Literature DB >> 24709603

Brain-computer interfaces: a powerful tool for scientific inquiry.

Jeremiah D Wander1, Rajesh P N Rao2.   

Abstract

Brain-computer interfaces (BCIs) are devices that record from the nervous system, provide input directly to the nervous system, or do both. Sensory BCIs such as cochlear implants have already had notable clinical success and motor BCIs have shown great promise for helping patients with severe motor deficits. Clinical and engineering outcomes aside, BCIs can also be tremendously powerful tools for scientific inquiry into the workings of the nervous system. They allow researchers to inject and record information at various stages of the system, permitting investigation of the brain in vivo and facilitating the reverse engineering of brain function. Most notably, BCIs are emerging as a novel experimental tool for investigating the tremendous adaptive capacity of the nervous system.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 24709603      PMCID: PMC3980496          DOI: 10.1016/j.conb.2013.11.013

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  50 in total

1.  Performance over time of congenitally deaf and postlingually deafened children using a multichannel cochlear implant.

Authors:  H Fryauf-Bertschy; R S Tyler; D M Kelsay; B J Gantz
Journal:  J Speech Hear Res       Date:  1992-08

2.  Closed-loop decoder adaptation on intermediate time-scales facilitates rapid BMI performance improvements independent of decoder initialization conditions.

Authors:  Amy L Orsborn; Siddharth Dangi; Helene G Moorman; Jose M Carmena
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2012-07       Impact factor: 3.802

3.  Reorganization of functional and effective connectivity during real-time fMRI-BCI modulation of prosody processing.

Authors:  Giuseppina Rota; Giacomo Handjaras; Ranganatha Sitaram; Niels Birbaumer; Grzegorz Dogil
Journal:  Brain Lang       Date:  2010-10-02       Impact factor: 2.381

Review 4.  Computational analysis in vitro: dynamics and plasticity of a neuro-robotic system.

Authors:  Amir Karniel; Michael Kositsky; Karen M Fleming; Michela Chiappalone; Vittorio Sanguineti; Simon T Alford; Ferdinando A Mussa-Ivaldi
Journal:  J Neural Eng       Date:  2005-08-31       Impact factor: 5.379

Review 5.  Volitional control of neural activity: implications for brain-computer interfaces.

Authors:  Eberhard E Fetz
Journal:  J Physiol       Date:  2007-01-18       Impact factor: 5.182

6.  Long-term motor cortex plasticity induced by an electronic neural implant.

Authors:  Andrew Jackson; Jaideep Mavoori; Eberhard E Fetz
Journal:  Nature       Date:  2006-10-22       Impact factor: 49.962

7.  Coadaptive brain-machine interface via reinforcement learning.

Authors:  Jack DiGiovanna; Babak Mahmoudi; Jose Fortes; Jose C Principe; Justin C Sanchez
Journal:  IEEE Trans Biomed Eng       Date:  2009-01       Impact factor: 4.538

8.  Distributed cortical adaptation during learning of a brain-computer interface task.

Authors:  Jeremiah D Wander; Timothy Blakely; Kai J Miller; Kurt E Weaver; Lise A Johnson; Jared D Olson; Eberhard E Fetz; Rajesh P N Rao; Jeffrey G Ojemann
Journal:  Proc Natl Acad Sci U S A       Date:  2013-06-10       Impact factor: 11.205

9.  Intraocular retinal prosthesis.

Authors:  M S Humayun
Journal:  Trans Am Ophthalmol Soc       Date:  2001

10.  Cortical adaptation to a chronic micro-electrocorticographic brain computer interface.

Authors:  Adam G Rouse; Jordan J Williams; Jesse J Wheeler; Daniel W Moran
Journal:  J Neurosci       Date:  2013-01-23       Impact factor: 6.167

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  17 in total

1.  Comparison of subdural and subgaleal recordings of cortical high-gamma activity in humans.

Authors:  Jared D Olson; Jeremiah D Wander; Lise Johnson; Devapratim Sarma; Kurt Weaver; Edward J Novotny; Jeffrey G Ojemann; Felix Darvas
Journal:  Clin Neurophysiol       Date:  2015-04-09       Impact factor: 3.708

2.  The receptive field is dead. Long live the receptive field?

Authors:  Adrienne Fairhall
Journal:  Curr Opin Neurobiol       Date:  2014-03-04       Impact factor: 6.627

3.  Shedding light on learning.

Authors:  Byron M Yu; Steven M Chase
Journal:  Nat Neurosci       Date:  2014-06       Impact factor: 24.884

Review 4.  Parsing learning in networks using brain-machine interfaces.

Authors:  Amy L Orsborn; Bijan Pesaran
Journal:  Curr Opin Neurobiol       Date:  2017-08-24       Impact factor: 6.627

5.  Learning active sensing strategies using a sensory brain-machine interface.

Authors:  Andrew G Richardson; Yohannes Ghenbot; Xilin Liu; Han Hao; Cole Rinehart; Sam DeLuccia; Solymar Torres Maldonado; Gregory Boyek; Milin Zhang; Firooz Aflatouni; Jan Van der Spiegel; Timothy H Lucas
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-13       Impact factor: 11.205

6.  Neural correlates of learning in an electrocorticographic motor-imagery brain-computer interface.

Authors:  Tim M Blakely; Jared D Olson; Kai J Miller; Rajesh P N Rao; Jeffrey G Ojemann
Journal:  Brain Comput Interfaces (Abingdon)       Date:  2014-07-01

Review 7.  Towards neural co-processors for the brain: combining decoding and encoding in brain-computer interfaces.

Authors:  Rajesh Pn Rao
Journal:  Curr Opin Neurobiol       Date:  2019-04-04       Impact factor: 6.627

Review 8.  Brain-computer interfaces for dissecting cognitive processes underlying sensorimotor control.

Authors:  Matthew D Golub; Steven M Chase; Aaron P Batista; Byron M Yu
Journal:  Curr Opin Neurobiol       Date:  2016-01-19       Impact factor: 6.627

9.  Computing Arm Movements with a Monkey Brainet.

Authors:  Arjun Ramakrishnan; Peter J Ifft; Miguel Pais-Vieira; Yoon Woo Byun; Katie Z Zhuang; Mikhail A Lebedev; Miguel A L Nicolelis
Journal:  Sci Rep       Date:  2015-07-09       Impact factor: 4.379

10.  Cortico-Cortical Interactions during Acquisition and Use of a Neuroprosthetic Skill.

Authors:  Jeremiah D Wander; Devapratim Sarma; Lise A Johnson; Eberhard E Fetz; Rajesh P N Rao; Jeffrey G Ojemann; Felix Darvas
Journal:  PLoS Comput Biol       Date:  2016-08-19       Impact factor: 4.475

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