He introduced the term Computational Neuroscience through the organization of a conference with this title which took place in Carmel California in 1985, under the sponsorship of the Systems Development Foundation.
Variants of this algorithm, especially the recent improvements contributed in the thesis work of Mukund Balasubramanian (see [15] Archived 2010-07-28 at the Wayback Machine) underlie most current quantitatively accurate approaches to cortical flattening.
In 1977, Schwartz pointed out that the hypercolumn model of Hubel and Weisel implied the existence of a periodic vortex like pattern of orientation singularities across the surface of visual cortex.
This observation was later used, via monte-carlo simulation of photon scattering in brain tissue, to demonstrate that much of modern optical recording "pin-wheel" structure is significantly contaminated by artifact due to the topological production and annihilation of spurious cortical pin-wheels, due to the low-pass nature of current optical recording, which has an intrinsic physical smoothing in the range of 300 micrometres [18] Archived 2008-07-25 at the Wayback Machine.
In addition to this work in brain imaging and functional neuroanatomy, Schwartz has developed a number of algorithms and robotic devices, related to the field of space-variant computer vision.
The key motivation for this work is the observations of detailed spatial structure in biological visual systems, related to the strongly space-variant (i.e. foveal) architecture.