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Monday, July 20 • 8:00pm - 9:00pm
P24: A bump-attractor spiking neural network for motor adaptation and washout based on Norepinephrine release in primary motor cortex

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Mariia Popova, Melanie Tschiersch, Nicolas Berberich, Stefan K. Ehrlich, David Franklin, Gordon Cheng

Link to the meeting: https://meet.google.com/ifn-ffzg-irb
In order to examine the formation of predictive motor memories, typical behavioural motor learning experiments perturb participants reaching movements using an external force field, to which they rapidly adapt, and exhibit after effects when the force field is removed. During the force field adaptation trials (Fig. 1), subjects move their hand from the start position (red circle) to the target position (black x) while a force field perturbs the movement (strength and direction indicated by yellow arrows) causing the hand to move to the final position (green circle). After the force field is removed, a washout effect is observed. While previous computational models can recreate the behavioral results, they do not account for the neural mechanisms involved. A computational model including a synaptic mechanism can help to explain the processes involved in motor learning. For this reason, we developed a bump-attractor, spiking neuron model of primary motor cortex (M1) proposing a synaptic mechanism using reward-based neurotransmitter release to explain motor adaptation and washout. The developed model consists of directionally-tuned neurons, shown to exist in M1 in biology, that encode the hand position through average neural firing. The force field is modeled through a simulated, external current perturbing the neural activity in the direction of the force field. In biology, Norepinephrine is released from locus coreuleus to M1 when errors are detected in the visual pathway. Norepinephrine affects M1 in a goal-directed manner, increasing the excitatory synaptic responses in the so-called hotspot, which is determined by arousal. For the model to remain close to biology, adaptation is modeled through an error-dependent increase in excitatory to excitatory conductance in the target position within the M1 model, leading to a decrease of the perturbation on the stable bump of neural activity across trials. Washout is implemented through a shift of the hotspot and the accumulated Norepinephrine through a motor-coordinate system shift during force field removal. After the initial washout trial, the wrongful coordinate system shift is detected and Norepinephrine in the shifted hotspot decays. The simulations from the proposed computational model qualitatively account for both: adaptation and washout as seen in comparison to the behavioural data from [1] (Fig. 1). Thus, the model suggests for the first time a biologically plausible synaptic mechanism in M1 that can explain the main features of motor learning of external dynamics.


1. Nozaki D, Kurtzer I, Scott S. Limited transfer of learning between unimanual and bimanual skills within the same limb. Nat Neurosci. 2006, 9, 1364–1366.

avatar for Mariia Popova

Mariia Popova

Department of Electrical and Computer Engineering, Technical University of Munich

Monday July 20, 2020 8:00pm - 9:00pm CEST
Slot 09