The effects of first-dose methylphenidate on the neural signatures of visual selective attention in children with attention-deficit/hyperactivity disorder

Guo, Jialiang; Luo, Xuyi; Kong, Yuanjun; Li, Bingkun; Si, Bailu; Jensen, Ole; Sun, Li; Song, Yan

doi:10.1016/j.biopsycho.2022.108481

Cited by 5 publications

(2 citation statements)

References 67 publications

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“…Still, low-dose METH has many other psychological and behavioral effects, including performance improvements in reversal learning ( Kulig and Calhoun, 1972 ; Calhoun and Jones, 1974 ) and induction of behavioral activation ( Hall et al, 2008 ; Miller et al, 2013 ) (but see Asami and Kuribara, 1989 ; Jing et al, 2014 ). Clinical application of low-concentration dopaminergic drugs for severe post-traumatic stress disorder (PTSD) ( Mithoefer et al, 2019 ) and attention deficit hyperactivity disorder (ADHD) ( Guo et al, 2023 ) further underlines the necessity of developing a quantitative method to enable analysis of behavioral effects by low-dose METH.…”

Section: Introductionmentioning

confidence: 99%

A reinforcement learning model with choice traces for a progressive ratio schedule

Ihara,

Shikano,

Kato

et al. 2024

Front. Behav. Neurosci.

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The progressive ratio (PR) lever-press task serves as a benchmark for assessing goal-oriented motivation. However, a well-recognized limitation of the PR task is that only a single data point, known as the breakpoint, is obtained from an entire session as a barometer of motivation. Because the breakpoint is defined as the final ratio of responses achieved in a PR session, variations in choice behavior during the PR task cannot be captured. We addressed this limitation by constructing four reinforcement learning models: a simple Q-learning model, an asymmetric model with two learning rates, a perseverance model with choice traces, and a perseverance model without learning. These models incorporated three behavioral choices: reinforced and non-reinforced lever presses and void magazine nosepokes, because we noticed that male mice performed frequent magazine nosepokes during PR tasks. The best model was the perseverance model, which predicted a gradual reduction in amplitudes of reward prediction errors (RPEs) upon void magazine nosepokes. We confirmed the prediction experimentally with fiber photometry of extracellular dopamine (DA) dynamics in the ventral striatum of male mice using a fluorescent protein (genetically encoded GPCR activation-based DA sensor: GRABDA2m). We verified application of the model by acute intraperitoneal injection of low-dose methamphetamine (METH) before a PR task, which increased the frequency of magazine nosepokes during the PR session without changing the breakpoint. The perseverance model captured behavioral modulation as a result of increased initial action values, which are customarily set to zero and disregarded in reinforcement learning analysis. Our findings suggest that the perseverance model reveals the effects of psychoactive drugs on choice behaviors during PR tasks.

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Section: Introductionmentioning

confidence: 99%

A reinforcement learning model with choice traces for a progressive ratio schedule

Ihara,

Shikano,

Kato

et al. 2024

Front. Behav. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Still, low- dose METH has many other psychological and behavioral effects, including enhancing discrimination of reversal learning (Calhoun and Jones, 1974; Kulig and Calhoun, 1972) and induction of behavioral activation (Hall et al, 2008; Miller et al, 2013) (but see Asami and Kuribara, 1989; Jing et al, 2014). Clinical application of low- concentration dopaminergic drugs for severe post- traumatic stress disorder (PTSD) (Mithoefer et al, 2019), and attention deficit hyperactivity disorder (ADHD) (Guo et al, 2023) further underlines the necessity of developing a quantitative method to enable analysis of behavioral effects by low-dose METH.…”

Section: Introductionmentioning

confidence: 99%

A Reinforcement Learning Model with Choice Traces for a Progressive Ratio Schedule

Ihara,

Shikano,

Kato

et al. 2023

Preprint

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The progressive ratio (PR) lever-press task serves as a benchmark for assessing goal-oriented motivation. However, a well-recognized limitation of the PR task is that only a single data point, known as the breakpoint, is obtained from an entire session as a barometer of motivation. Because the breakpoint is defined as the final ratio of responses achieved in a PR session, variations in choice behavior during the PR task cannot be captured. We addressed this limitation by constructing four reinforcement learning models: a Simple Q- learning model, an Asymmetric model with two learning rates, a Perseverance model with choice traces, and a Perseverance model without learning. These models incorporated three behavioral choices: reinforced and non-reinforced lever presses and void magazine nosepokes (MNPs), because we noticed that mice performed frequent MNPs during PR tasks. The best model was the Perseverance model, which predicted a gradual reduction in amplitudes of reward prediction errors (RPEs) upon void MNPs. We confirmed the prediction experimentally with fiber photometry of extracellular dopamine (DA) dynamics in the ventral striatum of mice using a fluorescent protein (genetically encoded GPCR activation-based DA sensor: GRABDA2m). We verified application of the model by acute intraperitoneal injection of low-dose methamphetamine (METH) before a PR task, which increased the frequency of MNPs during the PR session without changing the breakpoint. The Perseverance model captured behavioral modulation as a result of increased initial action values, which are customarily set to zero and disregarded in reinforcement learning analysis. Our findings suggest that the Perseverance model reveals effects of psychoactive drugs on choice behaviors during PR tasks.

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Temporal dynamics of spatial attentional biases toward weight-related words among females with weight dissatisfaction

Leng,

Yu,

Chen

et al. 2024

Biological Psychology

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The effects of first-dose methylphenidate on the neural signatures of visual selective attention in children with attention-deficit/hyperactivity disorder

Cited by 5 publications

References 67 publications

A reinforcement learning model with choice traces for a progressive ratio schedule

A reinforcement learning model with choice traces for a progressive ratio schedule

A Reinforcement Learning Model with Choice Traces for a Progressive Ratio Schedule

Temporal dynamics of spatial attentional biases toward weight-related words among females with weight dissatisfaction

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