Cognitive Neural Prosthetics.

The cognitive neural prosthetic (CNP) is a very versatile method for assisting paralyzed patients and patients with amputations. The CNP records the cognitive state of the subject, rather than signals strictly related to motor execution or sensation. We review a number of high-level cortical signals...

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Publicado en:Annual Review of Psychology Vol. 61; pp. 169 - 191
Autores principales: Andersen, Richard A., Hwang, Eun Jung, Mulliken, Grant H.
Formato: Artículo
Publicado: Annual Reviews Inc. 2010
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Acceso en línea:Ver este registro en EBSCOhost
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      pub: Annual Reviews Inc.
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        10.1146/annurev.psych.093008.100503
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        atl: Cognitive Neural Prosthetics.
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        au:
          Andersen, Richard A.
          Hwang, Eun Jung
          Mulliken, Grant H.
      su:
        Brain-computer interfaces
        People with paralysis
        Amputation
        Prosthetics
      sug:
        subj:
          Brain-computer interfaces
          People with paralysis
          Amputation
          Prosthetics
      keyword: Neural interfaces
      ab: The cognitive neural prosthetic (CNP) is a very versatile method for assisting paralyzed patients and patients with amputations. The CNP records the cognitive state of the subject, rather than signals strictly related to motor execution or sensation. We review a number of high-level cortical signals and their application for CNPs, including intention, motor imagery, decision making, forward estimation, executive function, attention, learning, and multi-effector movement planning. CNPs are defined by the cognitive function they extract, not the cortical region from which the signals are recorded. However, some cortical areas may be better than others for particular applications. Signals can also be extracted in parallel from multiple cortical areas using multiple implants, which in many circumstances can increase the range of applications of CNPs. The CNP approach relies on scientific understanding of the neural processes involved in cognition, and many of the decoding algorithms it uses also have parallels to underlying neural circuit functions.
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      doctype: Article
      src: R
    language: English
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