Do Cortical Neurons Process Luminance or Contrast to Encode Surface Properties?

1 Laboratory of Experimental Ophthalmology and NeuroImaging Centre, School of Behavioural and Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen 2 Department of Human Interfaces, Netherlands Organization for Applied Scientific Research-Human Factors, Soe...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of neurophysiology 2006-04, Vol.95 (4), p.2638-2649
Hauptverfasser: Vladusich, Tony, Lucassen, Marcel P, Cornelissen, Frans W
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:1 Laboratory of Experimental Ophthalmology and NeuroImaging Centre, School of Behavioural and Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen 2 Department of Human Interfaces, Netherlands Organization for Applied Scientific Research-Human Factors, Soesterberg, The Netherlands Submitted 27 September 2005; accepted in final form 25 December 2005 On the one hand, contrast signals provide information about surface properties, such as reflectance, and patchy illumination conditions, such as shadows. On the other hand, processing of luminance signals may provide information about global light levels, such as the difference between sunny and cloudy days. We devised models of contrast and luminance processing, using principles of logarithmic signal coding and half-wave rectification. We fit each model to individual response profiles obtained from 67 surface-responsive macaque V1 neurons in a center-surround paradigm similar to those used in human psychophysical studies. The most general forms of the luminance and contrast models explained, on average, 73 and 87% of the response variance over the sample population, respectively. We used a statistical technique, known as Akaike's information criterion, to quantify goodness of fit relative to number of model parameters, giving the relative probability of each model being correct. Luminance models, having fewer parameters than contrast models, performed substantially better in the vast majority of neurons, whereas contrast models performed similarly well in only a small minority of neurons. These results suggest that the processing of local and mean scene luminance predominates over contrast integration in surface-responsive neurons of the primary visual cortex. The sluggish dynamics of luminance-related cortical activity may provide a neural basis for the recent psychophysical demonstration that luminance information dominates brightness perception at low temporal frequencies. Address for reprint requests and other correspondence: T. Vladusich, Laboratory of Experimental Ophthalmology and NeuroImaging Centre, School of Behavioural and Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, PO Box 30.001, Groningen 9700 RB, The Netherlands (E-mail: t.vladusich{at}med.umcg.nl )
ISSN:0022-3077
1522-1598
DOI:10.1152/jn.01016.2005