A High-Dimensional Quantification of Mouse Defensive Behaviors Reveals Enhanced Diversity and Stimulus Specificity

Revisiting serotonin's role in spatial memory: A call for sensitive analytical approaches

The serotonergic system is involved in various psychiatric and neurological conditions, with serotonergic drugs often used in treatment. These conditions frequently affect spatial memory, which can serve as a model of declarative memory due to well-known cellular components and advanced methods that track neural activity and behavior with high temporal resolution. However, most findings on serotonin's effects on spatial learning and memory come from studies lacking refined analytical techniques and modern approaches needed to uncover the underlying neuronal mechanisms. This In Focus review critically investigates available studies to identify areas for further exploration. It finds that well-established behavioral models could yield more insights with modern tracking and data analysis approaches, while the cellular aspects of spatial memory remain underexplored. The review highlights the complex role of serotonin in spatial memory, which holds the potential for better understanding and treating memory-related disorders.

A pupillary contrast response in mice and humans: Neural mechanisms and visual functions

In the pupillary light response (PLR), increases in ambient light constrict the pupil to dampen increases in retinal illuminance. Here, we report that the pupillary reflex arc implements a second input-output transformation; it senses temporal contrast to enhance spatial contrast in the retinal image and increase visual acuity. The pupillary contrast response (PCoR) is driven by rod photoreceptors via type 6 bipolar cells and M1 ganglion cells. Temporal contrast is transformed into sustained pupil constriction by the M1's conversion of excitatory input into spike output. Computational modeling explains how the PCoR shapes retinal images. Pupil constriction improves acuity in gaze stabilization and predation in mice. Humans exhibit a PCoR with similar tuning properties to mice, which interacts with eye movements to optimize the statistics of the visual input for retinal encoding. Thus, we uncover a conserved component of active vision, its cell-type-specific pathway, computational mechanisms, and optical and behavioral significance.

Retinal origin of orientation but not direction selective maps in the superior colliculus

Neurons in the mouse superior colliculus ("colliculus") are arranged in ordered spatial maps. While orientation-selective (OS) neurons form a concentric map aligned to the center of vision, direction-selective (DS) neurons are arranged in patches with changing preferences across the visual field. It remains unclear whether these maps are a consequence of feedforward input from the retina or local computations in the colliculus. To determine whether these maps originate in the retina, we mapped the local and global distribution of OS and DS retinal ganglion cell axon boutons using in vivo two-photon calcium imaging. We found that OS boutons formed patches that matched the distribution of OS neurons within the colliculus. DS boutons displayed fewer regional specializations, better reflecting the organization of DS neurons in the retina. Both eyes convey similar orientation but different DS inputs to the colliculus, as shown in recordings from retinal explants. These data demonstrate that orientation and direction maps within the colliculus are independent, where orientation maps are likely inherited from the retina, but direction maps require additional computations.

Automated phenotyping of postoperative delirium-like behaviour in mice reveals the therapeutic efficacy of dexmedetomidine

Postoperative delirium (POD) is a complicated and harmful clinical syndrome. Traditional behaviour analysis mostly focuses on static parameters. However, animal behaviour is a bottom-up and hierarchical organizational structure composed of time-varying posture dynamics. Spontaneous and task-driven behaviours are used to conduct comprehensive profiling of behavioural data of various aspects of model animals. A machine-learning based method is used to assess the effect of dexmedetomidine. Fourteen statistically different spontaneous behaviours are used to distinguish the non-POD group from the POD group. In the task-driven behaviour, the non-POD group has greater deep versus shallow investigation preference, with no significant preference in the POD group. Hyperactive and hypoactive subtypes can be distinguished through pose evaluation. Dexmedetomidine at a dose of 25 μg kg-1 reduces the severity and incidence of POD. Here we propose a multi-scaled clustering analysis framework that includes pose, behaviour and action sequence evaluation. This may represent the hierarchical dynamics of delirium-like behaviours.

Behavioral decomposition reveals rich encoding structure employed across neocortex in rats

The cortical population code is pervaded by activity patterns evoked by movement, but it remains largely unknown how such signals relate to natural behavior or how they might support processing in sensory cortices where they have been observed. To address this we compared high-density neural recordings across four cortical regions (visual, auditory, somatosensory, motor) in relation to sensory modulation, posture, movement, and ethograms of freely foraging male rats. Momentary actions, such as rearing or turning, were represented ubiquitously and could be decoded from all sampled structures. However, more elementary and continuous features, such as pose and movement, followed region-specific organization, with neurons in visual and auditory cortices preferentially encoding mutually distinct head-orienting features in world-referenced coordinates, and somatosensory and motor cortices principally encoding the trunk and head in egocentric coordinates. The tuning properties of synaptically coupled cells also exhibited connection patterns suggestive of area-specific uses of pose and movement signals, particularly in visual and auditory regions. Together, our results indicate that ongoing behavior is encoded at multiple levels throughout the dorsal cortex, and that low-level features are differentially utilized by different regions to serve locally relevant computations.

