Granular Layer Neurons Control Cerebellar Neurovascular Coupling Through an NMDA Receptor/NO-Dependent System.

Neurovascular coupling (NVC) is the process whereby neuronal activity controls blood vessel diameter. In the cerebellum, the molecular layer is regarded as the main NVC determinant. However, the granular layer is a region with variable metabolic demand caused by large activity fluctuations that shows a prominent expression of NMDA receptors (NMDARs) and nitric oxide synthase (NOS) and is therefore much more suitable for effective NVC. Here, we show, in the granular layer of acute rat cerebellar slices, that capillary diameter changes rapidly after mossy fiber stimulation. Vasodilation required neuronal NMDARs and NOS stimulation and subsequent guanylyl cyclase activation that probably occurred in pericytes. Vasoconstriction required metabotropic glutamate receptors and CYP ω-hydroxylase, the enzyme regulating 20-hydroxyeicosatetraenoic acid production. Therefore, granular layer capillaries are controlled by the balance between vasodilating and vasoconstricting systems that could finely tune local blood flow depending on neuronal activity changes at the cerebellar input stage. SIGNIFICANCE STATEMENT The neuronal circuitry and the biochemical pathways that control local blood flow supply in the cerebellum are unclear. This is surprising given the emerging role played by this brain structure, not only in motor behavior, but also in cognitive functions. Although previous studies focused on the molecular layer, here, we shift attention onto the mossy fiber granule cell (GrC) relay. We demonstrate that GrC activity causes a robust vasodilation in nearby capillaries via the NMDA receptors-neuronal nitric oxide synthase signaling pathway. At the same time, metabotropic glutamate receptors mediate 20-hydroxyeicosatetraenoic acid-dependent vasoconstriction. These results reveal a complex signaling network that hints for the first time at the granular layer as a major determinant of cerebellar blood-oxygen-level-dependent signals.