A reservoir of foraging decision variables in the mouse brain.

In any given situation, the environment can be parsed in different ways to yield decision variables (DVs) defining strategies useful for different tasks. It is generally presumed that the brain only computes a single DV defining the current behavioral strategy. Here to test this assumption, we recorded neural ensembles in the frontal cortex of mice performing a foraging task admitting multiple DVs. Methods developed to uncover the currently employed DV revealed the use of multiple strategies and occasional switches in strategy within sessions. Optogenetic manipulations showed that the secondary motor cortex (M2) is needed for mice to use the different DVs in the task. Surprisingly, we found that regardless of which DV best explained the current behavior, M2 activity concurrently encoded a full basis set of computations defining a reservoir of DVs appropriate for alternative tasks. This form of neural multiplexing may confer considerable advantages for learning and adaptive behavior.

Standardized and reproducible measurement of decision-making in mice.

Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches.

In science, it is of vital importance that multiple studies corroborate the same result. Researchers therefore need to know all the details of previous experiments in order to implement the procedures as exactly as possible. However, this is becoming a major problem in neuroscience, as animal studies of behavior have proven to be hard to reproduce, and most experiments are never replicated by other laboratories. Mice are increasingly being used to study the neural mechanisms of decision making, taking advantage of the genetic, imaging and physiological tools that are available for mouse brains. Yet, the lack of standardized behavioral assays is leading to inconsistent results between laboratories. This makes it challenging to carry out large-scale collaborations which have led to massive breakthroughs in other fields such as physics and genetics. To help make these studies more reproducible, the International Brain Laboratory (a collaborative research group) et al. developed a standardized approach for investigating decision making in mice that incorporates every step of the process; from the training protocol to the software used to analyze the data. In the experiment, mice were shown images with different contrast and had to indicate, using a steering wheel, whether it appeared on their right or left. The mice then received a drop of sugar water for every correction decision. When the image contrast was high, mice could rely on their vision. However, when the image contrast was very low or zero, they needed to consider the information of previous trials and choose the side that had recently appeared more frequently. This method was used to train 140 mice in seven laboratories from three different countries. The results showed that learning speed was different across mice and laboratories, but once training was complete the mice behaved consistently, relying on visual stimuli or experiences to guide their choices in a similar way. These results show that complex behaviors in mice can be reproduced across multiple laboratories, providing an unprecedented dataset and open-access tools for studying decision making. This work could serve as a foundation for other groups, paving the way to a more collaborative approach in the field of neuroscience that could help to tackle complex research challenges.

Citric Acid Water as an Alternative to Water Restriction for High-Yield Mouse Behavior.

Powerful neural measurement and perturbation tools have positioned mice as an ideal species for probing the neural circuit mechanisms of cognition. Crucial to this success is the ability to motivate animals to perform specific behaviors. One successful strategy is to restrict their water intake, rewarding them with water during a behavioral task. However, water restriction requires rigorous monitoring of animals' health and hydration status and can be challenging for some mice. We present an alternative that allows mice more control over their water intake: free home-cage access to water, made slightly sour by a small amount of citric acid (CA). In a previous study, rats with free access to CA water readily performed a behavioral task for water rewards, although completing fewer trials than under water restriction (Reinagel, 2018). We here extend this approach to mice and confirm its robustness across multiple laboratories. Mice reduced their intake of CA water while maintaining healthy weights. Continuous home-cage access to CA water only subtly impacted their willingness to perform a decision-making task, in which they were rewarded with sweetened water. When free CA water was used instead of water restriction only on weekends, learning and decision-making behavior were unaffected. CA water is thus a promising alternative to water restriction, allowing animals more control over their water intake without interfering with behavioral performance.

Phasic Activation of Dorsal Raphe Serotonergic Neurons Increases Pupil Size.