Visual spatial location influences selection of instinctive behaviours in mouse

Visual stimuli can elicit instinctive approach and avoidance behaviours. In mouse, vision is known to be important for both avoidance of an overhead threat and approach toward a potential terrestrial prey. The stimuli used to characterize these behaviours, however, vary in both spatial location (overhead or near the ground plane) and visual feature (rapidly expanding disc or slowly moving disc). We therefore asked how mice responded to the same visual features presented in each location. We found that a looming black disc induced escape behaviour when presented overhead or to the side of the animal, but the escapes produced by side-looms were less vigorous and often preceded by freezing behaviour. Similarly, small moving discs induced freezing behaviour when presented overhead or to the side of the animal, but side sweeps also elicited approach behaviours, such that mice explored the area of the arena near where the stimulus had been presented. Our observations therefore show that mice combine cues to the location and features of visual stimuli when selecting among potential behaviours.

Three-dimensional unsupervised probabilistic pose reconstruction (3D-UPPER) for freely moving animals

A key step in understanding animal behaviour relies in the ability to quantify poses and movements. Methods to track body landmarks in 2D have made great progress over the last few years but accurate 3D reconstruction of freely moving animals still represents a challenge. To address this challenge here we develop the 3D-UPPER algorithm, which is fully automated, requires no a priori knowledge of the properties of the body and can also be applied to 2D data. We find that 3D-UPPER reduces by [Formula: see text] fold the error in 3D reconstruction of mouse body during freely moving behaviour compared with the traditional triangulation of 2D data. To achieve that, 3D-UPPER performs an unsupervised estimation of a Statistical Shape Model (SSM) and uses this model to constrain the viable 3D coordinates. We show, by using simulated data, that our SSM estimator is robust even in datasets containing up to 50% of poses with outliers and/or missing data. In simulated and real data SSM estimation converges rapidly, capturing behaviourally relevant changes in body shape associated with exploratory behaviours (e.g. with rearing and changes in body orientation). Altogether 3D-UPPER represents a simple tool to minimise errors in 3D reconstruction while capturing meaningful behavioural parameters.

Male and female mice display consistent lifelong ability to address potential life-threatening cues using different post-threat coping strategies

BACKGROUND

Sex differences ranging from physiological functions to pathological disorders are developmentally hard-wired in a broad range of animals, from invertebrates to humans. These differences ensure that animals can display appropriate behaviors under a variety of circumstances, such as aggression, hunting, sleep, mating, and parental care, which are often thought to be important in the acquisition of resources, including territory, food, and mates. Although there are reports of an absence of sexual dimorphism in the context of innate fear, the question of whether there is sexual dimorphism of innate defensive behavior is still an open question. Therefore, an in-depth investigation to determine whether there are sex differences in developmentally hard-wired innate defensive behaviors in life-threatening circumstances is warranted.

RESULTS

We found that innate defensive behavioral responses to potentially life-threatening stimuli between males and females were indistinguishable over their lifespan. However, by using 3 dimensional (3D)-motion learning framework analysis, we found that males and females showed different behavioral patterns after escaping to the refuge. Specifically, the defensive "freezing" occurred primarily in males, whereas females were more likely to return directly to exploration. Moreover, there were also no estrous phase differences in innate defensive behavioral responses after looming stimuli.

CONCLUSIONS

Our results demonstrate that visually-evoked innate fear behavior is highly conserved throughout the lifespan in both males and females, while specific post-threat coping strategies depend on sex. These findings indicate that innate fear behavior is essential to both sexes and as such, there are no evolutionary-driven sex differences in defensive ability.

Look-up and look-down neurons in the mouse visual thalamus during freely moving exploration

Visual information reaches cortex via the thalamic dorsal lateral geniculate nucleus (dLGN). dLGN activity is modulated by global sleep/wake states and arousal, indicating that it is not simply a passive relay station. However, its potential for more specific visuomotor integration is largely unexplored. We addressed this question by developing robust 3D video reconstruction of mouse head and body during spontaneous exploration paired with simultaneous neuronal recordings from dLGN. Unbiased evaluation of a wide range of postures and movements revealed a widespread coupling between neuronal activity and few behavioral parameters. In particular, postures associated with the animal looking up/down correlated with activity in >50% neurons, and the extent of this effect was comparable with that induced by full-body movements (typically locomotion). By contrast, thalamic activity was minimally correlated with other postures or movements (e.g., left/right head and body torsions). Importantly, up/down postures and full-body movements were largely independent and jointly coupled to neuronal activity. Thus, although most units were excited during full-body movements, some expressed highest firing when the animal was looking up ("look-up" neurons), whereas others expressed highest firing when the animal was looking down ("look-down" neurons). These results were observed in the dark, thus representing a genuine behavioral modulation, and were amplified in a lit arena. Our results demonstrate that the primary visual thalamus, beyond global modulations by sleep/awake states, is potentially involved in specific visuomotor integration and reveal two distinct couplings between up/down postures and neuronal activity.

