Computational neurorehabilitation: modeling plasticity and learning to predict recovery

Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling – regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity

Information and Control: Inventing the Communications Revolution in Post-War Britain

This thesis undertakes the first history of the post-war British telephone system, and addresses it through the lens of both actors’ and analysts’ emphases on the importance of ‘information’ and ‘control’. I explore both through a range of chapters on organisational history, laboratories, telephone exchanges, transmission technologies, futurology, transatlantic communications, and privatisation. The ideal of an ‘information network’ or an ‘information age’ is present to varying extents in all these chapters, as are deployments of different forms of control. The most pervasive, and controversial, form of control throughout this history is computer control, but I show that other forms of control, including environmental, spatial, and temporal, are all also important. I make three arguments: first, that the technological characteristics of the telephone system meant that its liberalisation and privatisation were much more ambiguous for competition and monopoly than expected; second, that information has been more important to the telephone system as an ideal to strive for, rather than the telephone system’s contribution to creating an apparent information age; third, that control is a more useful concept than information for analysing the history of the telephone system, but more work is needed to study the discursive significance of ‘control’ itself

A physiological increase in maternal cortisol alters uteroplacental metabolism in the pregnant ewe

Fetal nutrition is determined by maternal availability, placental transport and uteroplacental metabolism of carbohydrates. Cortisol affects maternal and fetal metabolism, but whether maternal cortisol concentrations within the physiological range regulate uteroplacental carbohydrate metabolism remains unknown. This study determined the effect of maternal cortisol infusion (1.2 mg kg−1 day−1 I.V. for 5 days, n = 20) on fetal glucose, lactate and oxygen supplies in pregnant ewes on day 130 of pregnancy (term = 145 days). Compared to saline infusion (n = 21), cortisol infusion increased maternal, but not fetal, plasma cortisol (P < 0.05). Cortisol infusion also raised maternal insulin, glucose and lactate concentrations, and blood pH, PCO2 and HCO3 − concentration. Although total uterine glucose uptake determined by Fick’s principle was unaffected, a greater proportion was consumed by the uteroplacental tissues, so net fetal glucose uptake was 29% lower in cortisol-infused than control ewes (P < 0.05). Concomitantly, uteroplacental lactate production was > 2-fold greater in cortisol- than saline-treated ewes (P < 0.05), although uteroplacental O2 consumption was unaffected by maternal treatment. Materno-fetal clearance of non-metabolizable [3H]methyl-D-glucose and placental SLC2A8 (glucose transporter 8) gene expression were also greater with cortisol treatment. Fetal plasma glucose, lactate or α-amino nitrogen concentrations were unaffected by treatment although fetal plasma fructose and hepatic lactate dehydrogenase activity were greater in cortisol- than saline-treated ewes (P < 0.05). Fetal plasma insulin levels and body weight were also unaffected by maternal treatment. During stress, cortisol-dependent regulation of uteroplacental glycolysis may allow increased maternal control over fetal nutrition and metabolism. However, when maternal cortisol concentrations are raised chronically, prolonged elevation of uteroplacental lactate production may compromise fetal wellbeing

A physiological increase in maternal cortisol alters uteroplacental metabolism in the pregnant ewe.

KEY POINTS: Fetal nutrient supply is dependent, in part, upon the transport capacity and metabolism of the placenta. The stress hormone, cortisol, alters metabolism in the adult and fetus but it is not known whether cortisol in the pregnant mother affects metabolism of the placenta. In this study, when cortisol concentrations were raised in pregnant sheep by infusion, proportionately more of the glucose taken up by the uterus was consumed by the uteroplacental tissues while less was transferred to the fetus, despite an increased placental glucose transport capacity. Concomitantly, the uteroplacental tissues produced lactate at a greater rate. The results show that maternal cortisol concentrations regulate uteroplacental glycolytic metabolism, producing lactate for use in utero. Prolonged increases in placental lactate production induced by cortisol overexposure may contribute to the adverse effects of maternal stress on fetal wellbeing. ABSTRACT: Fetal nutrition is determined by maternal availability, placental transport and uteroplacental metabolism of carbohydrates. Cortisol affects maternal and fetal metabolism, but whether maternal cortisol concentrations within the physiological range regulate uteroplacental carbohydrate metabolism remains unknown. This study determined the effect of maternal cortisol infusion (1.2 mg kg(-1)  day(-1) i.v. for 5 days, n = 20) on fetal glucose, lactate and oxygen supplies in pregnant ewes on day ∼130 of pregnancy (term = 145 days). Compared to saline infusion (n = 21), cortisol infusion increased maternal, but not fetal, plasma cortisol (P  2-fold greater in cortisol- than saline-treated ewes (P < 0.05), although uteroplacental O2 consumption was unaffected by maternal treatment. Materno-fetal clearance of non-metabolizable [(3) H]methyl-d-glucose and placental SLC2A8 (glucose transporter 8) gene expression were also greater with cortisol treatment. Fetal plasma glucose, lactate or α-amino nitrogen concentrations were unaffected by treatment although fetal plasma fructose and hepatic lactate dehydrogenase activity were greater in cortisol- than saline-treated ewes (P < 0.05). Fetal plasma insulin levels and body weight were also unaffected by maternal treatment. During stress, cortisol-dependent regulation of uteroplacental glycolysis may allow increased maternal control over fetal nutrition and metabolism. However, when maternal cortisol concentrations are raised chronically, prolonged elevation of uteroplacental lactate production may compromise fetal wellbeing

The new paradigm of hepatitis C therapy: integration of oral therapies into best practices.

