The Influence of Neural Activity and Neural Cytoarchitecture on Cerebrovascular Arborization: A Computational Model

Abstract

Normal functioning of the brain relies on a continual and efficient delivery of energy by a vast network of cerebral blood vessels. The bidirectional coupling between neurons and blood vessels consists of vasodilatory energy demand signals from neurons to blood vessels, and the retrograde flow of energy substrates from the vessels to neurons, which fuel neural firing, growth and other housekeeping activities in the neurons. Recent works indicate that, in addition to the functional coupling observed in the adult brain, the interdependence between the neural and vascular networks begins at the embryonic stage, and continues into subsequent developmental stages. The proposed Vascular Arborization Model (VAM) captures the effect of neural cytoarchitecture and neural activity on vascular arborization. The VAM describes three important stages of vascular tree growth: (i) The prenatal growth phase, where the vascular arborization depends on the cytoarchitecture of neurons and non-neural cells, (ii) the post-natal growth phase during which the further arborization of the vasculature depends on neural activity in addition to neural cytoarchitecture, and (iii) the settling phase, where the fully grown vascular tree repositions its vascular branch points or nodes to ensure minimum path length and wire length. The vasculature growth depicted by VAM captures structural characteristics like vascular volume density, radii, mean distance to proximal neurons in the cortex. VAM-grown vasculature agrees with the experimental observation that the neural densities do not covary with the vascular density along the depth of the cortex but predicts a high correlation between neural areal density and microvascular density when compared over a global scale (across animals and regions). To explore the influence of neural activity on vascular arborization, the VAM was used to grow the vasculature in neonatal rat whisker barrel cortex under two conditions: (i) Control, where the whiskers were intact and (ii) Lesioned, where one row of whiskers was cauterized. The model captures a significant reduction in vascular branch density in lesioned animals compared to control animals, concurring with experimental observation.

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

“…Although vessel location seems independent of map structure, there is a correlation between neural activity levels and vascular structure. Both experimental and modelling studies show that neural cytoarchitecture and neural activity levels influence vascular density, including higher capillary density in the more active layer 4 relative to layer 2/3 (Alonso & Martinez, 1998; Cho et al, 2022; Kumar et al, 2022; Lacoste et al, 2014). In our model, a higher vascular density could correspond to a smaller perfusion field (as explained above).…”

Could theropod dinosaurs have evolved to a human level of intelligence?

“…The greater size and axon length requirement than with a mammalian type of cortical organization might also have introduced problems of metabolic and thermoregulatory support of such an expanded brain (Heldstab et al., 2022; Hofman, 2014; Karbowski, 2014; Laughlin & Sejnowski, 2003; Pontzer et al., 2016; Sherwood et al., 2012), and thereby additionally limited the extent of expansion possible. Note that although an increase in pallial neuron density in a primate‐like theropod lineage could theoretically have compensated for the problems described above, there is likely to be a limit on neuron cell body packing density, due to the need for space for blood vessels for metabolic support (Kaas & Preuss, 2014; Kumar et al., 2022; Ventura‐Antunes & Herculano‐Houzel, 2023), dendrites for the plasticity underlying learning and cognition (Chklovskii et al., 2002; Harris, 1999; Segal, 2017; Spires‐Jones & Knafo, 2012), and glia for neuronal and axonal support (Hughes, 2012; Lenz & Nelson, 2018; Newman, 2003; Sierra et al., 2014; Simons & Nave, 2016; Wilson, 1997).…”