Action and learning shape the activity of neuronal circuits in the visual cortex

Acquisition of non-olfactory encoding improves odour discrimination in olfactory cortex

Olfaction is influenced by contextual factors, past experiences, and the animal's internal state. Whether this information is integrated at the initial stages of cortical odour processing is not known, nor how these signals may influence odour encoding. Here we revealed multiple and diverse non-olfactory responses in the primary olfactory (piriform) cortex (PCx), which dynamically enhance PCx odour discrimination according to behavioural demands. We performed recordings of PCx neurons from mice trained in a virtual reality task to associate odours with visual contexts to obtain a reward. We found that learning shifts PCx activity from encoding solely odours to a regime in which positional, contextual, and associative responses emerge on odour-responsive neurons that become mixed-selective. The modulation of PCx activity by these non-olfactory signals was dynamic, improving odour decoding during task engagement and in rewarded contexts. This improvement relied on the acquired mixed-selectivity, demonstrating how integrating extra-sensory inputs in sensory cortices can enhance sensory processing while encoding the behavioural relevance of stimuli.

Learning to learn: Single session acquisition of new rules by freely moving mice

Learning from examples and adapting to new circumstances are fundamental attributes of human cognition. However, it is unclear what conditions allow for fast and successful learning, especially in nonhuman subjects. To determine how rapidly freely moving mice can learn a new discrimination criterion (DC), we design a two-alternative forced-choice visual discrimination paradigm in which the DCs governing the task can change between sessions. We find that experienced animals can learn a new DC after being exposed to only five training and three testing trials. The propensity for single session learning improves over time and is accurately predicted based on animal experience and criterion difficulty. After establishing the procedural learning of a paradigm, mice continuously improve their performance in new circumstances. Thus, mice learn to learn.

Parental exposure to antidepressants has lasting effects on offspring? A case study with zebrafish

Fish have common neurotransmitter pathways with humans, exhibiting a significant degree of conservation and homology. Thus, exposure to fluoxetine makes fish potentially susceptible to biochemical and physiological changes, similarly to what is observed in humans. Over the years, several studies demonstrated the potential effects of fluoxetine on different fish species and at different levels of biological organization. However, the effects of parental exposure to unexposed offspring remain largely unknown. The consequences of 15-day parental exposure to relevant concentrations of fluoxetine (100 and 1000 ng/L) were assessed on offspring using zebrafish as a model organism. Parental exposure resulted in offspring early hatching, non-inflation of the swimming bladder, increased malformation frequency, decreased heart rate and blood flow, and reduced growth. Additionally, a significant behavioral impairment was also found (reduced startle response, basal locomotor activity, and altered non-associative learning during early stages and a negative geotaxis and scototaxis, reduced thigmotaxis, and anti-social behavior at later life stages). These behavior alterations are consistent with decreased anxiety, a significant increase in the expression of the monoaminergic genes slc6a4a (sert), slc6a3 (dat), slc18a2 (vmat2), mao, tph1a, and th2, and altered levels of monoaminergic neurotransmitters. Alterations in behavior, expression of monoaminergic genes, and neurotransmitter levels persisted until offspring adulthood. Given the high conservation of neuronal pathways between fish and humans, data show the possibility of potential transgenerational and multigenerational effects of pharmaceuticals' exposure. These results reinforce the need for transgenerational and multigenerational studies in fish, under realistic scenarios, to provide realistic insights into the impact of these pharmaceuticals.

Decision-making processes in perceptual learning depend on effectors

Visual perceptual learning is traditionally thought to arise in visual cortex. However, typical perceptual learning tasks also involve systematic mapping of visual information onto motor actions. Because the motor system contains both effector-specific and effector-unspecific representations, the question arises whether visual perceptual learning is effector-specific itself, or not. Here, we study this question in an orientation discrimination task. Subjects learn to indicate their choices either with joystick movements or with manual reaches. After training, we challenge them to perform the same task with eye movements. We dissect the decision-making process using the drift diffusion model. We find that learning effects on the rate of evidence accumulation depend on effectors, albeit not fully. This suggests that during perceptual learning, visual information is mapped onto effector-specific integrators. Overlap of the populations of neurons encoding motor plans for these effectors may explain partial generalization. Taken together, visual perceptual learning is not limited to visual cortex, but also affects sensorimotor mapping at the interface of visual processing and decision making.

Repeated passive visual experience modulates spontaneous and non-familiar stimuli-evoked neural activity

Familiarity creates subjective memory of repeated innocuous experiences, reduces neural and behavioral responsiveness to those experiences, and enhances novelty detection. The neural correlates of the internal model of familiarity and the cellular mechanisms of enhanced novelty detection following multi-day repeated passive experience remain elusive. Using the mouse visual cortex as a model system, we test how the repeated passive experience of a 45° orientation-grating stimulus for multiple days alters spontaneous and non-familiar stimuli evoked neural activity in neurons tuned to familiar or non-familiar stimuli. We found that familiarity elicits stimulus competition such that stimulus selectivity reduces in neurons tuned to the familiar 45° stimulus; it increases in those tuned to the 90° stimulus but does not affect neurons tuned to the orthogonal 135° stimulus. Furthermore, neurons tuned to orientations 45° apart from the familiar stimulus dominate local functional connectivity. Interestingly, responsiveness to natural images, which consists of familiar and non-familiar orientations, increases subtly in neurons that exhibit stimulus competition. We also show the similarity between familiar grating stimulus-evoked and spontaneous activity increases, indicative of an internal model of altered experience.

Flexible information representation to stabilize sensory perception despite minor external input variations

Sensory information about the environment constantly changes or varies depending on circumstances. However, once we repeatedly experience objects, our brain can perceive and recognize them as identical, even if they are slightly altered or include some diversity. We can stably perceive things without interference from minor external changes or variety. Our recent study focusing on visual perception showed that repeatedly viewing the same oriented grating stimuli enables information representation for low-contrast (or weak-intensity) orientations in the primary visual cortex. We observed low contrast-preferring neurons, whose firing rates increased by reducing the luminance contrast. The number of such neurons increased after the experience, and the neuronal population, including such neurons, can represent even low-contrast orientations. This study indicated that experience leads to flexible information representations that continuously respond to inputs of various strengths at the neuronal population level in the primary sensory cortex. In this perspective article, in addition to the above mechanism, I would discuss alternative mechanisms for perceptual stabilization. The primary sensory cortex represents external information faithfully without alterations, as well as in a state distorted by experience. Both sensory representations may cooperatively and dynamically affect hierarchical downstream, resulting in stable perception.

