Learning invariances with stationary subspace analysis

Recently, a novel subspace decomposition method, termed 'Stationary Subspace Analysis' (SSA), has been proposed by Bünau et al. [10]. SSA aims to find a linear projection to a lower dimensional subspace such that the distribution of the projected data does not change over successive epochs or sub-datasets. We show that by modifying the loss function and the optimization procedure we can obtain an algorithm that is both faster and more accurate. We discuss the problem of indeterminacies and provide a lower bound on the number of epochs that is needed. Finally, we show in an experiment with simulated image patches, that SSA can be used favourably in invariance learning

Estimating true brain connectivity from EEG/MEG data invariant to linear and static transformations in sensor space

The imaginary part of coherency is a measure to investigate the synchronization of brain sources on the EEG/MEG sensor level, robust to artifacts of volume conduction meaning that independent sources cannot generate a significant result. It does not mean, however, that volume conduction is irrelevant when true interactions are present. Here, we analyze in detail the possibilities to construct measures of true brain interactions which are strictly invariant to linear spatial transformations of the sensor data. Specifically, such measures can be constructed from maximization of imaginary coherency in virtual channels, bivariate measures as a corrected variate of imaginary coherence, and global measures indicating the total interaction contained within a space or between two spaces. A complete theoretic framework on this question is provided for second order statistical moments. Relations to existing linear and nonlinear approaches are presented. We applied the methods to resting state EEG data, showing clear interactions at all bands, and to a combined measurement of EEG and MEG during rest condition and a finger tapping task. We found that MEG was capable of observing brain interactions which were not observable in the EEG data

Gnosis, science, and mysticism: A history of self-referential theory designs

In this paper, we understand we advent of a ''scientific spirit'' as a revival of Gnosticism, which proclaims the superiority of man over his creator and considers knowledge (gnosis) to be the key to salvation. Salvation is here understood as from of ''emancipation''. Empirically, toe see our interpretation confirmed in the tremendous influence of the Corpus Hermeticum and the Lurianic Cabala on all the Renaissance scientists. In the second part of this essay, we continue a line of research inaugurated by Ferdinand Christian Baur in the 19th century, and look for Gnostic outlooks in contemporary philosophy and social science. By reading Niklas Luhmann's systems theory as a modem version of Gnostic mysticism, we do not intend to dismiss the relevance of his work. For if Gnosticism defines ''modernity'', we should not be surprised to find a speculative Gnostic system among society's self-descriptions

Tetrapyrrole Metabolism in Arabidopsis thaliana

Higher plants produce four classes of tetrapyrroles, namely, chlorophyll (Chl), heme, siroheme, and phytochromobilin. In plants, tetrapyrroles play essential roles in a wide range of biological activities including photosynthesis, respiration and the assimilation of nitrogen/sulfur. All four classes of tetrapyrroles are derived from a common biosynthetic pathway that resides in the plastid. In this article, we present an overview of tetrapyrrole metabolism in Arabidopsis and other higher plants, and we describe all identified enzymatic steps involved in this metabolism. We also summarize recent findings on Chl biosynthesis and Chl breakdown. Recent advances in this field, in particular those on the genetic and biochemical analyses of novel enzymes, prompted us to redraw the tetrapyrrole metabolic pathways. In addition, we also summarize our current understanding on the regulatory mechanisms governing tetrapyrrole metabolism. The interactions of tetrapyrrole biosynthesis and other cellular processes including the plastid-to-nucleus signal transduction are discussed