Transient variations in pupil size (PS) under constant luminance are coupled to rapid changes in arousal state,1-3 which have been interpreted as vigilance,4 salience,5 or a surprise signal.6-8 Neural control of such fluctuations presumably involves multiple brain regions5,9-11 and neuromodulatory systems,3,12,13 but it is often associated with phasic activity of the noradrenergic system.9,12,14,15 Serotonin (5-HT), a neuromodulator also implicated in aspects of arousal16 such as sleep-wake transitions,17 motivational state regulation,18 and signaling of unexpected events,19 seems to affect PS,20-24 but these effects have not been investigated in detail. Here we show that phasic 5-HT neuron stimulation causes transient PS changes. We used optogenetic activation of 5-HT neurons in the dorsal raphe nucleus (DRN) of head-fixed mice performing a foraging task. 5-HT-driven modulations of PS were maintained throughout the photostimulation period and sustained for a few seconds after the end of stimulation. We found no evidence that the increase in PS with activation of 5-HT neurons resulted from interactions of photostimulation with behavioral variables, such as locomotion or licking. Furthermore, we observed that the effect of 5-HT on PS depended on the level of environmental uncertainty, consistent with the idea that 5-HT could report a surprise signal.19 These results advance our understanding of the neuromodulatory control of PS, revealing a tight relationship between phasic activation of 5-HT neurons and changes in PS.

Synthesis of Hemispheric ITD Tuning from the Readout of a Neural Map: Commonalities of Proposed Coding Schemes in Birds and Mammals.

A major cue to infer sound direction is the difference in arrival time of the sound at the left and right ears, called interaural time difference (ITD). The neural coding of ITD and its similarity across species have been strongly debated. In the barn owl, an auditory specialist relying on sound localization to capture prey, ITDs within the physiological range determined by the head width are topographically represented at each frequency. The topographic representation suggests that sound direction may be inferred from the location of maximal neural activity within the map. Such topographical representation of ITD, however, is not evident in mammals. Instead, the preferred ITD of neurons in the mammalian brainstem often lies outside the physiological range and depends on the neuron's best frequency. Because of these disparities, it has been assumed that how spatial hearing is achieved in birds and mammals is fundamentally different. However, recent studies reveal ITD responses in the owl's forebrain and midbrain premotor area that are consistent with coding schemes proposed in mammals. Particularly, sound location in owls could be decoded from the relative firing rates of two broadly and inversely ITD-tuned channels. This evidence suggests that, at downstream stages, the code for ITD may not be qualitatively different across species. Thus, while experimental evidence continues to support the notion of differences in ITD representation across species and brain regions, the latest results indicate notable commonalities, suggesting that codes driving orienting behavior in mammals and birds may be comparable.

Emergence of an Adaptive Command for Orienting Behavior in Premotor Brainstem Neurons of Barn Owls.

The midbrain map of auditory space commands sound-orienting responses in barn owls. Owls precisely localize sounds in frontal space but underestimate the direction of peripheral sound sources. This bias for central locations was proposed to be adaptive to the decreased reliability in the periphery of sensory cues used for sound localization by the owl. Understanding the neural pathway supporting this biased behavior provides a means to address how adaptive motor commands are implemented by neurons. Here we find that the sensory input for sound direction is weighted by its reliability in premotor neurons of the midbrain tegmentum of owls (male and female), such that the mean population firing rate approximates the head-orienting behavior. We provide evidence that this coding may emerge through convergence of upstream projections from the midbrain map of auditory space. We further show that manipulating the sensory input yields changes predicted by the convergent network in both premotor neural responses and behavior. This work demonstrates how a topographic sensory representation can be linearly read out to adjust behavioral responses by the reliability of the sensory input.SIGNIFICANCE STATEMENT This research shows how statistics of the sensory input can be integrated into a behavioral command by readout of a sensory representation. The firing rate of midbrain premotor neurons receiving sensory information from a topographic representation of auditory space is weighted by the reliability of sensory cues. We show that these premotor responses are consistent with a weighted convergence from the topographic sensory representation. This convergence was also tested behaviorally, where manipulation of stimulus properties led to bidirectional changes in sound localization errors. Thus a topographic representation of auditory space is translated into a premotor command for sound localization that is modulated by sensory reliability.