Learning induced neuronal identity switch in the superficial layers of the primary somatosensory cortex

During learning, multi-dimensional inputs are integrated within the sensory cortices. However, the strategies by which the sensory cortex employs to achieve learning remains poorly understood. We studied the sensory cortical neuronal coding of trace eyeblink conditioning (TEC) in head-fixed, freely running mice, where whisker deflection was used as a conditioned stimulus (CS) and an air puff to the cornea delivered after an interval was used as unconditioned stimulus (US). After training, mice learned the task with a set of stereotypical behavioral changes, most prominent ones include prolonged closure of eyelids, and increased reverse running between CS and US onset. The local blockade of the primary somatosensory cortex (S1) activities with muscimol abolished the behavior learning suggesting that S1 is required for the TEC. In naive animals, based on the response properties to the CS and US, identities of the small proportion (~20%) of responsive primary neurons (PNs) were divided into two subtypes: CR (i.e. CS-responsive) and UR neurons (i.e. US-responsive). After animals learned the task, identity of CR and UR neurons changed: while the CR neurons are less responsive to CS, UR neurons gain responsiveness to CS, a new phenomenon we defined as 'learning induced neuronal identity switch (LINIS)'. To explore the potential mechanisms underlying LINIS, we found that systemic and local (i.e. in S1) administration of the nicotinic receptor antagonist during TEC training blocked the LINIS, and concomitantly disrupted the behavior learning. Additionally, we monitored responses of two types of cortical interneurons (INs) and observed that the responses of the somatostatin-expressing (SST), but not parvalbumin-expressing (PV) INs are negatively correlated with the learning performance, suggesting that SST-INs contribute to the LINIS. Thus, we conclude that L2/3 PNs in S1 encode perceptual learning by LINIS like mechanisms, and cholinergic pathways and cortical SST interneurons are involved in the formation of LINIS.

Emerging V1 neuronal ensembles with enhanced connectivity after associative learning

Introduction

The visual stimulus-specific responses in the primary visual cortex (V1) undergo plastic changes after associative learning. During the learning process, neuronal ensembles, defined as groups of coactive neurons, are well known to be related to learning and memory. However, it remains unclear what effect learning has on ensembles, and which neuronal subgroups within those ensembles play a key role in associative learning.

Methods

We used two-photon calcium imaging in mice to record the activity of V1 neurons before and after fear conditioning associated with a visual cue (blue light). We first defined neuronal ensembles by thresholding their functional connectivity in response to blue (conditioned) or green (control) light. We defined neurons that existed both before and after conditioning as stable neurons. Neurons which were recruited after conditioning were defined as new neurons. The graph theory-based analysis was performed to quantify the changes in connectivity within ensembles after conditioning.

Results

A significant enhancement in the connectivity strength (the average correlation with other neurons) was observed in the blue ensembles after conditioning. We found that stable neurons within the blue ensembles showed a significantly smaller clustering coefficient (the value represented the degree of interconnectedness among a node's neighbors) after conditioning than they were before conditioning. Additionally, new neurons within the blue ensembles had a larger clustering coefficient, similar relative degree (the value represented the number of functional connections between neurons) and connectivity strength compared to stable neurons in the same ensembles.

Discussion

Overall, our results demonstrated that the plastic changes caused by conditioning occurred in subgroups of neurons in the ensembles. Moreover, new neurons from conditioned ensembles may play a crucial role in memory formation, as they exhibited not only similar connection competence in relative degree and connectivity strength as stable neurons, but also showed a significantly larger clustering coefficient compared to the stable neurons within the same ensembles after conditioning.

Visual Cortical Plasticity: Molecular Mechanisms as Revealed by Induction Paradigms in Rodents

Assessing the molecular mechanism of synaptic plasticity in the cortex is vital for identifying potential targets in conditions marked by defective plasticity. In plasticity research, the visual cortex represents a target model for intense investigation, partly due to the availability of different in vivo plasticity-induction protocols. Here, we review two major protocols: ocular-dominance (OD) and cross-modal (CM) plasticity in rodents, highlighting the molecular signaling pathways involved. Each plasticity paradigm has also revealed the contribution of different populations of inhibitory and excitatory neurons at different time points. Since defective synaptic plasticity is common to various neurodevelopmental disorders, the potentially disrupted molecular and circuit alterations are discussed. Finally, new plasticity paradigms are presented, based on recent evidence. Stimulus-selective response potentiation (SRP) is one of the paradigms addressed. These options may provide answers to unsolved neurodevelopmental questions and offer tools to repair plasticity defects.

Crosstalk between autophagy and the Keap1-Nrf2-ARE pathway regulates realgar-induced neurotoxicity

ETHNOPHARMACOLOGICAL RELEVANCE

Realgar, the main component of which is As₂S₂ or As₄S₄ (≥90%), is a traditional Chinese natural medicine that has been used to treat carbuncles, furuncles, snake and insect bites, abdominal pain caused by parasitic worms, and epilepsy in China for many years. Because realgar contains arsenic, chronic or excessive use of single-flavor realgar and realgar-containing Chinese patent medicine can lead to drug-induced arsenic poisoning, but the exact mechanism underlying its toxicity to the central nervous system is unclear.

AIM OF THE STUDY

The aim of this study was to clarify the mechanism of realgar-induced neurotoxicity and to investigate the effects of realgar on autophagy and the Keap1-Nrf2-ARE pathway.

MATERIALS AND METHODS

We used rats treated with the autophagy inhibitor 3-methyladenine (3-MA) or adeno-associated virus (AAV2/9-r-shRNA-Sqstm1, sh-p62) to investigate realgar-induced neurotoxicity and explore the specific relationship between autophagy and the Keap1-Nrf2-ARE pathway (the Nrf2 pathway) in the cerebral cortex. Molecular docking analysis was used to assess the interactions among the Nrf2, p62 and Keap1 proteins.

RESULTS

Our results showed that arsenic from realgar accumulated in the brain and blood to cause neuronal and synaptic damage, decrease exploratory behavior and spontaneous movement, and impair memory ability in rats. The mechanism may have involved realgar-mediated autophagy impairment and continuous activation of the Nrf2 pathway via the LC3-p62-Keap1-Nrf2 axis. However, because this activation of the Nrf2 pathway was not sufficient to counteract oxidative damage, apoptosis was aggravated in the cerebral cortex.

CONCLUSIONS

This study revealed that autophagy, the Nrf2 pathway, and apoptosis are involved in realgar-induced central nervous system toxicity and identified p62 as the hub of the LC3-p62-Keap1-Nrf2 axis in the regulation of autophagy, the Nrf2 pathway, and apoptosis.

Engaging distributed cortical and cerebellar networks through motor execution, observation, and imagery

When we interact with the environment around us, we are sometimes active participants, making directed physical motor movements and other times only mentally engaging with our environment, taking in sensory information and internally planning our next move without directed physical movement. Traditionally, cortical motor regions and key subcortical structures such as the cerebellum have been tightly linked to motor initiation, coordination, and directed motor behavior. However, recent neuroimaging studies have noted the activation of the cerebellum and wider cortical networks specifically during various forms of motor processing, including the observations of actions and mental rehearsal of movements through motor imagery. This phenomenon of cognitive engagement of traditional motor networks raises the question of how these brain regions are involved in the initiation of movement without physical motor output. Here, we will review evidence for distributed brain network activation during motor execution, observation, and imagery in human neuroimaging studies as well as the potential for cerebellar involvement specifically in motor-related cognition. Converging evidence suggests that a common global brain network is involved in both movement execution and motor observation or imagery, with specific task-dependent shifts in these global activation patterns. We will further discuss underlying cross-species anatomical support for these cognitive motor-related functions as well as the role of cerebrocerebellar communication during action observation and motor imagery.

