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

The complexity of mating decisions in stalk-eyed flies

All too often, studies of sexual selection focus exclusively on the responses in one sex, on single traits, typically those that are exaggerated and strongly sexually dimorphic. They ignore a range of less obvious traits and behavior, in both sexes, involved in the interactions leading to mate choice. To remedy this imbalance, we analyze a textbook example of sexual selection in the stalk-eyed fly (Diasemopsis meigenii). We studied several traits in a novel, insightful, and efficient experimental design, examining 2,400 male–female pairs in a “round-robin” array, where each female was tested against multiple males and vice versa. In D. meigenii, females exhibit strong mate preference for males with highly exaggerated eyespan, and so we deliberately constrained variation in male eyespan to reveal the importance of other traits. Males performing more precopulatory behavior were more likely to attempt to mate with females and be accepted by them. However, behavior was not a necessary part of courtship, as it was absent from over almost half the interactions. Males with larger reproductive organs (testes and accessory glands) did not make more mating attempts, but there was a strong tendency for females to accept mating attempts from such males. How females detect differences in male reproductive organ size remains unclear. In addition, females with larger eyespan, an indicator of size and fecundity, attracted more mating attempts from males, but this trait did not alter female acceptance. Genetic variation among males had a strong influence on male mating attempts and female acceptance, both via the traits we studied and other unmeasured attributes. These findings demonstrate the importance of assaying multiple traits in males and females, rather than focusing solely on prominent and exaggerated sexually dimorphic traits. The approach allows a more complete understanding of the complex mating decisions made by both males and females

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

Do patients with advanced breast cancer benefit from chemotherapy?

This study aimed to assess the proportion of patients with advanced breast cancer who report benefit from first-line palliative chemotherapy using a simple global measure of wellbeing and to identify factors predicting benefit. A consecutive series of women with advanced breast cancer undergoing first-line palliative chemotherapy was evaluated. The main outcome measure was patient report of overall wellbeing assessed at post-treatment interview. Physical, psychological and functional status were assessed using the Rotterdam Symptom Checklist (RSCL) on three occasions (pretreatment, at the start of the third cycle and post treatment). It was planned that treatment would be discontinued after six cycles (i.e. 18-24 weeks). One hundred and sixty patients started treatment, of whom 155 were assessable for quality of life. After treatment, 41 (26%) patients reported they felt better, 29 (19%) felt the same and 34 (22%) felt worse than they did before treatment. The other 51 (33%) patients either died or stopped attending the hospital before the post-treatment interview and were assigned as treatment 'failures'. Patients who reported feeling better after treatment had improvements in psychological distress (P < 0.0001), pain (P = 0.01), lack of energy (P = 0.02) and tiredness (P = 0.02), as well as improvement in functional status (P = 0.07). Feeling better was also correlated with disease response (P = 0.03). Feeling worse after treatment or treatment 'failure' was predicted by the pretreatment presence of a dry mouth (P = 0.003) and high levels of psychological distress (P = 0.03). Pretreatment lack of energy (P = 0.01), dry mouth (P = 0.02), presence of liver metastases (P = 0.03) and breathlessness (P = 0.03) predicted treatment 'failures'. The results of this study suggest that first-line palliative chemotherapy for advanced breast cancer confers benefit on a substantial proportion of patients, with about one-quarter feeling better after treatment and nearly a half feeling better or the same some 4-6 months after the start of treatment. Factors identified in this study may assist clinicians in deciding which patients should not be offered treatment, because of high risk of feeling worse or treatment 'failure'. This work now needs to be validated on a further cohort of women receiving chemotherapy for advanced breast cancer

Iododoxorubicin in advanced breast cancer: a phase II evaluation of clinical activity, pharmacology and quality of life.

Iododoxorubicin 80 mg m-2 i.v. was given 3 weekly for a maximum of six cycles as first-line chemotherapy to 14 evaluable women with metastatic breast cancer. The response rate was 14% (95% confidence intervals 4-40%); median time to progression was 3.5 months (range 0.7 to > 9.3) and median survival was 10.2 months (range 2.3 to > 20.4). Neutropenia was the main toxicity but was not associated with severe sepsis. Two patients had a significant (> 10%) but asymptomatic fall in cardiac ejection fraction; other toxicities were mild. Plasma pharmacokinetics was studied during the first cycle of treatment. Iododoxorubicin was extensively metabolised to iododoxorubicinol. Neutropenia and thrombocytopenia were both significantly correlated with the area under the concentration-time curve (AUC) for iododoxorubicin and the total AUC for iododoxorubicin and iododoxorubicinol. Quality of life (QOL), evaluated by self-report questionnaire and interview, showed little evidence of benefit in terms of physical symptom relief, level of activity, psychological symptoms or global evaluation of QOL during treatment. Iododoxorubicin is subjectively less toxic than standard anthracyclines, but at the dose and schedule used has limited activity in metastatic breast cancer, possibly because iododoxorubicinol is not clinically active

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'

Prediction and Topological Models in Neuroscience

In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone