Neuregulin and BDNF Induce a Switch to NMDA Receptor-Dependent Myelination by Oligodendrocytes

<div><p>Myelination is essential for rapid impulse conduction in the CNS, but what determines whether an individual axon becomes myelinated remains unknown. Here we show, using a myelinating coculture system, that there are two distinct modes of myelination, one that is independent of neuronal activity and glutamate release and another that depends on neuronal action potentials releasing glutamate to activate NMDA receptors on oligodendrocyte lineage cells. Neuregulin switches oligodendrocytes from the activity-independent to the activity-dependent mode of myelination by increasing NMDA receptor currents in oligodendrocyte lineage cells 6-fold. With neuregulin present myelination is accelerated and increased, and NMDA receptor block reduces myelination to far below its level without neuregulin. Thus, a neuregulin-controlled switch enhances the myelination of active axons. <i>In vivo</i>, we demonstrate that remyelination after white matter damage is NMDA receptor-dependent. These data resolve controversies over the signalling regulating myelination and suggest novel roles for neuregulin in schizophrenia and in remyelination after white matter damage.</p></div

The glymphatic system:current understanding and modeling

Abstract We review theoretical and numerical models of the glymphatic system, which circulates cerebrospinal fluid and interstitial fluid around the brain, facilitating solute transport. Models enable hypothesis development and predictions of transport, with clinical applications including drug delivery, stroke, cardiac arrest, and neurodegenerative disorders like Alzheimer’s disease. We sort existing models into broad categories by anatomical function: Perivascular flow, transport in brain parenchyma, interfaces to perivascular spaces, efflux routes, and links to neuronal activity. Needs and opportunities for future work are highlighted wherever possible; new models, expanded models, and novel experiments to inform models could all have tremendous value for advancing the field