Neuromodulation influences synchronization and intrinsic read-out [version 2; referees: 2 approved, 1 approved with reservations, 1 not approved]
Background: The roles of neuromodulation in a neural network, such as in a cortical microcolumn, are still incompletely understood. Neuromodulation influences neural processing by presynaptic and postsynaptic regulation of synaptic efficacy. Neuromodulation also affects ion channels and intrinsic ex...
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2018-12-01
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| Series: | F1000Research |
| Online Access: | https://f1000research.com/articles/7-1277/v2 |
| _version_ | 1829461644547194880 |
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| author | Gabriele Scheler |
| author_facet | Gabriele Scheler |
| author_sort | Gabriele Scheler |
| collection | DOAJ |
| description | Background: The roles of neuromodulation in a neural network, such as in a cortical microcolumn, are still incompletely understood. Neuromodulation influences neural processing by presynaptic and postsynaptic regulation of synaptic efficacy. Neuromodulation also affects ion channels and intrinsic excitability. Methods: Synaptic efficacy modulation is an effective way to rapidly alter network density and topology. We alter network topology and density to measure the effect on spike synchronization. We also operate with differently parameterized neuron models which alter the neuron's intrinsic excitability, i.e., activation function. Results: We find that (a) fast synaptic efficacy modulation influences the amount of correlated spiking in a network. Also, (b) synchronization in a network influences the read-out of intrinsic properties. Highly synchronous input drives neurons, such that differences in intrinsic properties disappear, while asynchronous input lets intrinsic properties determine output behavior. Thus, altering network topology can alter the balance between intrinsically vs. synaptically driven network activity. Conclusion: We conclude that neuromodulation may allow a network to shift between a more synchronized transmission mode and a more asynchronous intrinsic read-out mode. This has significant implications for our understanding of the flexibility of cortical computations. |
| first_indexed | 2024-12-12T11:54:36Z |
| format | Article |
| id | doaj.art-7fd5ced8e7e349f8912dbb00b2b8d677 |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-12-12T11:54:36Z |
| publishDate | 2018-12-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-7fd5ced8e7e349f8912dbb00b2b8d6772022-12-22T00:25:14ZengF1000 Research LtdF1000Research2046-14022018-12-01710.12688/f1000research.15804.218791Neuromodulation influences synchronization and intrinsic read-out [version 2; referees: 2 approved, 1 approved with reservations, 1 not approved]Gabriele Scheler0Carl Correns Foundation for Mathematical Biology, Mountain View, CA, 94040, USABackground: The roles of neuromodulation in a neural network, such as in a cortical microcolumn, are still incompletely understood. Neuromodulation influences neural processing by presynaptic and postsynaptic regulation of synaptic efficacy. Neuromodulation also affects ion channels and intrinsic excitability. Methods: Synaptic efficacy modulation is an effective way to rapidly alter network density and topology. We alter network topology and density to measure the effect on spike synchronization. We also operate with differently parameterized neuron models which alter the neuron's intrinsic excitability, i.e., activation function. Results: We find that (a) fast synaptic efficacy modulation influences the amount of correlated spiking in a network. Also, (b) synchronization in a network influences the read-out of intrinsic properties. Highly synchronous input drives neurons, such that differences in intrinsic properties disappear, while asynchronous input lets intrinsic properties determine output behavior. Thus, altering network topology can alter the balance between intrinsically vs. synaptically driven network activity. Conclusion: We conclude that neuromodulation may allow a network to shift between a more synchronized transmission mode and a more asynchronous intrinsic read-out mode. This has significant implications for our understanding of the flexibility of cortical computations.https://f1000research.com/articles/7-1277/v2 |
| spellingShingle | Gabriele Scheler Neuromodulation influences synchronization and intrinsic read-out [version 2; referees: 2 approved, 1 approved with reservations, 1 not approved] F1000Research |
| title | Neuromodulation influences synchronization and intrinsic read-out [version 2; referees: 2 approved, 1 approved with reservations, 1 not approved] |
| title_full | Neuromodulation influences synchronization and intrinsic read-out [version 2; referees: 2 approved, 1 approved with reservations, 1 not approved] |
| title_fullStr | Neuromodulation influences synchronization and intrinsic read-out [version 2; referees: 2 approved, 1 approved with reservations, 1 not approved] |
| title_full_unstemmed | Neuromodulation influences synchronization and intrinsic read-out [version 2; referees: 2 approved, 1 approved with reservations, 1 not approved] |
| title_short | Neuromodulation influences synchronization and intrinsic read-out [version 2; referees: 2 approved, 1 approved with reservations, 1 not approved] |
| title_sort | neuromodulation influences synchronization and intrinsic read out version 2 referees 2 approved 1 approved with reservations 1 not approved |
| url | https://f1000research.com/articles/7-1277/v2 |
| work_keys_str_mv | AT gabrielescheler neuromodulationinfluencessynchronizationandintrinsicreadoutversion2referees2approved1approvedwithreservations1notapproved |