Behavior- and Modality-General Representation of Confidence in Orbitofrontal Cortex.

Every decision we make is accompanied by a sense of confidence about its likely outcome. This sense informs subsequent behavior, such as investing more-whether time, effort, or money-when reward is more certain. A neural representation of confidence should originate from a statistical computation and predict confidence-guided behavior. An additional requirement for confidence representations to support metacognition is abstraction: they should emerge irrespective of the source of information and inform multiple confidence-guided behaviors. It is unknown whether neural confidence signals meet these criteria. Here, we show that single orbitofrontal cortex neurons in rats encode statistical decision confidence irrespective of the sensory modality, olfactory or auditory, used to make a choice. The activity of these neurons also predicts two confidence-guided behaviors: trial-by-trial time investment and cross-trial choice strategy updating. Orbitofrontal cortex thus represents decision confidence consistent with a metacognitive process that is useful for mediating confidence-guided economic decisions.

Frontal cortex neuron types categorically encode single decision variables.

Individual neurons in many cortical regions have been found to encode specific, identifiable features of the environment or body that pertain to the function of the region1-3. However, in frontal cortex, which is involved in cognition, neural responses display baffling complexity, carrying seemingly disordered mixtures of sensory, motor and other task-related variables4-13. This complexity has led to the suggestion that representations in individual frontal neurons are randomly mixed and can only be understood at the neural population level14,15. Here we show that neural activity in rat orbitofrontal cortex (OFC) is instead highly structured: single neuron activity co-varies with individual variables in computational models that explain choice behaviour. To characterize neural responses across a large behavioural space, we trained rats on a behavioural task that combines perceptual and value-guided decisions. An unbiased, model-free clustering analysis identified distinct groups of OFC neurons, each with a particular response profile in task-variable space. Applying a simple model of choice behaviour to these categorical response profiles revealed that each profile quantitatively corresponds to a specific decision variable, such as decision confidence. Additionally, we demonstrate that a connectivity-defined cell type, orbitofrontal neurons projecting to the striatum, carries a selective and temporally sustained representation of a single decision variable: integrated value. We propose that neurons in frontal cortex, as in other cortical regions, form a sparse and overcomplete representation of features relevant to the region's function, and that they distribute this information selectively to downstream regions to support behaviour.

An intra-oral flavor detection task in freely moving mice.

Flavor plays a critical role in the pleasure of food. Flavor research has mainly focused on human subjects and revealed that many brain regions are involved in flavor perception. However, animal models for elucidating the mechanisms of neural circuits are lacking. Herein, we demonstrate the use of a novel behavioral task in which mice are capable of flavor detection. When the olfactory pathways of the mice were blocked, they could not perform the task. However, behavioral accuracy was not affected when the gustatory pathway was blocked by benzocaine. These results indicate that the mice performed this detection task mainly based on the olfaction. We conclude that this novel task can contribute to research on the neural mechanisms of flavor perception.

Auditory Cortex Neurons Show Task-Related and Learning-Dependent Selectivity toward Sensory Input and Reward during the Learning Process of an Associative Memory Task.

The activity of primary auditory cortex (A1) neurons is modulated not only by sensory inputs but also by other task-related variables in associative learning. However, it is unclear how A1 neural activity changes dynamically in response to these variables during the learning process of associative memory tasks. Therefore, we developed an associative memory task using auditory stimuli in rats. In this task, rats were required to associate tone frequencies (high and low) with a choice of ports (right or left) to obtain a reward. The activity of A1 neurons in the rats during the learning process of the task was recorded. A1 neurons increased their firing rates either when the rats were presented with a high or low tone (frequency-selective cells) before they chose either the left or right port (choice-direction cells), or when they received a reward after choosing either the left or right port (reward-direction cells). Furthermore, the proportion of frequency-selective cells and reward-direction cells increased with task acquisition and reached the maximum level in the last stage of learning. These results suggest that A1 neurons have task- and learning-dependent selectivity toward sensory input and reward when auditory tones and behavioral responses are gradually associated during task training. This selective activity of A1 neurons may facilitate the formation of associations, leading to the consolidation of associative memory.

Bi-directional encoding of context-based odors and behavioral states by the nucleus of the lateral olfactory tract.

The nucleus of the lateral olfactory tract (NLOT) is not only a part of the olfactory cortex that receives olfactory sensory inputs but also a part of the cortical amygdala, which regulates motivational behaviors. To examine how neural activity of the NLOT is modulated by decision-making processes that occur during various states of learned goal-directed behaviors, we recorded NLOT spike activities of mice performing odor-guided go/no-go tasks to obtain a water reward. We observed that several NLOT neurons exhibited sharp go-cue excitation and persistent no-go-cue suppression responses triggered by an odor onset. The bidirectional cue encoding introduced NLOT population response dynamics and provided a high odor decoding accuracy before executing cue-odor-evoked behaviors. The go-cue responsive neurons were also activated in the reward drinking state, indicating context-based odor-outcome associations. These findings suggest that NLOT neurons play an important role in the translation from context-based odor information to appropriate behavior.

Over-representation of fundamental decision variables in the prefrontal cortex underlies decision bias.

