PROCESSING LOW-CONTRAST IMAGES OF METALS AND ALLOYS ON THE BASIS OF BIOLOGICAL NEURAL NETWORK WITH HYSTERESIS PROPERTIES

The study of the principles of formation and development of the structure of the brain is necessary to replenish fundamental knowledge both in the field of neurophysiology and in medicine. A detailed description of all the features of the brain will allow you to choose the most effective therapy method, or check the effectiveness of the drugs being developed. The basis for creating a model of a biological neural network is a map of nerve cells and their connections. To obtain it, it is necessary to carry out microscopy of the cell culture. This will produce a low-contrast image. The study of these images is a difficult task therefore a computational method for processing images based on the Shearlet transform algorithm with contrast using color coding has been developed, designed to improve the process of creating a neural network model. To assess the functional characteristics of each cell a modified version of the MEA method is proposed. The new version will have movable microelectrodes capable of homing to the desired coordinates in accordance with the data from the analyzed microscopic images and interacting with a specific neuron. The contact of a microelectrode with a single cell allows one to study its individual adhesions with minimal noise from the excitation of neighboring cells.

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A Biological Neural Network Analysis of Learning and Memory: The Cerebellum and Sensory Motor Conditioning.

10.21236/ada304568 ◽

1995 ◽

Author(s):

Richard F. Thompson

Keyword(s):

Neural Network ◽

Network Analysis ◽

Learning And Memory ◽

Neural Network Analysis ◽

Biological Neural Network ◽

Sensory Motor ◽

Motor Conditioning

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An Automatic Particle Pickup Method Using a Neural Network Applicable to Low-Contrast Electron Micrographs

Journal of Structural Biology ◽

10.1006/jsbi.2002.4442 ◽

2001 ◽

Vol 136 (3) ◽

pp. 227-238 ◽

Cited By ~ 34

Author(s):

Toshihiko Ogura ◽

Chikara Sato

Keyword(s):

Neural Network ◽

Electron Micrographs ◽

Low Contrast

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CAJAL - 91: A Biological Neural Network Simulator

Neural Systems: Analysis and Modeling ◽

10.1007/978-1-4615-3560-7_8 ◽

1993 ◽

pp. 103-111

Author(s):

Edward K. Blum ◽

Peyvand M. Khademi ◽

Kevin Chau ◽

Patrick Leung ◽

Xin Wang

Keyword(s):

Neural Network ◽

Network Simulator ◽

Biological Neural Network

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The Inter-Human Cortex

10.1093/oxfordhb/9780190274054.013.9 ◽

2021 ◽

pp. 102-112

Author(s):

John Matthias

Keyword(s):

Neural Network ◽

Human Brain ◽

Sound Art ◽

Human Cortex ◽

Biological Neural Network ◽

Physical Network ◽

Human Culture ◽

Art Installation

This chapter outlines a theory of co-evolution of contexts and histories in human culture by making an analogy with the microscopic functionality of the human brain, and in particular Eugene Izhikevich’s idea of polychronization by mapping the network of ‘firing’ events in a biological neural network onto a network of ‘human events’ in the physical network of humans. The article utilizes the new theory to focus on the evolution of sound art by pointing to the multiplicity of origin contexts, and it examines a particular example of sound art installation, The Fragmented Orchestra (Jane Grant, John Matthias, and Nick Ryan) to exemplify the theory of the inter-human cortex.

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