Virtual Reality Platform for Systematic Investigation of Multisensory Integration and Training of Closed-Loop Prosthetic Control

被引:0
作者
Phataraphruk, Kris [1 ]
VanGilder, Paul [1 ]
Buneo, Christopher A. [1 ]
机构
[1] Arizona State Univ, Sch Biol & Hlth Syst Engn, Tempe, AZ 85287 USA
来源
42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20 | 2020年
基金
美国国家科学基金会;
关键词
BRAIN;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Multisensory integration is the process by which information from different sensory modalities is integrated by the nervous system. Understanding this process is important not only from a basic science perspective but also for translational reasons, e.g. for the development of closed-loop neural prosthetic systems. Here we describe a versatile virtual reality platform which can be used to study the neural mechanisms of multisensory integration for the upper limb and could potentially be incorporated into systems for training of robust neural prosthetic control. The platform involves the interaction of multiple computers and programs and allows for selection of different avatar arms and for modification of a selected arm's visual properties. The system was tested with two non-human primates (NHP) that were trained to reach to multiple targets on a tabletop. Reliability of arm visual feedback was altered by applying different levels of blurring to the arm. In addition, tactile feedback was altered by adding or removing physical targets from the environment. We observed differences in movement endpoint distributions that varied between animals and visual feedback conditions, as well as across targets. The results indicate that the system can be used to study multisensory integration in a well-controlled manner.
引用
收藏
页码:2942 / 2945
页数:4
相关论文
共 11 条
  • [1] Multisensory integration: psychophysics, neurophysiology, and computation
    Angelaki, Dora E.
    Gu, Yong
    DeAngelis, Gregory C.
    [J]. CURRENT OPINION IN NEUROBIOLOGY, 2009, 19 (04) : 452 - 458
  • [2] Learning to control a brain-machine interface for reaching and grasping by primates
    Carmena, JM
    Lebedev, MA
    Crist, RE
    O'Doherty, JE
    Santucci, DM
    Dimitrov, DF
    Patil, PG
    Henriquez, CS
    Nicolelis, MAL
    [J]. PLOS BIOLOGY, 2003, 1 (02) : 193 - 208
  • [3] Merging the senses into a robust percept
    Ernst, MO
    Bülthoff, HH
    [J]. TRENDS IN COGNITIVE SCIENCES, 2004, 8 (04) : 162 - 169
  • [4] Noise in the nervous system
    Faisal, A. Aldo
    Selen, Luc P. J.
    Wolpert, Daniel M.
    [J]. NATURE REVIEWS NEUROSCIENCE, 2008, 9 (04) : 292 - 303
  • [5] The Bayesian brain: the role of uncertainty in neural coding and computation
    Knill, DC
    Pouget, A
    [J]. TRENDS IN NEUROSCIENCES, 2004, 27 (12) : 712 - 719
  • [6] Bayesian integration in sensorimotor learning
    Körding, KP
    Wolpert, DM
    [J]. NATURE, 2004, 427 (6971) : 244 - 247
  • [7] An interpretative phenomenological analysis of the embodiment of artificial limbs
    Murray, CD
    [J]. DISABILITY AND REHABILITATION, 2004, 26 (16): : 963 - 973
  • [8] A training platform for many-dimensional prosthetic devices using a virtual reality environment
    Putrino, David
    Wong, Yan T.
    Weiss, Adam
    Pesaran, Bijan
    [J]. JOURNAL OF NEUROSCIENCE METHODS, 2015, 244 : 68 - 77
  • [9] Cortical neural prosthetics
    Schwartz, AB
    [J]. ANNUAL REVIEW OF NEUROSCIENCE, 2004, 27 : 487 - 507
  • [10] Multimodal representation of limb endpoint position in the posterior parietal cortex
    Shi, Ying
    Apker, Gregory
    Buneo, Christopher A.
    [J]. JOURNAL OF NEUROPHYSIOLOGY, 2013, 109 (08) : 2097 - 2107