TY - GEN
T1 - Reduced behavioral flexibility by aberrant sensory precision in autism spectrum disorder
T2 - 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, ICDL-EpiRob 2017
AU - Idei, Hayato
AU - Murata, Shingo
AU - Chen, Yiwen
AU - Yamashita, Yuichi
AU - Tani, Jun
AU - Ogata, Tetsuya
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/4/2
Y1 - 2018/4/2
N2 - Recently, the importance of the application of computational models utilized in cognitive neuroscience to psychiatric disorders has been recognized. This study utilizes a recurrent neural network model to test aberrant sensory precision, a normative theory of autism spectrum disorder. We particularly focus on the effects of increased and decreased sensory precision on adaptive behavior based on a prediction error minimization mechanism. To distinguish dysfunction at the behavioral and network levels, we employ a humanoid robot driven by a neural network and observe ball-playing interactions with a human experimenter. Experimental results show that behavioral rigidity characteristic of autism spectrum disorder - including stopping movement and repetitive behavior - was generated from both increased and decreased sensory precision, but through different processes at the network level. These results may provide a system-level explanation of different types of behavioral rigidity in psychiatric diseases such as compulsions and stereotypies. The results also support a system-level model for autism spectrum disorder that suggests core deficits in estimating the uncertainty of sensory evidence.
AB - Recently, the importance of the application of computational models utilized in cognitive neuroscience to psychiatric disorders has been recognized. This study utilizes a recurrent neural network model to test aberrant sensory precision, a normative theory of autism spectrum disorder. We particularly focus on the effects of increased and decreased sensory precision on adaptive behavior based on a prediction error minimization mechanism. To distinguish dysfunction at the behavioral and network levels, we employ a humanoid robot driven by a neural network and observe ball-playing interactions with a human experimenter. Experimental results show that behavioral rigidity characteristic of autism spectrum disorder - including stopping movement and repetitive behavior - was generated from both increased and decreased sensory precision, but through different processes at the network level. These results may provide a system-level explanation of different types of behavioral rigidity in psychiatric diseases such as compulsions and stereotypies. The results also support a system-level model for autism spectrum disorder that suggests core deficits in estimating the uncertainty of sensory evidence.
UR - http://www.scopus.com/inward/record.url?scp=85050359930&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050359930&partnerID=8YFLogxK
U2 - 10.1109/DEVLRN.2017.8329817
DO - 10.1109/DEVLRN.2017.8329817
M3 - Conference contribution
AN - SCOPUS:85050359930
T3 - 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, ICDL-EpiRob 2017
SP - 271
EP - 276
BT - 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, ICDL-EpiRob 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 18 September 2017 through 21 September 2017
ER -
