Noradrenergic regulation of two-armed bandit performance.

Abstract

Reversal learning depends on cognitive flexibility. Many reversal learning studies assess cognitive flexibility based on the number of reversals that occur over a test session. Reversals occur when an option is repeatedly chosen, e.g., eight times in a row. This design feature encourages win-stay behavior and thus makes it difficult to understand how win-stay decisions influence reversal performance. We used an alternative design, reversals over blocks of trials independent of performance, to study how perturbations of the medial orbital cortex and the noradrenergic system influence reversal learning. We found that choice accuracy varies independently of win-stay behavior and the noradrenergic system controls sensitivity to positive feedback during reversal learning.

Inhibition of noradrenergic signalling in rodent orbitofrontal cortex impairs the updating of goal-directed actions

“…OFC NA depletion can also alter cue-outcome reversal, but not dimensional shift, in an attentional set-shifting task ( Mokler et al, 2017 ). Recently, it was also shown that reversible inactivation of the medial OFC (mOFC) decreased performance accuracy on a two-armed bandit task in rats ( Swanson et al, 2022 ). Interestingly, performance accuracy was also impaired following systemic, but not intra-mOFC, administration of an NA antagonist ( Swanson et al, 2022 ).…”

“…Recently, it was also shown that reversible inactivation of the medial OFC (mOFC) decreased performance accuracy on a two-armed bandit task in rats ( Swanson et al, 2022 ). Interestingly, performance accuracy was also impaired following systemic, but not intra-mOFC, administration of an NA antagonist ( Swanson et al, 2022 ). This result seems consistent with our finding showing that reversal learning and expression is intact when the LC: A32 pathway is silenced and may suggest a potential role for the ventral and lateral regions of OFC, rather than mOFC, in this effect.…”

The flow of reward information through neuronal ensembles in the accumbens

“…Seventeen rats were trained in a self-guided probabilistic choice task that closely resembled the reinforcement learning paradigm of the two-armed bandit task. 28,30 The task structure is illustrated in Figure 1A : Each trial started when the house lights turned on, signaling the rat to visit the center port and break the photobeam with its nose. After a 250-ms delay, a sound (Go signal) played, and both levers extended into the box.…”

“…This task is a reinforcement learning paradigm in which rats learn to choose between two levers, each associated with a different probability of delivering a reward (3 drops of sucrose). 30 The outcome probability associated with each lever changed in blocks of 50 trials each, so the rat must adapt and constantly update their internal representation of reward probabilities. These features make this task ideal for disentangling the reward representation from the oromotor features evoked by licking and for a better understanding of how reward outcomes guide decision-making during a reinforcement learning task.…”

A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals

“…Computational models have been applied successfully to animal data to examine and explain the role that particular neural substrates or structures play in guiding behaviour: for instance, dopamine has been heavily implicated in the encoding of prediction errors (Glimcher, 2011 ; Montague et al, 1996 ; Schultz et al, 1993 , 1997 ), and it has been suggested that noradrenaline could modulate behaviour by specifically altering how actions are selected (Aston-Jones & Cohen, 2005 ; Doya, 2002 ; Swanson et al, 2022 ). They have also been used to understand how individual differences and maladaptive behaviour might arise (Bathellier et al, 2013 ; Noworyta-Sokolowska et al, 2019 ; Rivalan et al, 2013 ; Spiegler et al, 2020 ).…”