From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data.

Effects of hypoxic compound exercise to promote HIF-1α expression on cardiac pumping function, sleep activity behavior, and exercise capacity in Drosophila.

Alteration of HIF-1α expression levels under hypoxic conditions affects the sequence of its downstream target genes thereby producing different effects. In order to investigate whether the effect of hypoxic compound exercise (HE) on HIF-1α expression alters cardiac pumping function, myocardial structure, and exercise capacity, we developed a suitable model of hypoxic exercise using Drosophila, a model organism, and additionally investigated the effect of hypoxic compound exercise on nocturnal sleep and activity behavior. The results showed that hypoxic compound exercise at 6% oxygen concentration for five consecutive days, lasting 1 h per day, significantly improved the cardiac stress resistance of Drosophila. The hypoxic complex exercise promoted the whole-body HIF-1α expression in Drosophila, and improved the jumping ability, climbing ability, moving speed, and moving distance. The expression of HIF-1α in the heart was increased after hypoxic exercise, which made a closer arrangement of myofilaments, an increase in the diameter of cardiac tubules, and an increase in the pumping function of the heart. The hypoxic compound exercise improved the sleep quality of Drosophila by increasing its nocturnal sleep time, the number of deep sleeps, and decreasing its nocturnal awakenings and activities. Therefore, we conclude that hypoxic compound exercise promoted the expression of HIF-1α to enhance the exercise capacity and heart pumping function of Drosophila, and improved the quality of sleep.

Computational Analysis of Behavior.

In this review, we discuss the emerging field of computational behavioral analysis-the use of modern methods from computer science and engineering to quantitatively measure animal behavior. We discuss aspects of experiment design important to both obtaining biologically relevant behavioral data and enabling the use of machine vision and learning techniques for automation. These two goals are often in conflict. Restraining or restricting the environment of the animal can simplify automatic behavior quantification, but it can also degrade the quality or alter important aspects of behavior. To enable biologists to design experiments to obtain better behavioral measurements, and computer scientists to pinpoint fruitful directions for algorithm improvement, we review known effects of artificial manipulation of the animal on behavior. We also review machine vision and learning techniques for tracking, feature extraction, automated behavior classification, and automated behavior discovery, the assumptions they make, and the types of data they work best with.

Longitudinal Clusters of Long-Term Trajectories in Patients with Early-Onset Chronic Depression: 2 Years of Naturalistic Follow-Up after Extensive Psychological Treatment.

INTRODUCTION: In clinical trials, mostly group-level treatment effects of repeated cross-sectional measures are analyzed. However, substantial heterogeneity regarding individual symptom profiles and the variability of treatment effects are often neglected, especially over the long-term course. To provide effective personalized treatments, investigations of these characteristics are urgently needed. METHODS: Depression severity ratings over 104 weeks of follow-up after year-long treatment with the Cognitive Behavioral Analysis System of Psychotherapy (CBASP) or Supportive Psychotherapy (SP) were analyzed. Longitudinal cluster analysis and multinomial logistic regression analysis were conducted to investigate intraindividual trajectories from one of the largest psychotherapy trials in early-onset chronic depression. RESULTS: Two-year post-study-treatment trajectories of N = 188 patients with early-onset chronic depression were grouped into four prototypical clusters. Overall, 16.0% of patients remitted (cluster 1) and most of them did not receive any treatment during the 2-year follow-up. However, 84.0% of patients continued to experience subthreshold (37.2% cluster 2) or major depressive symptoms (46.8% clusters 3-4) and spent on average more than half of the follow-up in pharmacological and psychological treatment. Hierarchical regression analysis indicated that previous study treatment with CBASP or SP did not significantly predict cluster allocation, while baseline variables accounted for a large proportion of explained variance (R2 N = 0.64). CONCLUSION: While some patients experienced stable remission over 2 years of follow-up, the majority of patients experienced subthreshold or major depressive symptoms regardless of former study treatment with CBASP or SP. This calls for a long-term perspective implementing staging and innovative treatment approaches such as the sequential model or modular psychotherapy.

