White Matter Networks

Demyelination has long been associated with diseases such as multiple sclerosis, and more recently with psychiatric disorders including depression and schizophrenia (where structural differences in white matter networks are manifest). It has only relatively recently been established that myelin is also modifiable by experience and can affect information processing by regulating the velocity of signal transmission to produce synchronous arrival of synaptic inputs between distant (and multiple) cortical regions. Indeed, myelin plasticity is increasingly being seen as a complementary partner to synaptic plasticity and, as well as being important to nervous system development, it has a major role to play in complex information processing tasks that involve coupling and synchrony among different brain regions. Given that white matter comprises half of the human brain it is perhaps surprising that it has received so little attention in theoretical models of neural network function, especially as the loss of adaptive time-delays is known to exaggerate hyper- and hypo-synchrony of neuronal firing underpinning brain dysfunction including epilepsy and dyslexia. Applied mathematics, and specifically the combination of nonlinear dynamics, network science, and computational learning theory, is a powerful tool that will be used to redress this imbalance. The application of this mathematical work to the human brain will be accelerated by the use of white matter data direct from the Human Connectome Project. In combination with the formulation of myelin plasticity rules, it will allow in silico network studies for the design of new transcranial magnetic stimulation protocols for the treatment of mental health conditions.