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

Networks of neurons are the primary substrate of information processing. Conversely, blood vessels in the brain are generally viewed to have physiological functions unrelated to information processing, such as the timely supply of oxygen, and other nutrients to the neural tissue. However, recent studies have shown that cerebral microvessels, like neurons, exhibit tuned responses to sensory stimuli. Tuned neural responses to sensory stimuli may be enhanced with experience-dependent Hebbian plasticity and other forms of learning. Hence, it is possible that the microvascular network might also be subject to some form of 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 modelled the cortical neurovascular network by interconnecting two laterally connected self-organizing networks. The afferent and lateral connections of the neural and vascular networks 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 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 determines whether the cortical neural map develops into a clustered vs. salt-and-pepper organization.