Dynamic changes in seizure state and anxiety-like behaviors during pentylenetetrazole kindling in rats.

INTRODUCTION: Excessive anxiety is a mental disorder, and its treatment involves the use of benzodiazepines, a class of drugs that enhance the effects of the neurotransmitter gamma-aminobutyric acid (GABA) at the GABAA receptor. Anxiety disorders are frequent comorbidities in patients with epilepsy, and it has been speculated that anxiety disorders and epileptic seizures share common neurobiological mechanisms. However, conflicting results regarding anxiolytic and anxiogenic effects have been reported in animal models of epilepsy induced by pentylenetetrazole (PTZ) injections, and the causes of this discrepancy are unknown. We hypothesized that anxiety-like behaviors would change dynamically according to the changes in epilepsy susceptibility that occur during the PTZ kindling process. Therefore, we attempted to change anxiety-like behaviors bidirectionally depending on the number of PTZ injections. METHODS: Adult male rats were injected with PTZ 20 times every other day, and stages of seizure onset were classified according to the Racine staging system. Anxiety-like behaviors were measured after 10 and 20 injections. The control group was injected with an equal volume of saline solution. Anxiety-like behaviors were investigated using the open-field, light/dark transition, elevated plus maze, and social interaction tests. RESULTS: Bimodal changes in seizure stage were observed in response to PTZ kindling. The increase in the seizure stage was transiently suppressed after 10 injections, and this decrease in epileptic sensitivity disappeared after 20 injections. However, none of the rats reached a fully kindled state after 20 PTZ injections. After 10 PTZ injections, anxiety-like behaviors decreased compared with those of the control group in the open field, light/dark transition, and elevated plus-maze tests. The anxiolytic effects correlated with the seizure stage in individual rats. After 20 PTZ injections, anxiety-like behaviors returned to control levels. CONCLUSION: PTZ kindling induced bimodal changes in the seizure stage. Anxiety-like behaviors decreased with transient decrease in epileptic sensitivity and returned to control levels with the disappearance of these states. These findings suggest a common neurobiological mechanism underlying anxiety disorders and epileptic seizures. In addition, the discrepancy in the previous studies, in which anxiety levels increase or decrease in PTZ-kindled animals, may be due to examination at different phases of the kindling process.

Pharmacological Investigation of Hypoalbuminemia on the Prolonged and Potentiated Action of Midazolam in Rats.

Midazolam (MDZ) is clinically used for its sedative and anticonvulsant properties. However, its prolonged or potentiated effects are sometimes concerning. The main binding protein of MDZ is albumin, and reduced serum albumin levels could lead to MDZ accumulation, thereby potentiating or prolonging its effects. Previous investigations have not thoroughly examined these phenomena from a behavioral pharmacology standpoint. Consequently, this study aimed to evaluate both the prolonged and potentiated effects of MDZ, as well as the effects of serum albumin levels on the action of MDZ in low-albumin rats. Male Wistar rats were classified into control (20% protein diet), low-protein (5% protein), and non-protein groups (0% protein diet) and were fed the protein-controlled diets for 30 d to obtain low-albumin rats. The locomotor activity and muscle relaxant effects of MDZ were evaluated using the rotarod, grip strength, and open-field tests conducted 10, 60, and 120 min after MDZ administration. Serum albumin levels decreased significantly in the low-protein and non-protein diet groups compared with those in the control group. Compared with the control rats, low-albumin rats demonstrated a significantly shorter time to fall, decreased muscle strength, and a significant decrease in the distance traveled after MDZ administration in the rotarod, grip strength, and open-field tests, respectively. Decreased serum albumin levels potentiated and prolonged the effects of MDZ. Hence, serum albumin level is a critical parameter associated with MDZ administration, which should be monitored, and any side effects related to decreased albumin levels should be investigated.

Symptom-specific improvement across therapies and their putative mediators: A mediation network intervention analysis.

