Dissociable Effects of Dopamine and Serotonin on Reversal Learning

denOuden, Hanneke E.M.; Daw, Nathaniel D.; Fernández, Guillén; Elshout, Joris A.; Rijpkema, Mark; Hoogman, Martine; Franke, Barbara; Cools, Roshan

doi:10.1016/j.neuron.2013.12.008

Cited by 12 publications

(20 citation statements)

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“…In contrast, reality source monitoring revealed both the frontal old/new effect and the late posterior negativity (Leynes and Kakadia, 2013). These results mirror our results in s-carriers and l/l homozygotes where s-carriers, who have been shown to have difficulty with cognitive control (Roiser et al 2009; den Ouden et al, 2013), show the same pattern as the difficult internal source monitoring judgment and l/l homozygotes mirroring the easier reality monitoring results. Leynes and Kakadia (2013) interpret their results by suggesting that the reality monitoring condition only required a more general monitoring process due to the relative ease of the source judgment while the more difficult internal source judgment needed more extensive and specific monitoring.…”

Section: Discussionsupporting

confidence: 88%

“…In the probabilistic reversal-learning paradigm, participants must flexibly change their response after reward contingencies are switched. S-carriers are less likely to switch their response after receiving negative feedback, suggesting that s-carriers have decreased cognitive flexibility (den Ouden et al, 2013). Additionally, in a decision making task where prefrontal cortical control is needed to overcome choice bias, s-carriers are more susceptible to bias and show decreased prefrontal cortical function measured with fMRI (Roiser et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

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Genetic variation in the serotonin transporter gene influences ERP old/new effects during recognition memory

et al. 2015

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Recognition memory is defined as the ability to recognize a previously encountered stimulus and has been associated with spatially and temporally distinct event related potentials (ERPs). Allelic variations of the serotonin transporter gene (SLC6A4) have recently been shown to impact memory performance. Common variants of the serotonin transporter-linked polymorphic region (5HTTLPR) of the SLC6A4 gene result in long (l) and short (s) allelic variants with carriers of the s allele having lowered transcriptional efficiency. Thus, the current study examines the effects polymorphisms of the SLC6A4 gene have on performance and ERP amplitudes commonly associated with recognition memory. Electroencephalogram (EEG), genetic, and behavioral data were collected from sixty participants as they performed an item and source memory recognition task. In both tasks, participants studied and encoded 200 words, which were then mixed with 200 new words during retrieval. Participants were monitored with EEG during the retrieval portion of each memory task. EEG electrodes were grouped into four ROIs, left anterior superior, right anterior superior, left posterior superior, and right posterior superior. ERP mean amplitudes during hits in the item and source memory task were compared to correctly recognizing new items (correct rejections). Results show that s-carriers have decreased mean hit amplitudes in both the right anterior superior ROI 1000–1500 ms post stimulus during the source memory task and the left anterior superior ROI 300–500 ms post stimulus during the item memory task. These results suggest that individual differences due to genetic variation of the serotonin transporter gene influences recognition memory.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 99%

Genetic variation in the serotonin transporter gene influences ERP old/new effects during recognition memory

et al. 2015

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“…The quantity δ is the prediction error – the discrepancy between received and estimated reward. Note that equation 3 rescales the reward and next-state Q-value by the subject’s learning rate, α sub (Camerer and Ho, 1998; Den Ouden et al, In Press). This does not change the data likelihood, but has the effect of rescaling the inverse temperature parameters β sub in the choice rule, equation 6 below.…”

Section: Methodsmentioning

confidence: 99%

Multiple memory systems as substrates for multiple decision systems

Doll

Shohamy

Daw

2015

Neurobiology of Learning and Memory

101

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It has recently become widely appreciated that value-based decision making is supported by multiple computational strategies. In particular, animal and human behavior in learning tasks appears to include habitual responses described by prominent model-free reinforcement learning (RL) theories, but also more deliberative or goal-directed actions that can be characterized by a different class of theories, model-based RL. The latter theories evaluate actions by using a representation of the contingencies of the task (as with a learned map of a spatial maze), called an “internal model.” Given the evidence of behavioral and neural dissociations between these approaches, they are often characterized as dissociable learning systems, though they likely interact and share common mechanisms. In many respects, this division parallels a longstanding dissociation in cognitive neuroscience between multiple memory systems, describing, at the broadest level, separate systems for declarative and procedural learning. Procedural learning has notable parallels with model-free RL: both involve learning of habits and both are known to depend on parts of the striatum. Declarative memory, by contrast, supports memory for single events or episodes and depends on the hippocampus. The hippocampus is thought to support declarative memory by encoding temporal and spatial relations among stimuli and thus is often referred to as a relational memory system. Such relational encoding is likely to play an important role in learning an internal model, the representation that is central to model-based RL. Thus, insofar as the memory systems represent more general-purpose cognitive mechanisms that might subserve performance on many sorts of tasks including decision making, these parallels raise the question whether the multiple decision systems are served by multiple memory systems, such that one dissociation is grounded in the other. Here we investigated the relationship between model-based RL and relational memory by comparing individual differences across behavioral tasks designed to measure either capacity. Human subjects performed two tasks, a learning and generalization task (acquired equivalence) which involves relational encoding and depends on the hippocampus; and a sequential RL task that could be solved by either a model-based or model-free strategy. We assessed the correlation between subjects’ use of flexible, relational memory, as measured by generalization in the acquired equivalence task, and their differential reliance on either RL strategy in the decision task. We observed a significant positive relationship between generalization and model-based, but not model-free, choice strategies. These results are consistent with the hypothesis that model-based RL, like acquired equivalence, relies on a more general-purpose relational memory system.

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“…Taken together, there appears to be a link between ADHD and problem gambling via common susceptibility to dysregulated dopaminergic signaling. It is important to note that other neuromodulators, particularly 5-hydroxytryptamine, are also important for mediating choice avoidance after losses [49] and are impaired in ADHD [50].…”

Section: Discussionmentioning

confidence: 99%