Georgia Institute of Technology College of Sciences

We study to what extent cortical columns with their particular wiring, could boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of the expected enhancement. It is on a mesoscopic?intercolumnar?scale that the wiring among the columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks and we exhibit corroborating evidence for this suggestion. Despite the current emphasis on simpler, e.g., critical, networks, networks with more than one connectivity decay behavior may be the rule rather than the exception. Ref: Beyond Scale-Free Small-World Networks: Cortical Columns for Quick Brains Ralph Stoop, Victor Saase, Clemens Wagner, Britta Stoop, and Ruedi Stoop, PRL 108105 (2013)

We prove the dcdc conjecture in a class of lean fork graphs, argue that this class is substantial and show a path towards the complete solution. Joint work with Andrea Jimenez.

Given a family of ideals which are symmetric under some group action on the variables, a natural question to ask is whether the generating set stabilizes up to symmetry as the number of variables tends to infinity. We answer this in the affirmative for a broad class of toric ideals, settling several open questions in work by Aschenbrenner-Hillar, Hillar-Sullivant, and Hillar-Martin del Campo. The proof is largely combinatorial, making use of matchings on bipartite graphs, and well-partial orders.