A new rodent behavioral paradigm for studying forelimb movement

The center-out task is a standard paradigm often used to study the neural control of reaching movements in human and non-human primates. However, there are several disadvantages to the use of monkeys, notably costs, infrastructural requirements, and ethical considerations. Here we describe a similar task designed to examine forelimb movements in rats. Rats were trained to grasp a joystick with their forepaw and use it to control the movements of a sipper tube in two dimensions. The rats learned to move the joystick in four directions with at least 70% accuracy after about 45 days of training. In addition, rats were able to learn a reversed mapping between joystick and sipper tube movement. This is a more complicated behavior than has been previously demonstrated for rats, and it could allow more motor behavior studies to be conducted in rodents instead of monkeys. We currently are using this behavior to decode the rats' forelimb movements from their brain signals.

[1]  E. Bizzi,et al.  Neuronal Correlates of Motor Performance and Motor Learning in the Primary Motor Cortex of Monkeys Adapting to an External Force Field , 2001, Neuron.

[2]  Joseph T. Francis,et al.  Force field apparatus for investigating movement control in small animals , 2004, IEEE Transactions on Biomedical Engineering.

[3]  Nicholas G. Hatsopoulos,et al.  Brain-machine interface: Instant neural control of a movement signal , 2002, Nature.

[4]  I. Whishaw,et al.  Long–Evans and Sprague–Dawley rats have similar skilled reaching success and limb representations in motor cortex but different movements: some cautionary insights into the selection of rat strains for neurobiological motor research , 2003, Behavioural Brain Research.

[5]  J. Kalaska,et al.  A comparison of movement direction-related versus load direction- related activity in primate motor cortex, using a two-dimensional reaching task , 1989, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[6]  David A Washburn,et al.  A new breed of computer users: Rats control a cursor via joystick manipulation , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[7]  José Carlos Príncipe,et al.  Coadaptive Brain–Machine Interface via Reinforcement Learning , 2009, IEEE Transactions on Biomedical Engineering.

[8]  Em Mead,et al.  Society for Neuroscience Annual Meeting , 2009 .

[9]  F A Mussa-Ivaldi,et al.  Adaptive representation of dynamics during learning of a motor task , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[10]  Stephen H. Scott,et al.  Apparatus for measuring and perturbing shoulder and elbow joint positions and torques during reaching , 1999, Journal of Neuroscience Methods.

[11]  Jerald D. Kralik,et al.  Real-time prediction of hand trajectory by ensembles of cortical neurons in primates , 2000, Nature.

[12]  Ian C Fayé,et al.  An impedance controlled manipulandum for human movement studies , 1986 .

[13]  Miguel A. L. Nicolelis,et al.  Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex , 1999, Nature Neuroscience.

[14]  A P Georgopoulos,et al.  On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[15]  J. Si,et al.  Closed-loop cortical control of direction using support vector machines , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.