D-Index & Metrics Best Publications
Miguel A. L. Nicolelis

Miguel A. L. Nicolelis

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Neuroscience D-index 93 Citations 35,617 285 World Ranking 566 National Ranking 326

Research.com Recognitions

Awards & Achievements

2017 - IEEE Daniel E. Noble Award for Emerging Technologies "For seminal contributions to brain-machine interfaces."

2010 - National Institutes of Health Director's Pioneer Award

2004 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

What is he best known for?

The fields of study he is best known for:

  • Neuroscience
  • Artificial intelligence
  • Internal medicine

Miguel A. L. Nicolelis mostly deals with Neuroscience, Somatosensory system, Thalamus, Sensory system and Motor cortex. Neural ensemble, Premovement neuronal activity, Neurophysiology, Cortical neurons and Electrophysiology are the subjects of his Neuroscience studies. His studies in Somatosensory system integrate themes in fields like Stimulus, Stimulation and Neuron.

His research in Thalamus intersects with topics in Receptive field, Motor control, Trigeminal nerve, Anatomy and Cortex. The Sensory system study combines topics in areas such as Somatosensory evoked potential, Human arm, Perception and Human–computer interaction. His study in Motor cortex is interdisciplinary in nature, drawing from both Real-time Control System, Robotic arm, Trajectory and Motor learning.

His most cited work include:

  • Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates (1444 citations)
  • Brain–machine interfaces: past, present and future (1292 citations)
  • Real-time prediction of hand trajectory by ensembles of cortical neurons in primates (1230 citations)

What are the main themes of his work throughout his whole career to date?

His primary scientific interests are in Neuroscience, Somatosensory system, Sensory system, Brain–computer interface and Artificial intelligence. His Thalamus, Motor cortex, Premovement neuronal activity, Neurophysiology and Stimulation investigations are all subjects of Neuroscience research. His Thalamus study incorporates themes from Electrophysiology, Nucleus and Neuron.

His research in Somatosensory system tackles topics such as Cortex which are related to areas like Local field potential. His work deals with themes such as Tactile discrimination, Neuroplasticity, Taste and Microstimulation, which intersect with Sensory system. Miguel A. L. Nicolelis combines subjects such as Computer vision and Pattern recognition with his study of Artificial intelligence.

He most often published in these fields:

  • Neuroscience (72.45%)
  • Somatosensory system (31.89%)
  • Sensory system (20.74%)

What were the highlights of his more recent work (between 2015-2021)?

  • Neuroscience (72.45%)
  • Somatosensory system (31.89%)
  • Sensory system (20.74%)

In recent papers he was focusing on the following fields of study:

Miguel A. L. Nicolelis focuses on Neuroscience, Somatosensory system, Sensory system, Brain–computer interface and Artificial intelligence. His work on Neuroscience deals in particular with Neurophysiology, Motor cortex, Stimulation, Spinal cord and Local field potential. His Somatosensory system research incorporates elements of Neocortex, Neuroplasticity and Neuroprosthetics.

His Sensory system study combines topics from a wide range of disciplines, such as Stroke, Tactile discrimination, Neurological injury and Spinal cord stimulation. The various areas that he examines in his Brain–computer interface study include Hippocampal formation, Place cell, Premotor cortex and Simulation. His work on Robotics, Wavelet and Feature as part of general Artificial intelligence research is frequently linked to Train, bridging the gap between disciplines.

Between 2015 and 2021, his most popular works were:

  • Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients (182 citations)
  • Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation (178 citations)
  • Wireless Cortical Brain-Machine Interface for Whole-Body Navigation in Primates (47 citations)

In his most recent research, the most cited papers focused on:

  • Neuroscience
  • Artificial intelligence
  • Internal medicine

His scientific interests lie mostly in Neuroscience, Somatosensory system, Neurophysiology, Neurorehabilitation and Brain–computer interface. His study ties his expertise on Deep brain stimulation together with the subject of Neuroscience. His Somatosensory system research integrates issues from Neocortex and Sensory system.

His research in Sensory system intersects with topics in Neuroplasticity, Receptive field and Microstimulation. His research integrates issues of Motor cortex, Dopaminergic, Reward system and Midbrain in his study of Neurophysiology. Miguel A. L. Nicolelis studied Brain–computer interface and Simulation that intersect with Cortical neurons and Wireless.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates

Jose M Carmena;Mikhail A Lebedev;Roy E Crist;Joseph E O'Doherty.
PLOS Biology (2003)

2185 Citations

Brain–machine interfaces: past, present and future

Mikhail A. Lebedev;Miguel A. L. Nicolelis.
Trends in Neurosciences (2006)

2132 Citations

Real-time prediction of hand trajectory by ensembles of cortical neurons in primates

Johan Wessberg;Christopher R. Stambaugh;Jerald D. Kralik;Pamela D. Beck.
Nature (2000)

1837 Citations

Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex

John K. Chapin;Karen A. Moxon;Ronald S. Markowitz;Miguel A. L. Nicolelis.
Nature Neuroscience (1999)

1483 Citations

Actions from thoughts

Miguel A. L. Nicolelis.
Nature (2001)

1249 Citations

Chronic, multisite, multielectrode recordings in macaque monkeys

Miguel A. L. Nicolelis;Dragan Dimitrov;Jose M. Carmena;Roy Crist.
Proceedings of the National Academy of Sciences of the United States of America (2003)

911 Citations

Remote control of neuronal activity in transgenic mice expressing evolved G protein-coupled receptors.

Georgia M. Alexander;Sarah C. Rogan;Atheir I. Abbas;Blaine N. Armbruster.
Neuron (2009)

859 Citations

Brain-machine interfaces to restore motor function and probe neural circuits.

Miguel A L Nicolelis.
Nature Reviews Neuroscience (2003)

729 Citations

Sensorimotor encoding by synchronous neural ensemble activity at multiple levels of the somatosensory system

Miguel A. L. Nicolelis;Luiz A. Baccala;Rick C. S. Lin;John K. Chapin.
Science (1995)

694 Citations

Cortical Ensemble Adaptation to Represent Velocity of an Artificial Actuator Controlled by a Brain-Machine Interface

Mikhail A. Lebedev;Jose M. Carmena;Joseph E. O'Doherty;Miriam Zacksenhouse.
The Journal of Neuroscience (2005)

688 Citations

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