Background Neuroinflammation is an underlying pathology of all neurological conditions, the understanding of which is still being comprehended. A specific molecular pathway that has been overlooked in neuroinflammation is glycosylation (i.e., post-translational addition of glycans to the protein structure). N-glycosylation is a specific type of glycosylation with a cardinal role in the central nervous system (CNS), which is highlighted by congenital glycosylation diseases that result in neuropathological symptoms such as epilepsy and mental retardation. Changes in N-glycosylation can ultimately affect glycoproteins’ functions, which will have an impact on cell machinery. Therefore, characterisation of N-glycosylation alterations in a neuroinflammatory scenario can provide a potential target for future therapies. Methods With that aim, the unilateral intrastriatal injection of lipopolysaccharide (LPS) in the adult rat brain was used as a model of neuroinflammation. In vivo and post-mortem, quantitative and spatial characterisation of both neuroinflammation and N-glycome was performed at 1-week post-injection of LPS. These aspects were investigated through a multifaceted approach based on positron emission tomography (PET), quantitative histology, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), liquid chromatography and matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI). Results In the brain region showing LPS-induced neuroinflammation, a significant decrease in the abundance of sialylated and core fucosylated structures was seen (approximately 7.5% and 8.5%, respectively), whereas oligomannose N-glycans were significantly increased (13.5%). This was confirmed by MALDI-MSI, which provided a high-resolution spatial distribution of N-glycans, allowing precise comparison between normal and diseased brain hemispheres. Conclusions Together, our data show for the first time the complete profiling of N-glycomic changes in a well-characterised animal model of neuroinflammation. These data represent a pioneering step to identify critical targets that may modulate neuroinflammation in neurodegenerative diseases.