OBJECTIVE: We evaluated differential treatment effects on specific symptoms and their mediators for Cognitive Behavioral Analysis System of Psychotherapy (CBASP) and Supportive Psychotherapy (SP) in persistently depressed patients. METHOD: We conducted a Bayesian mediation network intervention analysis with data from a randomized controlled trial comparing CBASP and SP. Three networks were calculated to investigate (1) differential treatment effects on specific symptoms, (2) differential treatment effects on the potential mediators interpersonal problems and social functioning, and (3) associations between change in symptoms and change in the potential mediators. RESULTS: First, we found no evidence that CBASP more strongly improves most depressive symptoms specifically, except minimal evidence of symptom-specific effects on sleeping problems and self-esteem. Second, no and minimal evidence for differential treatment effects on interpersonal problems and social functioning was shown, respectively. Third, interpersonal problems and social functioning were strongly related to depressive symptoms. CONCLUSION: While CBASP showed superior treatment effects for overall symptom severity, this treatment might not be superior in improving specific symptoms and the potential mediators interpersonal problems and social functioning. Still, interpersonal problems and social functioning seem to play an important role for depression symptoms. Future research needs to further investigate potential working mechanisms of CBASP.Trial registration: ClinicalTrials.gov identifier: NCT00970437.

Behavioral and transcriptomic analyses of mecp2 function in zebrafish.

Rett syndrome (RTT), a human neurodevelopmental disorder characterized by severe cognitive and motor impairments, is caused by dysfunction of the conserved transcriptional regulator Methyl-CpG-binding protein 2 (MECP2). Genetic analyses in mouse Mecp2 mutants, which exhibit key features of human RTT, have been essential for deciphering the mechanisms of MeCP2 function; nonetheless, our understanding of these complex mechanisms is incomplete. Zebrafish mecp2 mutants exhibit mild behavioral deficits but have not been analyzed in depth. Here, we combine transcriptomic and behavioral assays to assess baseline and stimulus-evoked motor responses and sensory filtering in zebrafish mecp2 mutants from 5 to 7 days post-fertilization (dpf). We show that zebrafish mecp2 function is required for normal thigmotaxis but is dispensable for gross movement, acoustic startle response, and sensory filtering (habituation and sensorimotor gating), and reveal a previously unknown role for mecp2 in behavioral responses to visual stimuli. RNA-seq analysis identified a large gene set that requires mecp2 function for correct transcription at 4 dpf, and pathway analysis revealed several pathways that require MeCP2 function in both zebrafish and mammals. These findings show that MeCP2's function as a transcriptional regulator is conserved across vertebrates and supports using zebrafish to complement mouse modeling in elucidating these conserved mechanisms.

TrackUSF, a novel tool for automated ultrasonic vocalization analysis, reveals modified calls in a rat model of autism.

BACKGROUND: Various mammalian species emit ultrasonic vocalizations (USVs), which reflect their emotional state and mediate social interactions. USVs are usually analyzed by manual or semi-automated methodologies that categorize discrete USVs according to their structure in the frequency-time domains. This laborious analysis hinders the effective use of USVs as a readout for high-throughput analysis of behavioral changes in animals. RESULTS: Here we present a novel automated open-source tool that utilizes a different approach towards USV analysis, termed TrackUSF. To validate TrackUSF, we analyzed calls from different animal species, namely mice, rats, and bats, recorded in various settings and compared the results with a manual analysis by a trained observer. We found that TrackUSF detected the majority of USVs, with less than 1% of false-positive detections. We then employed TrackUSF to analyze social vocalizations in Shank3-deficient rats, a rat model of autism, and revealed that these vocalizations exhibit a spectrum of deviations from appetitive calls towards aversive calls. CONCLUSIONS: TrackUSF is a simple and easy-to-use system that may be used for a high-throughput comparison of ultrasonic vocalizations between groups of animals of any kind in any setting, with no prior assumptions.

