Section: Application Domains

Motor behavior

An improved understanding of the link between single neuron activity and neural population data allows to understand the planning and action of motor behavior. To this end we extract signal features in experimental neural population data obtained in the motor cortex in animals. Synchronously theoretical population models based on single neuron activity aim to understand the typical decoding of motor action by neural populations. Experimental single neuron data assists this model approach.

In addition, we employ and integrate numerically a neural population model whose activity features are compared to the signal features observed in experiments. In addition, we link the signal features to experimental behavioral data.