Study unravels mechanisms of psychostimulants on attention and learning

Study unravels mechanisms of psychostimulants on attention and learning
Task and main effects. a Reversal-learning paradigm. Two stimuli, a face and a scene, were presented simultaneously. One was associated with a reward outcome, the other with a punishment outcome, with 100% deterministic contingencies. On each trial the computer selected one image, and the participant’s task was to predict whether the highlighted stimulus would be followed by a reward or punishment outcome. Then the actual outcome was presented. The stimulus-outcome associations reversed regularly, which was signaled by either an unexpected reward or unexpected punishment outcome. Accuracy on trials immediately after an unexpected outcome (reversal trials) was the performance measure of interest. Task images were obtained with permission from ref. 48. b fMRI BOLD signal to unexpected versus expected outcomes collapsed across all three sessions (N = 94 participants). In these dual-coded images, color indicates the size of the contrast estimate and opacity codes the height of the t values (plotting procedure: refs. 113, 114). Voxels with t values above the threshold of P < 0.001, uncorrected, are fully opaque. Significant clusters (here, P < 0.05 after whole-brain cluster-level family-wise error correction) are encircled in black for red blobs or in white for blue blobs. The results are overlaid on the group-average T1-weighted anatomical scan in MNI152 coordinate space. c Across all three sessions, unexpected outcomes increased face/scene stimulus-specific BOLD signal in visual association cortex (N = 94 participants; main effect of expectancy in ANOVA: F(1,93) = 182.97, P = 2.2e-16). The stimulus-specificity index represents the outcome-related BOLD signal in the contrast (FFA: faces – scenes) – (PPA: faces – scenes). Boxplots show the median and 25th and 75th percentiles, with the whiskers extending max. 1.5 * interquartile range. Round dots next to the data density kernel represent the mean value. d, e Bayesian mixed-effects model coefficients for the main effects of methylphenidate and sulpiride (relative to placebo) on accuracy and response times (N = 88 participants). Boxplots defined as in panel c. Source data are provided with this paper. MPH methylphenidate, SUL sulpiride, arb units arbitrary units. Credit: Nature Communications (2022). DOI: 10.1038/s41467-022-32679-1

Psychostimulants are commonly used as treatments of psychiatric disorders or to improve cognition, but the benefits of these drugs are not the same for everyone, as their effects vary greatly both across individuals and within the same patient. This large variability poses a major problem for treatment strategies in psychiatry, and the reasons behind it are still not clear. Now, scientists of the Human Brain Project (HBP) have moved closer to understanding them.

One of these medications is , the active ingredient of the drugs Ritalin and Concerta that are used to treat (ADHD), but are also widely used by healthy people for its cognition-improving effects. Methylphenidate acts in part by increasing levels of dopamine, a neurotransmitter involved in the 's reward system. A new study by a team of researchers from Radboud University Medical Center (Netherlands) and Donders Institute for Brain, Cognition and Behavior (Netherlands) unravels the mechanisms by which methylphenidate gates both attention and reward learning.

The researchers tested the hypothesis that the effects of methylphenidate on learning based on reward or punishment depend on the baseline levels of dopamine in a person's brain. To test this, one hundred young healthy adults received (in different sessions) methylphenidate, sulpiride (a medication used to treat symptoms of schizophrenia that acts more selectively on ), or a placebo, and were later scanned with imaging (fMRI) during a reward/punishment reversal learning task.

In this task, participants learned to predict whether a picture (of a face or a landscape) that is selected by the computer is followed by reward or punishment. A reward outcome consisted of a green smiley and a + €100 sign. A punishment consisted of a red sad smiley and a -€100 sign. Whether the face or the landscape was associated with reward or punishment changed frequently in the task, so to perform well people had to continue to pay attention and flexibly update their behavior based on prediction errors.

The researchers observed that the degree to which both methylphenidate and sulpiride improved reward compared with learning depends on baseline dopamine synthesis capacity. Moreover, these effects on learning were accompanied by increased activity in the striatum, a dopamine-rich region deep inside the brain, and also by increased specificity of the activity in regions of the cortex near the back of the brain that are specialized for processing faces and landscapes.

Their findings provide strong support for two hypotheses related to methylphenidate: First, that dopamine enhances task-relevant cortical signals by acting on the striatum. Second, that differences between individuals in synthesis capacity in the striatum explain the variability in the drug's cognitive effects.

The research was published in Nature Communications.

More information: Ruben van den Bosch et al, Striatal dopamine dissociates methylphenidate effects on value-based versus surprise-based reversal learning, Nature Communications (2022). DOI: 10.1038/s41467-022-32679-1
Journal information: Nature Communications

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