  Brain function results from communication between neurons connected by
complex synaptic networks. Synapses are themselves highly complex and diverse
signaling machines, containing protein products of hundreds of different genes,
some in hundreds of copies, arranged in precise lattice at each individual
synapse. Synapses are fundamental not only to synaptic network function but
also to network development, adaptation, and memory. In addition, abnormalities
of synapse numbers or molecular components are implicated in most mental and
neurological disorders. Despite their obvious importance, mammalian synapse
populations have so far resisted detailed quantitative study. In human brains
and most animal nervous systems, synapses are very small and very densely
packed: there are approximately 1 billion synapses per cubic millimeter of
human cortex. This volumetric density poses very substantial challenges to
proteometric analysis at the critical level of the individual synapse. The
present work describes new probabilistic image analysis methods for
single-synapse analysis of synapse populations in both animal and human brains.
