Families that fire together smile together: Resting state connectome similarity and daily emotional synchrony in parent-child dyads

Despite emerging evidence suggesting a biological basis to our social tiles, our understanding of the neural processes which link two minds is unknown. We implemented a novel approach, which included connectome similarity analysis using resting state intrinsic networks of parent-child dyads as well as daily diaries measured across 14 days. Intrinsic resting-state networks for both parents and their adolescent child were identified using independent component analysis (ICA). Results indicate that parents and children who had more similar RSN connectome also had more similar day-to-day emotional synchrony. Furthermore, dyadic RSN connectome similarity was associated with children's emotional competence, suggesting that being neurally in-tune with their parents confers emotional benefits. We provide the first evidence that dyadic RSN similarity is associated with emotional synchrony in what is often our first and most essential social bond, the parent-child relationship

Clutter removal of near-field UWB SAR imaging for pipeline penetrating radar

Recently, ultrawideband (UWB) near-field synthetic aperture radar (SAR) imaging has been proposed for pipeline penetrating radar applications thanks to its capability in providing suitable resolution and penetration depth. Because of geometrical restrictions, there are many complicated sources of clutter in the pipe. However, this issue has not been investigated yet. In this article, we investigate some well-known clutter removal algorithms using full-wave simulated data and compare their results considering image quality, signal to clutter ratio and contrast. Among candidate algorithms, two-dimensional singular spectrum analysis (2-D SSA) shows a good potential to improve the signal to clutter ratio. However, basic 2-D SSA produces some artifacts in the image. Therefore, to mitigate this issue, we propose “modified 2-D SSA.” After developing the suitable clutter removal algorithm, wepropose a complete algorithm chain for pipeline imaging. An UWB nearfieldSARmonitoring system including anUWBM-sequence sensor and automatic positioner are implemented and the image of drilled perforations in a concrete pipe mimicking oil well structure as a case study is reconstructed to test the proposed algorithm. Compared to the literature, a comprehensive near-field SAR imaging algorithm including new clutter removal is proposed and its performance is verified by obtaining high-quality images in experimental results

Recent Applications in Graph Theory

Graph theory, being a rigorously investigated field of combinatorial mathematics, is adopted by a wide variety of disciplines addressing a plethora of real-world applications. Advances in graph algorithms and software implementations have made graph theory accessible to a larger community of interest. Ever-increasing interest in machine learning and model deployments for network data demands a coherent selection of topics rewarding a fresh, up-to-date summary of the theory and fruitful applications to probe further. This volume is a small yet unique contribution to graph theory applications and modeling with graphs. The subjects discussed include information hiding using graphs, dynamic graph-based systems to model and control cyber-physical systems, graph reconstruction, average distance neighborhood graphs, and pure and mixed-integer linear programming formulations to cluster networks

Brain-Computer Interface

Brain-computer interfacing (BCI) with the use of advanced artificial intelligence identification is a rapidly growing new technology that allows a silently commanding brain to manipulate devices ranging from smartphones to advanced articulated robotic arms when physical control is not possible. BCI can be viewed as a collaboration between the brain and a device via the direct passage of electrical signals from neurons to an external system. The book provides a comprehensive summary of conventional and novel methods for processing brain signals. The chapters cover a range of topics including noninvasive and invasive signal acquisition, signal processing methods, deep learning approaches, and implementation of BCI in experimental problems

Magnetoencephalography

This is a practical book on MEG that covers a wide range of topics. The book begins with a series of reviews on the use of MEG for clinical applications, the study of cognitive functions in various diseases, and one chapter focusing specifically on studies of memory with MEG. There are sections with chapters that describe source localization issues, the use of beamformers and dipole source methods, as well as phase-based analyses, and a step-by-step guide to using dipoles for epilepsy spike analyses. The book ends with a section describing new innovations in MEG systems, namely an on-line real-time MEG data acquisition system, novel applications for MEG research, and a proposal for a helium re-circulation system. With such breadth of topics, there will be a chapter that is of interest to every MEG researcher or clinician

Pen-type electrodermal activity sensing system for stress detection based on likelihood ratios