Evaluation of a simple activity measurement method in rats.

[Purpose] Behavioral analysis is widely used in animal research. However, such analysis requires specialized equipment and can be difficult to perform. Therefore, this study aimed to explore and validate a simple behavioral analysis method. [Participants and Methods] For behavioral assessments, Wistar rats were placed in a rearing cage and videotaped from two directions: overhead and side view. The filmed videos were analyzed using ImageJ software to calculate the distance traveled and activity and inactivity times of the rats. Intraclass correlation coefficients 1 and 2 were calculated to examine the reliability of the behavioral analysis method. [Results] Intraclass correlation coefficients 1 and 2 for distance traveled and activity and inactivity times determined using the behavioral analysis method showed high reliability. [Conclusion] The behavioral analysis method validated in this study used inexpensive and easily accessible equipment and devices. The results show high correlation coefficients for the measurement of distance traveled and activity time performed by experimental animals, demonstrating the reliability of this simple method.

A Novel Redundant Validation IoT System for Affective Learning Based on Facial Expressions and Biological Signals.

Teaching is an activity that requires understanding the class's reaction to evaluate the teaching methodology effectiveness. This operation can be easy to achieve in small classrooms, while it may be challenging to do in classes of 50 or more students. This paper proposes a novel Internet of Things (IoT) system to aid teachers in their work based on the redundant use of non-invasive techniques such as facial expression recognition and physiological data analysis. Facial expression recognition is performed using a Convolutional Neural Network (CNN), while physiological data are obtained via Photoplethysmography (PPG). By recurring to Russel's model, we grouped the most important Ekman's facial expressions recognized by CNN into active and passive. Then, operations such as thresholding and windowing were performed to make it possible to compare and analyze the results from both sources. Using a window size of 100 samples, both sources have detected a level of attention of about 55.5% for the in-presence lectures tests. By comparing results coming from in-presence and pre-recorded remote lectures, it is possible to note that, thanks to validation with physiological data, facial expressions alone seem useful in determining students' level of attention for in-presence lectures.

Designing Man's New Best Friend: Enhancing Human-Robot Dog Interaction through Dog-Like Framing and Appearance.

To understand how to improve interactions with dog-like robots, we evaluated the importance of "dog-like" framing and physical appearance on interaction, hypothesizing multiple interactive benefits of each. We assessed whether framing Aibo as a puppy (i.e., in need of development) versus simply a robot would result in more positive responses and interactions. We also predicted that adding fur to Aibo would make it appear more dog-like, likable, and interactive. Twenty-nine participants engaged with Aibo in a 2 × 2 (framing × appearance) design by issuing commands to the robot. Aibo and participant behaviors were monitored per second, and evaluated via an analysis of commands issued, an analysis of command blocks (i.e., chains of commands), and using a T-pattern analysis of participant behavior. Participants were more likely to issue the "Come Here" command than other types of commands. When framed as a puppy, participants used Aibo's dog name more often, praised it more, and exhibited more unique, interactive, and complex behavior with Aibo. Participants exhibited the most smiling and laughing behaviors with Aibo framed as a puppy without fur. Across conditions, after interacting with Aibo, participants felt Aibo was more trustworthy, intelligent, warm, and connected than at their initial meeting. This study shows the benefits of introducing a socially robotic agent with a particular frame and importance on realism (i.e., introducing the robot dog as a puppy) for more interactive engagement.

Behavioral Neuroscience in the Era of Genomics: Tools and Lessons for Analyzing High-Dimensional Datasets.

Behavioral neuroscience underwent a technology-driven revolution with the emergence of machine-vision and machine-learning technologies. These technological advances facilitated the generation of high-resolution, high-throughput capture and analysis of complex behaviors. Therefore, behavioral neuroscience is becoming a data-rich field. While behavioral researchers use advanced computational tools to analyze the resulting datasets, the search for robust and standardized analysis tools is still ongoing. At the same time, the field of genomics exploded with a plethora of technologies which enabled the generation of massive datasets. This growth of genomics data drove the emergence of powerful computational approaches to analyze these data. Here, we discuss the composition of a large behavioral dataset, and the differences and similarities between behavioral and genomics data. We then give examples of genomics-related tools that might be of use for behavioral analysis and discuss concepts that might emerge when considering the two fields together.

