Decomposing P300 to identify its genetic basis.
In this commentary, I explore reasons why it has been difficult to associate P300 amplitude with a gene or a single nucleotide polymorphism (SNP). I suggest we decompose P300 into the factors that contribute to it to get better traction on its genetic basis. Specifically, I note that we can improve the measurement of P300 to remove state-dependent contributions by including more than one measurement occasion; we can identify and extract the neural components contributing to P300 amplitude by estimating EEG power in specific bands of the P300; we can adjust P300 for single-trial variability; we can extract single-trial variability; and we can refine the tasks to isolate the separate psychological processes that P300 reflects. In the end, each of these factors that contribute to the conglomerate P300 may be a separate endophenotype mapping onto a separate SNP or gene.
San Francisco VA Medical Center, San Francisco, California, USA; Department of Psychiatry, University of California, San Francisco (UCSF), San Francisco, California, USA.
Judith M
JM
Ford
D001921:Brain / Q000502:physiology*; D004569:Electroencephalography; D058068:Endophenotypes; D018913:Event-Related Potentials, P300 / Q000235:genetics*; D006801:Humans
EEG; Genetic basis; P300 amplitude; SNPs