Correction: High-order social interactions in groups of mice

Long-term monitoring of huddling behavior in mice using online image processing

Many animal species, including mice, form societies of numerous individuals for survival. Understanding the interactions between individual animals is crucial for elucidating group behavior. One such behavior in mice is huddling, yet its analysis has been limited. In this study, we propose a cost-effective method for monitoring long-term huddling behavior in mice using online image processing with OpenCV. This method treats a single mouse or a group of mice as a cluster of pixels (a 'blob') in video images, extracting and saving only essential information such as areas, coordinates, and orientations. This approach reduces data storage needs to 1/200000th of what would be required if the video were recorded in its compressed form, thereby enabling long-term behavioral analysis. To validate the performance of our algorithm, ~2000 video frames were randomly chosen. We manually counted the number of clusters of mice in these frames and compared them with the number of blobs automatically detected by the algorithm. The results indicated a high level of consistency, exceeding 90% across the selected video frames. Initial observations of both male and female groups suggested some variations in huddling behavior among male and female groups; however, these results should be interpreted cautiously due to a small sample. Group behavior is known to be disrupted in several neuropsychiatric disorders, such as autism. Various mouse models of these disorders have been proposed. Our measurement system, when combined with drug or genetic modification screening, could provide a valuable tool for high-throughput analyses of huddling behavior.

EthoLoop: automated closed-loop neuroethology in naturalistic environments

Accurate tracking and analysis of animal behavior is crucial for modern systems neuroscience. However, following freely moving animals in naturalistic, three-dimensional (3D) or nocturnal environments remains a major challenge. Here, we present EthoLoop, a framework for studying the neuroethology of freely roaming animals. Combining real-time optical tracking and behavioral analysis with remote-controlled stimulus-reward boxes, this system allows direct interactions with animals in their habitat. EthoLoop continuously provides close-up views of the tracked individuals and thus allows high-resolution behavioral analysis using deep-learning methods. The behaviors detected on the fly can be automatically reinforced either by classical conditioning or by optogenetic stimulation via wirelessly controlled portable devices. Finally, by combining 3D tracking with wireless neurophysiology we demonstrate the existence of place-cell-like activity in the hippocampus of freely moving primates. Taken together, we show that the EthoLoop framework enables interactive, well-controlled and reproducible neuroethological studies in large-field naturalistic settings.

Opposing effects of antibiotics and germ-free status on neuropeptide systems involved in social behaviour and pain regulation

Background

Recent research has revealed that the community of microorganisms inhabiting the gut affects brain development, function and behaviour. In particular, disruption of the gut microbiome during critical developmental windows can have lasting effects on host physiology. Both antibiotic exposure and germ-free conditions impact the central nervous system and can alter multiple aspects of behaviour. Social impairments are typically displayed by antibiotic-treated and germ-free animals, yet there is a lack of understanding of the underlying neurobiological changes. Since the μ-opioid, oxytocin and vasopressin systems are key modulators of mammalian social behaviour, here we investigate the effect of experimentally manipulating the gut microbiome on the expression of these pathways.

Results

We show that social neuropeptide signalling is disrupted in germ-free and antibiotic-treated mice, which may contribute to the behavioural deficits observed in these animal models. The most notable finding is the reduction in neuroreceptor gene expression in the frontal cortex of mice administered an antibiotic cocktail post-weaning. Additionally, the changes observed in germ-free mice were generally in the opposite direction to the antibiotic-treated mice.

Conclusions

Antibiotic treatment when young can impact brain signalling pathways underpinning social behaviour and pain regulation. Since antibiotic administration is common in childhood and adolescence, our findings highlight the potential adverse effects that antibiotic exposure during these key neurodevelopmental periods may have on the human brain, including the possible increased risk of neuropsychiatric conditions later in life. In addition, since antibiotics are often considered a more amenable alternative to germ-free conditions, our contrasting results for these two treatments suggest that they should be viewed as distinct models.

Quantifying the social symptoms of autism using motion capture

Autism Spectrum Disorder (ASD) is a remarkably heterogeneous condition where individuals exhibit a variety of symptoms at different levels of severity. Quantifying the severity of specific symptoms is difficult, because it either requires long assessments or observations of the ASD individual, or reliance on care-giver questionnaires, which can be subjective. Here we present a new technique for objectively quantifying the severity of several core social ASD symptoms using a motion capture system installed in a clinical exam room. We present several measures of child-clinician interaction, which include the distance between them, the proportion of time that the child approached or avoided the clinician, and the direction that the child faced in relation to the clinician. Together, these measures explained ~30% of the variance in ADOS scores, when using only ~5 minute segments of “free play” from the recorded ADOS assessments. These results demonstrate the utility of motion capture for aiding researchers and clinicians in the assessment of ASD social symptoms. Further development of this technology and appropriate motion capture measures for use in kindergartens and at home is likely to yield valuable information that will aid in quantifying the initial severity of core ASD symptoms and their change over time.

Using sensory discrimination in a foraging-style task to evaluate human upper-limb sensorimotor performance

Object stiffness discrimination is fundamental to shaping the way we interact with our environment. Investigating the sensorimotor mechanisms underpinning stiffness discrimination may help further our understanding of healthy and sensory-impaired upper limb function. We developed a metric that leverages sensory discrimination techniques and a foraging-based analysis to characterize participant accuracy and discrimination processes of sensorimotor control. Our metric required searching and discriminating two variants of test-object: rubber blocks and spring cells, which emphasized cutaneous-force and proprioceptive feedback, respectively. We measured the number of test-objects handled, selection accuracy, and foraging duration. These values were used to derive six indicators of performance. We observed higher discrimination accuracies, with quicker search and handling durations, for blocks compared to spring cells. Correlative analyses of accuracy, error rates, and foraging times suggested that the block and spring variants were, in fact, unique sensory tasks. These results provide evidence that our metric is sensitive to the contributions of sensory feedback, motor control, and task performance strategy, and will likely be effective in further characterizing the impact of sensory feedback on motor control in healthy and sensory-impaired populations.