Explaining attention-related changes in behavior and electroencephalography data through computational modeling.
作者信息
Ku Yixuan, van Schouwenburg Martine R
机构信息
Key Laboratory of Brain Functional Genomics, Ministry of Education, Shanghai Key Laboratory of Brain Functional Genomics, East China Normal University, Shanghai, China; and Departments of Neurology, Physiology and Psychiatry, University of California, San Francisco, California
Departments of Neurology, Physiology and Psychiatry, University of California, San Francisco, California.
出版信息
J Neurophysiol. 2015 Oct;114(4):2087-9. doi: 10.1152/jn.01026.2014. Epub 2015 Jan 14.
In a recent article, Itthipuripat and colleagues combined psychophysics, neurophysiology, and mathematical modeling to investigate the neural mechanism underlying behavioral benefits of spatial attention (Itthipuripat S, Ester EF, Deering S, Serences JT. J Neurosci 34: 13384-13398, 2014). They found that attention-related effects on behavior as well as neural signals could be better explained by a response gain model than by a noise reduction model or an efficient read-out model. In this Neuro Forum we discuss these results and raise several interesting questions and potential interpretations.
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