Single Collateral Reconstructions Reveal Distinct Phases of Corticospinal Remodeling after Spinal Cord Injury

Injuries to the spinal cord often result in severe functional deficits that, in case of incomplete injuries, can be partially compensated by axonal remodeling. The corticospinal tract (CST), for example, responds to a thoracic transection with the formation of an intraspinal detour circuit. The key step for the formation of the detour circuit is the sprouting of new CST collaterals in the cervical spinal cord that contact local interneurons. How individual collaterals are formed and refined over time is incompletely understood

Thomas Graham Brown (1882–1965): Behind the Scenes at the Cardiff Institute of Physiology

Thomas Graham Brown undertook seminal experiments on the neural control of locomotion between 1910 and 1915. Although elected to the Royal Society in 1927, his locomotion research was largely ignored until the 1960s when it was championed and extended by the distinguished neuroscientist, Anders Lundberg. Puzzlingly, Graham Brown's published research stopped in the 1920s and he became renowned as a mountaineer. In this article, we review his life and multifaceted career, including his active neurological service in WWI. We outline events behind the scenes during his tenure at Cardiff's Institute of Physiology in Wales, UK, including an interview with his technician, Terrence J. Surman, who worked in this institute for over half a century

Building a realistic neuronal model that simulates multi-joint arm and hand movements in 3D space

The question as to how the brain controls voluntary movements of the arm and hand still remains largely unsolved despite much research focused on behavioral studies, neurophysiological investigations, and neuronal modeling in computer science. This is because behavioral studies are usually performed without detailed knowledge of the underlying neuronal networks, neurophysiological studies often lack an understanding of the function, and neuronal models are frequently focused on a particular control problem with restricted knowledge of the underlying neuronal networks involved. Therefore, it seems appropriate to start by trying to integrate knowledge of neuronal networks with known function and computer based neuronal models to seek more realistic models that can better control robots or artificial limbs and hands. We propose to combine knowledge of a behavioral model for reaching with the hand toward an object, which is based on detailed knowledge of the underlying neuronal network, and a neuronal model that includes several functional levels, from the planning level via intermediate levels to the final level of control of motoneurons and muscles