doi/intestelligence: Intestelligence: A pharmacological neural network using intestine data

Intestelligence: A pharmacological neural network using intestine data

Yusuke Watanabe d062d870ec update		6 ヶ月前
extended_data	e6e3e6f9d1 update	6 ヶ月前
scripts	37398ef990 update	6 ヶ月前
.gitignore	0e3cd18b71 first commit	1 年間前
LICENSE	1b2f6e5637 add license	6 ヶ月前
README.md	d062d870ec update	6 ヶ月前
datacite.yml	e6e3e6f9d1 update	6 ヶ月前
requirements.txt	37398ef990 update	6 ヶ月前

Intestelligence: A pharmacological neural network using intestine data

This repository includes the data and source code of our paper (This link will be updated to a DOI URL after being published).

Installation

$ git clone git@gin.g-node.org:/intestelligence/intestelligence.git && cd intestelligence
$ python -m venv env && source env/bin/activate && pip install -r requirements.txt

Scripts

./scripts/PerceptronOrINN.py:
Contains the definitions of Intestine-derived Neural Network (INN) and perceptron models.
./scripts/train_MNIST.py:
Trains and evaluates the INN or Perceptron model on the MNIST dataset.

Runs an example code

$ python ./scripts/train_MNIST.py --activation_function intestine_simulated # INN
$ python ./scripts/train_MNIST.py --activation_function sigmoid # Perceptron

BibTeX Citation

@article {Watanabe2023.04.15.537044,
	author = {Yusuke Watanabe and Hiroshi Ban and Nobuhiro Hagura and Yuji Ikegaya},
	title = {Intestelligence: A pharmacological neural network using intestine data},
	elocation-id = {2023.04.15.537044},
	year = {2023},
	doi = {10.1101/2023.04.15.537044},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {A neural network is a machine learning algorithm that can learn and make predictions by adjusting the strength of the connections between nodes. The sigmoid function is commonly used as an activation function in these nodes. This study explores the potential applicability of biological materials in the development of alternative activation functions. Inspired by the fact that acetylcholine induces intestinal contractions that follow a sigmoid function, we used pharmacological data obtained from guinea pig ilea in a layered neural network for image classification tasks. We found that the intestinal data-based neural network with the same structure as a conventional three-layer perceptron achieved an impressive classification accuracy of 85.7\% {\textpm} 0.6\% based on the MNIST handwritten digit dataset (chance = 10\%). Additionally, the neural network was trained to determine whether objects in photographs collected from the internet were digestible, achieving an accuracy of 88.5\% {\textpm} 0.9\% (chance = 50\%). Our approach highlights the potential applicability of intestine data in neural computations based on pharmacological mechanisms.Competing Interest StatementThe authors have declared no competing interest.},
	URL = {https://www.biorxiv.org/content/early/2023/04/17/2023.04.15.537044},
	eprint = {https://www.biorxiv.org/content/early/2023/04/17/2023.04.15.537044.full.pdf},
	journal = {bioRxiv}
}

datacite.yml
Title	Intestelligence: A pharmacological neural network using intestine data
Authors	Watanabe,Yusuke;Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo 113-0033, Japan; Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, 3010, Australia;ORCID:0000-0001-9541-6073 Ban,Hiroshi;Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita City, Osaka, 565-0871, Japan Hagura,Nobuhiro;Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita City, Osaka, 565-0871, Japan Ikegaya,Yuji;Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo 113-0033, Japan; Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita City, Osaka, 565-0871, Japan; Institute for AI and Beyond, The University of Tokyo, Tokyo 113-0033, Japan;ORCID:0000-0003-2260-8191
Description	"Background: A neural network is a machine learning algorithm that can learn and make predictions by adjusting the strength of the connections between nodes. The sigmoid function is commonly used as an activation function in these nodes. This study explores the potential applicability of biological materials in the development of alternative activation functions. Methods: Inspired by the fact that acetylcholine induces intestinal contractions that follow a sigmoid function, we used pharmacological data obtained from guinea pig ilea in a layered neural network for image classification tasks. Results: and Conclusions We found that the intestinal data-based neural network with the same structure as a conventional three-layer perceptron achieved an impressive classification accuracy of 85.7% ± 0.6% based on the MNIST handwritten digit dataset (chance = 10%). Additionally, the neural network was trained to determine whether objects in photographs collected from the internet were digestible, achieving an accuracy of 88.5% ± 0.9% (chance = 50%). Our approach highlights the potential applicability of intestine data in neural computations based on pharmacological mechanisms."
License	CC0 (http://creativecommons.org/publicdomain/zero/1.0)
References	Yusuke Watanabe, Hiroshi Ban, Nobuhiro Hagura, and Yuji Ikegaya (2024) Intestelligence: A pharmacological neural network using intestine data. F1000research, under review. [tba] (IsSupplementTo) Watanabe Y, Ban H, Haugra N, Ikegaya Y (2023) Intestelligence: A pharmacological neural network using intestine data. bioRxiv 2023.04.15.537044. https://doi.org/10.1101/2023.04.15.537044 [doi:10.1101/2023.04.15.537044] (IsSupplementTo)
Funding	Japan Science and Technology Agency (JST); Exploratory Research for Advanced Technology (ERATO) grant JPMJER1801
Keywords	Biologically-inspired Neural Network Activation Function Intestine
Resource Type	Software

README.md

Intestelligence: A pharmacological neural network using intestine data

Installation

Scripts

Runs an example code

BibTeX Citation