Selective enhancement of neural coding in V1 underlies fine-discrimination learning in tree shrew

Visual discrimination improves with training, a phenomenon that is thought to reflect plastic changes in the responses of neurons in primary visual cortex (V1). However, the identity of the neurons that undergo change, the nature of the changes, and the consequences of these changes for other visual behaviors remain unclear. We used chronic in vivo 2-photon calcium imaging to monitor the responses of neurons in the V1 of tree shrews learning a Go/No-Go fine orientation discrimination task. We observed increases in neural population measures of discriminability for task-relevant stimuli that correlate with performance and depend on a select subset of neurons with preferred orientations that include the rewarded stimulus and nearby orientations biased away from the non-rewarded stimulus. Learning is accompanied by selective enhancement in the response of these neurons to the rewarded stimulus that further increases their ability to discriminate the task stimuli. These changes persist outside of the trained task and predict observed enhancement and impairment in performance of other discriminations, providing evidence for selective and persistent learning-induced plasticity in the V1, with significant consequences for perception.

Distinct representation of cue-outcome association by D1 and D2 neurons in the ventral striatum's olfactory tubercle

Positive and negative associations acquired through olfactory experience are thought to be especially strong and long-lasting. The conserved direct olfactory sensory input to the ventral striatal olfactory tubercle (OT) and its convergence with dense dopaminergic input to the OT could underlie this privileged form of associative memory, but how this process occurs is not well understood. We imaged the activity of the two canonical types of striatal neurons, expressing D1- or D2-type dopamine receptors, in the OT at cellular resolution while mice learned odor-outcome associations ranging from aversive to rewarding. D1 and D2 neurons both responded to rewarding and aversive odors. D1 neurons in the OT robustly and bidirectionally represented odor valence, responding similarly to odors predicting similar outcomes regardless of odor identity. This valence representation persisted even in the absence of a licking response to the odors and in the absence of the outcomes, indicating a true transformation of odor sensory information by D1 OT neurons. In contrast, D2 neuronal representation of the odor-outcome associations was weaker, contingent on a licking response by the mouse, and D2 neurons were more selective for odor identity than valence. Stimulus valence coding in the OT was modality-sensitive, with separate sets of D1 neurons responding to odors and sounds predicting the same outcomes, suggesting that integration of multimodal valence information happens downstream of the OT. Our results point to distinct representation of identity and valence of odor stimuli by D1 and D2 neurons in the OT.

[Neural mechanism for modulation of auditory response of the striatum by locomotion]

OBJECTIVE

To explore whether the characteristic responses to sound stimulations of the auditory neurons in the striatum is regulated in different behavioral states.

METHODS

The auditory neurons in the striatum of awake C57BL/6J mice were selected for this study. We recorded the auditory response of the striatum to noises over a long period of time by building a synchronous in vivo electrophysiological and locomotion recording system and using glass microelectrode attachment recording. By analyzing the running speed of the mice, the behavioral states of the mice were divided into the quiet state and the active state, and the spontaneous activity and evoked responses of the auditory neurons in the striatum were analyzed in these two states.

RESULTS

Compared with those recorded in the quiet state, the spontaneous activity of the auditory neurons in the striatum of the mice increased significantly (37.06±12.02 vs 18.51±10.91, P < 0.001) while the auditory response of the neurons decreased significantly (noise intensity=60 dB, 3.45±2.99 vs 3.04±2.76, P < 0.001) in the active state.

CONCLUSION

Locomotion has a significant inhibitory effect on the auditory response of the striatum, which may importantly contribute to the decline of sound information recognition ability in the active state.

Homeostatic regulation through strengthening of neuronal network-correlated synaptic inputs

Homeostatic regulation is essential for stable neuronal function. Several synaptic mechanisms of homeostatic plasticity have been described, but the functional properties of synapses involved in homeostasis are unknown. We used longitudinal two-photon functional imaging of dendritic spine calcium signals in visual and retrosplenial cortices of awake adult mice to quantify the sensory deprivation-induced changes in the responses of functionally identified spines. We found that spines whose activity selectively correlated with intrinsic network activity underwent tumor necrosis factor alpha (TNF-α)-dependent homeostatic increases in their response amplitudes, but spines identified as responsive to sensory stimulation did not. We observed an increase in the global sensory-evoked responses following sensory deprivation, despite the fact that the identified sensory inputs did not strengthen. Instead, global sensory-evoked responses correlated with the strength of network-correlated inputs. Our results suggest that homeostatic regulation of global responses is mediated through changes to intrinsic network-correlated inputs rather than changes to identified sensory inputs thought to drive sensory processing.

Parametric Copula-GP model for analyzing multidimensional neuronal and behavioral relationships

One of the main goals of current systems neuroscience is to understand how neuronal populations integrate sensory information to inform behavior. However, estimating stimulus or behavioral information that is encoded in high-dimensional neuronal populations is challenging. We propose a method based on parametric copulas which allows modeling joint distributions of neuronal and behavioral variables characterized by different statistics and timescales. To account for temporal or spatial changes in dependencies between variables, we model varying copula parameters by means of Gaussian Processes (GP). We validate the resulting Copula-GP framework on synthetic data and on neuronal and behavioral recordings obtained in awake mice. We show that the use of a parametric description of the high-dimensional dependence structure in our method provides better accuracy in mutual information estimation in higher dimensions compared to other non-parametric methods. Moreover, by quantifying the redundancy between neuronal and behavioral variables, our model exposed the location of the reward zone in an unsupervised manner (i.e., without using any explicit cues about the task structure). These results demonstrate that the Copula-GP framework is particularly useful for the analysis of complex multidimensional relationships between neuronal, sensory and behavioral variables.

Understanding the relationship between a set of variables is a common problem in many fields, such as weather forecast or stock market data. In neuroscience, one of the main challenges is to characterize the dependencies between neuronal activity, sensory stimuli and behavioral outputs. A method of choice for modeling such statistical dependencies is based on copulas, which disentangle dependencies from single variable statistics. To account for changes in dependencies, we model changes in copula parameters by means of Gaussian Processes, conditioned on a task-related variable. The novelty of our approach includes 1) explicit modeling of the dependencies; and 2) combining different copulas to describe experimentally observed variability. We validate the goodness-of-fit as well as information estimates on synthetic data and on recordings from the visual cortex of mice performing a behavioral task. Our parametric model demonstrates significantly better performance in describing high dimensional dependencies compared to other commonly used techniques. We demonstrate that our model can estimate information and predict behaviorally-relevant parameters of the task without providing any explicit cues to the model. Our results indicate that our model is interpretable in the context of neuroscience applications, scalable to large datasets and suitable for accurate statistical modeling and information estimation.

