Image reconstruction method and device based on peak potential distribution time interval

A time interval, image reconstruction technology, applied in image data processing, neural learning methods, 2D image generation and other directions, can solve the problem of less consideration of the temporal structure information of spike signals

Inactive Publication Date: 2021-03-12
SUZHOU LANGCHAO INTELLIGENT TECH CO LTD
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  • Abstract
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Problems solved by technology

In the field of image reconstruction technology, using the effective features of neuron spike signals to reconstruct images is a decoding method different from the classification and recognition of external stimuli. The current research focuses on the reconstruction of brightness...

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  • Image reconstruction method and device based on peak potential distribution time interval
  • Image reconstruction method and device based on peak potential distribution time interval
  • Image reconstruction method and device based on peak potential distribution time interval

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Embodiment 1

[0041] Such as figure 1 As shown, this embodiment provides a method for image reconstruction based on the time interval of spike firing, including the following steps:

[0042] S1, extracting the release time interval characteristics of the spike;

[0043] The distribution of firing time intervals of action potential sequences also encodes external stimuli. As a common feature in neuronal time encoding patterns, the ISI (Inter-Spike Interval, peak potential firing interval) of neuronal firing sequences is usually irregular. , such irregular timing intervals may contain rich information coding, so this embodiment extracts the firing intervals of spike potentials for training to reconstruct images.

[0044] In this step, according to the acquired spike signal time series, the time interval between two adjacent spike signals in the spike signal time series under visual stimulation is counted, the length of the time window is set, and the release time that meets the length of eac...

Embodiment 2

[0063] Such as figure 2 As shown, based on Embodiment 1, this embodiment provides an image reconstruction device based on the time interval of spiking potential emission, including the following functional modules:

[0064] Feature extraction module 1: extract the release time interval feature of the spike;

[0065] Model building module 2: According to the characteristics of the time interval of the spike potential, the neural network learning algorithm is used to construct the reconstruction model;

[0066] Image reconstruction module 3: reconstruct the image based on the constructed reconstruction model.

[0067] Among them, the feature extraction module 1 calculates the time interval between two adjacent peak potential signals in the spike signal time series under visual stimulation according to the acquired spike signal time series, and sets the length of the time window. The length of the issuing time interval is counted, which specifically includes the following func...

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Abstract

The invention discloses an image reconstruction method and device based on a peak potential distribution time interval. The method comprises the following steps: extracting distribution time intervalcharacteristics of a peak potential; constructing a reconstruction model by using a neural network learning algorithm according to the distribution time interval characteristics of the peak potential;and reconstructing the image based on the constructed reconstruction model. According to the method, the issuing time interval characteristics in the peak potential signals are extracted, and the nonlinear neural network reconstruction model is combined, so that a complex gray level image is effectively reconstructed.

Description

technical field [0001] The invention relates to the field of spiking potential image reconstruction, in particular to an image reconstruction method and device based on the time interval of spiking potential emission. Background technique [0002] Spike potential is an important signal form for information integration and transmission between neurons. In a complex neural network, the effective characteristics of spike potential signals encode the information of external stimuli. In the field of image reconstruction technology, using the effective features of neuron spike signals to reconstruct images is a decoding method different from the classification and recognition of external stimuli. The current research focuses on the reconstruction of brightness information or simple artificial characters. The reconstructed signal features include spike firing rate and fMRI (functional magnetic resonance imaging, functional magnetic resonance imaging), etc., less consideration is gi...

Claims

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Application Information

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IPC IPC(8): G06T11/00G06N3/04G06N3/08A61B5/388
CPCG06T11/003G06N3/08A61B5/7235G06N3/045
Inventor 庞晨
Owner SUZHOU LANGCHAO INTELLIGENT TECH CO LTD
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