@article {3401, title = {Neurological principles and rehabilitation of action disorders: rehabilitation interventions.}, journal = {Neurorehabil Neural Repair}, volume = {25}, year = {2011}, month = {06/2011}, pages = {33S-43S}, abstract = {This third chapter discusses the evidence for the rehabilitation of the most common movement disorders of the upper extremity. The authors also present a framework, building on the computation, anatomy, and physiology (CAP) model, for incorporating some of the principles discussed in the 2 previous chapters by Frey et al and Sathian et al in the practice of rehabilitation and for discussing potentially helpful interventions based on emergent neuroscience principles.}, keywords = {Humans, Models, Neurological, Movement Disorders, Recovery of Function, Upper Extremity}, issn = {1552-6844}, doi = {10.1177/1545968311410942}, url = {http://www.ncbi.nlm.nih.gov/pubmed/21613536}, author = {Pomeroy, Valerie and Aglioti, Salvatore M and Mark, Victor W and Dennis J. McFarland and Stinear, Cathy and Wolf, Steven L and Corbetta, Maurizio and Fitzpatrick, Susan M} } @article {2191, title = {Evolution of brain-computer interfaces: going beyond classic motor physiology.}, journal = {Neurosurg Focus}, volume = {27}, year = {2009}, month = {07/2009}, pages = {E4}, abstract = {

The notion that a computer can decode brain signals to infer the intentions of a human and then enact those intentions directly through a machine is becoming a realistic technical possibility. These types of devices are known as brain-computer interfaces (BCIs). The evolution of these neuroprosthetic technologies could have significant implications for patients with motor disabilities by enhancing their ability to interact and communicate with their environment. The cortical physiology most investigated and used for device control has been brain signals from the primary motor cortex. To date, this classic motor physiology has been an effective substrate for demonstrating the potential efficacy of BCI-based control. However, emerging research now stands to further enhance our understanding of the cortical physiology underpinning human intent and provide further signals for more complex brain-derived control. In this review, the authors report the current status of BCIs and detail the emerging research trends that stand to augment clinical applications in the future.

}, keywords = {Brain, Cerebral Cortex, Humans, Man-Machine Systems, Motor Cortex, Movement, Movement Disorders, Neuronal Plasticity, Prostheses and Implants, Research, Signal Processing, Computer-Assisted, User-Computer Interface}, issn = {1092-0684}, doi = {10.3171/2009.4.FOCUS0979}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19569892}, author = {Leuthardt, E C and Gerwin Schalk and Roland, Jarod and Rouse, Adam and Moran, D} } @article {2189, title = {Advanced neurotechnologies for chronic neural interfaces: new horizons and clinical opportunities.}, journal = {J Neurosci}, volume = {28}, year = {2008}, month = {11/2008}, pages = {11830-8}, keywords = {Cerebral Cortex, Electrodes, Implanted, Electroencephalography, Electronics, Medical, Electrophysiology, Evoked Potentials, Movement Disorders, Neurons, Prostheses and Implants, User-Computer Interface}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.3879-08.2008}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19005048?report=abstract}, author = {Kipke, Daryl R and Shain, William and Buzs{\'a}ki, Gy{\"o}rgy and Fetz, Eberhard E and Henderson, Jaimie M and Hetke, Jamille F and Gerwin Schalk} } @article {2168, title = {A brain-computer interface using electrocorticographic signals in humans.}, journal = {J Neural Eng}, volume = {1}, year = {2004}, month = {06/2004}, pages = {63-71}, abstract = {

Brain-computer interfaces\ (BCIs) enable users to control devices with electroencephalographic (EEG) activity from the scalp or with single-neuron activity from within the\ brain. Both methods have disadvantages: EEG has limited resolution and requires extensive training, while single-neuron recording entails significant clinical risks and has limited stability. We demonstrate here for the first time that electrocorticographic (ECoG) activity recorded from the surface of the\ brain\ can enable users to control a one-dimensional\ computer\ cursor rapidly and accurately. We first identified ECoG signals that were associated with different types of motor and speech imagery. Over brief training periods of 3-24 min, four patients then used these signals to master closed-loop control and to achieve success rates of 74-100\% in a one-dimensional binary task. In additional open-loop experiments, we found that ECoG signals at frequencies up to 180 Hz encoded substantial information about the direction of two-dimensional joystick movements. Our results suggest that an ECoG-based BCI could provide for people with severe motor disabilities a non-muscular communication and control option that is more powerful than EEG-based BCIs and is potentially more stable and less traumatic than BCIs that use electrodes penetrating the\ brain.

}, keywords = {Adult, Brain, Communication Aids for Disabled, Computer Peripherals, Diagnosis, Computer-Assisted, Electrodes, Implanted, Electroencephalography, Evoked Potentials, Female, Humans, Imagination, Male, Movement Disorders, User-Computer Interface}, issn = {1741-2560}, doi = {10.1088/1741-2560/1/2/001}, url = {http://www.ncbi.nlm.nih.gov/pubmed/15876624}, author = {Leuthardt, E C and Gerwin Schalk and Jonathan Wolpaw and Ojemann, J G and Moran, D} }