High-throughput data analysis in behavior genetics

In recent years, a growing need has arisen in different fields for the development of computational systems for automated analysis of large amounts of data (high-throughput). Dealing with nonstandard noise structure and outliers, that could have been detected and corrected in manual analysis, must now be built into the system with the aid of robust methods. We discuss such problems and present insights and solutions in the context of behavior genetics, where data consists of a time series of locations of a mouse in a circular arena. In order to estimate the location, velocity and acceleration of the mouse, and identify stops, we use a nonstandard mix of robust and resistant methods: LOWESS and repeated running median. In addition, we argue that protection against small deviations from experimental protocols can be handled automatically using statistical methods. In our case, it is of biological interest to measure a rodent's distance from the arena's wall, but this measure is corrupted if the arena is not a perfect circle, as required in the protocol. The problem is addressed by estimating robustly the actual boundary of the arena and its center using a nonparametric regression quantile of the behavioral data, with the aid of a fast algorithm developed for that purpose.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS304 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

A multi-lab experimental assessment reveals that replicability can be improved by using empirical estimates of genotype-by-lab interaction.

The utility of mouse and rat studies critically depends on their replicability in other laboratories. A widely advocated approach to improving replicability is through the rigorous control of predefined animal or experimental conditions, known as standardization. However, this approach limits the generalizability of the findings to only to the standardized conditions and is a potential cause rather than solution to what has been called a replicability crisis. Alternative strategies include estimating the heterogeneity of effects across laboratories, either through designs that vary testing conditions, or by direct statistical analysis of laboratory variation. We previously evaluated our statistical approach for estimating the interlaboratory replicability of a single laboratory discovery. Those results, however, were from a well-coordinated, multi-lab phenotyping study and did not extend to the more realistic setting in which laboratories are operating independently of each other. Here, we sought to test our statistical approach as a realistic prospective experiment, in mice, using 152 results from 5 independent published studies deposited in the Mouse Phenome Database (MPD). In independent replication experiments at 3 laboratories, we found that 53 of the results were replicable, so the other 99 were considered non-replicable. Of the 99 non-replicable results, 59 were statistically significant (at 0.05) in their original single-lab analysis, putting the probability that a single-lab statistical discovery was made even though it is non-replicable, at 59.6%. We then introduced the dimensionless Genotype-by-Laboratory (GxL) factor-the ratio between the standard deviations of the GxL interaction and the standard deviation within groups. Using the GxL factor reduced the number of single-lab statistical discoveries and alongside reduced the probability of a non-replicable result to be discovered in the single lab to 12.1%. Such reduction naturally leads to reduced power to make replicable discoveries, but this reduction was small (from 87% to 66%), indicating the small price paid for the large improvement in replicability. Tools and data needed for the above GxL adjustment are publicly available at the MPD and will become increasingly useful as the range of assays and testing conditions in this resource increases

Knots: Attractive Places with High Path Tortuosity in Mouse Open Field Exploration

When introduced into a novel environment, mammals establish in it a preferred place marked by the highest number of visits and highest cumulative time spent in it. Examination of exploratory behavior in reference to this “home base” highlights important features of its organization. It might therefore be fruitful to search for other types of marked places in mouse exploratory behavior and examine their influence on overall behavior

Analysis of the Trajectory of Drosophila melanogaster in a Circular Open Field Arena

BACKGROUND: Obtaining a complete phenotypic characterization of a freely moving organism is a difficult task, yet such a description is desired in many neuroethological studies. Many metrics currently used in the literature to describe locomotor and exploratory behavior are typically based on average quantities or subjectively chosen spatial and temporal thresholds. All of these measures are relatively coarse-grained in the time domain. It is advantageous, however, to employ metrics based on the entire trajectory that an organism takes while exploring its environment. METHODOLOGY/PRINCIPAL FINDINGS: To characterize the locomotor behavior of Drosophila melanogaster, we used a video tracking system to record the trajectory of a single fly walking in a circular open field arena. The fly was tracked for two hours. Here, we present techniques with which to analyze the motion of the fly in this paradigm, and we discuss the methods of calculation. The measures we introduce are based on spatial and temporal probability distributions and utilize the entire time-series trajectory of the fly, thus emphasizing the dynamic nature of locomotor behavior. Marginal and joint probability distributions of speed, position, segment duration, path curvature, and reorientation angle are examined and related to the observed behavior. CONCLUSIONS/SIGNIFICANCE: The measures discussed in this paper provide a detailed profile of the behavior of a single fly and highlight the interaction of the fly with the environment. Such measures may serve as useful tools in any behavioral study in which the movement of a fly is an important variable and can be incorporated easily into many setups, facilitating high-throughput phenotypic characterization

