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. 2015 May 15;246:30-7.
doi: 10.1016/j.jneumeth.2015.03.008. Epub 2015 Mar 10.

An Automated Behavioral Box to Assess Forelimb Function in Rats

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Free PMC article

An Automated Behavioral Box to Assess Forelimb Function in Rats

Chelsea C Wong et al. J Neurosci Methods. .
Free PMC article

Abstract

Background: Rodent forelimb reaching behaviors are commonly assessed using a single-pellet reach-to-grasp task. While the task is widely recognized as a very sensitive measure of distal limb function, it is also known to be very labor-intensive, both for initial training and the daily assessment of function.

New method: Using components developed by open-source electronics platforms, we have designed and tested a low-cost automated behavioral box to measure forelimb function in rats. Our apparatus, made primarily of acrylic, was equipped with multiple sensors to control the duration and difficulty of the task, detect reach outcomes, and dispense pellets. Our control software, developed in MATLAB, was also used to control a camera in order to capture and process video during reaches. Importantly, such processing could monitor task performance in near real-time.

Results: We further demonstrate that the automated apparatus can be used to expedite skill acquisition, thereby increasing throughput as well as facilitating studies of early versus late motor learning. The setup is also readily compatible with chronic electrophysiological monitoring.

Comparison with existing methods: Compared to a previous version of this task, our setup provides a more efficient method to train and test rodents for studies of motor learning and recovery of function after stroke. The unbiased delivery of behavioral cues and outcomes also facilitates electrophysiological studies.

Conclusions: In summary, our automated behavioral box will allow high-throughput and efficient monitoring of rat forelimb function in both healthy and injured animals.

Keywords: Electrophysiology; Motor learning; Reach.

Figures

Figure 1
Figure 1. Behavioral apparatus
(A) Schematic drawing of the box with open gate. Red boxes represent the infrared (IR) light emitting diodes (LED); Blue boxes represent the IR detectors. Dashed lines indicate IR beams for pellet detection. (B) Schematic drawing of the side view of the box. (C) View of the entire reach box with pellet dispenser and gate-controlled slit on the left. (D) Customized dual-output pellet dispenser. Arrow indicates direction of pellet dispensing to left and right pellet trays. (E–F) Illustration of the dual pellet holders. With the gate closed, pellets can be easily dispensed to either the left or right position. Opening of the gate signals the start of the trial and presentation of the pellet.
Figure 2
Figure 2. Automated detection of trial outcomes
(A) Examples of video processing to detect single trial outcomes. Image above is a black and white depiction of a single video frame (30 Hz acquisition). Region of interest (ROI) is indicated by the red rectangle. Shown below is the processed indication of a dropped pellet (i.e., the white pixels in frames 10 and 13). The pellets and the detected trajectory of the pellet are outlined in green. (B) Single trial outcomes during multiple learning sessions in a single day. Stems indicate successful trials, while circles on the red line indicate failures. Top row is the first training session of the day.
Figure 3
Figure 3. Comparison of trial structure on the reach-to-grasp task
(A) Upper panels show the learning curve of one rat during regular training paradigm of one 25-trial session per day. The lower panel shows the mean curve for 6 rats. (B) Upper panel shows multiple individual examples of multiple daily sessions per day (25 trials/session). Mean curve is shown below (n=8 rats). (C) Examples and mean for rats performing multiple sessions of 100 trials/session.
Figure 4
Figure 4. Recovery after stroke
Mean recovery curve after a focal M1 stroke (n=4). Each of these rats were trained using multiple sessions/day. The inset shows the histological analysis (cresyl violet stain) of the stroke from one animal (coronal section). Scale bar is 1 mm. M=Medial; L=Lateral.
Figure 5
Figure 5. Electrophysiological recordings from the rat primary motor cortex (M1) during reaching
(A) Trial structure during reaching movements. (B) Still frames of video tracking of limb movements. The red line shows a single example of the reach trajectory. (C) Example firing of a single neuron in M1 during reaching movements. Each row represents activity during a single reaching movement and each bar represents an action potential/spike. (D) Colormap of the temporal evolution of the neural spiking activity during reaching movements (combined from recording sessions in three rats). Time 0 is the reach onset. Each row represents the mean normalized event-related firing of task-related neurons. Color gradient represents the normalized peak firing intensity (i.e. normalized firing rate).

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