Unexpected Rule-Changes in a Working Memory Task Shape the Firing of Histologically Identified Delay-Tuned Neurons in the Prefrontal Cortex

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Dissonant Representations of Visual Space in Prefrontal Cortex during Eye Movements

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Differential Interactions of Desipramine with Amphetamine and Methamphetamine: Evidence that Amphetamine Releases Dopamine from Noradrenergic Neurons in the Medial Prefrontal Cortex

Amphetamine is more effective than methamphetamine at raising dopamine levels in the prefrontal cortex. The current study tested the hypothesis that norepinephrine transporters are involved in this difference. Using microdialysis, dopamine, norepinephrine, and serotonin were measured in the rat prefrontal cortex after administration of methamphetamine or amphetamine, with and without perfusion of desipramine. Amphetamine raised norepinephrine levels more than methamphetamine did. Desipramine raised dopamine and serotonin levels but did not alter metabolite levels. Desipramine attenuated the increase in dopamine by amphetamine while increasing the dopamine released by methamphetamine. These data suggest that methamphetamine and amphetamine differ in altering prefrontal cortical dopamine levels and in interacting with norepinephrine transporters. It is proposed that amphetamine releases dopamine in the prefrontal cortex primarily through norepinephrine transporters, whereas methamphetamine interacts minimally with norepinephrine transporters.     

An evolutionary computational theory of prefrontal executive function in decision-making

The prefrontal cortex subserves executive control and decision-making, that is, the coordination and selection of thoughts and actions in the service of adaptive behaviour. We present here a computational theory describing the evolution of the prefrontal cortex from rodents to humans as gradually adding new inferential Bayesian capabilities for dealing with a computationally intractable decision problem: exploring and learning new behavioural strategies versus exploiting and adjusting previously learned ones through reinforcement learning (RL). We provide a principled account identifying three inferential steps optimizing this arbitration through the emergence of (i) factual reactive inferences in paralimbic prefrontal regions in rodents; (ii) factual proactive inferences in lateral prefrontal regions in primates and (iii) counterfactual reactive and proactive inferences in human frontopolar regions. The theory clarifies the integration of model-free and model-based RL through the notion of strategy creation. The theory also shows that counterfactual inferences in humans yield to the notion of hypothesis testing, a critical reasoning ability for approximating optimal adaptive processes and presumably endowing humans with a qualitative evolutionary advantage in adaptive behaviour.     

A Method for High Fidelity Optogenetic Control of Individual Pyramidal Neurons In vivo

Optogenetic methods have emerged as a powerful tool for elucidating neural circuit activity underlying a diverse set of behaviors across a broad range of species. Optogenetic tools of microbial origin consist of light-sensitive membrane proteins that are able to activate (e.g., channelrhodopsin-2, ChR2) or silence (e.g., halorhodopsin, NpHR) neural activity ingenetically-defined cell types over behaviorally-relevant timescales. We first demonstrate a simple approach for adeno-associated virus-mediated delivery of ChR2 and NpHR transgenes to the dorsal subiculum and prelimbic region of the prefrontal cortex in rat. Because ChR2 and NpHR are genetically targetable, we describe the use of this technology to control the electrical activity of specific populations of neurons (i.e., pyramidal neurons) embedded in heterogeneous tissue with high temporal precision. We describe herein the hardware, custom software user interface, and procedures that allow for simultaneous light delivery and electrical recording from transduced pyramidal neurons in an anesthetized in vivo preparation. These light-responsive tools provide the opportunity for identifying the causal contributions of different cell types to information processing and behavior.