Spontaneous emergence of topographic organization in a multistream convolutional neural network
This study shows that a multistream convolutional neural network spontaneously develops topographic organization, improving model performance.
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Center for Information and Neural NetworksORCID 0000-0002-4530-2315Unclaimed ORCID profile · follow to get notified of new preprints
4 papers
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This study shows that a multistream convolutional neural network spontaneously develops topographic organization, improving model performance.
The paper examines how the temporal pattern of thalamic neuron spiking activity relates to cortical activation, finding that specific spike patterns induce greater cortical LFP modulation than high-frequency spiking.
The paper examines spiking activity correlations across three visual cortical areas in macaques, finding differences in correlation strength and suggesting unique circuitry and encoding mechanisms in each area.
Hiroshi Tamura, Haruki Otsuka, Y. Yamane
The paper investigates how neurons in the macaque monkey's inferior temporal cortex respond to surface features of natural objects, finding that a significant fraction of neurons selectively respond to these features.