Differential modulation of thermal preference after sensitization by optogenetic or pharmacological activation of heat-sensitive nociceptors.

Common approaches to studying mechanisms of chronic pain and sensory changes in pre-clinical animal models involve measurement of acute, reflexive withdrawal responses evoked by noxious stimuli. These methods typically do not capture more subtle changes in sensory processing nor report on the consequent behavioral changes. In addition, data collection and analysis protocols are often labour-intensive and require direct investigator interactions, potentially introducing bias. In this study, we develop and characterize a low-cost, easily assembled behavioral assay that yields self-reported temperature preference from mice that is responsive to peripheral sensitization. This system uses a partially automated and freely available analysis pipeline to streamline the data collection process and enable objective analysis. We found that after intraplantar administration of the TrpV1 agonist, capsaicin, mice preferred to stay in cooler temperatures than saline injected mice. We further observed that gabapentin, a non-opioid analgesic commonly prescribed to treat chronic pain, reversed this aversion to higher temperatures. In contrast, optogenetic activation of the central terminals of TrpV1+ primary afferents via in vivo spinal light delivery did not induce a similar change in thermal preference, indicating a possible role for peripheral nociceptor activity in the modulation of temperature preference. We conclude that this easily produced and robust sensory assay provides an alternative approach to investigate the contribution of central and peripheral mechanisms of sensory processing that does not rely on reflexive responses evoked by noxious stimuli.

Digging behavior discrimination test to probe burrowing and exploratory digging in male and female mice.

Digging behavior is often used to test motor function and repetitive behaviors in mice. Different digging paradigms have been developed for behaviors related to anxiety and compulsion in mouse lines generated to recapitulate genetic mutations leading to psychiatric and neurological disorders. However, the interpretation of these tests has been confounded by the difficulty of determining the motivation behind digging in mice. Digging is a naturalistic mouse behavior that can be focused toward different goals, that is foraging for food, burrowing for shelter, burying objects, or even for recreation as has been shown for dogs, ferrets, and human children. However, the interpretation of results from current testing protocols assumes the motivation behind the behavior often concluding that increased digging is a repetitive or compulsive behavior. We asked whether providing a choice between different types of digging activities would increase sensitivity to assess digging motivation. Here, we present a test to distinguish between burrowing and exploratory digging in mice. We found that mice prefer burrowing when the option is available. When food restriction was used to promote a switch from burrowing to exploration, males readily switched from burrowing to digging outside, while females did not. In addition, when we tested a model of intellectual disability and autism spectrum disorder that had shown inconsistent results in the marble burying test, the Cc2d1a conditional knockout mouse, we found greatly reduced burrowing only in males. Our findings indicate that digging is a nuanced motivated behavior and suggest that male and female rodents may perform it differently.

FreeClimber: automated quantification of climbing performance in Drosophila.

Negative geotaxis (climbing) performance is a useful metric for quantifying Drosophila health. Manual methods to quantify climbing performance are tedious and often biased, while many available computational methods have challenging hardware or software requirements. We present an alternative: FreeClimber. This open source, Python-based platform subtracts a video's static background to improve detection for flies moving across heterogeneous backgrounds. FreeClimber calculates a cohort's velocity as the slope of the most linear portion of a mean vertical position versus time curve. It can run from a graphical user interface for optimization or a command line interface for high-throughput and automated batch processing, improving accessibility for users with different expertise. FreeClimber outputs calculated slopes, spot locations for follow-up analyses (e.g. tracking), and several visualizations and plots. We demonstrate FreeClimber's utility in a longitudinal study for endurance exercise performance in Drosophila mitonuclear genotypes using six distinct mitochondrial haplotypes paired with a common D. melanogaster nuclear background.

