An introduction to time-resolved decoding analysis for M/EEG

The human brain is constantly processing and integrating information in order to make decisions and interact with the world, for tasks from recognizing a familiar face to playing a game of tennis. These complex cognitive processes require communication between large populations of neurons. The non-invasive neuroimaging methods of electroencephalography (EEG) and magnetoencephalography (MEG) provide population measures of neural activity with millisecond precision that allow us to study the temporal dynamics of cognitive processes. However, multi-sensor M/EEG data is inherently high dimensional, making it difficult to parse important signal from noise. Multivariate pattern analysis (MVPA) or "decoding" methods offer vast potential for understanding high-dimensional M/EEG neural data. MVPA can be used to distinguish between different conditions and map the time courses of various neural processes, from basic sensory processing to high-level cognitive processes. In this chapter, we discuss the practical aspects of performing decoding analyses on M/EEG data as well as the limitations of the method, and then we discuss some applications for understanding representational dynamics in the human brain

Statistical features of the thermal neutron capture cross sections

We discuss the existence of huge thermal neutron capture cross sections in several nuclei. The values of the cross sections are several orders of magnitude bigger than expected at these very low energies. We lend support to the idea that this phenomenon is random in nature and is similar to what we have learned from the study of parity violation in the actinide region. The idea of statistical doorways is advanced as a unified concept in the delineation of large numbers in the nuclear world. The average number of maxima per unit mass, $$ in the capture cross section is calculated and related to the underlying cross section correlation function and found to be $= 3/(\pi \sqrt{2}\gamma_{A})$, where $\gamma_{A}$ is a characteristic mass correlation width which designates the degree of remnant coherence in the system. We trace this coherence to nucleosynthesis which produced the nuclei whose neutron capture cross sections are considered here.Comment: 7 pages, 6 figures. To appear in Acta Physica Polonica B as a Contribution to the proceedings of:Jagiellonian Symposium of Fundamental and Applied Subatomic Physics, June 7- 12, 2015 Krakow, Polan

Noise Predictions for STM in Systems with Local Electron Nematic Order

We propose that thermal noise in local stripe orientation should be readily detectable via STM on systems in which local stripe orientations are strongly affected by quenched disorder. Stripes, a unidirectional, nanoscale modulation of electronic charge, are strongly affected by quenched disorder in two-dimensional and quasi-two-dimensional systems. While stripe orientations tend to lock to major lattice directions, dopant disorder locally breaks rotational symmetry. In a host crystal with otherwise $C_4$ rotational symmetry, stripe orientations in the presence of quenched disorder map to the random field Ising model. While the low temperature state of such a system is generally a stripe glass in two dimensional or strongly layered systems, as the temperature is raised, stripe orientational fluctuations become more prevalent. We propose that these thermally excited fluctuations should be readily detectable in scanning tunneling spectroscopy as {\em telegraph noise} in the high voltage part of the local $I(V)$ curves. We predict the spatial, temporal, and thermal evolution of such noise, including the circumstances under which such noise is most likely to be observed. In addition, we propose an in-situ test, amenable to any local scanning probe, for assessing whether such noise is due to correlated fluctuations rather than independent switchers.Comment: 8 pages, 8 figure

Hysteresis and Noise from Electronic Nematicity in High Temperature Superconductors

An electron nematic is a translationally invariant state which spontaneously breaks the discrete rotational symmetry of a host crystal. In a clean square lattice, the electron nematic has two preferred orientations, while dopant disorder favors one or the other orientations locally. In this way, the electron nematic in a host crystal maps to the random field Ising model (RFIM). Since the electron nematic has anisotropic conductivity, we associate each Ising configuration with a resistor network, and use what is known about the RFIM to predict new ways to test for electron nematicity using noise and hysteresis. In particular, we have uncovered a remarkably robust linear relation between the orientational order and the resistance anisotropy which holds over a wide range of circumstances.Comment: References added; minor wording change

Primer selection impacts specific population abundances but not community dynamics in a monthly time-series 16S rRNA gene amplicon analysis of coastal marine bacterioplankton.

Primers targeting the 16S small subunit ribosomal RNA marker gene, used to characterize bacterial and archaeal communities, have recently been re-evaluated for marine planktonic habitats. To investigate whether primer selection affects the ecological interpretation of bacterioplankton populations and community dynamics, amplicon sequencing with four primer sets targeting several hypervariable regions of the 16S rRNA gene was conducted on both mock communities constructed from cloned 16S rRNA genes and a time-series of DNA samples from the temperate coastal Santa Barbara Channel. Ecological interpretations of community structure (delineation of depth and seasonality, correlations with environmental factors) were similar across primer sets, while population dynamics varied. We observed substantial differences in relative abundances of taxa known to be poorly resolved by some primer sets, such as Thaumarchaeota and SAR11, and unexpected taxa including Roseobacter clades. Though the magnitude of relative abundances of common OTUs differed between primer sets, the relative abundances of the OTUs were nonetheless strongly correlated. We do not endorse one primer set but rather enumerate strengths and weaknesses to facilitate selection appropriate to a system or experimental goal. While 16S rRNA gene primer bias suggests caution in assessing quantitative population dynamics, community dynamics appear robust across studies using different primers