A novel computerized system for analyzing motor and social behavior in groups of animals

Smartphone and a freely available application as a new tool to record locomotor activity rhythm in large mammals and humans

Daily pattern of locomotor activity (LA), one of the most studied rhythms in humans and rodents, has not been widely investigated in large mammals. This is partly due to the high cost and breakability of used automatic devices. Since last decade, smartphones are becoming ubiquitous. Meanwhile, several applications detecting activity by using internal sensors were made available. In this study, we assumed that this device could be a cheaper and easier way to measure the LA rhythm in humans and large mammals, like camel and goat. A smartphone application (Nokia Mate Health), normally used to quantify physical activities in humans, was chosen for the study. To validate the rhythm data obtained from the smartphone, LA rhythm was simultaneously recorded using an automatic device, the Actiwatch-Mini®. Results showed that the smartphone provided a clear and significant daily rhythm of LA. The visual assessment of the superimposed LA rhythm's curves in all three species showed that the smartphone application displayed similar rhythms as those recorded by the Actiwatch-Mini. Highly significant positive correlation (p≤ 0.0001) exists between the two recording rhythms. The daily periods were both the same at 24.0 h. Acrophases were also significantly similar and occurring around mid-day: 11:40 ± 0.35 h vs 11:41 ± 0.35 h for the camel, 11:25 ± 0.19 h vs 11:37 ± 0.25 h for the goat and 13:04 ± 0.11 h vs 13:51 ± 0.28 h for humans using smartphone and Actiwatch, respectively. The related mesor and amplitude were also close between the two recording devices. Results indicate clearly that using smartphones constitutes a reliable cheap tool to study LA rhythm for chronobiology studies, especially in laboratories facing lack of funding.

Validation of locomotion scoring as a new and inexpensive technique to record circadian locomotor activity in large mammals

Background

The locomotor activity (LA) rhythm, widely studied in rodents, has not been fully investigated in large mammals. This is due to the high cost and the brittleness of the required devices. Alternatively, the locomotion scoring method (SM), consisting of attribution of a score to various levels of activity would be a consistent method to assess the circadian LA rhythm in such species.

New method

To test this, a SM with a score ranging from 0 to 5 has been developed and used in two domestic large mammals, the camel and the goat. One minute interval scoring was performed using visual screening and monitoring of infra-red camera recording videos and carried out by two evaluators.

Results

The SM provides a clear daily LA rhythm that has been validated using an automate device, the Actiwatch-Mini. The obtained curves and actograms were indeed highly similar to those acquired from the Actiwatch-Mini. Moreover, there were no statistical differences in the period and acrophase. The period was exactly of 24.0h and the acrophases occurred at 12h05 ± 00h03 and 12h14 ± 00h07 for the camel and at 13h13 ± 00h09 and 12h57 ± 00h09 for the goat using SM and Actiwatch-Mini respectively.

Comparison with existing methods

Compared to the automatic system, the SM is inexpensive and has the advantage of describing all types of performed movements.

Conclusions

The new developed SM is highly reliable and sufficiently accurate to assess conveniently the LA rhythm and specific behaviors in large mammals. This opens new perspectives to study chronobiology in animal models of desert, tropical and equatorial zones.

Real-Time Localization of Moving Dipole Sources for Tracking Multiple Free-Swimming Weakly Electric Fish

In order to survive, animals must quickly and accurately locate prey, predators, and conspecifics using the signals they generate. The signal source location can be estimated using multiple detectors and the inverse relationship between the received signal intensity (RSI) and the distance, but difficulty of the source localization increases if there is an additional dependence on the orientation of a signal source. In such cases, the signal source could be approximated as an ideal dipole for simplification. Based on a theoretical model, the RSI can be directly predicted from a known dipole location; but estimating a dipole location from RSIs has no direct analytical solution. Here, we propose an efficient solution to the dipole localization problem by using a lookup table (LUT) to store RSIs predicted by our theoretically derived dipole model at many possible dipole positions and orientations. For a given set of RSIs measured at multiple detectors, our algorithm found a dipole location having the closest matching normalized RSIs from the LUT, and further refined the location at higher resolution. Studying the natural behavior of weakly electric fish (WEF) requires efficiently computing their location and the temporal pattern of their electric signals over extended periods. Our dipole localization method was successfully applied to track single or multiple freely swimming WEF in shallow water in real-time, as each fish could be closely approximated by an ideal current dipole in two dimensions. Our optimized search algorithm found the animal’s positions, orientations, and tail-bending angles quickly and accurately under various conditions, without the need for calibrating individual-specific parameters. Our dipole localization method is directly applicable to studying the role of active sensing during spatial navigation, or social interactions between multiple WEF. Furthermore, our method could be extended to other application areas involving dipole source localization.

