Hidden Markov model analysis of maternal behavior patterns in inbred and reciprocal hybrid mice

Relationship between physical activity and central sensitization in chronic low back pain: Insights from machine learning

BACKGROUND AND OBJECTIVES

Chronic low back pain (CLBP) is a leading cause of disability. The management guidelines for the management of CLBP often recommend optimizing physical activity (PA). Among a subsample of patients with CLBP, central sensitization (CS) is present. However, knowledge about the association between PA intensity patterns, CLBP, and CS is limited. The objective PA computed by conventional approaches (e.g. cut-points) may not be sensitive enough to explore this association. This study aimed to investigate PA intensity patterns in patients with CLBP and low or high CS (CLBP-, CLBP+, respectively) by using advanced unsupervised machine learning approach, Hidden semi-Markov model (HSMM).

METHODS

Forty-two patients were included (23 CLBP-, 19 CLBP+). CS-related symptoms (e.g. fatigue, sensitivity to light, psychological features) were assessed by a CS Inventory. Patients wore a standard 3D-accelerometer for one week and PA was recorded. The conventional cut-points approach was used to compute the time accumulation and distribution of PA intensity levels in a day. For the two groups, two HSMMs were developed to measure the temporal organization of and transition between hidden states (PA intensity levels), based on the accelerometer vector magnitude.

RESULTS

Based on the conventional cut-points approach, no significant differences were found between CLBP- and CLBP+ groups (p = 0.87). In contrast, HSMMs revealed significant differences between the two groups. For the 5 identified hidden states (rest, sedentary, light PA, light locomotion, and moderate-vigorous PA), the CLBP- group had a higher transition probability from rest, light PA, and moderate-vigorous PA states to the sedentary state (p < 0.001). In addition, the CBLP- group had a significantly shorter bout duration of the sedentary state (p < 0.001). The CLBP+ group exhibited longer durations of active (p < 0.001) and inactive states (p = 0.037) and had higher transition probabilities between active states (p < 0.001).

CONCLUSIONS

HSMM discloses the temporal organization and transitions of PA intensity levels based on accelerometer data, yielding valuable and detailed clinical information. The results imply that patients with CLBP- and CLBP+ have different PA intensity patterns. CLBP+ patients may adopt the distress-endurance response pattern with a prolonged bout duration of activity engagement.

Sex differences in appetitive and reactive aggression

Aggression is an evolutionarily conserved, adaptive component of social behavior. Studies in male mice illustrate that aggression is influenced by numerous factors including the degree to which an individual finds aggression rewarding and will work for access to attack and subordinate mice. While such studies have expanded our understanding of the molecular and circuit mechanisms of male aggression very little is known about female aggression, within these established contexts. Here we use an ethologically relevant model of male vs. female aggression by pair housing adult male and female outbred CFW mice with opposite sex cage mates. We assess reactive (defensive) aggression in the resident intruder (RI) test and appetitive (rewarding) aggression in the aggression conditioned place preference (CPP) and operant self-administration (SA) tests. Our results show dramatic sex differences in both qualitative and quantitative aspects of reactive vs. appetitive aggression. Males exhibit more wrestling and less investigative behavior during RI, find aggression rewarding, and will work for access to a subordinate to attack. Females exhibit more bites, alternate between aggressive behaviors and investigative behaviors more readily during RI, however, they do not find aggression to be rewarding or reinforcing. These results establish sex differences in aggression in mice, providing an important resource for the field to better understand the circuit and molecular mechanisms of aggression in both sexes.

Parenting as a model for behavioural switches

Adaptability to ethologically relevant cues is fundamental for social interactions. As such, reproductive success relies on the ability of an animal to transition between parental and nonparental states. Though driven by genetically pre-programmed circuits, these instinctive repertoires are reshaped by internal state and experience, making parenting a robust model for the study of behavioural flexibility. As a functional wiring diagram for parenting emerges in mice, we are well placed to identify neural substrates and posit associated mechanisms underlying caregiving transitions. In this review, we discuss the importance of comprehensively characterising behaviour, highlight the role of shared circuit elements for behavioural malleability and explore plastic mechanisms that might guide switches between parental and nonparental repertoires.

Prospects for the Analysis and Reduction of Damaging Behaviour in Group-Housed Livestock, With Application to Pig Breeding

Innovations in the breeding and management of pigs are needed to improve the performance and welfare of animals raised in social groups, and in particular to minimise biting and damage to group mates. Depending on the context, social interactions between pigs can be frequent or infrequent, aggressive, or non-aggressive. Injuries or emotional distress may follow. The behaviours leading to damage to conspecifics include progeny savaging, tail, ear or vulva biting, and excessive aggression. In combination with changes in husbandry practices designed to improve living conditions, refined methods of genetic selection may be a solution reducing these behaviours. Knowledge gaps relating to lack of data and limits in statistical analyses have been identified. The originality of this paper lies in its proposal of several statistical methods for common use in analysing and predicting unwanted behaviours, and for genetic use in the breeding context. We focus on models of interaction reflecting the identity and behaviour of group mates which can be applied directly to damaging traits, social network analysis to define new and more integrative traits, and capture-recapture analysis to replace missing data by estimating the probability of behaviours. We provide the rationale for each method and suggest they should be combined for a more accurate estimation of the variation underlying damaging behaviours.

Rage Against the Machine: Advancing the study of aggression ethology via machine learning

RATIONALE

Aggression, comorbid with neuropsychiatric disorders, exhibits with diverse clinical presentations and places a significant burden on patients, caregivers, and society. This diversity is observed because aggression is a complex behavior that can be ethologically demarcated as either appetitive (rewarding) or reactive (defensive), each with its own behavioral characteristics, functionality, and neural basis that may transition from adaptive to maladaptive depending on genetic and environmental factors. There has been a recent surge in the development of preclinical animal models for studying appetitive aggression-related behaviors and identifying the neural mechanisms guiding their progression and expression. However, adoption of these procedures is often impeded by the arduous task of manually scoring complex social interactions. Manual observations are generally susceptible to observer drift, long analysis times, and poor inter-rater reliability, and are further incompatible with the sampling frequencies required of modern neuroscience methods.

OBJECTIVES

In this review, we discuss recent advances in the preclinical study of appetitive aggression in mice, paired with our perspective on the potential for machine learning techniques in producing automated, robust scoring of aggressive social behavior. We discuss critical considerations for implementing valid computer classifications within behavioral pharmacological studies.

KEY RESULTS

Open-source automated classification platforms can match or exceed the performance of human observers while removing the confounds of observer drift, bias, and inter-rater reliability. Furthermore, unsupervised approaches can identify previously uncharacterized aggression-related behavioral repertoires in model species.

DISCUSSION AND CONCLUSIONS

Advances in open-source computational approaches hold promise for overcoming current manual annotation caveats while also introducing and generalizing computational neuroethology to the greater behavioral neuroscience community. We propose that currently available open-source approaches are sufficient for overcoming the main limitations preventing wide adoption of machine learning within the context of preclinical aggression behavioral research.

Effects of sleep restriction during pregnancy on postpartum maternal behavior in female rats

Preclinical studies evaluating the effects of gestational sleep restriction on maternal behavior are needed in order to provide information on the background mechanisms underlying this relationship. In this study, 32 female 90 days-old Wistar-Hannover rats were distributed in two groups: Control group (CTRL - n = 13), not subjected to any manipulation during pregnancy; and sleep restriction group (SR - n = 19) - subjected to sleep restriction during the whole pregnancy (21 days). Maternal behavioral analysis was conducted from postpartum day 1 (PPD1) to PPD7, based on observational ethograms. On PPD11 the animals were subjected to the grooming analysis algorithm, followed by the elevated plus maze. Results from an ethogram-based analysis indicated a decrease in self-grooming among sleep-deprived rats (denoting reduced anxiety-like behavior), but no significant differences were found in maternal behavior (except for a slight increase in high arched-back nursing). Controlled analysis detected an impairment in high-arched back nursing in sleep-deprived animals. The grooming microstructure analysis showed an increased frequency of incorrect transitions among sleep restricted animals, indicating increased anxiety-like behavior. No significant differences were observed in the elevated-plus maze. In conclusion, sleep-restricted pregnant rats display an equivalent or slightly increased maternal behavior during the postpartum period, when compared to control animals.

Pergola: Boosting Visualization and Analysis of Longitudinal Data by Unlocking Genomic Analysis Tools

The growing appetite of behavioral neuroscience for automated data production is prompting the need for new computational standards allowing improved interoperability, reproducibility, and shareability. We show here how these issues can be solved by repurposing existing genomic formats whose structure perfectly supports the handling of time series. This allows existing genomic analysis and visualization tools to be deployed onto behavioral data. As a proof of principle, we implemented the conversion procedure in Pergola, an open source software, and used genomics tools to reproduce results obtained in mouse, fly, and worm. We also show how common genomics techniques such as principal component analysis, hidden Markov modeling, and volcano plots can be deployed on the reformatted behavioral data. These analyses are easy to share because they depend on the scripting of public software. They are also easy to reproduce thanks to their integration within Nextflow, a workflow manager using containerized software.

Early-Life Stress Paradigm Transiently Alters Maternal Behavior, Dam-Pup Interactions, and Offspring Vocalizations in Mice

Animal models can help elucidate the mechanisms through which early-life stress (ELS) has pathophysiological effects on the developing brain. One model that has been developed for rodents consists of limiting the amount of bedding and nesting material during the first postnatal weeks of pup life. This ELS environment has been shown to induce "abusive" behaviors by rat dams towards pups, while mouse dams have been hypothesized to display "fragmented care". Here, as part of an ongoing study of gene-environment interactions that impact brain development, we analyzed long observation periods of wild-type C57Bl/6J dams caring for wild-type and Met heterozygous pups. Met encodes for the MET receptor tyrosine kinase, which is involved in cortical and hippocampal synaptogenesis. Dams with limited resources from postnatal day (P)2 to P9 preserved regular long on-nest periods, and instead increased the number of discrete dam-pup interactions during regular off-nest periods. Immediately after dams entered the nest during off-nest periods in this ELS environment, pups responded to these qualitatively different interactions with an increased number of ultrasonic vocalizations (USV) and audible vocalizations (AV), communication signals that have been associated with aversive and painful stimuli. After returning to control conditions, nest entry behaviors normalized, and dams did not show altered anxiety-like or contextual fear learning behaviors after pup weaning. Furthermore, female mice that had undergone ELS as pups did not show atypical nest entry behaviors in control conditions in adulthood, suggesting that these specific maternal behaviors are not learned during the ELS period. The results suggest that atypical responses of both mother and pups during exposure to this ELS environment likely contribute to long-term negative outcomes in mice, and that these responses more closely resemble the effects of limited bedding on rat dams and pups than was previously suggested. Discerning how different early-life stressors mediate changes in maternal-pup interactions can help elucidate the mechanisms of ELS on brain development and behavior.

Maternal behavior in basic science: translational research and clinical applicability

Clinical aspects of the mother-infant relationship and related issues are well studied and very relevant to medical practice. Nevertheless, some approaches in this context cannot plausibly be investigated in humans due to their ethical implications and to the potential harm to the mother's and child's health. Studies on maternal behavior in animals have evident importance to some clinical fields, such as psychiatry and psychology, particularly considering topics, including mother-infant relationship, postpartum depression, cognitive and behavioral development of children, and associated issues. Hence, this theoretical article draws attention to the clinical applicability of studies about maternal behavior in animals to psychobiology, taking into account a translational perspective.

The geometry of locomotive behavioral states in C. elegans

We develop a new hidden Markov model-based method to analyze C elegans locomotive behavior and use this method to quantitatively characterize behavioral states. In agreement with previous work, we find states corresponding to roaming, dwelling, and quiescence. However, we also find evidence for a continuum of intermediate states. We suggest that roaming, dwelling, and quiescence may best be thought of as extremes which, mixed in any proportion, define the locomotive repertoire of C elegans foraging and feeding behavior.