Leaving flatland: Advances in 3D behavioral measurement

Animals move in three dimensions (3D). Thus, 3D measurement is necessary to report the true kinematics of animal movement. Existing 3D measurement techniques draw on specialized hardware, such as motion capture or depth cameras, as well as deep multi-view and monocular computer vision. Continued advances at the intersection of deep learning and computer vision will facilitate 3D tracking across more anatomical features, with less training data, in additional species, and within more natural, occlusive environments. 3D behavioral measurement enables unique applications in phenotyping, investigating the neural basis of behavior, and designing artificial agents capable of imitating animal behavior.

MouseVenue3D: A Markerless Three-Dimension Behavioral Tracking System for Matching Two-Photon Brain Imaging in Free-Moving Mice

Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional (3-D) space. However, there is no available three-dimensional behavior capture system that focuses on rodents. Here, we present MouseVenue3D, an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents. We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module. Then, we validated this process in behavior recognition tasks, and showed that 3-D behavioral data achieved higher accuracy than 2-D data. Subsequently, MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse. Finally, we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice. Our findings reveal that subtle, spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.

Quantifying the kinematic features of dexterous finger movements in nonhuman primates with markerless tracking

Research using nonhuman primate models for human disease frequently requires behavioral observational techniques to quantify functional outcomes. The ability to assess reaching and grasping patterns is of particular interest in clinical conditions that affect the motor system (e.g., spinal cord injury, SCI). Here we explored the use of DeepLabCut, an open-source deep learning toolset, in combination with a standard behavioral task (Brinkman Board) to quantify nonhuman primate performance in precision grasping. We examined one male rhesus macaque (Macaca mulatta) in the task which involved retrieving rewards from variously-oriented shallow wells. Simultaneous recordings were made using GoPro Hero7 Black cameras (resolution 1920 x 1080 at 120 fps) from two different angles (from the side and top of the hand motion). The task/device design necessitates use of the right hand to complete the task. Two neural networks (corresponding to the top and side view cameras) were trained using 400 manually annotated images, tracking 19 unique landmarks each. Based on previous reports, this produced sufficient tracking (Side: trained pixel error of 2.15, test pixel error of 11.25; Top: trained pixel error of 2.06, test pixel error of 30.31) so that landmarks could be tracked on the remaining frames. Landmarks included in the tracking were the spatial location of the knuckles and the fingernails of each digit, and three different behavioral measures were quantified for assessment of hand movement (finger separation, middle digit extension and preshaping distance). Together, our preliminary results suggest that this markerless approach is a possible method to examine specific kinematic features of dexterous function.Clinical Relevance- The methodology presented below allows for the markerless tracking of kinematic features of dexterous finger movement by non-human primates. This method could allow for direct comparisons between human patients and non-human primate models of clinical conditions (e.g., spinal cord injury). This would provide objective quantitative metrics and crucial information for assessing movement impairments across populations and the potential translation of treatments, interventions and their outcomes.

Measuring Behavior in the Home Cage: Study Design, Applications, Challenges, and Perspectives

The reproducibility crisis (or replication crisis) in biomedical research is a particularly existential and under-addressed issue in the field of behavioral neuroscience, where, in spite of efforts to standardize testing and assay protocols, several known and unknown sources of confounding environmental factors add to variance. Human interference is a major contributor to variability both within and across laboratories, as well as novelty-induced anxiety. Attempts to reduce human interference and to measure more "natural" behaviors in subjects has led to the development of automated home-cage monitoring systems. These systems enable prolonged and longitudinal recordings, and provide large continuous measures of spontaneous behavior that can be analyzed across multiple time scales. In this review, a diverse team of neuroscientists and product developers share their experiences using such an automated monitoring system that combines Noldus PhenoTyper® home-cages and the video-based tracking software, EthoVision® XT, to extract digital biomarkers of motor, emotional, social and cognitive behavior. After presenting our working definition of a "home-cage", we compare home-cage testing with more conventional out-of-cage tests (e.g., the open field) and outline the various advantages of the former, including opportunities for within-subject analyses and assessments of circadian and ultradian activity. Next, we address technical issues pertaining to the acquisition of behavioral data, such as the fine-tuning of the tracking software and the potential for integration with biotelemetry and optogenetics. Finally, we provide guidance on which behavioral measures to emphasize, how to filter, segment, and analyze behavior, and how to use analysis scripts. We summarize how the PhenoTyper has applications to study neuropharmacology as well as animal models of neurodegenerative and neuropsychiatric illness. Looking forward, we examine current challenges and the impact of new developments. Examples include the automated recognition of specific behaviors, unambiguous tracking of individuals in a social context, the development of more animal-centered measures of behavior and ways of dealing with large datasets. Together, we advocate that by embracing standardized home-cage monitoring platforms like the PhenoTyper, we are poised to directly assess issues pertaining to reproducibility, and more importantly, measure features of rodent behavior under more ethologically relevant scenarios.

