Biology subjects

Charlton, J. A.

Publications and source records attributed to Charlton, J. A..

6 recordsLinked to original sources

bioRxiv2025

FixGrower: An efficient and robust curriculum for shaping fixation behavior in rodents

Center-port fixation is a common prerequisite for many freely-moving rodent tasks in neuroscience and psychology. However, typical protocols for shaping this behavior are non-standardized and inefficient. Moreover, motor errors in fixation termed violations often account for a significant fraction of experimental trials, leading to notable data loss during experiments. In light of this, we developed FixGrower, a standardized protocol for center-port fixation training. FixGrower (1) requires a longer initial fixation requirement, (2) increases the required fixation duration at session boundaries customized to each animals performance, and (3) delays the introduction of violation penalties until the end of training. We demonstrate FixGrower decreases training time by 61%, yields low violation rates, and generalizes across rodent species and task difficulty. Moreover, the success of this curriculum is well supported by theories of operant conditioning and reinforcement learning. Our findings establish FixGrower as an efficient and broadly applicable curriculum for training fixation behavior in rodents, thereby accelerating training of many tasks in the field.

animal behavior and cognition↗

bioRxiv2024

Bayesian inference by visuomotor neurons in prefrontal cortex

Perceptual judgements of the environment emerge from the concerted activity of neural populations in decision-making areas downstream of sensory cortex [1, 2, 3]. When the sensory input is ambiguous, perceptual judgements can be biased by prior expectations shaped by environmental regularities [4, 5, 6, 7, 8, 9, 10, 11]. These effects are examples of Bayesian inference, a reasoning method in which prior knowledge is leveraged to optimize uncertain decisions [12, 13]. However, it is not known how decision-making circuits combine sensory signals and prior expectations to form a perceptual decision. Here, we study neural population activity in the prefrontal cortex of macaque monkeys trained to report perceptual judgments of ambiguous visual stimuli under two different stimulus distributions. We analyze the component of the neural population response that represents the formation of the perceptual decision (the decision variable, DV), and find that its dynamical evolution reflects the integration of sensory signals and prior expectations. Prior expectations impact the DVs trajectory both before and during stimulus presentation such that DV trajectories with a smaller dynamic range result in more biased and less sensitive perceptual decisions. These results reveal a mechanism by which prefrontal circuits can execute Bayesian inference.

neuroscience↗

bioRxiv2024

Coordinated cross-brain activity during accumulation of sensory evidence and decision commitment

Decision-making is thought to involve two phases: first, evidence accumulation, then, decision commitment. Accumulation is represented broadly in the brain, but whether this best matches single versus multiple accumulator models is unknown. Here, analysis of simultaneous, bilateral recordings across sensory, association, and motor regions, in both cortex and subcortical structures, strongly supports a single accumulator, and suggests that accumulated noise (diffusion) originates frontally. Decision commitment can occur internally, without an overt report. Long-standing competing models of covert commitment disagree as to whether it is abrupt or continuous. Temporally aligning data on a single-trial estimator of internal, covert commitment ("nTc") revealed a rapid ([≤]50 ms) drop in the accumulators sensitivity to incoming sensory evidence, favoring abrupt transition models, and indicating a discrete cross-brain state change at nTc that was first detectable in motor regions. These data discriminate between decades-old models of accumulation, and between decades-old models of the transition to commitment.

neuroscience↗

bioRxiv2024

To integrate or not to integrate: Testing degenerate strategies for solving an accumulation of perceptual evidence decision-making task

A common approach in the study of cognition is to train subjects to perform a task that requires a particular cognitive process to solve. Analysis of the subjects response behavior while they perform these tasks can offer valuable insight into the underlying mechanisms that give rise to cognition. However, if subjects are able to accurately perform such a task by using a strategy that doesnt involve the targeted cognitive process, data from those experiments becomes more difficult to interpret. A number of perceptual decision-making tasks have been designed to study the accumulation of evidence, i.e. how noisy information presented over time is used to form a decision. Recent work, however, has highlighted how a variety of non-integration strategies can by some measures yield strikingly near-optimal performance on such tasks, raising the possibility that past conclusions from these experiments may be incorrect. Here we assemble the largest data set of animals performing one such task - the "Poisson Clicks" task - which is optimally solved by the gradual integration of pulsatile auditory noise. To investigate whether rats are in fact using this strategy, we compiled data from 515 rats performing over 35 million trials. We compare performance of 3 degenerate strategies (that circumvent the need to integrate evidence) to the optimal (integration) strategy. We demonstrate that the pulsatile nature of the stimuli used in the Poisson Clicks Task makes it possible to distinguish which strategy subjects use. Overwhelmingly, we find the rats are using an integration strategy when performing the Poisson Clicks Task.

animal behavior and cognition↗

bioRxiv2022

Abstract deliberation by visuomotor neurons in prefrontal cortex

During visually guided behavior, the prefrontal cortex plays a pivotal role in mapping sensory inputs onto appropriate motor plans [1]. When the sensory input is ambiguous, this involves deliberation. It is not known whether the deliberation is implemented as a competition between possible stimulus interpretations [2, 3] or between possible motor plans [4, 5, 6]. Here we study neural population activity in prefrontal cortex of macaque monkeys trained to flexibly report categorical judgments of ambiguous visual stimuli. Our task design allowed for the dissociation of neural predictors of the upcoming categorical choice and the upcoming motor response used to report this choice. We find that the population activity initially represents the formation of a categorical choice before transitioning into the stereotypical representation of the motor plan. We show that stimulus strength and prior expectations both bear on the formation of the categorical choice, but not on the formation of the action plan. These results suggest that prefrontal circuits involved in action selection are also used for the deliberation of abstract propositions divorced from a specific motor plan, thus providing a crucial mechanism for abstract reasoning.

neuroscience↗

bioRxiv2022

Perceptual decisions exhibit hallmarks of dynamic Bayesian inference

To interpret the sensory environment, the brain combines ambiguous sensory measurements with context-specific prior experience. But environmental contexts can change abruptly and unpredictably, resulting in uncertainty about the current context. Here we address two questions: how should context-specific prior knowledge optimally guide the interpretation of sensory stimuli in changing environments, and do human decision-making strategies resemble this optimum? We probe these questions with a task in which subjects report the orientation of ambiguous visual stimuli that were drawn from three dynamically switching distributions, representing different environmental contexts. We derive predictions for an ideal Bayesian observer that leverages the statistical structure of the task to maximize decision accuracy and show that its decisions are biased by task context. The magnitude of this decision bias is not a fixed property of the sensory measurement but depends on the observers belief about the current context. The model therefore predicts that decision bias will grow with the reliability of the context cue, the stability of the environment, and with the number of trials since the last context switch. Analysis of human choice data validates all three predictions, providing evidence that the brain continuously updates probabilistic representations of the environment to best interpret an uncertain, ever-changing world. SIGNIFICANCEThe brain relies on prior knowledge to make perceptual inferences when sensory information is ambiguous. However, when the environmental context changes, the appropriate prior knowledge often changes with it. Here, we develop a Bayesian observer model to investigate how to make optimal perceptual inferences when sensory information and environmental context are both uncertain. The behavioral signature of this strategy is a context-appropriate decision bias whose strength grows with the reliability of the context cue, the stability of the environment, and with the number of decisions since the most recent change in context. We identified exactly this pattern in the behavior of human subjects performing a dynamic orientation discrimination task. Together, our results suggest that the brain continuously updates probabilistic representations of the environment to make perceptual decisions in the face of uncertainty over both sensory and contextual information.

neuroscience↗