Optogenetics in Caenorhabditis elegans.

With a compact neural circuit consisting of entirely mapped 302 neurons, Caenorhabditis elegans plays an important role in the development and application of optogenetics. Optogenetics in C. elegans offers the opportunity that drastically changes experimental designs with increasing accessibility for neural activity and various cellular processes, thereby accelerating the studies on the functions of neural circuits and multicellular systems. Combining optogenetics with other approaches such as electrophysiology increases the resolution of elucidation. In particular, technologies like patterned illumination specifically developed in combination with optogenetics provide new tools to interrogate neural functions. In this chapter, we introduce the reasons to use optogenetics in C. elegans, and discuss the technical issues raised, especially for C. elegans by revisiting our chapter in the first edition of this book. Throughout the chapter, we review early and recent milestone works using optogenetics to investigate a variety of biological systems including neural and behavioral regulation.

Multimodal Functional Analysis Platform: 3. Spherical Treadmill System for Small Animals.

In the application of advanced neuroscience techniques including optogenetics to small awake animals, it is often necessary to restrict the animal's movements. A spherical treadmill is a beneficial option that enables virtual locomotion of body- or head-restrained small animals. Besides, it has a wide application range, including virtual reality experiments. This chapter describes the fundamentals of a spherical treadmill for researchers who want to start experiments with it. First, we describe the physical aspect of a spherical treadmill based on the simple mechanical analysis. Next, we explain the basics of data logging and preprocessing for behavioral analysis. We also provide simple computer programs that work for the purpose.

Behavioral Analysis and Individual Tracking Based on Kalman Filter: Application in an Urban Environment.

In order to improve behavioral analysis systems in urban environments, this paper proposes, using data extracted from video surveillance cameras, a tracking method through two approaches. The first approach consists in comparing the position of people between two images of a video and to perform tracking by proximity. The second method using Kalman filters is based on the anticipation of the position of an individual in the upcoming image. The use of this method proves to be more efficient as it allows continuing a detection even when people cross each other or when they pass behind obstacles. The use of Kalman filters in this domain provides a new approach to obtain reliable tracking and information on speed and trajectory variations. The proposed method is innovative in the way the tracking is performed and the results are exploited. Experiments were conducted in a real situation and showed that the use of some elements of the first method could be reused to integrate a notion of distance in the method based on the Kalman filter and thus improve the latter both in tracking and in detecting of abnormal behavior. This article deals with the functioning of the two methods as well as the results obtained with the same scenarios. The experimentation concludes through concrete results that the Kalman filter method is more efficient than the proximity method alone. A sample result is available online for two of the seven videos used in this article (accessed on 19 July 2021).

Toggle toolkit: A tool for conducting experiments in unity virtual environments.

This article presents and offers Toggle Toolkit, which is an original collection of Unity scripts designed to control various aspects of interactive 3D experiments. The toolkit enables researchers in different fields to design, conduct and evaluate experiments and include interactive elements in immersive virtual environments. This was achieved by using the internal functionalities of the Unity engine and solutions of our own design. The structure of Toggle Toolkit allows triggers and toggles to be allocated to existing virtual objects and throughout the Unity scene. Once a trigger is executed (with a pre-described action, such as colliding with a virtual object, pressing a key, gazing at an object, etc.), the toggles associated with the trigger are activated and then change the attributes or behaviors of linked objects. All interactive behavior is logged and made available for further statistical analysis. Examples of applications in research are presented and discussed. The Toggle Toolkit's utility lies in its simplicity and modularity. The Toolkit was especially produced for experimenters with few coding skills and high customization requirements in their experiments. The tool is freely available for use in research and can be enhanced with custom scripts. A video tutorial is provided to facilitate use of the tool. The paper aims to not only introduce beginners to experimentation with VR but also offers more experienced researchers who are potentially interested in using and adjusting the features the Toolkit a deeper insight into its structure.