Master of ScienceDepartment of Electrical and Computer EngineeringSteven WarrenPsychological stress experienced during academic testing is known to be a significant performance factor for some students. While a student may be able to recognize and self-report stress experienced during an exam, unobtrusive tools to track stress in real time (and in association with specific test problems) are lacking. This effort pursued the design and initial assessment of an electrodermal activity (EDA) sensor - essentially a sweat sensor - mounted to a pen/pencil 'trainer:' a holder into which a pen/pencil is inserted that can help a person learn how to properly grip a writing instrument. This small assembly was held in the hand of a given subject during early human subject experiments and can be used for follow-on, mock test-taking scenarios. Data were acquired with this handheld device for 37 subjects (Kansas State University Internal Review Board Protocol #9864) while they each viewed approximately 30 minutes of emotion-evoking videos. Data collected by the EDA sensor were processed with an EDA signal processing app, which calculated and stored parameters associated with significant phasic EDA peaks. These peak data were then evaluated by a hypothesis driven stress-detection test that employed an approach using likelihood ratios for the ‘relaxed’ and ‘stressed’ groups. For these initial, motion-free testing scenarios, this pen-type EDA sensing system was able to discern which phasic responses were associated with ‘relaxed’ versus ‘stressed’ responses with 85% accuracy, where subject self-assessments of perceived stress levels were used to establish ground truth

Electroencephalography (EEG) as a Research Tool in the Information Systems Discipline: Foundations, Measurement, and Applications

The concept of neuro-information systems (neuroIS) has emerged in the IS discipline recently. Since the neuroIS field’s genesis, several neuroIS papers have been published. Investigating empirical papers published in scientific journals and conference proceedings reveals that electroencephalography (EEG) is a widely used tool. Thus, considering its relevance in contemporary research and the fact that it will also play a major role in future neuroIS research, we describe EEG from a layman’s perspective. Because previous EEG descriptions in the neuroIS literature have only scantily outlined theoretical and methodological aspects related to this tool, we urgently need a more thorough one. As such, we inform IS scholars about the fundamentals of EEG in a compact way and discuss EEG’s potential for IS research. Based on the knowledge base provided in this paper, IS researchers can make an informed decision about whether EEG could, or should, become part of their toolbox

A multimodal investigation in eye movements

While functional magnetic resonance imaging (fMRI) has identified which regions of interest (ROIs) are functionally active during a vergence movement (inward or outward eye rotation), task-modulated coactivation between ROIs is less understood. This study tests the following hypotheses: (1) significant task-modulated coactivation would be observed between the frontal eye fields (FEFs), the posterior parietal cortex (PPC), and the cerebellar vermis (CV); (2) significantly more functional activity and task-modulated coactivation would be observed in binocularly normal controls (BNCs) compared with convergence insufficiency (CI) subjects; and (3) after vergence training, the functional activity and task-modulated coactivation would increase in CIs compared with their baseline measurements. A block design of sustained fixation versus vergence eye movements stimulates activity in the FEFs, PPC, and CV. fMRI data from four CI subjects before and after vergence training are compared with seven BNCs. Functional activity is assessed using the blood oxygenation level dependent (BOLD) percent signal change. Task-modulated coactivation is assessed using an ROI-based task modulated coactivation analysis that reveals significant correlation between ROIs

Characterization of the angular memory effect of scattered light in biological tissues.

This is the final version of the article. Available via open access from Optical Society of America via the DOI in this record.High resolution optical microscopy is essential in neuroscience but suffers from scattering in biological tissues and therefore grants access to superficial brain layers only. Recently developed techniques use scattered photons for imaging by exploiting angular correlations in transmitted light and could potentially increase imaging depths. But those correlations ('angular memory effect') are of a very short range and should theoretically be only present behind and not inside scattering media. From measurements on neural tissues and complementary simulations, we find that strong forward scattering in biological tissues can enhance the memory effect range and thus the possible field-of-view by more than an order of magnitude compared to isotropic scattering for ∼1 mm thick tissue layers.This work was funded by European Research Council Grant 278025 and the Agence Nationale de la Recherche (Investissements d’Avenir ANR-10-LABX-54 MEMO LIFE, ANR-11-IDEX- 0001-02 PSL* Research University). We thank Prof. Georg Maret for enabling Sam Schott’s stay at institut Langevin and his support of the project and David Martina for technical help in the development of the experimental setup