The development of bi-directionally coupled self-organizing neurovascular networks captures orientation-selective neural and hemodynamic cortical responses

Abstract

AbstractThe network of neurons in the brain is considered the primary substrate of information processing. Despite growing evidence on the possible role of cerebral blood flow in information processing, the cerebrovascular network is generally viewed as an irrigation system that ensures a timely supply of oxygen, glucose, and nutrients to the neural tissue. However, a recent study has shown that cerebral microvessels, like neurons, also exhibit tuned responses to sensory stimuli. Tuned neural responses to sensory stimuli are certainly enhanced with experience-dependent Hebbian plasticity and other forms of learning. Hence it is possible that the densely interconnected microvascular network might also be subject to some form of plasticity or competitive learning rules during early postnatal development such that its fine-scale structure becomes optimized for metabolic delivery to a given neural micro-architecture. To explore the possibility of adaptive lateral interactions and tuned responses in cerebral microvessels, we modeled the cortical neurovascular network by interconnecting two laterally connected self-organizing networks (Laterally Interconnected Synergetically Self-Organizing Map - LISSOM). The afferent and lateral connections of the LISSOM were defined by trainable weights. By varying the topology of lateral connectivity in the vascular network layer, we observed that the partial correspondence of feature selectivity between neural and hemodynamic responses could be explained by lateral coupling across local blood vessels such that the central domain receives an excitatory drive of more blood flow and a more distal surrounding region where blood flow is reduced. Critically, our simulations suggest a new role for feedback from the vascular to the neural network because the radius of vascular perfusion seems to determine whether the cortical neural map develops into a clustered and columnar vs. salt-and-pepper organization.