While nearly comprehensive proteome coverage can be achieved from bulk tissue or cultured cells, the data usually lacks spatial resolution. As a result, tissue based proteomics averages protein abundance across multiple cell types and/or localisations. With proteomics platforms lacking sensitivity and throughput to undertake deep single-cell proteome studies to resolve spatial or cell type dependent protein expression gradients within tissue, proteome analysis has been combined with sorting techniques to enrich for certain cell populations. However, the tissue context and spatial resolution is lost in the sorting process. Here, we report an optimised method for the proteomic analysis of neurons isolated from post-mortem human brain by Laser Capture Microdissection (LCM). We tested combinations of sample collection methods, lysis buffers and digestion methods to maximize the number of identifications and quantitative performance, identifying up to 1500 proteins from 60,000 µm2 of cerebellar molecular layer with excellent reproducibility. In order to demonstrate the ability of our workflow to resolve for the first time cell type specific proteomes within a tissue, we isolated sets of individual Betz and Purkinje cells. Both neuronal cell types are involved in motor coordination and were found to express highly specific proteomes to a depth of 2800 to 3600 proteins.