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.

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.

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.

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.

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.

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.

Tuning of olfactory cortex ventral tenia tecta neurons to distinct task elements of goal-directed behavior.

The ventral tenia tecta (vTT) is a component of the olfactory cortex and receives both bottom-up odor signals and top-down signals. However, the roles of the vTT in odor-coding and integration of inputs are poorly understood. Here, we investigated the involvement of the vTT in these processes by recording the activity from individual vTT neurons during the performance of learned odor-guided reward-directed tasks in mice. We report that individual vTT cells are highly tuned to a specific behavioral epoch of learned tasks, whereby the duration of increased firing correlated with the temporal length of the behavioral epoch. The peak time for increased firing among recorded vTT cells encompassed almost the entire temporal window of the tasks. Collectively, our results indicate that vTT cells are selectively activated during a specific behavioral context and that the function of the vTT changes dynamically in a context-dependent manner during goal-directed behaviors.

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.

Reinforcement biases subsequent perceptual decisions when confidence is low, a widespread behavioral phenomenon.

Learning from successes and failures often improves the quality of subsequent decisions. Past outcomes, however, should not influence purely perceptual decisions after task acquisition is complete since these are designed so that only sensory evidence determines the correct choice. Yet, numerous studies report that outcomes can bias perceptual decisions, causing spurious changes in choice behavior without improving accuracy. Here we show that the effects of reward on perceptual decisions are principled: past rewards bias future choices specifically when previous choice was difficult and hence decision confidence was low. We identified this phenomenon in six datasets from four laboratories, across mice, rats, and humans, and sensory modalities from olfaction and audition to vision. We show that this choice-updating strategy can be explained by reinforcement learning models incorporating statistical decision confidence into their teaching signals. Thus, reinforcement learning mechanisms are continually engaged to produce systematic adjustments of choices even in well-learned perceptual decisions in order to optimize behavior in an uncertain world.

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.

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.

Cortical networks of the mouse brain elaborate within the gray matter.

In primates, proximal cortical areas are interconnected via within-cortex "intrinsic" pathway, whereas distant areas are connected via "extrinsic" white matter pathway. To date, such distinction has not been clearly done for small-brained mammals like rodents. In this study, we systematically analyzed the data of Allen Mouse Brain Connectivity Atlas to answer this question and found that the ipsilateral cortical connections in mice are almost exclusively contained within the gray matter, although we observed exceptions for projections from the retrosplenial area and the medial/orbital frontal areas. By analyzing axonal projections within the gray matter using Cortical Box method, which enabled us to investigate the layer patterns across different cortical areas, we obtained the following results. First, widespread axonal projections were observed in both upper and lower layers in the vicinity of injections, whereas highly specific "point-to-point" projections were observed toward remote areas. Second, such long-range projections were predominantly aligned in the anteromedial-posterolateral direction. Third, in the majority of these projections, the connecting axons traveled through layer 6. Finally, the projections from the primary and higher order areas to distant targets preferentially terminated in the middle and superficial layers, respectively, suggesting hierarchical connections similar to those of primates. Overall, our study demonstrated conspicuous differences in gray/white matter segregation of axonal projections between rodents and primates, despite certain similarities in the hierarchical cortical organization.

Multiple Approaches to the Investigation of Cell Assembly in Memory Research-Present and Future.

In this review article we focus on research methodologies for detecting the actual activity of cell assemblies, which are populations of functionally connected neurons that encode information in the brain. We introduce and discuss traditional and novel experimental methods and those currently in development and briefly discuss their advantages and disadvantages for the detection of cell-assembly activity. First, we introduce the electrophysiological method, i.e., multineuronal recording, and review former and recent examples of studies showing models of dynamic coding by cell assemblies in behaving rodents and monkeys. We also discuss how the firing correlation of two neurons reflects the firing synchrony among the numerous surrounding neurons that constitute cell assemblies. Second, we review the recent outstanding studies that used the novel method of optogenetics to show causal relationships between cell-assembly activity and behavioral change. Third, we review the most recently developed method of live-cell imaging, which facilitates the simultaneous observation of firings of a large number of neurons in behaving rodents. Currently, all these available methods have both advantages and disadvantages, and no single measurement method can directly and precisely detect the actual activity of cell assemblies. The best strategy is to combine the available methods and utilize each of their advantages with the technique of operant conditioning of multiple-task behaviors in animals and, if necessary, with brain-machine interface technology to verify the accuracy of neural information detected as cell-assembly activity.