The contribution of low contrast-preferring neurons to information representation in the primary visual cortex after learning

Animals exhibit improved perception of lower-contrast visual objects after training. We explored this neuronal mechanism using multiple single-unit recordings from deep layers of the primary visual cortex (V1) of trained rats during orientation discrimination. We found that the firing rates of a subset of neurons increased by reducing luminance contrast, being at least above basal activities at low contrast. These low contrast–preferring neurons were rare during passive viewing without training or anesthesia after training. They fired more frequently in correct-choice than incorrect-choice trials. At single-neuron and population levels, they efficiently represented low-contrast orientations. Following training, in addition to generally enhanced excitation, the phase synchronization of spikes to beta oscillations at high contrast was stronger in putative inhibitory than excitatory neurons. The change in excitation-inhibition balance might contribute to low-contrast preference. Thus, low-contrast preference in V1 activity is strengthened in an experience-dependent manner, which may contribute to low-contrast visual discrimination.

[Evolution of auditory response signal-to-noise ratio in ascending auditory pathways]

OBJECTIVE

To explore the characteristics of the evolution of auditory response signal-to-noise ratio at all levels of the ascending auditory pathway, its modulation by different brain states in different brain regions, and its potential value as an effective indicator for encoding sound characteristics.

METHODS

Eighty C57BL/6J awake mice were used for recording the best frequency auditory response of the neurons in the inferior colliculus (n=20), medial geniculate body (n=20), and primary auditory cortex using a glass microelectrode. The probability density of spontaneous and evoked firing of the neurons was calculated to establish a distribution model of spontaneous and evoked firing, and the evolution of the auditory response signal-to-noise ratio was statistically analyzed. The changes in spontaneous and evoked firing of the neurons and the auditory response signal-to-noise ratio in different brain regions were analyzed at rest and during running.

RESULTS

In different brain regions in the ascending auditory pathway, the spontaneous firing of the neurons all showed a Poisson distribution, and the evoked firing showed a lognormal distribution. The auditory response signal-to-noise ratio was significantly greater in the inferior colliculus than in the medial geniculate body and auditory cortex (P < 0.001). The auditory response signal-to-noise ratio in the 3 brain regions remained stable irrespective of the states of motion (P>0.05).

CONCLUSION

Auditory response signal-to-noise ratio may serve as an effective indicator of encoding sound characteristics.

Spatial orientation during gondola centrifugation with subjects upright versus supine: Evidence for Gestalt psychological mechanisms in vestibular perception

BACKGROUND

Recent theories suggest that perception of complex self-motion is governed by familiarity of the motion pattern as a whole in 3D.

OBJECTIVE

To explore how familiarity determines the perceived angular displacement with respect to the Earth during a simulated coordinated turn in a gondola centrifuge.

METHOD

The centrifuge was accelerated to 2G (gondola displacement 60°) within 12.5 s. Using visual indicators in darkness, responses to the gondola displacement were recorded with subjects (n = 10) in two positions: sitting-upright, facing-forward versus lying-supine, feet-forwards. Each subject underwent 2×2 6-minute runs.

RESULT

When upright, subjects indicated a tilt of initially 18.8±11.3°, declining with T = 66±37 s. In the supine position (subject's yaw plane coinciding with the plane of gondola displacement) the indicated displacement was negligible (-0.3±4.8°).

CONCLUSION

Since the canal system is most responsive to stimuli in yaw, these findings are difficult to explain by bottom-up models. Rather, the motion pattern during acceleration would be recognized as a familiar or meaningful whole (entering a co-ordinated turn) only when the subject is upright. Presumably, the degree of familiarity is reflected in the subject's ability to discern and estimate a single stimulus component. Findings are discussed in connection with human factors in aviation and the principles of Gestalt psychology.

Probing mechanisms of visual spatial attention in mice

The role of spatial attention for visual perception has been thoroughly studied in primates, but less so in mice. Several behavioral tasks in mice reveal spatial attentional effects, with similarities to observations in primates. Pairing these tasks with large-scale, cell-type-specific techniques could enable deeper access to underlying mechanisms, and help define the utility and limitations of resolving attentional effects on visual perception and neural activity in mice. In this Review, we evaluate behavioral and neural evidence for visual spatial attention in mice; assess how specializations of the mouse visual system and behavioral repertoire impact interpretation of spatial attentional effects; and outline how several measurement and manipulation techniques in mice could precisely test and refine models of attentional modulation across scales.

V1 as an egocentric cognitive map

We typically distinguish between V1 as an egocentric perceptual map and the hippocampus as an allocentric cognitive map. In this article, we argue that V1 also functions as a post-perceptual egocentric cognitive map. We argue that three well-documented functions of V1, namely (i) the estimation of distance, (ii) the estimation of size, and (iii) multisensory integration, are better understood as post-perceptual cognitive inferences. This argument has two important implications. First, we argue that V1 must function as the neural correlates of the visual perception/cognition distinction and suggest how this can be accommodated by V1's laminar structure. Second, we use this insight to propose a low-level account of visual consciousness in contrast to mid-level accounts (recurrent processing theory; integrated information theory) and higher-level accounts (higher-order thought; global workspace theory). Detection thresholds have been traditionally used to rule out such an approach, but we explain why it is a mistake to equate visibility (and therefore the presence/absence of visual experience) with detection thresholds.

Rethinking Single Neuron Electrical Compartmentalization: Dendritic Contributions to Network Computation In Vivo

Decades of experimental and theoretical work support a now well-established theory that active dendritic processing contributes to the computational power of individual neurons. This theory is based on the high degree of electrical compartmentalization observed in the dendrites of single neurons in ex vivo preparations. Compartmentalization allows dendrites to conduct semi-independent operations on their inputs before final integration and output at the axon, producing a "network-in-a-neuron." However, recent in vivo functional imaging experiments in mouse cortex have reported surprisingly little evidence for strong dendritic compartmentalization. In this review, we contextualize these new findings and discuss their impact on the future of the field. Specifically, we consider how highly coordinated, and thus less compartmentalized, activity in soma and dendrites can contribute to cortical computations including nonlinear mixed selectivity, prediction/expectation, multiplexing, and credit assignment.

