Artificial Neural Networks for In-silico Experiments on Perception

Simon Odense

2015

Abstract

Here the potential use of artificial neural networks for the purpose of understanding the biological processes behind perception is investigated. Current work in computer vision is surveyed focusing on methods to determine how a neural network utilizes it's resources. Analogies between feature detectors in deep neural networks and signaling pathways in the human brain are made. With these analogies in mind, procedures are outlined for experiments on perception using the recurrent temporal restricted Boltzmann machine as an example. The potential use of these experiments to help explain disorders of human perception is then described.

Paper Citation

in Harvard Style

Odense S. (2015). Artificial Neural Networks for In-silico Experiments on Perception . In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 3: NCTA, (ECTA 2015) ISBN 978-989-758-157-1, pages 163-167. DOI: 10.5220/0005633701630167

in Bibtex Style

@conference{ncta15,
author={Simon Odense},
title={Artificial Neural Networks for In-silico Experiments on Perception},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 3: NCTA, (ECTA 2015)},
year={2015},
pages={163-167},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005633701630167},
isbn={978-989-758-157-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 3: NCTA, (ECTA 2015)
TI - Artificial Neural Networks for In-silico Experiments on Perception
SN - 978-989-758-157-1
AU - Odense S.
PY - 2015
SP - 163
EP - 167
DO - 10.5220/0005633701630167