Mouse Cognition-Related Behavior in the Open-Field: Emergence of Places of Attraction

Spatial memory is often studied in the Morris Water Maze, where the animal's spatial orientation has been shown to be mainly shaped by distal visual cues. Cognition-related behavior has also been described along “well-trodden paths”—spatial habits established by animals in the wild and in captivity reflecting a form of spatial memory. In the present study we combine the study of Open Field behavior with the study of behavior on well-trodden paths, revealing a form of locational memory that appears to correlate with spatial memory. The tracked path of the mouse is used to examine the dynamics of visiting behavior to locations. A visit is defined as either progressing through a location or stopping there, where progressing and stopping are computationally defined. We then estimate the probability of stopping at a location as a function of the number of previous visits to that location, i.e., we measure the effect of visiting history to a location on stopping in it. This can be regarded as an estimate of the familiarity of the mouse with locations. The recently wild-derived inbred strain CZECHII shows the highest effect of visiting history on stopping, C57 inbred mice show a lower effect, and DBA mice show no effect. We employ a rarely used, bottom-to-top computational approach, starting from simple kinematics of movement and gradually building our way up until we end with (emergent) locational memory. The effect of visiting history to a location on stopping in it can be regarded as an estimate of the familiarity of the mouse with locations, implying memory of these locations. We show that the magnitude of this estimate is strain-specific, implying a genetic influence. The dynamics of this process reveal that locations along the mouse's trodden path gradually become places of attraction, where the mouse stops habitually

On the growth and form of animal behavior

In this study we highlight the architecture (bauplan) of vertebrate and partly also of arthropod growth and form of behavior. We show in what sense behavior is an extension of anatomy. Then we show that movement-based behavior shares linearity and modularity with the skeletal body plan, and with the Hox genes (genes that specify regions of the body plan of an embryo); that it mirrors the geometry of the physical environment; and that it reveals the animal’s understanding of the animate and physical situation, with implications for perception, attention, emotion, and primordial cognition. First, as in comparative anatomy, we define the primitives of movement in relational terms. This yields homological primitives. Then we define the modules, the generative rules and the architectural plan of behavior in terms of these primitives. In this way we expose the homology of behaviors and establish a rigorous trans-phyletic comparative discipline of the morphogenesis of movement-based behavior. In morphogenesis, behavior builds up and narrows incessantly according to strict geometric rules. The same rules apply in moment to moment behavior, in ontogenesis, and partly also in phylogenesis. We demonstrate the rules in development, in neurological recovery, with drugs (dopamine-stimulated striatal modulation), in stressful situations, in locomotor behavior, and partly also in human pathology. The buildup of movement culminates in free, undistracted, exuberant behavior. It is observed in play, in superior animals during agonistic interactions, and in humans in higher states of functioning. Geometrization promotes the study of genetics, anatomy, and behavior within one and the same discipline. The geometrical bauplan portrays both already evolved dimensions, and prospective dimensional constraints on evolutionary behavioral innovations

Data from: Vertical exploration and dimensional modularity in mice

Exploration is a central component of animal behaviour studied extensively in rodents. Previous tests of free exploration limited vertical movement to rearing and jumping. Here we attach a wire mesh to the arena wall, allowing vertical exploration. This provides an opportunity to study the morphogenesis of behaviour along the vertical dimension, and examine the context in which it is performed. In the current setup, the mice first use the doorway as a point reference for establishing a borderline linear path along the circumference of the arena floor, and then use this path as a linear reference for performing horizontal forays towards the center (incursions) and vertical forays on the wire mesh (ascents). Vertical movement starts with rearing on the wall, and commences with straight vertical ascents that increase in extent and complexity. The mice first reach the top of the wall, then mill about within circumscribed horizontal sections, and then progress horizontally for increasingly longer distances on the upper edge of the wire mesh. Examination of the sequence of borderline segments, incursions and ascents reveals dimensional modularity: an initial series ("bout") of borderline segments precedes alternating bouts of incursions and bouts of ascents, thus exhibiting sustained attention to each dimension separately. The exhibited separate growth in extent and in complexity of movement and the sustained attention to each of the three dimensions disclose the mice's modular perception of this environment and validate all three as natural kinds