Mice with mutations in Trpm1, a gene in the locus of 15q13.3 microdeletion syndrome, display pronounced hyperactivity and decreased anxiety-like behavior

The 15q13.3 microdeletion syndrome is a genetic disorder characterized by a wide spectrum of psychiatric disorders that is caused by the deletion of a region containing 7 genes on chromosome 15 (MTMR10, FAN1, TRPM1, MIR211, KLF13, OTUD7A, and CHRNA7). The contribution of each gene in this syndrome has been studied using mutant mouse models, but no single mouse model recapitulates the whole spectrum of human 15q13.3 microdeletion syndrome. The behavior of Trpm1-/- mice has not been investigated in relation to 15q13.3 microdeletion syndrome due to the visual impairment in these mice, which may confound the results of behavioral tests involving vision. We were able to perform a comprehensive behavioral test battery using Trpm1 null mutant mice to investigate the role of Trpm1, which is thought to be expressed solely in the retina, in the central nervous system and to examine the relationship between TRPM1 and 15q13.3 microdeletion syndrome. Our data demonstrate that Trpm1-/- mice exhibit abnormal behaviors that may explain some phenotypes of 15q13.3 microdeletion syndrome, including reduced anxiety-like behavior, abnormal social interaction, attenuated fear memory, and the most prominent phenotype of Trpm1 mutant mice, hyperactivity. While the ON visual transduction pathway is impaired in Trpm1-/- mice, we did not detect compensatory high sensitivities for other sensory modalities. The pathway for visual impairment is the same between Trpm1-/- mice and mGluR6-/- mice, but hyperlocomotor activity has not been reported in mGluR6-/- mice. These data suggest that the phenotype of Trpm1-/- mice extends beyond that expected from visual impairment alone. Here, we provide the first evidence associating TRPM1 with impairment of cognitive function similar to that observed in phenotypes of 15q13.3 microdeletion syndrome.

Enhanced modulation of cell-type specific neuronal responses in mouse dorsal auditory field during locomotion

As we move through the environment we experience constantly changing sensory input that must be merged with our ongoing motor behaviors - creating dynamic interactions between our sensory and motor systems. Active behaviors such as locomotion generally increase the sensory-evoked neuronal activity in visual and somatosensory cortices, but evidence suggests that locomotion largely suppresses neuronal responses in the auditory cortex. However, whether this effect is ubiquitous across different anatomical regions of the auditory cortex is largely unknown. In mice, auditory association fields such as the dorsal auditory cortex (AuD), have been shown to have different physiological response properties, protein expression patterns, and cortical as well as subcortical connections, in comparison to primary auditory regions (A1) - suggesting there may be important functional differences. Here we examined locomotion-related modulation of neuronal activity in cortical layers ⅔ of AuD and A1 using two-photon Ca²⁺ imaging in head-fixed behaving mice that are able to freely run on a spherical treadmill. We determined the proportion of neurons in these two auditory regions that show enhanced and suppressed sensory-evoked responses during locomotion and quantified the depth of modulation. We found that A1 shows more suppression and AuD more enhanced responses during locomotion periods. We further revealed differences in the circuitry between these auditory regions and motor cortex, and found that AuD is more highly connected to motor cortical regions. Finally, we compared the cell-type specific locomotion-evoked modulation of responses in AuD and found that, while subpopulations of PV-expressing interneurons showed heterogeneous responses, the population in general was largely suppressed during locomotion, while excitatory population responses were generally enhanced in AuD. Therefore, neurons in primary and dorsal auditory fields have distinct response properties, with dorsal regions exhibiting enhanced activity in response to movement. This functional distinction may be important for auditory processing during navigation and acoustically guided behavior.

Adjudicating Between Local and Global Architectures of Predictive Processing in the Subcortical Auditory Pathway

Predictive processing, a leading theoretical framework for sensory processing, suggests that the brain constantly generates predictions on the sensory world and that perception emerges from the comparison between these predictions and the actual sensory input. This requires two distinct neural elements: generative units, which encode the model of the sensory world; and prediction error units, which compare these predictions against the sensory input. Although predictive processing is generally portrayed as a theory of cerebral cortex function, animal and human studies over the last decade have robustly shown the ubiquitous presence of prediction error responses in several nuclei of the auditory, somatosensory, and visual subcortical pathways. In the auditory modality, prediction error is typically elicited using so-called oddball paradigms, where sequences of repeated pure tones with the same pitch are at unpredictable intervals substituted by a tone of deviant frequency. Repeated sounds become predictable promptly and elicit decreasing prediction error; deviant tones break these predictions and elicit large prediction errors. The simplicity of the rules inducing predictability make oddball paradigms agnostic about the origin of the predictions. Here, we introduce two possible models of the organizational topology of the predictive processing auditory network: (1) the global view, that assumes that predictions on the sensory input are generated at high-order levels of the cerebral cortex and transmitted in a cascade of generative models to the subcortical sensory pathways; and (2) the local view, that assumes that independent local models, computed using local information, are used to perform predictions at each processing stage. In the global view information encoding is optimized globally but biases sensory representations along the entire brain according to the subjective views of the observer. The local view results in a diminished coding efficiency, but guarantees in return a robust encoding of the features of sensory input at each processing stage. Although most experimental results to-date are ambiguous in this respect, recent evidence favors the global model.

Defying Expectations: How Neurons Compute Prediction Errors in Visual Cortex

In this issue of Neuron, Jordan and Keller (2020) explore subthreshold computations underlying predictive coding using whole-cell recordings in mouse visual cortex. Their findings suggest that layer 2/3, but not layer 5/6, neurons compute prediction errors by subtracting predicted and actual visual flow inputs generated by locomotion.

Spatial navigation signals in rodent visual cortex

During navigation, animals integrate sensory information with body movements to guide actions. The impact of both navigational and movement-related signals on cortical visual information processing remains largely unknown. We review recent studies in awake rodents that have revealed navigation-related signals in the primary visual cortex (V1) including speed, distance travelled and head-orienting movements. Both cortical and subcortical inputs convey self-motion related information to V1 neurons: for example, top-down inputs from secondary motor and retrosplenial cortices convey information about head movements and spatial expectations. Within V1, subtypes of inhibitory neurons are critical for the integration of navigation-related and visual signals. We conclude with potential functional roles of navigation-related signals in V1 including gain control, motor error signals and predictive coding.

The Olfactory Bulb Facilitates Use of Category Bounds for Classification of Odorants in Different Intensity Groups

Signal processing of odor inputs to the olfactory bulb (OB) changes through top-down modulation whose shaping of neural rhythms in response to changes in stimulus intensity is not understood. Here we asked whether the representation of a high vs. low intensity odorant in the OB by oscillatory neural activity changed as the animal learned to discriminate odorant concentration ranges in a go-no go task. We trained mice to discriminate between high vs. low concentration odorants by learning to lick to the rewarded group (low or high). We recorded the local field potential (LFP) in the OB of these mice and calculated the theta-referenced beta or gamma oscillation power (theta phase-referenced power, or tPRP). We found that as the mouse learned to differentiate odorant concentrations, tPRP diverged between trials for the rewarded vs. the unrewarded concentration range. For the proficient animal, linear discriminant analysis was able to predict the rewarded odorant group and the performance of this classifier correlated with the percent correct behavior in the odor concentration discrimination task. Interestingly, the behavioral response and decoding accuracy were asymmetric as a function of concentration when the rewarded stimulus was shifted between the high and low odorant concentration ranges. A model for decision making motivated by the statistics of OB activity that uses a single threshold in a logarithmic concentration scale displays this asymmetry. Taken together with previous studies on the intensity criteria for decisions on odorant concentrations, our finding suggests that OB oscillatory events facilitate decision making to classify concentrations using a single intensity criterion.

