Document Detail


Heterogeneous response dynamics in retinal ganglion cells: the interplay of predictive coding and adaptation.
MedLine Citation:
PMID:  20357061     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
To make efficient use of their limited signaling capacity, sensory systems often use predictive coding. Predictive coding works by exploiting the statistical regularities of the environment--specifically, by filtering the sensory input to remove its predictable elements, thus enabling the neural signal to focus on what cannot be guessed. To do this, the neural filters must remove the environmental correlations. If predictive coding is to work well in multiple environments, sensory systems must adapt their filtering properties to fit each environment's statistics. Using the visual system as a model, we determine whether this happens. We compare retinal ganglion cell dynamics in two very different environments: white noise and natural. Because natural environments have more power than that of white noise at low temporal frequencies, predictive coding is expected to produce a suppression of low frequencies and an enhancement of high frequencies, compared with the behavior in a white-noise environment. We find that this holds, but only in part. First, predictive coding behavior is not uniform: most on cells manifest it, whereas off cells, on average, do not. Overlaid on this nonuniformity between cell classes is further nonuniformity within both cell classes. These findings indicate that functional considerations beyond predictive coding play an important role in shaping the dynamics of sensory adaptation. Moreover, the differences in behavior between on and off cell classes add to the growing evidence that these classes are not merely homogeneous mirror images of each other and suggest that their roles in visual processing are more complex than expected from the classic view.
Authors:
Sheila Nirenberg; Illya Bomash; Jonathan W Pillow; Jonathan D Victor
Publication Detail:
Type:  In Vitro; Journal Article; Research Support, N.I.H., Extramural     Date:  2010-03-31
Journal Detail:
Title:  Journal of neurophysiology     Volume:  103     ISSN:  1522-1598     ISO Abbreviation:  J. Neurophysiol.     Publication Date:  2010 Jun 
Date Detail:
Created Date:  2010-06-10     Completed Date:  2010-09-09     Revised Date:  2011-07-28    
Medline Journal Info:
Nlm Unique ID:  0375404     Medline TA:  J Neurophysiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  3184-94     Citation Subset:  IM    
Affiliation:
Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA.
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MeSH Terms
Descriptor/Qualifier:
Animals
Data Interpretation, Statistical
Fourier Analysis
Mice
Models, Neurological*
Nonlinear Dynamics*
Predictive Value of Tests
Principal Component Analysis
Retina / cytology*
Retinal Ganglion Cells / physiology*
Grant Support
ID/Acronym/Agency:
EY-12978/EY/NEI NIH HHS; EY-7977/EY/NEI NIH HHS; EY-9314/EY/NEI NIH HHS
Comments/Corrections

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