Editorial: Bridging Scales and Levels

Network neuroscience strives to understand the networks of the brain on all spatiotemporal scales and levels of observation. Current experimental and theoretical capabilities are beginning to facilitate a more holistic perspective, uniting these networks. This focus feature, “Bridging Scales and Levels,” aims to document current research and looks to future progress towards this vision

NiCE Teacher Workshop: Engaging K-12 Teachers in the Development of Curricular Materials That Utilize Complex Networks Concepts

Our educational systems must prepare students for an increasingly interconnected future, and teachers require equipping with modern tools, such as network science, to achieve this. We held a Networks in Classroom Education (NiCE) workshop for a group of 21 K-12 teachers with various disciplinary backgrounds. The explicit aim of this was to introduce them to concepts in network science, show them how these concepts can be utilized in the classroom, and empower them to develop resources, in the form of lesson plans, for themselves and the wider community. Here we detail the nature of the workshop and present its outcomes - including an innovative set of publicly available lesson plans. We discuss the future for successful integration of network science in K-12 education, and the importance of inspiring and enabling our teachers.Comment: 11 pages, 4 figures, 2 table

Caenorhabditis elegans and the network control framework-FAQs.

Control is essential to the functioning of any neural system. Indeed, under healthy conditions the brain must be able to continuously maintain a tight functional control between the system's inputs and outputs. One may therefore hypothesize that the brain's wiring is predetermined by the need to maintain control across multiple scales, maintaining the stability of key internal variables, and producing behaviour in response to environmental cues. Recent advances in network control have offered a powerful mathematical framework to explore the structure-function relationship in complex biological, social and technological networks, and are beginning to yield important and precise insights on neuronal systems. The network control paradigm promises a predictive, quantitative framework to unite the distinct datasets necessary to fully describe a nervous system, and provide mechanistic explanations for the observed structure and function relationships. Here, we provide a thorough review of the network control framework as applied to Caenorhabditis elegans (Yan et al. 2017 Nature550, 519-523. (doi:10.1038/nature24056)), in the style of Frequently Asked Questions. We present the theoretical, computational and experimental aspects of network control, and discuss its current capabilities and limitations, together with the next likely advances and improvements. We further present the Python code to enable exploration of control principles in a manner specific to this prototypical organism.This article is part of a discussion meeting issue 'Connectome to behaviour: modelling C. elegans at cellular resolution'

Practitioners' Perceptions of the Soccer Extra-Time Period: Implications for Future Research

Qualitative research investigating soccer practitioners’ perceptions can allow researchers to create practical research investigations. The extra-time period of soccer is understudied compared to other areas of soccer research. Using an open-ended online survey containing eleven main and nine sub questions, we gathered the perceptions of extra-time from 46 soccer practitioners, all working for different professional soccer clubs. Questions related to current practices, views on extra-time regulations, and ideas for future research. Using inductive content analysis, the following general dimensions were identified: ‘importance of extra-time’, ‘rule changes’, ‘efficacy of extra-time hydro-nutritional provision’, ‘nutritional timing’, ‘future research directions’, ‘preparatory modulations’ and ‘recovery’. The majority of practitioners (63%) either agreed or strongly agreed that extra-time is an important period for determining success in knockout football match-play. When asked if a fourth substitution should be permitted in extra-time, 67% agreed. The use of hydro-nutritional strategies prior to extra-time was predominately considered important or very important. However; only 41% of practitioners felt that it was the most important time point for the use of nutritional products. A similar number of practitioners account (50%) and do not (50%) account for the potential of extra-time when training and preparing players and 89% of practitioners stated that extra-time influences recovery practices following matches. In the five minute break prior to extra-time, the following practices (in order of priority) were advocated to players: hydration, energy provision, massage, and tactical preparations. Additionally, 87% of practitioners advocate a particular nutritional supplementation strategy prior to extra-time. In order of importance, practitioners see the following as future research areas: nutritional interventions, fatigue responses, acute injury risk, recovery modalities, training paradigms, injury epidemiology, and environmental considerations. This study presents novel insight into the practitioner perceptions of extra-time and provides information to readers about current applied practices and potential future research opportunities

Brain Networks Reveal the Effects of Antipsychotic Drugs on Schizophrenia Patients and Controls.

