Topic: probabilistic reversal learning

Interactions across the frontal cortex are critical for cognition. Animal studies suggest a role for mediodorsal thalamus (MD) in these interactions, but the computations performed and direct relevance to human reasoning are unclear. Here, inspired by animal work, we build a neural model to derive computational insights and find consistent evidence in fMRI data of humans performing the same probabilistic reversal learning task. We used a reservoir recurrent neural network as a model of the dorso-lateral prefrontal cortex (dlPFC) and found that adding an MD layer with multiplicative inputs to d

When faced with a constantly changing, uncertain environment it is necessary to infer its underlying structure to guide behaviour. This has often been formalised as a value updating problem – where actions are chosen based on an incrementally updated weighted average of past reward. Activity of midbrain dopamine neurons has been commonly associated with the error in such value prediction, and it has been proposed to be crucial for learning and updating of values that inform decision making. However, it has become increasingly apparent that both humans and animals often use an alternative strat

Experiencing stress during adolescence profoundly alters the neural systems that control goal-directed flexible behaviour. These changes are persistent and are thought to drive behavioural inflexibility in adults, a hallmark symptom of several mental illnesses, including addiction, depression, obsessive compulsive disorder and schizophrenia. The ventral hippocampus (vH) is heavily impacted by stress, however, its role in flexible behaviour remains unclear, partially due to its heterogeneity. Thus, the current study investigates how individual vH projection populations contribute to behavioural

Asymmetry in choice patterns across rewarding and punishing contexts has long been observed in behavioural economics. Within existing theories of reinforcement learning, the mechanistic account of these behavioural differences is still debated. We propose that motivational salience - the degree of bottom-up attention attracted by a stimulus with relation to motivational value - offers a potential mechanism to modulate stimulus value updating and decision policy. In a probabilistic reversal learning task, we identified post-feedback signals from EEG and pupillometry that captured differential a

Humans and other animals require flexibility to make decisions appropriate for an ever-changing environment. The way mammalian brains achieve flexible decision making is not fully understood. The probabilistic reversal learning (PRL) task is a powerful tool used to assess behavioral flexibility and how positive and negative feedbacks influence decision making, both in healthy subjects and in patients with a wide range of neurological conditions like Autistic Spectrum Disorder and Schizophrenia, as well as animal models. We trained C57BL/6 mice on PRL and conducted high-density single unit reco

Humans continuously learn the properties of their environment, allowing them to predict and prepare for future (sensory) events. Bayesian predictive processing posits that these expectations play a major role in sensory processing, perception being the result of their integration with sensory evidence in this framework. Placebo hypoalgesia (when expectations of pain relief are sufficient to relieve pain) is probably the best example of expectations biassing perception. In this experiment, we manipulated pain expectations using a classic probabilistic reversal learning task (2 visual cues assoc

Making optimal decisions in a noisy and ever-changing world is difficult. To do this, we must continuously track the outcomes of our actions and the uncertainty associated with them over both long and short timescales. This allows identification of the underlying regularities in the world that can be used to guide behavior. But how neural circuits support the integration of experience is poorly understood. Neuromodulators are ideal candidates for tracking such variables as they can signal over multiple timescales from milliseconds to seconds. Specifically, acetylcholine has frequently been pro