Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Summary

A paradigm is presented for training and analysis of an automated skilled reaching task in rats. Analysis of pulling attempts reveals distinct subprocesses of motor learning.

Abstract

Skilled reaching tasks are commonly used in studies of motor skill learning and motor function under healthy and pathological conditions, but can be time-intensive and ambiguous to quantify beyond simple success rates. Here, we describe the training procedure for reach-and-pull tasks with ETH Pattus, a robotic platform for automated forelimb reaching training that records pulling and hand rotation movements in rats. Kinematic quantification of the performed pulling attempts reveals the presence of distinct temporal profiles of movement parameters such as pulling velocity, spatial variability of the pulling trajectory, deviation from midline, as well as pulling success. We show how minor adjustments in the training paradigm result in alterations in these parameters, revealing their relation to task difficulty, general motor function or skilled task execution. Combined with electrophysiological, pharmacological and optogenetic techniques, this paradigm can be used to explore the mechanisms underlying motor learning and memory formation, as well as loss and recovery of function (e.g. after stroke).

Introduction

Motor tasks are widely used to assess behavioral and neural changes related to motor learning or to alterations in motor function in neurological or pharmacological animal models. Fine motor function can be difficult to quantify in rodents, however. Tasks requiring manual dexterity, such as manipulation of cereal¹, pasta², or sunflower seeds³ are sensitive and do not require extensive training of the animal. Their main drawback is that these tasks yield mostly qualitative results and can be difficult to score unambiguously.

Skilled reaching tasks, such as variations of ....

Protocol

The experiments presented here were approved by the Veterinary Office of the Canton of Zurich, Switzerland and were carried out according to national and institutional regulations.

1. Feeding Conditions

NOTE: All training sessions are performed under a scheduled feeding protocol.

1. Feed the rats 50 g/kg of standard chow once per day, after training is completed. This amount of food is sufficient to prevent major weight loss (body weight is >90% of free-feeding weight), but small enough to ensure reproducible behavioral conditioning. Weigh the rats daily to ensure their body weight remains stable.

Results

Here, we show 3 variations of a reach-and pull task using male Long-Evans rats (10-12 weeks old). In the free-pull (FP) group (N = 6), rats were trained to pull the robot's handle for a 22 day period without lateral restrictions. Animals in the straight-pull 1 (SP1) group (N = 12) were trained to pull the handle without deviating more than 2 mm from midline. These animals transitioned directly from reward-touch (step 2.3) to straight-pull training (step 2.5). For both FP and SP1 animals, .......

Discussion

Skilled reaching tasks are commonly used to study motor skill acquisition as well as impairment of motor function under pathological conditions⁶. Reliable and unambiguous analysis of reaching behavior is essential for the study of cellular mechanisms underlying motor skill acquisition, as well as neurophysiological processes involved in loss and subsequent recovery of function in animal models of neurological disease. The results presented here show how spatial and temporal aspects of the pulling .......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
ETH Pattus			ETH Pattus was made by the Rehabilitation Engineering Laboratory of Prof. Gassert at ETH Zurich.
Training cage			The plexiglass training cage was made in-house.
Pellet dispenser	Campden Instruments	80209
45-mg dustless precision pellets	Bio-Serv	F0021-J
GoPro Hero 3+ Silver Edition	digitec.ch	284528	Small highspeed camera
Small display	Adafruit Industries	#50, #661	128 x 32 SPI OLED display controlled via an Arduino Uno microcontroller and Labview software
LabVIEW 2012	National Instruments	776678-3513	ETH Pattus is compatible with more recent Labview versions.
Matlab 2014b	The Mathworks	MLALL