Topic: sensory feedback

How does the motor cortex (MC) achieve generalizable and purposeful movements from the complex non-linear musculoskeletal system? This understanding can help us uncover how does the cortical activity relates to the movement. To elucidate this relationship, we build a model of the MC with realistic properties. To mimic the recurrent connections between cortical neurons, we use recurrent neural networks (RNNs) to model the MC. The MC model receives sensory feedback and delivers muscle excitations to anatomically accurate musculoskeletal models to produce experimentally observed movements. The se

To organize various experiences in a coherent mental representation, we need to properly estimate the duration and temporal order of different events. Yet, our perception of time is noisy and vulnerable to various illusions. Studying these illusions can elucidate the mechanism by which the brain perceives time. In this talk, I will review a few studies on how the brain perceives duration of events and the temporal order between self-generated motion and sensory feedback. Combined with computational models at different levels, these experiments illustrated that the brain incorporates the prior

Today, considerable information is available on the organization and operation of the neural networks that generate the motor output for animal locomotion, such as swimming, walking, or flying. In recent years, the question of which neural mechanisms are responsible for task-specific and flexible adaptations of locomotor patterns has gained increased attention in the field of motor control. I will report on advances we made with respect to this topic for walking in insects, i.e. the leg muscle control system of phasmids and fruit flies. I will present insights into the neural basis of speed co