Home Research Project Details D2 - Adaptive visuomotor transformations in parietal cortex for neuroprosthetic control
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D2 - Adaptive visuomotor transformations in parietal cortex for neuroprosthetic control

Alexander Gail and Florentin Wörgötter

We have shown that the posterior parietal cortex of primates encodes the motor-goals of planned reach movements in a context-specific manner [Gail et al. 2006, Brozovic et al. 2007, Gail et al. 2009, Westendorff et al. 2010]. Our results suggest that PPC represents explicit reach plans based on abstract visuomotor associations. Control signals from such highly adaptive brain areas denote a major advantage for learning to control neuroprosthetic devices [Gail 2007, Musallam et al. 2004]. Aim of this project is to investigate the neuronal mechanism underlying the adaptive, implicit learning of visuomotor transformations and its applicability to robotic control.

In psychophysical tests with humans we will develop a novel adaptation paradigm. While subjects conduct goal-directed reaches, we will induce systematic reach errors by perturbing the sensory input. The visuomotor system adapts in such situations to compensate the error.

Further, we will conduct multi-channel microelectrode recordings in trained monkeys during visuomotor adaptation. These adaptation experiments will allow us to analyze visuomotor learning on the neuronal level, and help to identify effects of implicit motor-goal learning. We will test, in cooperation with project D1, if neural computations in the parietal cortex could contribute to predictions of the sensory consequences of a planned movement. Understanding such mechanisms will help to improve corresponding learning algorithms in robot control.

Belongs to Group(s):
Sensorimotor transformations, Computational Neuroscience

Is part of  Section D 

Members working within this Project:
Wörgötter, Florentin 
Gail, Alexander 

Selected Publication(s):

Fauth, M, Wörgötter, F, and Tetzlaff, C (2015).
The Formation of Multi-synaptic Connections by the Interaction of Synaptic and Structural Plasticity and Their Functional Consequences
Plos Computational Biology 11(1):e1004031.

Kuang, S, and Gail, A (2015).
When adaptive control fails: Slow recovery of reduced rapid online control during reaching under reversed vision
Vision Research 110, Part B:155-165.

Kuang, S, Morel, P, and Gail, A (2015).
Planning Movements in Visual and Physical Space in Monkey Posterior Parietal Cortex
Cerebral Cortex:bhu312, 1-17.

Westendorff, S, Kuang, S, Taghizadeh, B, Donchin, O, and Gail, A (2015).
Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model
Journal of Neurophysiology 113(7):2360-2375.

Taghizadeh, B, and Gail, A (2014).
Spatial task context makes short-latency reaches prone to induced Roelofs illusion
Frontiers in Human Neuroscience 8:673.

Chakrabarti, S, Hebert, P, Wolf, MT, Campos, M, Burdick, JW, and Gail, A (2012).
Expert-like performance of an autonomous spike tracking algorithm in isolating and maintaining single units in the macaque cortex
Journal of Neuroscience Methods 205:72-85.

Tetzlaff, C, Kolodziejski, C, Timme, M, and Wörgötter, F (2012).
Analysis of synaptic scaling in combination with Hebbian plasticity in several simple networks
Front. Comput. Neurosci 6.

Tetzlaff, C, Kolodziejski, C, Timme, M, and Wörgötter, F (2011).
Synaptic scaling in combination with many generic plasticity mechanisms stabilizes circuit connectivity
Frontiers Comput. Neurosci. 5:47.