Cue Reliability Represented in the Shape of Tuning Curves in the Owl's Sound Localization System.

Optimal use of sensory information requires that the brain estimates the reliability of sensory cues, but the neural correlate of cue reliability relevant for behavior is not well defined. Here, we addressed this issue by examining how the reliability of spatial cue influences neuronal responses and behavior in the owl's auditory system. We show that the firing rate and spatial selectivity changed with cue reliability due to the mechanisms generating the tuning to the sound localization cue. We found that the correlated variability among neurons strongly depended on the shape of the tuning curves. Finally, we demonstrated that the change in the neurons' selectivity was necessary and sufficient for a network of stochastic neurons to predict behavior when sensory cues were corrupted with noise. This study demonstrates that the shape of tuning curves can stand alone as a coding dimension of environmental statistics. SIGNIFICANCE STATEMENT: In natural environments, sensory cues are often corrupted by noise and are therefore unreliable. To make the best decisions, the brain must estimate the degree to which a cue can be trusted. The behaviorally relevant neural correlates of cue reliability are debated. In this study, we used the barn owl's sound localization system to address this question. We demonstrated that the mechanisms that account for spatial selectivity also explained how neural responses changed with degraded signals. This allowed for the neurons' selectivity to capture cue reliability, influencing the population readout commanding the owl's sound-orienting behavior.

Neural representation of probabilities for Bayesian inference.

Bayesian models are often successful in describing perception and behavior, but the neural representation of probabilities remains in question. There are several distinct proposals for the neural representation of probabilities, but they have not been directly compared in an example system. Here we consider three models: a non-uniform population code where the stimulus-driven activity and distribution of preferred stimuli in the population represent a likelihood function and a prior, respectively; the sampling hypothesis which proposes that the stimulus-driven activity over time represents a posterior probability and that the spontaneous activity represents a prior; and the class of models which propose that a population of neurons represents a posterior probability in a distributed code. It has been shown that the non-uniform population code model matches the representation of auditory space generated in the owl's external nucleus of the inferior colliculus (ICx). However, the alternative models have not been tested, nor have the three models been directly compared in any system. Here we tested the three models in the owl's ICx. We found that spontaneous firing rate and the average stimulus-driven response of these neurons were not consistent with predictions of the sampling hypothesis. We also found that neural activity in ICx under varying levels of sensory noise did not reflect a posterior probability. On the other hand, the responses of ICx neurons were consistent with the non-uniform population code model. We further show that Bayesian inference can be implemented in the non-uniform population code model using one spike per neuron when the population is large and is thus able to support the rapid inference that is necessary for sound localization.

Spatial cue reliability drives frequency tuning in the barn Owl's midbrain.

The robust representation of the environment from unreliable sensory cues is vital for the efficient function of the brain. However, how the neural processing captures the most reliable cues is unknown. The interaural time difference (ITD) is the primary cue to localize sound in horizontal space. ITD is encoded in the firing rate of neurons that detect interaural phase difference (IPD). Due to the filtering effect of the head, IPD for a given location varies depending on the environmental context. We found that, in barn owls, at each location there is a frequency range where the head filtering yields the most reliable IPDs across contexts. Remarkably, the frequency tuning of space-specific neurons in the owl's midbrain varies with their preferred sound location, matching the range that carries the most reliable IPD. Thus, frequency tuning in the owl's space-specific neurons reflects a higher-order feature of the code that captures cue reliability.

Abnormal cholesterol is associated with prefrontal white matter abnormalities among obese adults, a diffusion tensor imaging study.