Validation of a digital video tracking system for recording pig locomotor behaviour

We are introducing a system for automatically tracking pig locomotor behaviour. Transposing methods for the video-based tracking of rodent behaviour engenders several problems. We have therefore improved existing methods, based on image-subtraction, to offer increased flexibility and accuracy in tracking large-sized animals in situations with a constantly changing background. The improved tracking algorithms introduce a reference frame, which does not include the animal and is automatically updated, and implementation of an automatic threshold detection algorithm. This makes the system more robust to the tracking environment, which could even be of the same colour as the animal, and allows the tracking environment to change during recording. We validated the system by estimating the repeatability, accuracy, and basic noise level, and tested the system in different levels of animal activity evoked by administration of apomorphine (APO) to minipigs in an open field test. Seven pigs each received the vehicle and three doses of APO (0.05, 0.1, and 0.3 mg/kg i.m.), and the locomotor behaviour of each session was recorded for 60-min. The calculated coefficient of repeatability was 0.6%, indicating high repeatability and the basic noise level of the tracking system was estimated to be 2%. Administration of the two lowest doses of APO was accompanied by increased locomotor activity of the pigs. Thus, this digital video-based tracking system for automatically tracking the spontaneous locomotor behaviour of pigs is highly reliable and accurate, and was able to detect well-known effects of APO in pig locomotor activity.

A simple integrated circuit device for measuring distances traveled and determining speed in open-field environments

An easily constructed and inexpensive device for measuring distance and determining mean speed, which utilizes an integrated circuit (IC) photosensor system, is described. It was designed for evaluating activity of small animals in open-field environments, being used in conjunction with a video-recording system. The horizontal locomotor path of the animal is manually tracked directly from the video monitor image or from a tracing made of the image.

Body modeling and model-based tracking for neuroethology

The accurate tracking of an animal's movements and postures through time has broad applicability to questions in neuroethology and animal behavior. In this paper we describe methods for precision body modeling and model-based tracking of non-rigid animal movements without the use of external markers. We describe the process of obtaining high-fidelity urethane casts of a model organism, the weakly electric knifefish Apteronotus albifrons, and the use of a stylus-type 3-D digitizer to create a polygonal model of the animal from the cast. We describe the principles behind markerless model-based tracking software that allows the user to translate, rotate, and deform the polygon model to fit it to digitized video images of the animal. As an illustration of these methods, we discuss how we have used model-based tracking in the study of prey capture in nocturnal weakly electric fish to estimate sensory input during behavior. These methods may be useful for bridging between the analytical approaches of quantitative neurobiology and the synthetic approaches of integrative computer simulations and the building of biomimetic robots.

Preoperative open field behavior predicts levels of neuropathic pain-related behavior in mice

Exploratory open field (OF) activity was assessed in seven different mouse strains and selection lines. We counted the number of beam interruptions made by three cagemate mice at a time. This assay tests reactivity to aversive stimuli, anxiety and emotionality. One hindlimb was then totally denervated by transecting the sciatic and saphenous nerves on one side, and autotomy, a behavior thought to be related to neuropathic pain, was quantified over 35 days. We report that OF activity and autotomy are highly variable across different strains/lines. These results reaffirm the genetic control of these behaviors. We also found that these behaviors are inversely and significantly correlated. We suggest that common genetically-determined neural mechanisms may underlie anxiety, emotionality and neuropathic pain in mice.