On the properties of input-to-output transformations in neuronal networks
Information processing in neuronal networks in certain important cases can be considered as maps of binary vectors, where ones (spikes) and zeros (no spikes) of input neurons are transformed into spikes and no spikes of output neurons. A simple but fundamental characteristic of such a map is how it...
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| Format: | Article |
| Language: | English |
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AIMS Press
2015-12-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2016009 |
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| author | Andrey Olypher Jean Vaillant |
| author_facet | Andrey Olypher Jean Vaillant |
| author_sort | Andrey Olypher |
| collection | DOAJ |
| description | Information processing in neuronal networks in certain important cases can be considered as maps of binary vectors, where ones (spikes) and zeros (no spikes) of input neurons are transformed into spikes and no spikes of output neurons. A simple but fundamental characteristic of such a map is how it transforms distances between input vectors into distances between output vectors. We advanced earlier known results by finding an exact solution to this problem for McCulloch-Pitts neurons. The obtained explicit formulas allow for detailed analysis of how the network connectivity and neuronal excitability affect the transformation of distances in neurons. As an application, we explored a simple model of information processing in the hippocampus, a brain area critically implicated in learning and memory. We found network connectivity and neuronal excitability parameter values that optimize discrimination between similar and distinct inputs. A decrease of neuronal excitability, which in biological neurons may be associated with decreased inhibition, impaired the optimality of discrimination. |
| format | Article |
| id | doaj-art-6eb6fe492a704767ae91843322b0973b |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2015-12-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-6eb6fe492a704767ae91843322b0973b2025-01-24T02:35:23ZengAIMS PressMathematical Biosciences and Engineering1551-00182015-12-0113357959610.3934/mbe.2016009On the properties of input-to-output transformations in neuronal networksAndrey Olypher0Jean Vaillant1School of Science and Technology, Georgia Gwinnett College, Lawrenceville, GA 30043Department of Mathematics and Informatics, Université des Antilles, Pointe-à-Pitre, GuadeloupeInformation processing in neuronal networks in certain important cases can be considered as maps of binary vectors, where ones (spikes) and zeros (no spikes) of input neurons are transformed into spikes and no spikes of output neurons. A simple but fundamental characteristic of such a map is how it transforms distances between input vectors into distances between output vectors. We advanced earlier known results by finding an exact solution to this problem for McCulloch-Pitts neurons. The obtained explicit formulas allow for detailed analysis of how the network connectivity and neuronal excitability affect the transformation of distances in neurons. As an application, we explored a simple model of information processing in the hippocampus, a brain area critically implicated in learning and memory. We found network connectivity and neuronal excitability parameter values that optimize discrimination between similar and distinct inputs. A decrease of neuronal excitability, which in biological neurons may be associated with decreased inhibition, impaired the optimality of discrimination.https://www.aimspress.com/article/doi/10.3934/mbe.2016009pattern discriminationmcculloch-pitts neurons.neuronal networksinformation processinghippocampus |
| spellingShingle | Andrey Olypher Jean Vaillant On the properties of input-to-output transformations in neuronal networks Mathematical Biosciences and Engineering pattern discrimination mcculloch-pitts neurons. neuronal networks information processing hippocampus |
| title | On the properties of input-to-output transformations in neuronal networks |
| title_full | On the properties of input-to-output transformations in neuronal networks |
| title_fullStr | On the properties of input-to-output transformations in neuronal networks |
| title_full_unstemmed | On the properties of input-to-output transformations in neuronal networks |
| title_short | On the properties of input-to-output transformations in neuronal networks |
| title_sort | on the properties of input to output transformations in neuronal networks |
| topic | pattern discrimination mcculloch-pitts neurons. neuronal networks information processing hippocampus |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2016009 |
| work_keys_str_mv | AT andreyolypher onthepropertiesofinputtooutputtransformationsinneuronalnetworks AT jeanvaillant onthepropertiesofinputtooutputtransformationsinneuronalnetworks |