Disynaptic cerebrocerebellar pathways originating from multiple functionally distinct cortical areas

The cerebral cortex and cerebellum both play important roles in sensorimotor processing, however, precise connections between these major brain structures remain elusive. Using anterograde mono-trans-synaptic tracing, we elucidate cerebrocerebellar pathways originating from primary motor, sensory, and association cortex. We confirm a highly organized topography of corticopontine projections in mice; however, we found no corticopontine projections originating from primary auditory cortex and detail several potential extra-pontine cerebrocerebellar pathways. The cerebellar hemispheres were the major target of resulting disynaptic mossy fiber terminals, but we also found at least sparse cerebrocerebellar projections to every lobule of the cerebellum. Notably, projections originating from association cortex resulted in less laterality than primary sensory/motor cortices. Within molecularly defined cerebellar modules we found spatial overlap of mossy fiber terminals, originating from functionally distinct cortical areas, within crus I, paraflocculus, and vermal regions IV/V and VI - highlighting these regions as potential hubs for multimodal cortical influence.

Movement-Related Signals in Sensory Areas: Roles in Natural Behavior

Recent studies have demonstrated prominent and widespread movement-related signals in the brain of head-fixed mice, even in primary sensory areas. However, it is still unknown what role these signals play in sensory processing. Why are these sensory areas 'contaminated' by movement signals? During natural behavior, animals actively acquire sensory information as they move through the environment and use this information to guide ongoing actions. In this context, movement-related signals could allow sensory systems to predict self-induced sensory changes and extract additional information about the environment. In this review we summarize recent findings on the presence of movement-related signals in sensory areas and discuss how their study, in the context of natural freely moving behaviors, could advance models of sensory processing.

Fully Affine Invariant Methods for Cross-Session Registration of Calcium Imaging Data

In vivo two-photon microscopy permits simultaneous recording of the activity of the same neuronal population across multiple sessions in days or weeks, which is crucial for addressing many fundamental questions of neuroscience. The field-of-view (FOV) alignment is a necessary step for identifying the same neurons across multiple imaging sessions. Accurate FOV alignment becomes challenging in the situations of image blurring, insufficient common neurons, or uneven background brightness. The existing methods largely fail to align FOV pairs in these situations. The fully affine invariant approach has been applied in computer vision to register real scene images with different backgrounds. However, its performance in calcium imaging data is unknown. We explored the feasibility of using the fully affine invariant approach to align calcium FOV images across multiple sessions by examining the performance of five methods. Further, we compared their performance with common feature-based methods as well as some classical methods with or without adaptive contrast enhancement. Using cellular resolution calcium imaging data recorded from two areas of the mouse motor cortex over weeks, we show that all fully affine invariant methods provide more accurate FOV alignment results than other methods in general and in the case of a few common neurons identified, uneven background brightness or image blurring. This study demonstrated the feasibility and reliability of the fully affine invariant methods in cross-session FOV alignment. These methods could be useful for neuroscience research, especially on questions that involve experience-dependent plasticity spanning over days or weeks.

Ultrafast Two-Photon Imaging of a High-Gain Voltage Indicator in Awake Behaving Mice

Optical interrogation of voltage in deep brain locations with cellular resolution would be immensely useful for understanding how neuronal circuits process information. Here, we report ASAP3, a genetically encoded voltage indicator with 51% fluorescence modulation by physiological voltages, submillisecond activation kinetics, and full responsivity under two-photon excitation. We also introduce an ultrafast local volume excitation (ULoVE) method for kilohertz-rate two-photon sampling in vivo with increased stability and sensitivity. Combining a soma-targeted ASAP3 variant and ULoVE, we show single-trial tracking of spikes and subthreshold events for minutes in deep locations, with subcellular resolution and with repeated sampling over days. In the visual cortex, we use soma-targeted ASAP3 to illustrate cell-type-dependent subthreshold modulation by locomotion. Thus, ASAP3 and ULoVE enable high-speed optical recording of electrical activity in genetically defined neurons at deep locations during awake behavior.

Population coupling predicts the plasticity of stimulus responses in cortical circuits

Some neurons have stimulus responses that are stable over days, whereas other neurons have highly plastic stimulus responses. Using a recurrent network model, we explore whether this could be due to an underlying diversity in their synaptic plasticity. We find that, in a network with diverse learning rates, neurons with fast rates are more coupled to population activity than neurons with slow rates. This plasticity-coupling link predicts that neurons with high population coupling exhibit more long-term stimulus response variability than neurons with low population coupling. We substantiate this prediction using recordings from the Allen Brain Observatory, finding that a neuron's population coupling is correlated with the plasticity of its orientation preference. Simulations of a simple perceptual learning task suggest a particular functional architecture: a stable 'backbone' of stimulus representation formed by neurons with low population coupling, on top of which lies a flexible substrate of neurons with high population coupling.

Two stream hypothesis of visual processing for navigation in mouse

Vision research has traditionally been studied in stationary subjects observing stimuli, and rarely during navigation. Recent research using virtual reality environments for mice has revealed that responses even in the primary visual cortex are modulated by spatial context - identical scenes presented in different positions of a room can elicit different responses. Here, we review these results and discuss how information from visual areas can reach navigational areas of the brain. Based on the observation that mouse higher visual areas cover different parts of the visual field, we propose that spatial signals are processed along two-streams based on visual field coverage. Specifically, this hypothesis suggests that landmark related signals are processed by areas biased to the central field, and self-motion related signals are processed by areas biased to the peripheral field.

Reward Association Enhances Stimulus-Specific Representations in Primary Visual Cortex

The potential for neuronal representations of external stimuli to be modified by previous experience is critical for efficient sensory processing and improved behavioral outcomes. To investigate how repeated exposure to a visual stimulus affects its representation in mouse primary visual cortex (V1), we performed two-photon calcium imaging of layer 2/3 neurons and assessed responses before, during, and after the presentation of a repetitive stimulus over 5 consecutive days. We found a stimulus-specific enhancement of the neuronal representation of the repetitively presented stimulus when it was associated with a reward. This was observed both after mice actively learned a rewarded task and when the reward was randomly received. Stimulus-specific enhanced representation resulted both from neurons gaining selectivity and from increased response reliability in previously selective neurons. In the absence of reward, there was either no change in stimulus representation or a decreased representation when the stimulus was viewed at a fixed temporal frequency. Pairing a second stimulus with a reward led to a similar enhanced representation and increased discriminability between the equally rewarded stimuli. Single-neuron responses showed that separate subpopulations discriminated between the two rewarded stimuli depending on whether the stimuli were displayed in a virtual environment or viewed on a single screen. We suggest that reward-associated responses enable the generalization of enhanced stimulus representation across these V1 subpopulations. We propose that this dynamic regulation of visual processing based on the behavioral relevance of sensory input ultimately enhances and stabilizes the representation of task-relevant features while suppressing responses to non-relevant stimuli.

