Regional specificity in dopamine signaling during reward‐related learning (Commentary on Aragona <i>et al.</i>)
Bibliographic record
Abstract
Dopamine transmission is known to play a critical role in associative learning about environmental stimuli linked to natural or drug rewards. Much of our understanding of how the dopamine system contributes to learning comes from studies analyzing changes in midbrain dopamine neuron activity occurring while animals learn to associate predictive cues with food rewards. Dopamine neurons initially respond with brief phasic bursts of activity in response to primary rewards, but over training, control of this phasic activity transfers to conditioned stimuli that are predictive of these rewards (Schultz, 1998, 2007). These bursts of activity in dopamine neurons are thought to represent a fundamental form of communication in this system (Floresco, 2007; Grace et al., 2007). Despite these findings, it remains as of yet unclear how these patterns of midbrain dopamine neural activity translate into transmitter release in forebrain terminal regions. Do phasic dopamine bursts, triggered by reward-related stimuli, result in corresponding increases in dopamine release? Are these changes uniform across different terminal regions? Moreover, do changes in dopamine signaling that occur during learning natural rewards, such as food, also occur during learning about drug rewards (e.g. cocaine), which cause unconditioned increases in dopamine release? In this issue of EJN, Aragona et al. (2009) investigated these questions by employing fast-scan cyclic voltametry to monitor real-time (sub-second) changes in dopamine release in two adjacent regions of the ventral striatum, the nucleus accumbens core and shell. Each of these regions receives dense dopaminergic innervation from midbrain dopamine neurons, and can be distinguished based on efferent and afferent connectivity and their functional contributions to reward-related behaviors (Zahm & Brog, 1992; Brog et al., 1993; Corbit et al., 2001; Ito et al., 2004). In this study, rats were subjected to a Pavlovian conditioning procedure, whereby over one session, they learned to associate the presentation of a discrete light and tone stimulus with intravenous delivery of cocaine. During the early phases of learning (i.e. the first few conditioning trials), presentation of the cue did not induce any reliable change in dopamine release. However, after about ten trials, the dopamine signal in the accumbens core appeared to ‘learn’ the predictive nature of the conditioned stimulus. Presentation of the drug-associated cue yielded a rapid and robust increase in dopamine release, in a manner similar to that displayed by the activity of midbrain dopamine neurons during similar learning about food rewards. What is particularly striking about these data is the fact that this effect was not observed in the adjacent nucleus accumbens shell region. Instead, repeated presentation of the cocaine-associated stimulus eventually resulted in cue-induced decreases in dopamine efflux, followed by an increase in release that corresponded to the pharmacological time course of cocaine effects. Similar phasic decreases in dopamine release were also observed in a separate experiment, where subjects were trained to associate a cue with a sucrose reward, suggesting that these effects could not be attributed to conditioned aversive properties of the cocaine infusions. These findings highlight the complexity of the dopamine system with respect to how rapid fluctuations in release contribute to associative learning about natural and drug rewards. Instead of showing similar changes in activity across terminal regions, dopamine signaling actually shows distinct regional specificity in terms of how it responds to reward-related stimuli. Phasic dopamine transmission within the accumbens core may serve as an incentive signal during early acquisition and subsequent maintenance of learned association with both food and drug rewards. Conversely, dynamic changes in dopamine signaling in the shell may be related to unconditioned rewarding properties of drugs of abuse. Perhaps the greatest impact of this study is that it suggests that a ‘grand unified theory’ of dopamine function may not be the most appropriate manner in which to view this neurotransmitter. Instead, dopamine transmission in different brain regions may require different theories to best explain its function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.022 | 0.032 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".