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Articles, Behavioral/Systems/Cognitive

Gambling Severity Predicts Midbrain Response to Near-Miss Outcomes

Henry W. Chase and Luke Clark
Journal of Neuroscience 5 May 2010, 30 (18) 6180-6187; DOI: https://doi.org/10.1523/JNEUROSCI.5758-09.2010
Henry W. Chase
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Luke Clark
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    Figure 1.

    Task design. The slot machine task presents two reels, with the six identical play icons displayed on each reel, and a horizontal payline across the center of the screen. On trials with a white screen background (as displayed), the volunteer selected one icon on the left reel, using two buttons to scroll through the icons, and one button to select. On trials with a black screen background, the computer selected the play icon. Following icon selection, the right hand reel spun for a variable duration (2.8–6 s), and decelerated to a standstill. During outcome (4 s), if the right reel stopped on the selected icon (i.e., matching icons were aligned in the payline), the subject was awarded £0.50 (approximately $0.80); all other outcomes won nothing. Following the outcome phase, there was an intertrial interval of variable duration (2–7 s). On intermittent (1/3) trials, two ratings were acquired using an on-screen visual analog scale: following selection, subjects were asked “How do you rate your chances of winning?,” and following outcome, subjects were asked “How much do you want to continue to play the game?”

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    Figure 2.

    A, Win-related activation (win > nonwin outcomes) in the regular gamblers, using an ROI mask of win activity from an independent sample (Clark et al., 2009). Activity is displayed at p < 0.001 uncorrected, k = 10, to illustrate the anatomical extent of the activations and several responses falling just below the FWE threshold. B, Figure showing near-miss-related activation (near-miss events > full-miss events, within the ROI mask) across all participants, displayed at p < 0.001 uncorrected, k = 10. Activations are displayed on the ch2bet template, using MRIcron software (http://www.sph.sc.edu/comd/rorden/mricron/).

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    Figure 3.

    A, Effect of gambling severity (South Oaks Gambling Screen; SOGS) on near-miss-related activation, within the ROI mask (displayed at p < 0.001 uncorrected, k = 10). B, Extracted signal for the near-miss minus full-miss contrast in the midbrain, plotted against SOGS score. Midbrain signal was extracted from an independent region defined by the win minus nonwin contrast (contrast 1; peak voxel: x= −8, y= −20, z= −14). C, Extracted signal for the win minus nonwin contrast, plotted against SOGS score, for the same midbrain ROI as above.

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    Figure 4.

    A, The association between gambling severity (SOGS score) and near-miss-related activation (near miss minus full miss) in the midbrain (z = −18 and z = −12), using a smaller (4 mm) smoothing kernel. Activity thresholded at p < 0.005 uncorrected for display purposes, with the clusters significant at the p < 0.001 threshold encircled in blue (x, y, z = −8, −18, −18 and 12, −16, −12). B, Between-groups comparison of the regular gamblers (n = 20) against 14 healthy volunteers with minimal gambling involvement (SOGS 0–2) from our previous experiment (Clark et al., 2009), illustrating reduced activity to monetary wins in the regular gamblers in the striatum and medial prefrontal cortex (p < 0.001 uncorrected, k = 10).

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The Journal of Neuroscience: 30 (18)
Journal of Neuroscience
Vol. 30, Issue 18
5 May 2010
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Gambling Severity Predicts Midbrain Response to Near-Miss Outcomes
Henry W. Chase, Luke Clark
Journal of Neuroscience 5 May 2010, 30 (18) 6180-6187; DOI: 10.1523/JNEUROSCI.5758-09.2010

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Gambling Severity Predicts Midbrain Response to Near-Miss Outcomes
Henry W. Chase, Luke Clark
Journal of Neuroscience 5 May 2010, 30 (18) 6180-6187; DOI: 10.1523/JNEUROSCI.5758-09.2010
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