Subjective decision threshold for accurate visual detection performance in rats.

The dissociation between a subjective-criterion performance and forced performance in a sensory detection can provide critical insights into the neural correlates of sensory awareness. Here, we established a behavioral task for rats to test their spatial-visual cue detection ability, using a two alternative choice task with and without a third choice option where animals get rewards only in the objective absence of a visual cue. In the trials without the third option, spatial choice accuracy decreased from near perfect to near chance levels as the visual cue brightness decreased. In contrast, with the third option, the rats exhibited >90% spatial choice accuracy regardless of the cue brightness. The rats chose the third choice option less frequently when the cue was brighter, suggesting that rats have a generalized strategy to make spatial choices only when their internal detection criterion is met. Interestingly, even when the animals chose the third option, they could still significantly and correctly choose the direction of the visual stimuli if they were forced. Our data suggest that the rats' variable detection performance with identical set of stimuli is derived from stochastic processing of visual signals with a certain internal detection threshold rather than general motivational threshold.

The limits of deliberation in a perceptual decision task.

While it is commonly assumed that decisions taken slowly result in superior outcomes, is it possible that optimal decision making does not always require sacrificing speed? For odor categorization decisions, it was previously shown that rats use <300 ms regardless of difficulty, but these findings could be interpreted as a tradeoff of accuracy for speed. Here, by systematically manipulating the task contingencies, we demonstrate that this is the maximum time over which sampling time can improve accuracy. Furthermore, we show that decision accuracy increases at no temporal cost when rats can better anticipate either the identity of stimuli or the required timing of responses. These experiments suggest that uncertainty in odor category decisions arises from noise sources that fluctuate slowly from trial-to-trial rather than rapidly within trials and that category decisions in other species and modalities might likewise be optimally served by rapid choices.

Area-specific substratification of deep layer neurons in the rat cortex.

Gene markers are useful tools to identify cell types for fine mapping of neuronal circuits. Here we report area-specific sublamina structure of the rat cerebral cortex using cholecystokinin (cck) and purkinje cell protein4 (pcp4) mRNAs as the markers for excitatory neuron subtypes in layers 5 and 6. We found a segregated expression, especially pronounced in layer 6, where corticothalamic and corticocortical projecting neurons reside. To examine the relationship between gene expression and projection target, we injected retrograde tracers into several thalamic subnuclei, ventral posterior (VP), posterior (PO), mediodorsal (MD), medial and lateral geniculate nuclei (MGN and LGN); as well as into two cortical areas (M1 and V1). This combination of tracer-in situ hybridization (ISH) experiments revealed that corticocortical neurons predominantly express cck and corticothalamic neurons predominantly express pcp4 mRNAs in all areas tested. In general, cck(+) and pcp4(+) cells occupied the upper and lower compartment of layer 6a, respectively. However, the sublaminar distribution and the relative abundance of cck(+) and pcp4(+) cells were quite distinctive across areas. For example, layer 6 of the prelimbic cortex was almost devoid of cck(+) neurons, and was occupied instead by corticothalamic pcp4(+) neurons. In the lateral areas, such as S2, there was an additional layer of cck(+) cells positioned below the pcp4(+) compartment. The claustrum, which has a tight relationship with the cortex, mostly consisted of cck(+)/pcp4(-) cells. In summary, the combination of gene markers and retrograde tracers revealed a distinct sublaminar organization, with conspicuous cross-area variation in the arrangement and relative density of corticothalamic connections.

