Results 41 to 50 of about 97,052 (301)

Deep Learning for Whole-Brain Cognitive Decoding [PDF]

, 2022
2224Accurately decoding brain activities is both a challenge for machine learning and a potential vehicle for gaining insight into complex cognitive brain states and their dynamics. In this brief note, we will touch upon selected recent directions of our
K.-R. Muller, W. Samek, Thomas, Armin W., Müller, Klaus-Robert, Samek, Wojciech, A. W. Thomas   +5 more
core   +1 more source

Future developments in brain-machine interface research [PDF]

, 2011
Neuroprosthetic devices based on brain-machine interface technology hold promise for the restoration of body mobility in patients suffering from devastating motor deficits caused by brain injury, neurologic diseases and limb loss. During the last decade,
Andrew M. Fuller, Nicolelis, Miguel A. L., Je Hi An, Jesse A. Winans, Fuller, Andrew M., Mikhail A. Lebedev, Lebedev, Mikhail A., Schwarz, David A., Andrew J. Tate, Katie Z. Zhuang, Miguel A. L. Nicolelis, Peter J. Ifft, Li, Zheng, Fitzsimmons, Nathan A., Zheng Li, Ifft, Peter J., Timothy L. Hanson, An, Je Hi, Winans, Jesse A., David A. Schwarz, Zhuang, Katie Z., Joseph E. O'Doherty, Tate, Andrew J., O\u27Doherty, Joseph E., Nathan A. Fitzsimmons, Hanson, Timothy L.   +25 more
core   +1 more source

Evaluating Classifiers to Detect Arm Movement Intention from EEG Signals

Sensors, 2014
This paper presents a methodology to detect the intention to make a reaching movement with the arm in healthy subjects before the movement actually starts.
Daniel Planelles, Enrique Hortal, Álvaro Costa, Andrés Úbeda, Eduardo Iáez, José M. Azorín   +5 more
doaj   +1 more source

Neural encoding of actual and imagined touch within human posterior parietal cortex

eLife, 2021
In the human posterior parietal cortex (PPC), single units encode high-dimensional information with partially mixed representations that enable small populations of neurons to encode many variables relevant to movement planning, execution, cognition, and
Srinivas Chivukula, Carey Y Zhang, Tyson Aflalo, Matiar Jafari, Kelsie Pejsa, Nader Pouratian, Richard A Andersen   +6 more
doaj   +1 more source

Brain-Machine: nuevas interfaces / Brain Machines: New Interfaces

Bajo Palabra, 2017
A pesar del creciente número de descubrimientos en la neurociencia, los enormes logros tecnológicos y algún nuevo impulso teórico, aún sigue firme entre los científicos –así como en el sentido común– un contraste claro y marcado entre la mente y el cuerpo.
openaire   +2 more sources

Brain–machine interface for eye movements [PDF]

Proceedings of the National Academy of Sciences, 2014
SignificanceWe developed a brain–machine interface (BMI) that records single cell activity from populations of neurons for decoding planned eye movements (i.e., saccades) without the animals executing them. The recordings were made from the lateral intraparietal area, an important cortical node in the primate saccade system.
Graf, Arnulf B. A., Andersen, Richard A.
openaire   +3 more sources

Conditional associative learning examined in a paralyzed patient with amyotrophic lateral sclerosis using brain-computer interface technology [PDF]

, 2008
Background Brain-computer interface methodology based on self-regulation of slow-cortical potentials (SCPs) of the EEG (electroencephalogram) was used to assess conditional associative learning in one severely paralyzed, late-stage ALS patient.
Ghanayim, Nimr, J Kaiser, N Neumann, Iversen IH, Birbaumer N, Neumann, Nicola, Iversen, Iver H., Kaiser, Jochen, Kaiser J, Ghanayim N, Kübler, Andrea, Neumann N, N Birbaumer, N Ghanayim, IH Iversen, A Kübler, IH Iversen, Birbaumer, Niels, Kübler A   +18 more
core   +1 more source

Mobile Brain-Body Imaging and Visual Data of Theatrical Actors During Rehearsal and Performance

Scientific Data
This longitudinal Mobile Brain-Body Imaging dataset was acquired during six rehearsal sessions and three public performances of a scene from a play with highly emotional components.
Manuel Flurin Hendry, Jesus G. Cruz-Garza, Esther A. Delgado-Jiménez, Yoshua E. Lima-Carmona, Aime J. Aguilar-Herrera, Mauricio A. Ramírez-Moreno, Akshay Sujatha Ravindran, Andrew Y. Paek, Michelle Smith, Julia Kan, Mikayla Fors, Amirah Alam, Ruofan Liu, Adam Noble, Jose L. Contreras-Vidal   +14 more
doaj   +1 more source

Time-Frequency Analysis of Motor Imagery During Plantar and Dorsal Flexion Movements Using a Low-Cost Ankle Exoskeleton

Sensors
Sensor technology plays a fundamental role in neuro-motor rehabilitation by enabling precise movement analysis and control. This study explores the integration of brain–machine interfaces (BMIs) and wearable sensors to enhance motor recovery in ...
Cristina Polo-Hortigüela, Mario Ortiz, Paula Soriano-Segura, Eduardo Iáñez, José M. Azorín   +4 more
doaj   +1 more source

Real-time EEG-based brain-computer interface to a virtual avatar enhances cortical involvement in human treadmill walking

Scientific Reports, 2017
Recent advances in non-invasive brain-computer interface (BCI) technologies have shown the feasibility of neural decoding for both users’ gait intent and continuous kinematics. However, the dynamics of cortical involvement in human upright walking with a
Trieu Phat Luu, Sho Nakagome, Yongtian He, Jose L. Contreras-Vidal   +3 more
doaj   +1 more source