The brain is organized into anatomically distinct structures consisting of a variety of projection neurons. While such evolutionarily conserved neural circuit organization underlies the innate ability of animals to swiftly adapt to environments, they can cause biased cognition and behavior. Although recent studies have begun to address the causal importance of projection-neuron types as distinct computational units, it remains unclear how projection types are functionally organized in encoding variables during cognitive tasks. This review focuses on the neural computation of decision making in the prefrontal cortex and discusses what decision variables are encoded by single neurons, neuronal populations, and projection type, alongside how specific projection types constrain decision making. We focus particularly on "over-representations" of distinct decision variables in the prefrontal cortex that reflect the biological and subjective significance of the variables for the decision makers. We suggest that task-specific over-representation in the prefrontal cortex involves the refinement of the given decision making, while generalized over-representation of fundamental decision variables is associated with suboptimal decision biases, including pathological ones such as those in patients with psychiatric disorders. Such over-representation of the fundamental decision variables in the prefrontal cortex appear to be tightly constrained by afferent and efferent connections that can be optogenetically intervened on. These ideas may provide critical insights into potential therapeutic targets for psychiatric disorders, including addiction and depression.

Contribution of non-sensory neurons in visual cortical areas to visually guided decisions in the rat.

It is widely assumed that trial-by-trial variability in visual detection performance is explained by the fidelity of visual responses in visual cortical areas influenced by fluctuations of internal states, such as vigilance and behavioral history. However, it is not clear which neuronal ensembles represent such different internal states. Here, we utilized a visual detection task, which distinguishes internal states in response to identical stimuli, while recording neurons simultaneously from the primary visual cortex (V1) and the posterior parietal cortex (PPC). We found that rats sometimes withheld their responses to visual stimuli despite the robust presence of visual responses in V1. Our unsupervised analysis revealed distinct population dynamics segregating hit responses from misses, orthogonally embedded to visual response dynamics in both V1 and PPC. Heterogeneous non-sensory neurons in V1 and PPC significantly contributed to population-level encoding accompanied with the modulation of noise correlation only in V1. These results highlight the non-trivial contributions of non-sensory neurons in V1 and PPC for population-level computations that reflect the animals' internal states to drive behavioral responses to visual stimuli.

Hippocampal CA1 Neurons Represent Positive Feedback During the Learning Process of an Associative Memory Task.

The hippocampus is crucial for forming associations between environmental stimuli. However, it is unclear how neural activities of hippocampal neurons dynamically change during the learning process. To address this question, we developed an associative memory task for rats with auditory stimuli. In this task, the rats were required to associate tone pitches (high and low) and ports (right and left) to obtain a reward. We recorded the firing activity of neurons in rats hippocampal CA1 during the learning process of the task. As a result, many hippocampal CA1 neurons increased their firing rates when the rats received a reward after choosing either the left or right port. We referred to these cells as "reward-direction cells." Furthermore, the proportion of the reward-direction cells increased in the middle-stage of learning but decreased after the completion of learning. This result suggests that the activity of reward-direction cells might serve as "positive feedback" signal that facilitates the formation of associations between tone pitches and port choice.

Dynamics of memory engrams.

In this update article, we focus on "memory engrams", which are traces of long-term memory in the brain, and emphasizes that they are not static but dynamic. We first introduce the major findings in neuroscience and psychology reporting that memory engrams are sometimes diffuse and unstable, indicating that they are dynamically modified processes of consolidation and reconsolidation. Second, we introduce and discuss the concepts of cell assembly and engram cell, the former has been investigated by psychological experiments and behavioral electrophysiology and the latter is defined by recent combination of activity-dependent cell labelling with optogenetics to show causal relationships between cell population activity and behavioral changes. Third, we discuss the similarities and differences between the cell assembly and engram cell concepts to reveal the dynamics of memory engrams. We also discuss the advantages and problems of live-cell imaging, which has recently been developed to visualize multineuronal activities. The last section suggests the experimental strategy and background assumptions for future research of memory engrams. The former encourages recording of cell assemblies from different brain regions during memory consolidation-reconsolidation processes, while the latter emphasizes the multipotentiality of neurons and regions that contribute to dynamics of memory engrams in the working brain.

Dynamic coordination of the perirhinal cortical neurons supports coherent representations between task epochs.

Cortical neurons show distinct firing patterns across multiple task epochs characterized by different computations. Recent studies suggest that such distinct patterns underlie dynamic population code achieving computational flexibility, whereas neurons in some cortical areas often show coherent firing patterns across epochs. To understand how coherent single-neuron code contributes to dynamic population code, we analyzed neural responses in the rat perirhinal cortex (PRC) during cue and reward epochs of a two-alternative forced-choice task. We found that the PRC neurons often encoded the opposite choice directions between those epochs. By using principal component analysis as a population-level analysis, we identified neural subspaces associated with each epoch, which reflected coordination across the neurons. The cue and reward epochs shared neural dimensions where the choice directions were consistently discriminated. Interestingly, those dimensions were supported by dynamically changing contributions of the individual neurons. These results demonstrated heterogeneity of coherent single-neuron representations in their contributions to population code.