By Christoph Guger, Theresa Vaughan, Brendan Allison

This e-book presents a state of the art evaluate of the newest advancements in Brain-Computer-Interfaces (BCIs), mentioned by way of major learn teams. because the reader will notice, BCI learn is relocating forward speedily, with many new rules, learn projects, and better applied sciences, e.g. BCIs that let humans to speak simply by pondering – with none stream in any respect. a number of diversified teams are aiding critically disabled clients converse utilizing BCIs, and BCI expertise can also be being prolonged to facilitate restoration from stroke, epilepsy, and different conditions.

Each yr, 1000s of the pinnacle BCI scientists, engineers, medical professionals, and different visionaries compete for the main prestigious honor within the BCI learn group: the once a year BCI Award. The 2013 BCI Award pageant was once via some distance the main aggressive, with over one hundred sixty learn teams vying for a nomination. The chapters of this booklet summarize the 10 initiatives that have been nominated, particularly the profitable venture, and analyses how those mirror basic tendencies in BCI improvement. every one undertaking precis comprises an advent, description of tools, effects, and likewise comprises more recent paintings accomplished after the undertaking used to be entered for the contest. The texts are awarded in obtainable type with a variety of assisting photographs, graphs, and figures.

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1088/1741-2560/5/1/008 Schiefer MA, Polasek KH, Tiolo RJ, Pinault GCJ, Tyler DJ (2010) Selective stimulation of the human femoral nerve with a flat interface nerve electrode. J Neural Eng 7(2). Selective Shanechi MM, Williams ZM, Wornell GW, Hu RC, Powers M, Brown EN (2013) A real-time brain-machine interface combining motor target and trajectory intent using an optimal feedback control design. PLoS ONE 8(4):e59049. 0059049 Shokur S, O’Doherty JE, Winans JA, Bleuler H, Lebedev MA, Nicolelis MA (2013) Expanding the primate body schema in sensorimotor cortex by virtual touches of an avatar.

As one would predict from its importance for normal limb function, there is growing direct evidence that artificial proprioception would improve motor performance with prosthetic limbs. Monkeys making virtual reaches with a BrainComputer Interface (BCI) controlled cursor demonstrated better performance levels when an exoskeletal robot passively moved their forelimb to track the cursor movement, compared to performance when their limb was held still or moved randomly (Suminski et al. 2010). Although visual feedback of the state of the cursor A Learning-Based Approach to Artificial Sensory Feedback 33 was available in all conditions, BCI control only approached natural levels of performance and fluidity when additional state information was provided by intact proprioceptive feedback.

Neural Comput 18(7):1527–1554. 1527 Histed MH, Bonin V, Reid RC (2009) Direct activation of sparse, distributed populations of cortical neurons by electrical microstimulation. Neuron 63(4):508–522. 1016/j. 016 Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, Branner A, Chen D, Penn RD, Donoghue JP (2006) Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442(7099):164–171. 1038/nature04970 Hochberg LR, Bacher D, Jarosiewicz B, Masse NY, Simeral JD, Vogel J, Haddadin S, Liu J, Cash SS, van der Smagt P, Donoghue JP (2012) Reach and grasp by people with tetraplegia using a neurally controlled robotic arm.

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