PubMed Health⌕ Search

Biomedical subjects

P Read Montague

Publications and source records attributed to P Read Montague.

6 recordsLinked to original sources

Dynamic gain control of dopamine delivery in freely moving animals.

Activity changes in a large subset of midbrain dopamine neurons fulfill numerous assumptions of learning theory by encoding a prediction error between actual and predicted reward. This computational interpretation of dopaminergic spike activity invites the important question of how changes in spike rate are translated into changes in dopamine delivery at target neural structures. Using electrochemical detection of rapid dopamine release in the striatum of freely moving rats, we established that a single dynamic model can capture all the measured fluctuations in dopamine delivery. This model revealed three independent short-term adaptive processes acting to control dopamine release. These short-term components generalized well across animals and stimulation patterns and were preserved under anesthesia. The model has implications for the dynamic filtering interposed between changes in spike production and forebrain dopamine release.

Adaptation, Physiological↗

Temporal prediction errors in a passive learning task activate human striatum.

Functional MRI experiments in human subjects strongly suggest that the striatum participates in processing information about the predictability of rewarding stimuli. However, stimuli can be unpredictable in character (what stimulus arrives next), unpredictable in time (when the stimulus arrives), and unpredictable in amount (how much arrives). These variables have not been dissociated in previous imaging work in humans, thus conflating possible interpretations of the kinds of expectation errors driving the measured brain responses. Using a passive conditioning task and fMRI in human subjects, we show that positive and negative prediction errors in reward delivery time correlate with BOLD changes in human striatum, with the strongest activation lateralized to the left putamen. For the negative prediction error, the brain response was elicited by expectations only and not by stimuli presented directly; that is, we measured the brain response to nothing delivered (juice expected but not delivered) contrasted with nothing delivered (nothing expected).

Adult↗

A computational substrate for incentive salience.

Theories of dopamine function are at a crossroads. Computational models derived from single-unit recordings capture changes in dopaminergic neuron firing rate as a prediction error signal. These models employ the prediction error signal in two roles: learning to predict future rewarding events and biasing action choice. Conversely, pharmacological inhibition or lesion of dopaminergic neuron function diminishes the ability of an animal to motivate behaviors directed at acquiring rewards. These lesion experiments have raised the possibility that dopamine release encodes a measure of the incentive value of a contemplated behavioral act. The most complete psychological idea that captures this notion frames the dopamine signal as carrying 'incentive salience'. On the surface, these two competing accounts of dopamine function seem incommensurate. To the contrary, we demonstrate that both of these functions can be captured in a single computational model of the involvement of dopamine in reward prediction for the purpose of reward seeking.

Algorithms↗

Neural economics and the biological substrates of valuation.

A recent flurry of neuroimaging and decision-making experiments in humans, when combined with single-unit data from orbitofrontal cortex, suggests major additions to current models of reward processing. We review these data and models and use them to develop a specific computational relationship between the value of a predictor and the future rewards or punishments that it promises. The resulting computational model, the predictor-valuation model (PVM), is shown to anticipate a class of single-unit neural responses in orbitofrontal and striatal neurons. The model also suggests how neural responses in the orbitofrontal-striatal circuit may support the conversion of disparate types of future rewards into a kind of internal currency, that is, a common scale used to compare the valuation of future behavioral acts or stimuli.

Animals↗

Hyperscanning: simultaneous fMRI during linked social interactions.

"Plain question and plain answer make the shortest road out of most perplexities." Mark Twain-Life on the Mississippi. A new methodology for the measurement of the neural substrates of human social interaction is described. This technology, termed "Hyperscan," embodies both the hardware and the software necessary to link magnetic resonance scanners through the internet. Hyperscanning allows for the performance of human behavioral experiments in which participants can interact with each other while functional MRI is acquired in synchrony with the behavioral interactions. Data are presented from a simple game of deception between pairs of subjects. Because people may interact both asymmetrically and asynchronously, both the design and the analysis must accommodate this added complexity. Several potential approaches are described.

Brain↗

Activity in human ventral striatum locked to errors of reward prediction.

The mesolimbic dopaminergic system has long been known to be involved in the processing of rewarding stimuli, although recent evidence from animal research has suggested a more specific role of signaling errors in the prediction of rewards. We tested this hypothesis in humans, using functional magnetic resonance imaging (fMRI) and an operant conditioning paradigm for the discrete delivery of small quantities of fruit juice, along with a control experiment in which juice was substituted with a neutral visual stimulus. A local estimation of the activity in the ventral striatum showed a significant differentiation when the juice was withheld at the expected time of delivery; this finding was not replicated in the case of visual stimulation, providing evidence for time-locked processing of reward prediction errors in human ventral striatum.

Adult↗