How Synchronization Protects from Noise
The functional role of synchronization has attracted much interest and debate: in particular, synchronization may allow distant sites in the brain to communicate and cooperate with each other, and therefore may play a role in temporal binding, in attention or in sensory-motor integration mechanism...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Public Library of Science
2010
|
| Online Access: | http://hdl.handle.net/1721.1/54775 https://orcid.org/0000-0002-7161-7812 |
| _version_ | 1826204575506366464 |
|---|---|
| author | Pham, Quang-Cuong Tabareau, Nicolas Slotine, Jean-Jacques E. |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Pham, Quang-Cuong Tabareau, Nicolas Slotine, Jean-Jacques E. |
| author_sort | Pham, Quang-Cuong |
| collection | MIT |
| description | The functional role of synchronization has attracted much interest and debate: in particular, synchronization may allow
distant sites in the brain to communicate and cooperate with each other, and therefore may play a role in temporal binding,
in attention or in sensory-motor integration mechanisms. In this article, we study another role for synchronization: the socalled
‘‘collective enhancement of precision’’. We argue, in a full nonlinear dynamical context, that synchronization may help
protect interconnected neurons from the influence of random perturbations—intrinsic neuronal noise—which affect all
neurons in the nervous system. More precisely, our main contribution is a mathematical proof that, under specific,
quantified conditions, the impact of noise on individual interconnected systems and on their spatial mean can essentially be
cancelled through synchronization. This property then allows reliable computations to be carried out even in the presence
of significant noise (as experimentally found e.g., in retinal ganglion cells in primates). This in turn is key to obtaining
meaningful downstream signals, whether in terms of precisely-timed interaction (temporal coding), population coding, or
frequency coding. Similar concepts may be applicable to questions of noise and variability in systems biology. |
| first_indexed | 2024-09-23T12:57:38Z |
| format | Article |
| id | mit-1721.1/54775 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:57:38Z |
| publishDate | 2010 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/547752022-10-01T12:07:59Z How Synchronization Protects from Noise Pham, Quang-Cuong Tabareau, Nicolas Slotine, Jean-Jacques E. Massachusetts Institute of Technology. Department of Mechanical Engineering Massachusetts Institute of Technology. Nonlinear Systems Laboratory Slotine, Jean-Jacques E. Slotine, Jean-Jacques E. The functional role of synchronization has attracted much interest and debate: in particular, synchronization may allow distant sites in the brain to communicate and cooperate with each other, and therefore may play a role in temporal binding, in attention or in sensory-motor integration mechanisms. In this article, we study another role for synchronization: the socalled ‘‘collective enhancement of precision’’. We argue, in a full nonlinear dynamical context, that synchronization may help protect interconnected neurons from the influence of random perturbations—intrinsic neuronal noise—which affect all neurons in the nervous system. More precisely, our main contribution is a mathematical proof that, under specific, quantified conditions, the impact of noise on individual interconnected systems and on their spatial mean can essentially be cancelled through synchronization. This property then allows reliable computations to be carried out even in the presence of significant noise (as experimentally found e.g., in retinal ganglion cells in primates). This in turn is key to obtaining meaningful downstream signals, whether in terms of precisely-timed interaction (temporal coding), population coding, or frequency coding. Similar concepts may be applicable to questions of noise and variability in systems biology. European Community (contract number FP6-IST-027140) 2010-05-12T19:46:22Z 2010-05-12T19:46:22Z 2009-01 2008-06 Article http://purl.org/eprint/type/JournalArticle 1553-7358 1553-734X http://hdl.handle.net/1721.1/54775 Tabareau, Nicolas, Jean-Jacques Slotine, and Quang-Cuong Pham. “How Synchronization Protects from Noise.” PLoS Comput Biol 6.1 (2010): e1000637. © 2010 Tabareau et al. https://orcid.org/0000-0002-7161-7812 en_US http://dx.doi.org/10.1371/journal.pcbi.1000637 PLoS Computational Biology Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Public Library of Science PLoS |
| spellingShingle | Pham, Quang-Cuong Tabareau, Nicolas Slotine, Jean-Jacques E. How Synchronization Protects from Noise |
| title | How Synchronization Protects from Noise |
| title_full | How Synchronization Protects from Noise |
| title_fullStr | How Synchronization Protects from Noise |
| title_full_unstemmed | How Synchronization Protects from Noise |
| title_short | How Synchronization Protects from Noise |
| title_sort | how synchronization protects from noise |
| url | http://hdl.handle.net/1721.1/54775 https://orcid.org/0000-0002-7161-7812 |
| work_keys_str_mv | AT phamquangcuong howsynchronizationprotectsfromnoise AT tabareaunicolas howsynchronizationprotectsfromnoise AT slotinejeanjacquese howsynchronizationprotectsfromnoise |