The brain is the most cholesterol-rich organ in the body. Although most of the cholesterol in the brain is produced endogenously, some studies suggest that systemic cholesterol may be able to enter the brain. We investigated whether abnormal cholesterol profiles correlated with diffusion-tensor-imaging-based estimates of white matter microstructural integrity of lean and overweight/obese (o/o) adults. Twenty-two lean and 39 obese adults underwent magnetic resonance imaging, kept a 3-day food diary, and had a standardized assessment of fasting blood lipids. The lean group ate less cholesterol rich food than o/o although both groups ate equivalent servings of food per day. Voxelwise correlational analyses controlling for age, diabetes, and white matter hyperintensities, resulted in two significant clusters of negative associations between abnormal cholesterol profile and fractional anisotropy, located in the left and right prefrontal lobes. When the groups were split, the lean subjects showed no associations, whereas the o/o group expanded the association to three significant clusters, still in the frontal lobes. These findings suggest that cholesterol profile abnormalities may explain some of the reductions in white matter microstructural integrity that are reported in obesity.

Automatic removal of high-amplitude stimulus artefact from neuronal signal recorded in the subthalamic nucleus.

Over the last few years, deep brain stimulation (DBS) with targets such as the subthalamic nucleus or the pallidum were found to be beneficial in the treatment of Parkinson's disease and dystonia. The investigation of the mechanisms of action of DBS by recording concomitant neural activities in basal ganglia is hampered by the large stimulus artefacts (SA). Approaches to remove the SA with conventional filters, or other conventional digital methods, are not always effective due to the significant overlap between the spectral contents of the neuronal signal and the SA. Thus, such approaches may produce a significant residual SA or alter the neuronal signal dynamics by removing its frequency contents. In this work, we propose a method based on an on-line SA template extraction and on the Ensemble empirical mode decomposition (EEMD) to automatically detect and remove the dynamics of the SA without altering the embedded dynamics of the neuronal signal during stimulation. The results, based on real signals recorded in the subthalamic nucleus during Motor cortex stimulation (MCS) experiments, show that this technique, which may be applied on-line, effectively identifies, separates and removes the SA, and uncovers neuronal potentials superimposed on the artefact.

Obesity-mediated inflammation may damage the brain circuit that regulates food intake.

Adiposity is associated with chronic low-grade systemic inflammation and increased inflammation in the hypothalamus, a key structure in feeding behavior. It remains unknown whether inflammation impacts other brain structures that regulate feeding behavior. We studied 44 overweight/obese and 19 lean individuals with MRI and plasma fibrinogen levels (marker of inflammation). We performed MRI-based segmentations of the medial and lateral orbitofrontal cortex (OFC) and hippocampal volumes. Gray matter (GM) volumes were adjusted for head size variability. We conducted logistic and hierarchical regressions to assess the association between fibrinogen levels and brain volumetric data. Using diffusion tensor imaging (DTI), we created apparent diffusion coefficient (ADC) maps and conducted voxelwise correlational analyses. Fibrinogen concentrations were higher among the overweight/obese (t[61] = -2.33, P = 0.023). Lateral OFC associated together with fibrinogen correctly classified those with excess of weight (accuracy = 76.2%, sensitivity = 95.5%, and specificity=31.6%). The lateral OFC volumes of overweight/obese were negatively associated with fibrinogen (r = -0.37, P = 0.016) and after accounting for age, hypertension, waist/hip ratio and lipid and sugar levels, fibrinogen significantly explained an additional 9% of the variance in the lateral OFC volume (ß = -0.348, ΔR(2) = 0.093, ΔF P = 0.046). Among overweight/obese the associations between GM ADC and fibrinogen were significantly positive (P < 0.001) in the left and right amygdala and the right parietal region. Among lean individuals these associations were negative and located in the left prefrontal, the right parietal and the left occipital lobes. This is the first study to report that adiposity-related inflammation may reduce the integrity of some of the brain structures involved in reward and feeding behaviors.