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Natural image random forest imaging method based on an action potential discharging interval

A technology of natural images and action potentials, applied in the field of information science, can solve problems such as stimulation, inability to obtain external natural images, etc., and achieve good imaging effects.

Inactive Publication Date: 2018-12-11
TSINGHUA UNIV
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a natural image random forest imaging method based on action potential firing intervals, which solves the current technical problem that the stimulation content of external natural images cannot be obtained through biological EEG signals

Method used

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  • Natural image random forest imaging method based on an action potential discharging interval
  • Natural image random forest imaging method based on an action potential discharging interval
  • Natural image random forest imaging method based on an action potential discharging interval

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Experimental program
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specific Embodiment

[0063] Step 1: Select different natural images to stimulate animals, and collect action potential signals of the visual cortex of the animals;

[0064] Includes surgery on laboratory animals:

[0065] Before carrying out the experiment, it is necessary to select a suitable subject for surgery. The purpose of the surgery is to implant the 32-channel microelectrode array into the neurons of the visual cortex of the animal for the subsequent collection of action potential signals. The equipment required for the operation includes: 1) Surgical anti-vibration table; 2) Stereotaxic instrument; 3) Skull drill; 4) Cold light source; 5) Microscope; 6) Micro manipulator; ; 9) colloidal sponge; 10) microelectrode array, etc., wherein the microelectrode array uses 32 channels, and some channels are selected for reconstruction according to the actual situation in the test.

[0066] Build an experimental platform:

[0067] The purpose of this test platform is to realize the collection and...

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Abstract

The invention discloses a natural image random forest imaging method based on an action potential discharging interval, aiming at solving the problem of directly using a biological vision system as animaging system, obtaining a natural image by decoding an action potential signal of a visual cortex, and further realizing the imaging of an external natural image scene. The method includes: by selecting natural images to stimulate animals, collecting action potential signals of the visual cortex of the animals, extracting cluster release interval features of the action potential signals, and imaging the extracted cluster release interval features with a random forest model algorithm to obtain natural images. The realization process is simple, the imaging effect of the natural image is good,and the imaging accuracy is high.

Description

technical field [0001] The invention relates to the field of information science, in particular to a natural image random forest imaging method based on action potential firing intervals. Background technique [0002] When the prelude to brain science research began and human beings began to enter the field of neuroscience research, artificial intelligence based on computers is gradually becoming a representative of new "intelligence" activities. The visual system is an important part of the brain. Among them, the visual system is the main sensory system for animals to observe the external environment. Studies have proved that visual information accounts for more than 80% of the external information received by the animal brain. It is a very challenging problem to detect the action potential signal of brain neurons through implanted microelectrode array, extract the response features, construct the reconstruction model, and realize the reconstruction of visual perception i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62A61B5/0484
CPCA61B5/378G06F18/24323G06F18/214
Inventor 师丽王治忠王松伟牛晓可
Owner TSINGHUA UNIV
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