Short term memory properties of sensory neural architectures
| Autor: | Alexis Dubreuil |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Functional role Sensory Receptor Cells Computer science Cognitive Neuroscience Short-term memory Sensory system Stimulus (physiology) Memory performance 03 medical and health sciences Cellular and Molecular Neuroscience 0302 clinical medicine medicine Animals Humans Computer Simulation Transient (computer programming) Divergence (statistics) Cerebral Cortex business.industry Pattern recognition Sensory Systems Tree (data structure) 030104 developmental biology Memory Short-Term medicine.anatomical_structure Cerebral cortex Theory of computation Neural Networks Computer Artificial intelligence Nerve Net business 030217 neurology & neurosurgery Algorithms Psychomotor Performance |
| DOI: | 10.1101/590851 |
| Popis: | A functional role of the cerebral cortex is to form and hold representations of the sensory world for behavioral purposes. This is achieved by a sheet of neurons, organized in modules called cortical columns, that receives inputs in a peculiar manner, with only a few neurons driven by sensory inputs through thalamic projections, and a vast majority of neurons receiving mainly cortical inputs. How should cortical modules be organized, with respect to sensory inputs, in order for the cortex to efficiently hold sensory representations in memory? To address this question we investigate the memory performance of trees of recurrent networks (TRN) that are composed of recurrent networks, modeling cortical columns, connected with each others through a tree-shaped feed-forward backbone of connections, with sensory stimuli injected at the root of the tree. On these sensory architectures two types of short-term memory (STM) mechanisms can be implemented, STM via transient dynamics on the feed-forward tree, and STM via reverberating activity on the recurrent connectivity inside modules. We derive equations describing the dynamics of such networks, which allow us to thoroughly explore the space of possible architectures and quantify their memory performance. By varying the divergence ratio of the tree, we show that serial architectures, where sensory inputs are successively processed in different modules, are better suited to implement STM via transient dynamics, while parallel architectures, where sensory inputs are simultaneously processed by all modules, are better suited to implement STM via reverberating dynamics. |
| Databáze: | OpenAIRE |
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