2004
DOI: 10.1038/nature02966
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A general mechanism for perceptual decision-making in the human brain

Abstract: Findings from single-cell recording studies suggest that a comparison of the outputs of different pools of selectively tuned lower-level sensory neurons may be a general mechanism by which higher-level brain regions compute perceptual decisions. For example, when monkeys must decide whether a noisy field of dots is moving upward or downward, a decision can be formed by computing the difference in responses between lower-level neurons sensitive to upward motion and those sensitive to downward motion. Here we us… Show more

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Cited by 676 publications
(707 citation statements)
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“…Response times were also slower for the identity task (0.81 T 0.13 s vs. 0.66 T 0.13 ms., P < 10 À5 , paired t test). A previous study, however, has shown that increased difficulty alone does not increase DLPFC activity (Barch et al, 1997;Heekeren et al, 2004). The increased activity may instead be due to additional working memory load or recruitment of neurons specialized for object working memory.…”
Section: Resultsmentioning
confidence: 75%
“…Response times were also slower for the identity task (0.81 T 0.13 s vs. 0.66 T 0.13 ms., P < 10 À5 , paired t test). A previous study, however, has shown that increased difficulty alone does not increase DLPFC activity (Barch et al, 1997;Heekeren et al, 2004). The increased activity may instead be due to additional working memory load or recruitment of neurons specialized for object working memory.…”
Section: Resultsmentioning
confidence: 75%
“…We also assessed the effect of difficulty using the Temporal and Spatial tasks in Exp 2. The contrast “hard > easy” Temporal trials revealed one single activation cluster in the supplementary frontal eye field, which has been associated with difficult decision making [Heekeren et al, 2004]. None of the critical task‐specific regions (Figs 2, 3, 4) was activated by this “hard > easy” comparison.…”
Section: Discussionmentioning
confidence: 99%
“…18 A total of 50 images (25 cats, 25 dogs) from an open online database (http://www.kaggle.com) were converted to grayscale and Fourier transformed. The phase matrix of each image was combined with white noise and the average magnitude matrix of the whole stimulus set using an inverse Fourier transform 19. The resulting image was sheared using an affine matrix transformation (3 levels of skew: 0, 1.4, and 2.3 arbitrary units, order pseudorandomized).…”
Section: Methodsmentioning
confidence: 99%