Medial prefrontal lesions impair performance in an operant delayed nonmatch to sample working memory task

Cognitive functions, such as working memory, are disrupted in most psychiatric disorders. Many of these processes are believed to depend on the medial prefrontal cortex (mPFC). Traditionally, maze-based behavioral tasks, which have a strong exploratory component, have been used to study the role of the mPFC in working memory in mice. In maze tasks, mice navigate through the environment and require a significant amount of time to complete each trial, thereby limiting the number of trials that can be run per day. Here, we show that an operant-based delayed nonmatch to sample (DNMS) working memory task, with shorter trial lengths and a smaller exploratory component, is also mPFC-dependent. We created excitotoxic lesions in the mPFC of mice and found impairments in both the acquisition of the task, with no delay, and in the performance with delays introduced. Importantly, we saw no differences in trial length, reward collection, or lever-press latencies, indicating that the difference in performance was not due to a change in motivation or mobility. Using this operant DNMS task will facilitate the analysis of working memory and improve our understanding of the physiology and circuit mechanisms underlying this cognitive process. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Experience shapes activity dynamics and stimulus coding of VIP inhibitory cells

Cortical circuits can flexibly change with experience and learning, but the effects on specific cell types, including distinct inhibitory types, are not well understood. Here we investigated how excitatory and VIP inhibitory cells in layer 2/3 of mouse visual cortex were impacted by visual experience in the context of a behavioral task. Mice learned a visual change detection task with a set of eight natural scene images. Subsequently, during 2-photon imaging experiments, mice performed the task with these familiar images and three sets of novel images. Strikingly, the temporal dynamics of VIP activity differed markedly between novel and familiar images: VIP cells were stimulus-driven by novel images but were suppressed by familiar stimuli and showed ramping activity when expected stimuli were omitted from a temporally predictable sequence. This prominent change in VIP activity suggests that these cells may adopt different modes of processing under novel versus familiar conditions.

Learning improves decoding of odor identity with phase-referenced oscillations in the olfactory bulb

Local field potential oscillations reflect temporally coordinated neuronal ensembles-coupling distant brain regions, gating processing windows, and providing a reference for spike timing-based codes. In phase amplitude coupling (PAC), the amplitude of the envelope of a faster oscillation is larger within a phase window of a slower carrier wave. Here, we characterized PAC, and the related theta phase-referenced high gamma and beta power (PRP), in the olfactory bulb of mice learning to discriminate odorants. PAC changes throughout learning, and odorant-elicited changes in PRP increase for rewarded and decrease for unrewarded odorants. Contextual odorant identity (is the odorant rewarded?) can be decoded from peak PRP in animals proficient in odorant discrimination, but not in naïve mice. As the animal learns to discriminate the odorants the dimensionality of PRP decreases. Therefore, modulation of phase-referenced chunking of information in the course of learning plays a role in early sensory processing in olfaction.

High and asymmetric somato-dendritic coupling of V1 layer 5 neurons independent of visual stimulation and locomotion

Active dendrites impact sensory processing and behaviour. However, it remains unclear how active dendritic integration relates to somatic output in vivo. We imaged semi-simultaneously GCaMP6s signals in the soma, trunk and distal tuft dendrites of layer 5 pyramidal neurons in the awake mouse primary visual cortex. We found that apical tuft signals were dominated by widespread, highly correlated calcium transients throughout the tuft. While these signals were highly coupled to trunk and somatic transients, the frequency of calcium transients was found to decrease in a distance-dependent manner from soma to tuft. Ex vivo recordings suggest that low-frequency back-propagating action potentials underlie the distance-dependent loss of signals, while coupled somato-dendritic signals can be triggered by high-frequency somatic bursts or strong apical tuft depolarization. Visual stimulation and locomotion increased neuronal activity without affecting somato-dendritic coupling. High, asymmetric somato-dendritic coupling is therefore a widespread feature of layer 5 neurons activity in vivo.

Inhibitory microcircuits for top-down plasticity of sensory representations

Rewards influence plasticity of early sensory representations, but the underlying changes in circuitry are unclear. Recent experimental findings suggest that inhibitory circuits regulate learning. In addition, inhibitory neurons are highly modulated by diverse long-range inputs, including reward signals. We, therefore, hypothesise that inhibitory plasticity plays a major role in adjusting stimulus representations. We investigate how top-down modulation by rewards interacts with local plasticity to induce long-lasting changes in circuitry. Using a computational model of layer 2/3 primary visual cortex, we demonstrate how interneuron circuits can store information about rewarded stimuli to instruct long-term changes in excitatory connectivity in the absence of further reward. In our model, stimulus-tuned somatostatin-positive interneurons develop strong connections to parvalbumin-positive interneurons during reward such that they selectively disinhibit the pyramidal layer henceforth. This triggers excitatory plasticity, leading to increased stimulus representation. We make specific testable predictions and show that this two-stage model allows for translation invariance of the learned representation.

Rewards can improve stimulus processing in early sensory areas but the underlying neural circuit mechanisms are unknown. Here, the authors build a computational model of layer 2/3 primary visual cortex and suggest that plastic inhibitory circuits change first and then increase excitatory representations beyond the presence of rewards.

Causes and consequences of representational drift

The nervous system learns new associations while maintaining memories over long periods, exhibiting a balance between flexibility and stability. Recent experiments reveal that neuronal representations of learned sensorimotor tasks continually change over days and weeks, even after animals have achieved expert behavioral performance. How is learned information stored to allow consistent behavior despite ongoing changes in neuronal activity? What functions could ongoing reconfiguration serve? We highlight recent experimental evidence for such representational drift in sensorimotor systems, and discuss how this fits into a framework of distributed population codes. We identify recent theoretical work that suggests computational roles for drift and argue that the recurrent and distributed nature of sensorimotor representations permits drift while limiting disruptive effects. We propose that representational drift may create error signals between interconnected brain regions that can be used to keep neural codes consistent in the presence of continual change. These concepts suggest experimental and theoretical approaches to studying both learning and maintenance of distributed and adaptive population codes.

The Role of Neuronal Oscillations in Visual Active Sensing

Visual perception is most often studied as a "passive" process in which an observer fixates steadily at point in space so that stimuli can be delivered to the system with spatial precision. Analysis of neuronal signals related to vision is generally keyed to stimulus onset, stimulus movement, etc.; i.e., events external to the observer. In natural "active" vision, however, information is systematically acquired by using eye movements including rapid (saccadic) eye movements, as well as smooth ocular pursuit of moving objects and slower drifts. Here we consider the use of alternating saccades and fixations to gather information from a visual scene. The underlying motor sampling plan contains highly reliable information regarding "where" and "when" the eyes will land, this information can be used predictively to modify firing properties of neurons precisely at the time when this "contextual" information is most useful - when a volley of retinal input enters the system at the onset of each fixation. Analyses focusing on neural events leading to and resulting from shifts in fixation, as well as visual events external to the observer, can provide a more complete and mechanistic understanding of visual information processing. Studies thus far suggest that active vision may be a fundamentally different from that process we usually study with more traditional passive viewing paradigms. In this Perspective we note that active saccadic sampling behavior imposes robust temporal patterning on the activity of neuron ensembles and large-scale neural dynamics throughout the brain's visual pathways whose mechanistic effects on information processing are not yet fully understood. The spatio-temporal sequence of eye movements elicits a succession of temporally predictable quasi-rhythmic sensory inputs, whose encoding is enhanced by entrainment of low frequency oscillations to the rate of eye movements. Review of the pertinent findings underscores the fact that temporal coordination between motor and visual cortices is critical for understanding neural dynamics of active vision and posits that phase entrainment of neuronal oscillations plays a mechanistic role in this process.

