Reconciling Predictive Coding and Biased Competition Models of Cortical Function

A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding. Specifically, it is shown that a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the inputs to a cortical region, is mathematically equivalent to the linear predictive coding model. This observation demonstrates that these two important and influential rival theories of cortical function are minor variations on the same underlying mathematical model

CAMMUAZA, or the ceremony used at the Induction of a Birman into the Order of Priesthood, called Phonghi, or Rhahaan (1795) by Michael Symes, edited by Michael W. Charney

This account of the induction ceremony for Buddhist monks was included as Appendix V in Michael Symes, An Acount of an Embassy to the Kingdom of Ava, Sent by the Governor-General of India in the Year 1795 (London: W. Bulmer & Co., 496-500). Symes, then a major in the 76th Regiment, made numerous valuable observations on Burmese culture, society, government, and history. While it is clear that he did consult the accounts of other visitors to Burma, most of his material was derived from first-hand observation or from material provided by Burmese acquaintances, and the following account was likely derived from the latter

Morphological and population genomic evidence that human faces have evolved to signal individual identity.

Facial recognition plays a key role in human interactions, and there has been great interest in understanding the evolution of human abilities for individual recognition and tracking social relationships. Individual recognition requires sufficient cognitive abilities and phenotypic diversity within a population for discrimination to be possible. Despite the importance of facial recognition in humans, the evolution of facial identity has received little attention. Here we demonstrate that faces evolved to signal individual identity under negative frequency-dependent selection. Faces show elevated phenotypic variation and lower between-trait correlations compared with other traits. Regions surrounding face-associated single nucleotide polymorphisms show elevated diversity consistent with frequency-dependent selection. Genetic variation maintained by identity signalling tends to be shared across populations and, for some loci, predates the origin of Homo sapiens. Studies of human social evolution tend to emphasize cognitive adaptations, but we show that social evolution has shaped patterns of human phenotypic and genetic diversity as well

When are two Coxeter orbifolds diffeomorphic?

One can define what it means for a compact manifold with corners to be a "contractible manifold with contractible faces." Two combinatorially equivalent, contractible manifolds with contractible faces are diffeomorphic if and only if their 4-dimensional faces are diffeomorphic. It follows that two simple convex polytopes are combinatorially equivalent if and only if they are diffeomorphic as manifolds with corners. On the other hand, by a result of Akbulut, for each n > 3, there are smooth, contractible n-manifolds with contractible faces which are combinatorially equivalent but not diffeomorphic. Applications are given to rigidity questions for reflection groups and smooth torus actions.Comment: 24 page

Approximate Computation and Implicit Regularization for Very Large-scale Data Analysis

Database theory and database practice are typically the domain of computer scientists who adopt what may be termed an algorithmic perspective on their data. This perspective is very different than the more statistical perspective adopted by statisticians, scientific computers, machine learners, and other who work on what may be broadly termed statistical data analysis. In this article, I will address fundamental aspects of this algorithmic-statistical disconnect, with an eye to bridging the gap between these two very different approaches. A concept that lies at the heart of this disconnect is that of statistical regularization, a notion that has to do with how robust is the output of an algorithm to the noise properties of the input data. Although it is nearly completely absent from computer science, which historically has taken the input data as given and modeled algorithms discretely, regularization in one form or another is central to nearly every application domain that applies algorithms to noisy data. By using several case studies, I will illustrate, both theoretically and empirically, the nonobvious fact that approximate computation, in and of itself, can implicitly lead to statistical regularization. This and other recent work suggests that, by exploiting in a more principled way the statistical properties implicit in worst-case algorithms, one can in many cases satisfy the bicriteria of having algorithms that are scalable to very large-scale databases and that also have good inferential or predictive properties.Comment: To appear in the Proceedings of the 2012 ACM Symposium on Principles of Database Systems (PODS 2012

Prospects for Burma After Aung San Suu Kyi’s Release (ARI)

Aung San Suu Kyi’s release coincided with the holding of national elections for a military-designed state to provide the ruling junta with a veneer of legitimacy. Nevertheless, the lifting of sanctions will remain the central issue facing Burma’s relations with foreign countries, which will have to balance out human rights issues and investment opportunities. Aung San Suu Kyi and her treatment by the new government will play a determining role in deciding this issue