Models of Dopamine in Prefrontal Cortex

George Chadderdon and Olaf Sporns have recently published a large scale neurocomputational model of task-oriented behavior selection, including such disparate brain regions as early visual areas, inferotemporal cortex, prefrontal cortex, basal ganglia, and anterior cingulate cortex. At the heart of this new model is a mechanism that simulates exogenously induced changes in prefrontal dopamine release, which is thought to underlie the updating and maintenance functions of working memory.

The model is meant to simulate the selection of behaviors in the delayed match/nonmatch-to-sample task. In this task, a sample stimulus is displayed, after which the stimulus will usually disappear (although there are versions in which it remains visible). After a delay, from 1 to 3 novel stimuli will appear and the subject must identify either the matching (in the match-to-sample) or the non-matching (in the nonmatch-to-sample) task.

During a trial, a working memory "task" layer fires to indicate whether the current trial is a match-to-sample (DMS), nonmatch-to-sample (DNMS), or idle task. Given the scale of this model, each unit has been designed to simulate the action of a cortical column, in which there are both excitatory and inhibitory neurons that implement feedforward, feedback, and lateral inhibition. Three layers of prefrontal cortex represent different aspects of the task: PFC(s) represents the current stimulus, PFC(d) represents the remembered stimulus, and representations in PFC(m) show the degree of match between PFC(d) and PFC(s). PFC(s) activation is projected to PFC(d) when the task units are firing for a non-idle task. Both DMS and DNMS cause dopamine release within PFC(d) (modeled as a proportional increase in the gain of the excitatory sigmoid activation functgion), which solidifies a persistent representation of the current stimulus until a response is required; units representing the anterior cingulate cortex are used to suppress responses during the cue period.

The model captures many of the qualitative aspects of dopamine/PFC interaction. First, PFC(d) units become dysfunctional under conditions of too low, or too-high extracellular dopamine, which is consistent with empirical evidence. Second, this model implements one way that PFC may intrinsically regulate dopamine levels for optimal function, and predicts task-relevant fluctuations in tonic DA release. However, several things remain unaddressed, including the precise role of phasic DA release by VTA in which working memory representations are updated or maintained, and its interactions with intrinsic PFC dopamine regulation.

The authors conclude that future work "will involve the implementation of the present model as part of the control architecture of an autonomous robot" which could provide a unique opportunity to assess the role of dopamine concentration on behavior given the difficulty of monitoring realtime dopamine fluctuations in behaving animals.

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Neurorobotics
Emotional Robotics (and dopamine fluctuations)
Selection Efficiency and Inhibition