The brain is divided into grey matter “processing nodes” linked by white matter “information superhighways” to minimize conduction delays and energy use. For the white matter, the information propagation speed is increased and the axonal energy cost is reduced by oligodendrocytes wrapping myelin around axons, thus decreasing their capacitance and decreasing the Na+ influx needed at Ranvier nodes to produce an action potential. This arrangement may not just speed action potentials, however, it may also be a previously unsuspected substrate for information storage in the CNS.
Information is generally thought to be stored in the CNS by virtue of grey matter plasticity, i.e. changes in the structure and electrophysiological strength of synapses. However, recently, white matter plasticity has also been suggested to exist, based in part on diffusion tensor magnetic resonance imaging of changes in the brains of people learning to play the piano or juggle. White matter plasticity may adjust action potential arrival times in the CNS, to promote firing of target neurons. Surprisingly, it is unknown which parameters of myelinated axons change to alter the speed. Does white matter plasticity solely reflect changes of myelin thickness, or are there also activity-dependent alterations of Ranvier node Na+ channel density, internode length, or axon diameter at the nodes or internodes? In addition, could alterations of Ranvier node geometry or of the size of the conducting periaxonal space under the myelin be employed to tune the conduction speed of myelinated axons?
I will employ a combination of cutting-edge electrophysiological and imaging methods to elucidate the cellular mechanisms underlying plasticity of myelinated axons, and their functional significance for axon conduction speed. This work will significantly advance the methodology used to study the brain’s white matter, and provide new insight into how information is stored in the brain.
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