Strategically managing learning during perceptual decision making

Disentangling sources of variability in decision-making

Even the most highly-trained observers presented with identical choice-relevant stimuli will reliably exhibit substantial trial-to-trial variability in the timing and accuracy of their choices. Despite being a pervasive feature of choice behaviour and a prominent phenotype for numerous clinical disorders, the capability to disentangle the sources of such intra-individual variability (IIV) remains limited. In principle, computational models of decision-making offer a means of parsing and estimating these sources, but methodological limitations have prevented this potential from being fully realized in practice. In this Review, we first discuss current limitations of algorithmic models for understanding variability in decision-making behaviour. We then highlight recent advances in behavioural paradigm design, novel analyses of cross-trial behavioural and neural dynamics, and the development of neurally grounded computational models that are now making it possible to link distinct components of IIV to well-defined neural processes. Taken together, we demonstrate how these methods are opening up new avenues for systematically analysing the neural origins of IIV, paving the way for a more refined, holistic understanding of decision-making in health and disease.

Neural correlates of visual object recognition in rats

Invariant object recognition-the ability to recognize objects across size, rotation, or context-is fundamental for making sense of a dynamic visual world. Though traditionally studied in primates, emerging evidence suggests rodents recognize objects across a range of identity-preserving transformations. We demonstrate that rats robustly perform visual object recognition and explore a neural pathway that may underlie this capacity by developing a pipeline from high-throughput behavior training to cellular resolution imaging in awake, head-fixed animals. Leveraging our optical approach, we systematically profile neurons in primary and higher-order visual areas and their spatial organization. We find that rat visual cortex exhibits several features similar to those observed in the primate ventral stream but also marked deviations, suggesting species-specific differences in how brains solve visual object recognition. This work reinforces the sophisticated visual abilities of rats and offers the technical foundation to use them as a powerful model for mechanistic perception.

The dynamic strategy shifting task: Optimisation of an operant task for assessing cognitive flexibility in rats

Introduction

Although schizophrenia is associated with a broad range of symptoms including hallucinations, delusions, and reduced motivation, measures of cognitive dysfunction, including cognitive flexibility and executive function, are the strongest predictors of functional outcomes. Antipsychotic medications are useful for reducing psychotic symptoms, but they are ineffective at improving cognitive deficits. Despite extensive investment by industry, the transition from preclinical to clinical trials has not been successful for developing precognitive medications for individuals with schizophrenia. Here, we describe the optimisation of a novel dynamic strategy shifting task (DSST) using standard operant chambers to investigate the optimal stimuli required to limit the extensive training times required in previous tasks.

Methods

We determined that optimal learning by male and female Sprague Dawley rats for the flexibility task incorporated dynamic strategy shifts between spatial rules, such as following a visual cue or responding at one location, and non-spatial rules, such as responding to a central visual or auditory cue. A minimum of 6 correct consecutive responses were required to make a within-session change in the behavioural strategies. As a proof of concept, we trained and tested 84 Sprague Dawley rats on the DSST, and then assessed their cognitive flexibility using a within-subject design after an acute dose of ketamine (0, 3, 10 mg/kg). Rats made fewer premature and more perseverant responses to initiate a trial following ketamine. The effects of ketamine on trials to criterion was dependent on the rule.

Results

Ketamine induced a significant improvement on the reversal of a non-spatial visual discrimination rule. There was no significant effect of ketamine on the spatial visual or response discrimination rules.

Discussion

The DSST is a novel assay for studying distinct forms of cognitive flexibility and offers a rapid and adaptable means of assessing the ability to shift between increasingly challenging rule conditions. The DSST has potential utility in advancing our understanding of cognitive processes and the underlying neurobiological mechanisms related to flexibility in neuropsychiatric and neurological conditions where executive dysfunctions occur.>.

Expanding horizons in reinforcement learning for curious exploration and creative planning

Curiosity and creativity are expressions of the trade-off between leveraging that with which we are familiar or seeking out novelty. Through the computational lens of reinforcement learning, we describe how formulating the value of information seeking and generation via their complementary effects on planning horizons formally captures a range of solutions to striking this balance.

Learning to Choose: Behavioral Dynamics Underlying the Initial Acquisition of Decision-Making

Current theories of decision-making propose that decisions arise through competition between choice options. Computational models of the decision process estimate how quickly information about choice options is integrated and how much information is needed to trigger a choice. Experiments using this approach typically report data from well-trained participants. As such, we do not know how the decision process evolves as a decision-making task is learned for the first time. To address this gap, we used a behavioral design separating learning the value of choice options from learning to make choices. We trained male rats to respond to single visual stimuli with different reward values. Then, we trained them to make choices between pairs of stimuli. Initially, the rats responded more slowly when presented with choices. However, as they gained experience in making choices, this slowing reduced. Response slowing on choice trials persisted throughout the testing period. We found that it was specifically associated with increased exponential variability when the rats chose the higher value stimulus. Additionally, our analysis using drift diffusion modeling revealed that the rats required less information to make choices over time. These reductions in the decision threshold occurred after just a single session of choice learning. These findings provide new insights into the learning process of decision-making tasks. They suggest that the value of choice options and the ability to make choices are learned separately and that experience plays a crucial role in improving decision-making performance.

Learning to Choose: Behavioral Dynamics Underlying the Initial Acquisition of Decision Making

Current theories of decision making propose that decisions arise through competition between choice options. Computational models of the decision process estimate how quickly information about choice options is integrated and how much information is needed to trigger a choice. Experiments using this approach typically report data from well-trained participants. As such, we do not know how the decision process evolves as a decision-making task is learned for the first time. To address this gap, we used a behavioral design separating learning the value of choice options from learning to make choices. We trained male rats to respond to single visual stimuli with different reward values. Then, we trained them to make choices between pairs of stimuli. Initially, the rats responded more slowly when presented with choices. However, as they gained experience in making choices, this slowing reduced. Response slowing on choice trials persisted throughout the testing period. We found that it was specifically associated with increased exponential variability when the rats chose the higher value stimulus. Additionally, our analysis using drift diffusion modeling revealed that the rats required less information to make choices over time. Surprisingly, we observed reductions in the decision threshold after just a single session of choice learning. These findings provide new insights into the learning process of decision-making tasks. They suggest that the value of choice options and the ability to make choices are learned separately, and that experience plays a crucial role in improving decision-making performance.

Pushing the Bounds of Bounded Optimality and Rationality

All forms of cognition, whether natural or artificial, are subject to constraints of their computing architecture. This assumption forms the tenet of virtually all general theories of cognition, including those deriving from bounded optimality and bounded rationality. In this letter, we highlight an unresolved puzzle related to this premise: what are these constraints, and why are cognitive architectures subject to cognitive constraints in the first place? First, we lay out some pieces along the puzzle edge, such as computational tradeoffs inherent to neural architectures that give rise to rational bounds of cognition. We then outline critical next steps for characterizing cognitive bounds, proposing that some of these bounds can be subject to modification by cognition and, as such, are part of what is being optimized when cognitive agents decide how to allocate cognitive resources. We conclude that these emerging views may contribute to a more holistic perspective on the nature of cognitive bounds, as well as their alteration subject to cognition.

Unlocking a new dimension in the speed-accuracy trade-off

Why do we sometimes spend too much time on seemingly impossible-to-solve tasks instead of just moving on? Masís et al. provide a new perspective on the speed-accuracy trade-off (SAT), showing that, although prolonging deliberation looks suboptimal in the short run, it is a long-term investment that helps organisms reach proficient performance more rapidly.