A Complex Network Approach to Topographical Connections

The neuronal networks in the mammals cortex are characterized by the coexistence of hierarchy, modularity, short and long range interactions, spatial correlations, and topographical connections. Particularly interesting, the latter type of organization implies special demands on the evolutionary and ontogenetic systems in order to achieve precise maps preserving spatial adjacencies, even at the expense of isometry. Although object of intensive biological research, the elucidation of the main anatomic-functional purposes of the ubiquitous topographical connections in the mammals brain remains an elusive issue. The present work reports on how recent results from complex network formalism can be used to quantify and model the effect of topographical connections between neuronal cells over a number of relevant network properties such as connectivity, adjacency, and information broadcasting. While the topographical mapping between two cortical modules are achieved by connecting nearest cells from each module, three kinds of network models are adopted for implementing intracortical connections (ICC), including random, preferential-attachment, and short-range networks. It is shown that, though spatially uniform and simple, topographical connections between modules can lead to major changes in the network properties, fostering more effective intercommunication between the involved neuronal cells and modules. The possible implications of such effects on cortical operation are discussed.Comment: 5 pages, 5 figure

A Qualitative Exploration of Using Experiential Groups to Train Future Group Counselors

As counselors routinely provide both individual and group-based services, it is important to prepare trainees to effectively utilize both approaches. One popular method for engaging students in group work training requires them to participate in experiential small groups. Although this requirement meets CACREP’s (2015) standard that students engage in 10 hours of group membership, less specific focus is placed on engaging students in active group facilitation training. This study analyzes qualitative interviews with seven counseling graduates who participated in experiential small groups during their training. Five emergent themes provide insight for counselor educators and accreditors into students’ group training experiences

Artificially cemented sand under multiaxial loading

Distinct improvement techniques can be used when civil engineering structures are to be built on soils that do not present suitable mechanical characteristics. The soil improvement techniques can vary from compaction to chemical and mechanical stabilisation. This work focuses on the specific case of granular soils treated with low amount of cement. The study aims to investigate the behaviour of a cemented sand under multiaxial loading conditions. A series of advanced tests on reconstituted cemented sand were conducted in a Cubical Cell Apparatus (CCA) and exploration of material response including failure limits under different constant stress paths (θ = 0° and θ = 120°) in the octahedral (π) plane were performed. Results showed strength is higher in vertical direction than in horizontal direction

Divergence Measure Between Chaotic Attractors

We propose a measure of divergence of probability distributions for quantifying the dissimilarity of two chaotic attractors. This measure is defined in terms of a generalized entropy. We illustrate our procedure by considering the effect of additive noise in the well known H\'enon attractor. Comparison of two H\'enon attractors for slighly different parameter values, has shown that the divergence has complex scaling structure. Finally, we show how our approach allows to detect non-stationary events in a time series.Comment: 9 pages, 6 figure

Wavelet analysis of epileptic spikes

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous, pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.Comment: 4 pages, 3 figure