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Information processing in the LGN: a comparison of neural codes and cell types
A. Pregowska, A. Casti, E. Kaplan, E. Wajnryb, J. Szczepanski,
Jazyk angličtina Země Německo
Typ dokumentu srovnávací studie, časopisecké články, Research Support, N.I.H., Extramural, práce podpořená grantem
Grantová podpora
P50 GM071558
NIGMS NIH HHS - United States
R01 EY016224
NEI NIH HHS - United States
K25 MH067225
NIMH NIH HHS - United States
R21 MH093868
NIMH NIH HHS - United States
NLK
ProQuest Central
od 1997-01-01 do Před 1 rokem
Medline Complete (EBSCOhost)
od 1996-08-01 do Před 1 rokem
Health & Medicine (ProQuest)
od 1997-01-01 do Před 1 rokem
- MeSH
- akční potenciály fyziologie MeSH
- duševní procesy fyziologie MeSH
- kočky MeSH
- metathalamus cytologie fyziologie MeSH
- neurony fyziologie MeSH
- světelná stimulace metody MeSH
- zrakové dráhy cytologie fyziologie MeSH
- zrakové korové centrum cytologie fyziologie MeSH
- zvířata MeSH
- Check Tag
- kočky MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- srovnávací studie MeSH
To understand how anatomy and physiology allow an organism to perform its function, it is important to know how information that is transmitted by spikes in the brain is received and encoded. A natural question is whether the spike rate alone encodes the information about a stimulus (rate code), or additional information is contained in the temporal pattern of the spikes (temporal code). Here we address this question using data from the cat Lateral Geniculate Nucleus (LGN), which is the visual portion of the thalamus, through which visual information from the retina is communicated to the visual cortex. We analyzed the responses of LGN neurons to spatially homogeneous spots of various sizes with temporally random luminance modulation. We compared the Firing Rate with the Shannon Information Transmission Rate , which quantifies the information contained in the temporal relationships between spikes. We found that the behavior of these two rates can differ quantitatively. This suggests that the energy used for spiking does not translate directly into the information to be transmitted. We also compared Firing Rates with Information Rates for X-ON and X-OFF cells. We found that, for X-ON cells the Firing Rate and Information Rate often behave in a completely different way, while for X-OFF cells these rates are much more highly correlated. Our results suggest that for X-ON cells a more efficient "temporal code" is employed, while for X-OFF cells a straightforward "rate code" is used, which is more reliable and is correlated with energy consumption.
Citace poskytuje Crossref.org
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- $a To understand how anatomy and physiology allow an organism to perform its function, it is important to know how information that is transmitted by spikes in the brain is received and encoded. A natural question is whether the spike rate alone encodes the information about a stimulus (rate code), or additional information is contained in the temporal pattern of the spikes (temporal code). Here we address this question using data from the cat Lateral Geniculate Nucleus (LGN), which is the visual portion of the thalamus, through which visual information from the retina is communicated to the visual cortex. We analyzed the responses of LGN neurons to spatially homogeneous spots of various sizes with temporally random luminance modulation. We compared the Firing Rate with the Shannon Information Transmission Rate , which quantifies the information contained in the temporal relationships between spikes. We found that the behavior of these two rates can differ quantitatively. This suggests that the energy used for spiking does not translate directly into the information to be transmitted. We also compared Firing Rates with Information Rates for X-ON and X-OFF cells. We found that, for X-ON cells the Firing Rate and Information Rate often behave in a completely different way, while for X-OFF cells these rates are much more highly correlated. Our results suggest that for X-ON cells a more efficient "temporal code" is employed, while for X-OFF cells a straightforward "rate code" is used, which is more reliable and is correlated with energy consumption.
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