Neuron-specific enolase (NSE) has been suggested as a prognostic biomarker for neuronal alterations resulting from conditions such as traumatic brain injury (TBI), neurodegenerative disease, or cardiac arrest. To validate serum NSE (sNSE) as a brain-specific biomarker, we related it to functional brain imaging data in 38 healthy adults to create a physiological framework for future studies in neuropsychiatric diseases. sNSE was measured by monoclonal two-site immunoluminometric assays, and functional connectivity was investigated with resting-state functional magnetic resonance imaging (rfMRI). To identify neural hubs most essentially related to sNSE, we applied graph theory approaches, namely, the new data-driven and parameter-free approach, eigenvector centrality mapping. sNSE and eigenvector centrality were negatively correlated in the female cerebellum, without any effects in male subjects. In cerebellar cortex, NSE expression was significantly higher than whole-brain expression as investigated in the whole brain and whole genome-wide atlas of the Allen Institute for Brain Sciences (Seattle, WA). Our study shows a specific linkage between the neuronal marker protein, sNSE, and cerebellar connectivity as measured with rfMRI in the female human brain, although this finding shall be proven in future studies including more subjects. Results suggest that the inclusion of sNSE in the analysis of imaging data is a useful approach to obtain more-specific information on the neuronal mechanisms that underlie functional connectivity at rest. Establishing such a baseline resting-state pattern that is tied to a neuronal serum marker opens new perspectives in the characterization of neuropsychiatric disorders as disconnective syndromes or nexopathies, in particular, resulting from TBI, neurodegenerative disease, or cardiac arrest, in the future.