Model structure of sparse/predictive coding (SPC).

Model structure of sparse/predictive coding (SPC).

<p>The first layer computes the prediction error between the input and reconstruction of the model, and then sends error signals to the second layer. The second layer takes input from the first layer and incorporates the response-regulating mechanism, . This two-layer network implements the dy...

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Bibliographic Details
Main Author: Yanbo Lian (10219563) (author)
Other Authors: Anthony N. Burkitt (6732233) (author)
Published: 2025
Subjects:
Physiology
Science Policy
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
substantial experimental evidence
replicates different forms
primary visual cortex
learn simple cells
still poorly understood
implementing predictive coding
regulates neural responses
implements sparse coding
learning framework based
predictive coding
neural responses
sparse coding
sparse responses
predictive structure
neural circuits
well investigated
unified framework
study demonstrates
relating sparse
network structure
many parts
learning framework
integrate input
hebbian learning
framework incorporates
explicitly within
divisive normalization
described within
contrast saturation
biophysical properties
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Summary:<p>The first layer computes the prediction error between the input and reconstruction of the model, and then sends error signals to the second layer. The second layer takes input from the first layer and incorporates the response-regulating mechanism, . This two-layer network implements the dynamics described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013059#pcbi.1013059.e055" target="_blank">Eq 10</a>.</p>

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