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. 2020 Aug 8:7:101024.
doi: 10.1016/j.mex.2020.101024. eCollection 2020.

An open-source capacitive touch sensing device for three chamber social behavior test

Affiliations

An open-source capacitive touch sensing device for three chamber social behavior test

Giovanni Barbera et al. MethodsX. .

Abstract

A common feature of many neuropsychiatric disorders is deficit in social behavior. In order to study mouse models for such disorders, several behavioral tests involving social interaction with other mice have been developed. While a precise annotation of rodent behavioral state is necessary for these types of experiments, manual annotation of rodent social behavior is time-consuming and subjective. Therefore, an automated system that can instantly and independently quantify the animal's social exploration is desirable. We developed a capacitive touch device for automated detection of direct social-exploration in a modified three-chamber social behavior test. In this device, capacitive sensors can readily detect nose-pokes and other direct physical touches from the rodent under investigation. In addition, a conductive barrier makes mouse behavioral output immediately available for real-time use, by sending data to a host computer via a custom Field-Programmable Gate Array (FPGA) platform. Our capacitive touch sensing device produced similar results to the manually annotated data, demonstrating the ability to instantly and independently analyze direct social-exploration of animals in a social behavior test. Compared to the manual annotation method, this capacitive touch sensing system can be used to instantaneously quantify direct social-exploration, saving significant amount of time of post-hoc video scoring. Furthermore, this low-cost method enhances the objectivity of data by reducing experimenter involvement in analysis.

Keywords: Automatic touch detection; Closed-loop experiments; Rodent models of brain disorders; Social behavior.

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Conflict of interest statement

The authors declare no competing financial interests or conflicts of interest. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image, graphical abstract
Graphical abstract
Fig 1
Fig. 1
Capacitive sensor device. (a) Capacitive sensor device in social behavior test: 2 of the 12 MPR121 electrodes are connected to the custom mice containers (here shown without top) through a screw attached to the center of the container base plate. The sensor readouts are sent through I2C interface to a custom FPGA platform streaming data to a host PC. (b) Social behavior test includes 3 stages: habituation (two empty containers), sociability (a stranger mouse in position S1), and social novelty (same mouse in position S1 plus a stranger mouse in position S2). For each stage, two 5-minute sessions were recorded.
Fig 2
Fig. 2
Capacitive sensor results during the sociability and the preference of social novelty test. (a) Raw traces for a sample trial from sensor 1 (S1) and sensor 2 (S2) and their respective threshold used for binary output generation (top), and manually scored direct-exploration time on the two containers (bottom), compared with binary output from the capacitive sensor apparatus (black traces). Balanced accuracy was 76.99% for S1 and 77.29% for S2. (b) Standard deviation of the raw output from the sensor during the calibration procedure both with empty container and with a mouse present inside the container. (c) Percentage of positive predictive values for S1 and S2 for touch (+) and no-touch (-). (d) Balanced accuracy (average accuracy for prediction of touch and no-touch) for S1 and S2. (e) Results from the three-chamber sociability test based on the output of the capacitive sensors thresholded at 10 times their standard deviation: total exploration time ratio (left panel), average number of explorations per minute (center panel), and average duration of each exploration (right panel). Each panel compares the results based on manual scoring (left bar plot) with the results based on the binary output from the capacitive sensor apparatus (right bar plot). (f) Bland-Altman plot for the average binary touch detection of the manually scored data vs automatically scored data for sensor 1 (left) and sensor 2 (right) for n = 66 trials. Dotted lines denote bias and 95% limits of agreement. (g) Maximum peak-to-peak variation for sensor 1 (left) and sensor 2 (right) during calibration with empty cups (empty dotted line bars), calibration with mouse inside the cup (empty solid line bars), and during trials recordings (solid bars): no significant difference was measured between empty cups (sensor 1: 11.48 ± 0.6368 SD, n = 33; sensor 2: 12.18 ± 0.743 SD, n=33) and cups with mouse (sensor 1: 11.97 ± 0.7531 SD, n=33; sensor 2: 12.52 ± 0.7179 SD, n=33).

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