Multisensory information facilitates reaction speed by enlarging activity difference between superior colliculus hemispheres in rats.

Animals can make faster behavioral responses to multisensory stimuli than to unisensory stimuli. The superior colliculus (SC), which receives multiple inputs from different sensory modalities, is considered to be involved in the initiation of motor responses. However, the mechanism by which multisensory information facilitates motor responses is not yet understood. Here, we demonstrate that multisensory information modulates competition among SC neurons to elicit faster responses. We conducted multiunit recordings from the SC of rats performing a two-alternative spatial discrimination task using auditory and/or visual stimuli. We found that a large population of SC neurons showed direction-selective activity before the onset of movement in response to the stimuli irrespective of stimulation modality. Trial-by-trial correlation analysis showed that the premovement activity of many SC neurons increased with faster reaction speed for the contraversive movement, whereas the premovement activity of another population of neurons decreased with faster reaction speed for the ipsiversive movement. When visual and auditory stimuli were presented simultaneously, the premovement activity of a population of neurons for the contraversive movement was enhanced, whereas the premovement activity of another population of neurons for the ipsiversive movement was depressed. Unilateral inactivation of SC using muscimol prolonged reaction times of contraversive movements, but it shortened those of ipsiversive movements. These findings suggest that the difference in activity between the SC hemispheres regulates the reaction speed of motor responses, and multisensory information enlarges the activity difference resulting in faster responses.

Analysis of area-specific expression patterns of RORbeta, ER81 and Nurr1 mRNAs in rat neocortex by double in situ hybridization and cortical box method.

BACKGROUND: The mammalian neocortex is subdivided into many areas, each of which exhibits distinctive lamina architecture. To investigate such area differences in detail, we chose three genes for comparative analyses, namely, RORbeta, ER81 and Nurr1, mRNAs of which have been reported to be mainly expressed in layers 4, 5 and 6, respectively. To analyze their qualitative and quantitative coexpression profiles in the rat neocortex, we used double in situ hybridization (ISH) histochemistry and cortical box method which we previously developed to integrate the data of different staining and individuals in a standard three-dimensional space. PRINCIPAL FINDINGS: Our new approach resulted in three main observations. First, the three genes showed unique area distribution patterns that are mostly complementary to one another. The patterns revealed by cortical box method matched well with the cytoarchitectonic areas defined by Nissl staining. Second, at single cell level, RORbeta and ER81 mRNAs were coexpressed in a subpopulation of layer 5 neurons, whereas Nurr1 and ER81 mRNAs were not colocalized. Third, principal component analysis showed that the order of hierarchical processing in the cortex correlates well with the expression profiles of these three genes. Based on this analysis, the dysgranular zone (DZ) in the somatosensory area was considered to exhibit a profile of a higher order area, which is consistent with previous proposal. CONCLUSIONS/SIGNIFICANCE: The tight relationship between the expression of the three layer specific genes and functional areas were revealed, demonstrating the usefulness of cortical box method in the study on the cerebral cortex. In particular, it allowed us to perform statistical evaluation and pattern matching, which would become important in interpreting the ever-increasing data of gene expression in the cortex.

Atomic force microscopy studies of interaction of the 20S proteasome with supported lipid bilayers.

The 20S proteasome plays important roles in degradation of intracellular proteins. Mechanisms of its activation, its localization in cells, and its binding to biomembranes are not well understood. In this study, we used atomic force microscopy (AFM) to investigate interactions between the 20S proteasome and supported bilayers of various lipids in a buffer. We found that the 20S proteasome specifically bound to supported bilayers containing phosphatidylinositol (PI), but did not bind to supported bilayers containing phosphatidylcholine, phosphatidic acid or dioleoyltrimethylammonium propane. Binding of the 20S proteasomes had a high orientation; almost all were in a top view position. The specific and orientational binding of the 20S proteasome with PI may play important roles inside cells such as endoplasmic reticulum (ER) membrane. Use of AFM to study supported bilayers provides new information on ligand-receptor interactions.