J Neurophysiol (2013) 0.91

Variational Bayesian least squares: an application to brain-machine interface data. Neural Netw (2008) 0.91

Decoding movement intent from human premotor cortex neurons for neural prosthetic applications. J Clin Neurophysiol (2006) 0.91

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Selective visual attention to drive cognitive brain-machine interfaces: from concepts to neurofeedback and rehabilitation applications. Front Syst Neurosci (2014) 0.89

Dopamine modulates the neural representation of subjective value of food in hungry subjects. J Neurosci (2014) 0.89

Vacillation, indecision and hesitation in moment-by-moment decoding of monkey motor cortex. Elife (2015) 0.89

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