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Modeling task-specific manifestations of serotonin in basal ganglia using risk-based decision making

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(A) The reward punishment sensitivity for simulated (Sims) PD (α = 0.1) and controls (α = 0.3) to explain the experiment (Expt) [3], (B) Analysis of the effect of 5HT (α) on PD patients' sensitivity profile in comparison to that of controls.
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Figure 1: (A) The reward punishment sensitivity for simulated (Sims) PD (α = 0.1) and controls (α = 0.3) to explain the experiment (Expt) [3], (B) Analysis of the effect of 5HT (α) on PD patients' sensitivity profile in comparison to that of controls.

Mentions: Existing abstract models of serotonin (5HT) in basal ganglia (BG) suffer from their inability to account for the diverse functions of 5HT including punishment prediction and behavioural inhibition, time scale of reward-punishment prediction, and risk sensitivity [1]. We here propose an abstract model of risk based decision making in BG wherein dopamine (DA-denoted by δ) controls the reward prediction error and serotonin (5HT- denoted by α) affects the risk prediction error [1]. This model effectively reconciles not only the diverse functions of 5HT but also predicts that BG computes utility rather than value, a feature that differentiates from several value-based actor-critic models of BG. Here, value is an expectation of the discounted future rewards, risk is the reward variance, and utility is a weighted summation of the value and risk function with 5HT controlling the weightage or contribution of risk component to utility function. Such a result explains that the primary function of 5HT is to account for the risk computation in decision making—a function that links 5HT to the multiple roles explained above [1]. Just as value has been thought to be computed in the striatum, we propose that utility is also computed in the striatum; and the BG dynamics for utility (instead of value) maximization is described by the Go/Explore/NoGo model of Magdoom et al. (2011)[2]. The proposed abstract model is applied here to a clinical study on the effect of DA agonist medication on reward-punishment sensitivity in Parkinson’s disease (PD) patients (recently / ON, and never / OFF medicated) compared to healthy controls [3]. This experiment demonstrates an increased reward sensitivity in PD-ON, and increased punishment sensitivity in PD-OFF conditions—a trend that is captured by the proposed model of 5HT-DA in BG (Fig. 1A). PD OFF condition is simulated by clamping δ; while PD-ON condition simulation is by multiplying δ with a positive factor (>1).


Modeling task-specific manifestations of serotonin in basal ganglia using risk-based decision making
(A) The reward punishment sensitivity for simulated (Sims) PD (α = 0.1) and controls (α = 0.3) to explain the experiment (Expt) [3], (B) Analysis of the effect of 5HT (α) on PD patients' sensitivity profile in comparison to that of controls.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4126569&req=5

Figure 1: (A) The reward punishment sensitivity for simulated (Sims) PD (α = 0.1) and controls (α = 0.3) to explain the experiment (Expt) [3], (B) Analysis of the effect of 5HT (α) on PD patients' sensitivity profile in comparison to that of controls.
Mentions: Existing abstract models of serotonin (5HT) in basal ganglia (BG) suffer from their inability to account for the diverse functions of 5HT including punishment prediction and behavioural inhibition, time scale of reward-punishment prediction, and risk sensitivity [1]. We here propose an abstract model of risk based decision making in BG wherein dopamine (DA-denoted by δ) controls the reward prediction error and serotonin (5HT- denoted by α) affects the risk prediction error [1]. This model effectively reconciles not only the diverse functions of 5HT but also predicts that BG computes utility rather than value, a feature that differentiates from several value-based actor-critic models of BG. Here, value is an expectation of the discounted future rewards, risk is the reward variance, and utility is a weighted summation of the value and risk function with 5HT controlling the weightage or contribution of risk component to utility function. Such a result explains that the primary function of 5HT is to account for the risk computation in decision making—a function that links 5HT to the multiple roles explained above [1]. Just as value has been thought to be computed in the striatum, we propose that utility is also computed in the striatum; and the BG dynamics for utility (instead of value) maximization is described by the Go/Explore/NoGo model of Magdoom et al. (2011)[2]. The proposed abstract model is applied here to a clinical study on the effect of DA agonist medication on reward-punishment sensitivity in Parkinson’s disease (PD) patients (recently / ON, and never / OFF medicated) compared to healthy controls [3]. This experiment demonstrates an increased reward sensitivity in PD-ON, and increased punishment sensitivity in PD-OFF conditions—a trend that is captured by the proposed model of 5HT-DA in BG (Fig. 1A). PD OFF condition is simulated by clamping δ; while PD-ON condition simulation is by multiplying δ with a positive factor (>1).

View Article: PubMed Central - HTML

No MeSH data available.