|
|
||||||||
1 Catholic University, Washington, DC, 2 Cornell University, New York, NY
Reprint requests should be sent to P. M. Greenwood, Department of Psychology, MSN 3F5, George Mason University, Fairfax, VA 22030-4444, or via e-mail: pgreenw1{at}gmu.edu.
Cortical neurotransmitter availability is known to exert domain-specific effects on cognitive performance. Hence, normal variation in genes with a role in neurotransmission may also have specific effects on cognition. We tested this hypothesis by examining associations between polymorphisms in genes affecting cholinergic and noradrenergic neurotransmission and individual differences in visuospatial attention. Healthy individuals were administered a cued visual search task which varied the size of precues to the location of a target letter embedded in a 15-letter array. Cues encompassed 1, 3, 9, or 15 letters. Search speed increased linearly with precue size, indicative of a spatial attentional scaling mechanism. The strength of attentional scaling increased progressively with the number of C alleles (0, 1, or 2) of the alpha-4 nicotinic receptor gene C1545T polymorphism (n = 104). No association was found for the dopamine beta hydroxylase gene G444A polymorphism (n = 135). These findings point to the specificity of genetic neuromodulation. Whereas variation in a gene linked to cholinergic transmission systematically modulated the ability to scale the focus of visuospatial attention, variation in a gene governing dopamine availability did not. The results show that normal variation in a gene controlling a nicotinic receptor makes a selective contribution to individual differences in visuospatial attention.
This article has been cited by other articles:
![]() |
M. A. BELLGROVE and J. B. MATTINGLEY Molecular Genetics of Attention Ann. N.Y. Acad. Sci., May 1, 2008; 1129(1): 200 - 212. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. Giessing, G. R. Fink, F. Rosler, and C. M. Thiel FMRI data predict individual differences of behavioral effects of nicotine: a partial least square analysis. J. Cogn. Neurosci., April 1, 2007; 19(4): 658 - 670. [Abstract] [Full Text] [PDF] |
||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| NEURAL COMPUTATION | J COGNITIVE NEUROSCIENCE | MIT PRESS JOURNALS |