The study of brain networks, including those derived from functional neuroimaging data, attracts a broad interest and represents a rapidly growing interdisciplinary field. Comparing networks of healthy volunteers with those of patients can potentially offer new, quantitative diagnostic methods and a framework for better understanding brain and mind disorders. We explore resting state functional Magnetic Resonance Imaging (fMRI) data through network measures. We construct networks representing 15 healthy individuals and 12 schizophrenia patients (males and females), all of whom are administered three drug treatments: i) a placebo; and two antipsychotic medications ii) aripiprazole and iii) sulpiride. We compare these resting state networks to a performance at an "N-back" working memory task. We demonstrate that not only is there a distinctive network architecture in the healthy brain that is disrupted in schizophrenia but also that both networks respond to antipsychotic medication. We first reproduce the established finding that brain networks of schizophrenia patients exhibit increased efficiency and reduced clustering compared with controls. Our data then reveal that the antipsychotic medications mitigate this effect, shifting the metrics toward those observed in healthy volunteers, with a marked difference in efficacy between the two drugs. Additionally, we find that aripiprazole considerably alters the network statistics of healthy controls. Examining the "N-back" working memory task, we establish that aripiprazole also adversely affects their performance. This suggests that changes to macroscopic brain network architecture result in measurable behavioral differences. This is one of the first studies to directly compare different medications using a whole-brain graph theoretical analysis with accompanying behavioral data. The small sample size is an inherent limitation and means a degree of caution is warranted in interpreting the findings. Our results lay the groundwork for an objective methodology with which to calculate and compare the efficacy of different treatments of mind and brain disorders

NiCE Teacher Workshop: Engaging K-12 Teachers in the Development of Curricular Materials That Utilize Complex Networks Concepts

Our educational systems must prepare students for an increasingly interconnected future, and teachers require equipping with modern tools, such as network science, to achieve this. We held a Networks in Classroom Education (NiCE) workshop for a group of 21 K-12 teachers with various disciplinary backgrounds. The explicit aim of this was to introduce them to concepts in network science, show them how these concepts can be utilized in the classroom, and empower them to develop resources, in the form of lesson plans, for themselves and the wider community. Here we detail the nature of the workshop and present its outcomes – including an innovative set of publicly available lesson plans. We discuss the future for successful integration of network science in K- 12 education, and the importance of inspiring and enabling our teachers

Caenorhabditis elegans and the network control framework-FAQs.

Control is essential to the functioning of any neural system. Indeed, under healthy conditions the brain must be able to continuously maintain a tight functional control between the system's inputs and outputs. One may therefore hypothesize that the brain's wiring is predetermined by the need to maintain control across multiple scales, maintaining the stability of key internal variables, and producing behaviour in response to environmental cues. Recent advances in network control have offered a powerful mathematical framework to explore the structure-function relationship in complex biological, social and technological networks, and are beginning to yield important and precise insights on neuronal systems. The network control paradigm promises a predictive, quantitative framework to unite the distinct datasets necessary to fully describe a nervous system, and provide mechanistic explanations for the observed structure and function relationships. Here, we provide a thorough review of the network control framework as applied to Caenorhabditis elegans (Yan et al. 2017 Nature550, 519-523. (doi:10.1038/nature24056)), in the style of Frequently Asked Questions. We present the theoretical, computational and experimental aspects of network control, and discuss its current capabilities and limitations, together with the next likely advances and improvements. We further present the Python code to enable exploration of control principles in a manner specific to this prototypical organism.This article is part of a discussion meeting issue 'Connectome to behaviour: modelling C. elegans at cellular resolution'