AutoRG: An automatized reach-to-grasp platform technology for assessing forelimb motor function, neural circuit activation, and cognition in rodents

Abstract

Background: Rodent reach-to-grasp function assessment is a translationally powerful model for evaluating neurological function impairments and recovery responses. Existing assessment platforms are experimenter-dependent, costly, or low-throughput with limited output measures. Further, a direct histologic comparison of neural activation has never been conducted between any novel, automated platform and the well-established single pellet skilled reach task (SRT).

New method: To address these technological and knowledge gaps, we designed an open-source, low-cost Automatized Reach-to-Grasp (AutoRG) pull platform that reduces experimenter interventions and variability. We assessed reach-to-grasp function in rats across seven progressively difficult stages using AutoRG. We mapped AutoRG and SRT-activated motor circuitries in the rat brain using volumetric imaging of the immediate early gene-encoded Arc (activity-regulated cytoskeleton-associated) protein.

Results: Rats demonstrated robust forelimb reaching and pulling behavior after training in AutoRG. Reliable force versus time responses were recorded for individual reach events in real time, which were used to derive several secondary functional measures of performance. Moreover, we provide the first demonstration that for a training period of 30 min, AutoRG and SRT both engage similar neural responses in the caudal forelimb area (CFA), rostral forelimb area (RFA), and sensorimotor area (S1).

Conclusion: AutoRG is the first low-cost, open-source pull system designed for the scale-up of volitional forelimb motor function testing and characterization of rodent reaching behavior. The similarities in neuronal activation patterns observed in the rat motor cortex after SRT and AutoRG assessments validate the AutoRG as a rigorously characterized, scalable alternative to the conventional SRT and expensive commercial systems.

Keywords: Immediate early gene; Motor circuitry; Open-source; Reach-to-grasp; Rodents; Volumetric brain imaging.

Fig. 1.

Modular assembly of 3D-printed parts and electronic components that make up the AutoRG setup. (a) Frontal schematic of the AutoRG setup. Inset AA depicts an overview of all major 3D-printed parts, including stage quadrants, handle base, pellet dispense tower, pellet dispenser, CPX frame, pellet receptacle, positional servo casing, load cell carriage, and load cell handle adapter. (b) Picture of assembled AutoRG apparatus. Lowercase letters label individual components listed in Supplementary Tables S-I and S-II. Inset BB depicts aerial schematic and dimensions of stage and acrylic cage. (c) Wiring diagram for the electronic control system. (d) Screenshot of the AutoRG graphic user interface (GUI) showing a single pull trial.

Fig. 2.

AutoRG accurately reads the applied force and reliably reinforces successful trials. (a) Experiments with an independently verified 227 g force demonstrated the accuracy of the AutoRG force measurement system across various handle positions. Readouts deviated minimally from 227 g, and accuracy was not affected by the position of the handle. (b) Independently verified forces ranging from 0 to 300 g, the relevant range of pull forces for rats in an isometric pull task, were accurately measured by AutoRG. (c) AutoRG calibration is consistent and stable after extensive use. (d) AutoRG dispenses 1–3 pellets approximately 95 % of the time, allowing for reliable, automated conditioning of rodent reaching behavior.

Fig. 3.

AutoRG facilitated a 7-stage automated training of rats over 4 weeks, on average. (a) Schematics showing the handle position and force threshold for the critical Stages 1, 4, 6, and 7. Plots on the left show individual rat progression (gray) and average rat progression (black) as the percentage of the stage’s passing criterion, defined as (number of successes achieved in session) / (minimum number of successes required to pass stage). 100 % is defined as ≥ 60 successes for Stage 1 and ≥ 30 successes for Stages 4, 6, and 7. Colored dots indicate one or more rats finishing the stage. Graphs indicate mean and SEM. (b) Distribution of pull forces at stage 4 (mid-training, first stage of forced reaching - blue) and stage 7 (trained rats - green). The median force is indicated with a dashed line. (c) Cumulative bar graph showing the time spent at each stage for each rat. The number of sessions until completion of training varied from 19 to 40 sessions, with a mean of 30.2 sessions.

Fig. 4.

AutoRG quantified the reaching style of trained rats during successful trials. (a) Five randomly chosen force vs. time graphs of successful trials demonstrate different pulling behaviors. (b) Annotated representative graph highlights defined variables. Peaks are annotated in blue, the maximum force in orange, the area under the curve in gray, and the latency to first success in green. (c-f) Histograms of the number of peaks, maximum force (in grams), area under the curve (in grams*second), and latency to first success (in seconds), n = 796 successful trials after passing stage 7. Black curves represent probability functions.

Fig. 5.

Trained rats exhibited outcome-induced adaptation of force, pulling frequency, and latency to success. (a) Representative trials demonstrate changes in behavior trends following a failed trial (top) or a successful trial (bottom). (b-f). Changes in pulling behavior, relative to the previous trial, when the previous trial resulted in either a failure or a success. (b) Change in latency to the trial maximum force, where positive values indicate a longer latency from trial onset. (c) The maximum force peak occurs later in trials following a failure than trials following success. (d-f) The area under the curve, maximum force, and number of peaks increases in the (n + 1) trial when the (n) trial was a failure and decreases when (n) was a success. N = 24 sessions for all panels, significance levels: *** p < 0.001.

Fig. 6.

AutoRG training elicits the activation of neuronal circuitry in the motor cortex. (a) The experimental timeline of the terminal motor assay which elicited Arc expression. (b) Heatmaps of Arc expression in the dorsal-ventral (top) and anterior-posterior (bottom) planes. Warmer colors indicate higher levels of Arc expression. (c) Representative image denoting defined regions of interest: blue (rostral forelimb area, RFA), green (caudal forelimb area, CFA), yellow (somatosensory cortex, S), white line (bregma). (d) Heatmap demonstrating differences in Arc intensity between AutoRG and SRT. Purple indicates greater Arc intensity in the AutoRG animals in that area, red indicates greater Arc intensity in SRT animals. (e) Arc expression as a function of cortical depth in control (blue), SRT (yellow), and AutoRG (orange). (f) Change in Arc expression, relative to control, across the imaged brain. Pixels were binned and compared to their spatial counterpart. Dashed black lines indicate differences in Arc expression, + /− 1 % change omitted from the graph. (g) The number of Arc+ cells in the caudal forelimb area, rostral forelimb area, and somatosensory cortex in control, SRT, and AutoRG animals. (h) The ratio of Arc+ expression in the right:left hemispheres in the CFA, RFA, and S of control, SRT, and AutoRG animals. Significance levels: * p < 0.05, ** p < 0.01.