Fitting predictive coding to the neurophysiological data

Recent neurophysiological data showing the effects of locomotion on neural activity in mouse primary visual cortex has been interpreted as providing strong support for the predictive coding account of cortical function. Specifically, this work has been interpreted as providing direct evidence that prediction-error, a distinguishing property of predictive coding, is encoded in cortex. This article evaluates these claims and highlights some of the discrepancies between the proposed predictive coding model and the neuro-biology. Furthermore, it is shown that the model can be modified so as to fit the empirical data more successfully.

Timing Is of the Essence: Improvement in Perception During Active Sensing

Active sensing refers to the concept of animals perceiving their environment while involving self-initiated motor acts. As a consequence of these motor acts, this activity produces direct and timely changes in the sensory surface. Is the brain able to take advantage of the precise time-locking that occurs during active sensing? Is the intrinsic predictability present during active sensing, impacting the sensory processes? We conjecture that if stimuli presentation is evoked by a self-initiated motor act, sensory discrimination and timing accuracy would improve. We studied this phenomenon when rats had to locate the position of a brief light stimulus, either when it was elicited by a warning light [passive condition (PC)] or when it was generated by a lever press [active condition (AC)]. We found that during the PC, rats had 66% of correct responses, vs. a significantly higher 77% of correct responses in AC. Furthermore, reaction times reduced from 1,181 ms during AC to 816 ms during PC For the latter condition, the probability of detecting the side of the light stimulus was negatively correlated with the time lag between the motor act and the evoked light and with a 38% reduction on performance per second of delay. These experiment shows that the mechanism that underlies sensory improvement during active behaviors have a constrained time dynamic, where the peak performances occur during the motor act, decreasing proportionally to the lag between the motor act and the stimulus presentation. This result is consistent with the evidence already found in humans, of a precise time dynamic of the improvement of sensory acuity after a motor act and reveals an equivalent process in rodents. Our results support the idea that perception and action are precisely coordinated in the brain.

Adrenergic Modulation of Visually-Guided Behavior

Iontophoretic application of norepinephrine (NE) into the primary visual cortex (V1) in vivo reduces spontaneous and evoked activity, without changing the functional selectivity of cortical units. One possible consequence of this phenomenon is that adrenergic receptors (ARs) regulate the signal-to-noise ratio (SNR) of neural responses in this circuit. However, despite such strong inhibitory action of NE on neuronal firing patterns in V1, its specific action on visual behavior has not been studied. Furthermore, the majority of observations regarding cortical NE from in vivo recordings have been performed in anesthetized animals and have not been tested behaviorally. Here, we describe how micro-infusion of AR agonists/antagonists into mouse V1 influences visually-guided behavior at different contrasts and spatial frequencies. We found that cortical activation of α₁- and β-AR produced a substantial reduction in visual discrimination performance at high contrasts and low spatial frequencies, consistent with a divisive effect. This reduction was reversible and was accompanied by a rise in escape latencies as well as an increase in the group averaged choice variance as a function of stimulus contrast. We conclude that pharmacological activation of cortical AR regulates visual perception and adaptive behavior through a divisive gain control of visual responses.

Abstract Representation of Prospective Reward in the Hippocampus

Motivation enhances memory by increasing hippocampal engagement during encoding. However, whether such increased hippocampal activation reflects encoding of the value of highly rewarding events per se is less understood. Here, using a monetary incentive encoding task with a novel manipulation, we tested in humans whether the hippocampus represents abstract reward value, independent of perceptual content. During functional MRI scanning, men and women studied object pairs, each preceded by a monetary reward cue indicating the amount of money they would receive if they successfully remembered the object pair at test. Reward cues varied on both the level of reward (penny, dime, and dollar) and visual form (picture or word) across trials to dissociate hippocampal responses to reward value from those reflecting the perceptual properties of the cues. Behaviorally, participants remembered pairs associated with the high reward (dollar) more often than pairs associated with lower rewards. Neural pattern-similarity analysis revealed that hippocampal and parahippocampal cortex activation patterns discriminated between cues of different value regardless of their visual form, and that hippocampal discrimination of value was most pronounced in participants who showed the greatest behavioral sensitivity to reward. Strikingly, hippocampal patterns were most distinct for reward cues that differed in value but had similar visual appearance, consistent with theoretical proposals of hippocampal-pattern differentiation of competing representations. Our data illustrate how contextual representations within the hippocampus go beyond space and time to include information about the motivational salience of events, with hippocampal reward coding tracking the motivational impact on later memory.SIGNIFICANCE STATEMENT Motivation, such as the promise of future rewards, enhances hippocampal engagement during encoding and promotes successful retention of events associated with valuable rewards. However, whether the hippocampus explicitly encodes reward value, dissociable from sensory information, is unclear. Here, we show that the hippocampus forms abstract representation of valuable rewards, encoding conceptual rather than perceptual information about the motivational context of individual events. Reward representation within the hippocampus is associated with preferential retention of high-value events in memory. Furthermore, we show that hippocampal-pattern differentiation serves to emphasize differences between visually similar events with distinct motivational salience. Collectively, these findings indicate that hippocampal contextual representations enable individuals to distinguish the motivational value of events, leading to prioritized encoding of significant memories.

The Impact of Visual Cues, Reward, and Motor Feedback on the Representation of Behaviorally Relevant Spatial Locations in Primary Visual Cortex

The integration of visual stimuli and motor feedback is critical for successful visually guided navigation. These signals have been shown to shape neuronal activity in the primary visual cortex (V1), in an experience-dependent manner. Here, we examined whether visual, reward, and self-motion-related inputs are integrated in order to encode behaviorally relevant locations in V1 neurons. Using a behavioral task in a virtual environment, we monitored layer 2/3 neuronal activity as mice learned to locate a reward along a linear corridor. With learning, a subset of neurons became responsive to the expected reward location. Without a visual cue to the reward location, both behavioral and neuronal responses relied on self-motion-derived estimations. However, when visual cues were available, both neuronal and behavioral responses were driven by visual information. Therefore, a population of V1 neurons encode behaviorally relevant spatial locations, based on either visual cues or on self-motion feedback when visual cues are absent.