Optogenetic fUSI for brain-wide mapping of neural activity mediating collicular-dependent behaviors

Neuronal cell types are arranged in brain-wide circuits that guide behavior. In mice, the superior colliculus innervates a set of targets that direct orienting and defensive actions. We combined functional ultrasound imaging (fUSI) with optogenetics to reveal the network of brain regions functionally activated by four collicular cell types. Stimulating each neuronal group triggered different behaviors and activated distinct sets of brain nuclei. This included regions not previously thought to mediate defensive behaviors, for example, the posterior paralaminar nuclei of the thalamus (PPnT), which we show to play a role in suppressing habituation. Neuronal recordings with Neuropixels probes show that (1) patterns of spiking activity and fUSI signals correlate well in space and (2) neurons in downstream nuclei preferentially respond to innately threatening visual stimuli. This work provides insight into the functional organization of the networks governing innate behaviors and demonstrates an experimental approach to explore the whole-brain neuronal activity downstream of targeted cell types.

Pupillary reflex and behavioral masking responses to light as functional measures of retinal degeneration in mice

BACKGROUND

Pre-clinical testing of retinal pathology and treatment efficacy depends on reliable and valid measures of retinal function. The electroretinogram (ERG) and tests of visual acuity are the ideal standard, but can be unmeasurable while useful vision remains. Non-image-forming responses to light such as the pupillary light reflex (PLR) are attractive surrogates. However, it is not clear how accurately such responses reflect changes in visual capability in specific disease models. The purpose of this study was to test whether measures of non-visual responses to light correlate with previously determined visual function in two photoreceptor degenerations.

METHODS

The sensitivity of masking behavior (light induced changes in running wheel activity) and the PLR were measured in 3-month-old wild-type mice (WT) with intact inner retinal circuitry, Pde6b-rd1/rd1 mice (rd1) with early and rapid loss of rods and cones, and Prph2-Rd2/Rd2 mice (Rd2) with a slower progressive loss of rods and cones.

RESULTS

In rd1 mice, negative masking had increased sensitivity, positive masking was absent, and the sensitivity of the PLR was severely reduced. In Rd2 mice, positive masking identified useful vision at higher light levels, but there was a limited decrease in the irradiance sensitivity of negative masking and the PLR, and the amplitude of change for both underestimated the reduction in irradiance sensitivity of image-forming vision.

CONCLUSIONS

Together these data show that in a given disease, two responses to light can be affected in opposite ways, and that for a given response to light, the change in the response does not accurately represent the degree of pathology. However, the extent of the deficit in the PLR means that even a limited rescue of rod/cone function might be measured by increased PLR amplitude. In addition, positive masking has the potential to measure effective treatment in both models by restoring responses or shifting thresholds to lower irradiances.

Quantifying behavior to understand the brain

Over the past years, numerous methods have emerged to automate the quantification of animal behavior at a resolution not previously imaginable. This has opened up a new field of computational ethology and will, in the near future, make it possible to quantify in near completeness what an animal is doing as it navigates its environment. The importance of improving the techniques with which we characterize behavior is reflected in the emerging recognition that understanding behavior is an essential (or even prerequisite) step to pursuing neuroscience questions. The use of these methods, however, is not limited to studying behavior in the wild or in strictly ethological settings. Modern tools for behavioral quantification can be applied to the full gamut of approaches that have historically been used to link brain to behavior, from psychophysics to cognitive tasks, augmenting those measurements with rich descriptions of how animals navigate those tasks. Here we review recent technical advances in quantifying behavior, particularly in methods for tracking animal motion and characterizing the structure of those dynamics. We discuss open challenges that remain for behavioral quantification and highlight promising future directions, with a strong emphasis on emerging approaches in deep learning, the core technology that has enabled the markedly rapid pace of progress of this field. We then discuss how quantitative descriptions of behavior can be leveraged to connect brain activity with animal movements, with the ultimate goal of resolving the relationship between neural circuits, cognitive processes and behavior.