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Authors: Ian Bright and Raymond Pavloski

Affiliation: Indiana University of Pennsylvania, United States

ISBN: 978-989-758-161-8

Keyword(s): Hard Problem, Neurotechnology, Qualia, Recurrent Neural Network, Tolerance Space, Topological Vision, Visual Object Unity.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Biomedical Instruments and Devices ; Brain-Computer Interfaces ; Devices ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Physiological Computing Systems

Abstract: In response to a simulated retinal image of an object, the recurrent input to a richly connected artificial neural network organizes into a connected open set (COS) of ionic conductance values, which models the continuity and unity of a visual object. As the density of light dots on a dark background increases and then decreases, a COS appears at a density that is higher than that at which it disappears (hysteresis). This experiment tested the hypothesis that humans will show hysteresis similar to that of the simulation. In addition, the effect of dot lightness on the perception of a unified visual object was also tested.

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Paper citation in several formats:
Bright, I. and Pavloski, R. (2015). Hysteresis in the Perception of Visual Unity - Confirmation of a Neural Network Model Prediction.In Proceedings of the 3rd International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX, ISBN 978-989-758-161-8, pages 49-53. DOI: 10.5220/0005663300490053

@conference{neurotechnix15,
author={Ian Bright. and Raymond Pavloski.},
title={Hysteresis in the Perception of Visual Unity - Confirmation of a Neural Network Model Prediction},
booktitle={Proceedings of the 3rd International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX,},
year={2015},
pages={49-53},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005663300490053},
isbn={978-989-758-161-8},
}

TY - CONF

JO - Proceedings of the 3rd International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX,
TI - Hysteresis in the Perception of Visual Unity - Confirmation of a Neural Network Model Prediction
SN - 978-989-758-161-8
AU - Bright, I.
AU - Pavloski, R.
PY - 2015
SP - 49
EP - 53
DO - 10.5220/0005663300490053

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