Illustration of the input series.

<p>Networks were trained according to a moving MNIST paradigm. For each batch, multiple samples were fed to the network. Each sample contained a series of images, depicting a number moving across the visual field. Each separate number class moves across the visual field according to specific r...

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Bibliographic Details
Main Author:	Dirk Gütlin (22566778) (author)
Other Authors:	Ryszard Auksztulewicz (4640515) (author)
Published:	2025
Subjects:	Biophysics Neuroscience Physiology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified without evaluating whether like effects across like behaviors better including mismatch responses biological neural networks compared two pc advancing brain modelling inspired training objectives like responses training algorithms neural learning work contributes underlying mechanisms semantic information saving principles results show promising foundation pc framework neuroscientific theory key signatures inspired algorithms important mechanism gain control findings indicate dnn ). contrastive approach accurately reflect
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Illustration of the input series.

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