Emerging data indicate that all-oral antiviral treatments for chronic hepatitis C virus (HCV) will become a reality in the near future. In replacing interferon-based therapies, all-oral regimens are expected to be more tolerable, more effective, shorter in duration and simpler to administer. Coinciding with new treatment options are novel methodologies for disease screening and staging, which create the possibility of more timely care and treatment. Assessments of histologic damage typically are performed using liver biopsy, yet noninvasive assessments of histologic damage have become the norm in some European countries and are becoming more widespread in the United States. Also in place are new Centers for Disease Control and Prevention (CDC) initiatives to simplify testing, improve provider and patient awareness and expand recommendations for HCV screening beyond risk-based strategies. Issued in 2012, the CDC recommendations aim to increase HCV testing among those with the greatest HCV burden in the United States by recommending one-time testing for all persons born during 1945-1965. In 2013, the United States Preventive Services Task Force adopted similar recommendations for risk-based and birth-cohort-based testing. Taken together, the developments in screening, diagnosis and treatment will likely increase demand for therapy and stimulate a shift in delivery of care related to chronic HCV, with increased involvement of primary care and infectious disease specialists. Yet even in this new era of therapy, barriers to curing patients of HCV will exist. Overcoming such barriers will require novel, integrative strategies and investment of resources at local, regional and national levels

Are there valid proxy measures of clinical behaviour?

Background: Accurate measures of health professionals' clinical practice are critically important to guide health policy decisions, as well as for professional self-evaluation and for research-based investigation of clinical practice and process of care. It is often not feasible or ethical to measure behaviour through direct observation, and rigorous behavioural measures are difficult and costly to use. The aim of this review was to identify the current evidence relating to the relationships between proxy measures and direct measures of clinical behaviour. In particular, the accuracy of medical record review, clinician self-reported and patient-reported behaviour was assessed relative to directly observed behaviour. Methods: We searched: PsycINFO; MEDLINE; EMBASE; CINAHL; Cochrane Central Register of Controlled Trials; science/social science citation index; Current contents (social & behavioural med/clinical med); ISI conference proceedings; and Index to Theses. Inclusion criteria: empirical, quantitative studies; and examining clinical behaviours. An independent, direct measure of behaviour (by standardised patient, other trained observer or by video/audio recording) was considered the 'gold standard' for comparison. Proxy measures of behaviour included: retrospective self-report; patient-report; or chart-review. All titles, abstracts, and full text articles retrieved by electronic searching were screened for inclusion and abstracted independently by two reviewers. Disagreements were resolved by discussion with a third reviewer where necessary. Results: Fifteen reports originating from 11 studies met the inclusion criteria. The method of direct measurement was by standardised patient in six reports, trained observer in three reports, and audio/video recording in six reports. Multiple proxy measures of behaviour were compared in five of 15 reports. Only four of 15 reports used appropriate statistical methods to compare measures. Some direct measures failed to meet our validity criteria. The accuracy of patient report and chart review as proxy measures varied considerably across a wide range of clinical actions. The evidence for clinician self-report was inconclusive. Conclusion: Valid measures of clinical behaviour are of fundamental importance to accurately identify gaps in care delivery, improve quality of care, and ultimately to improve patient care. However, the evidence base for three commonly used proxy measures of clinicians' behaviour is very limited. Further research is needed to better establish the methods of development, application, and analysis for a range of both direct and proxy measures of behaviour

On chains in HH-closed topological pospaces

We study chains in an $H$-closed topological partially ordered space. We give sufficient conditions for a maximal chain $L$ in an $H$-closed topological partially ordered space such that $L$ contains a maximal (minimal) element. Also we give sufficient conditions for a linearly ordered topological partially ordered space to be $H$-closed. We prove that any $H$-closed topological semilattice contains a zero. We show that a linearly ordered $H$-closed topological semilattice is an $H$-closed topological pospace and show that in the general case this is not true. We construct an example an $H$-closed topological pospace with a non-$H$-closed maximal chain and give sufficient conditions that a maximal chain of an $H$-closed topological pospace is an $H$-closed topological pospace.Comment: We have rewritten and substantially expanded the manuscrip

Agreed Definitions and a Shared Vision for New Standards in Stroke Recovery Research: The Stroke Recovery and Rehabilitation Roundtable Taskforce

The first Stroke Recovery and Rehabilitation Roundtable established a game changing set of new standards for stroke recovery research. Common language and definitions were required to develop an agreed framework spanning the four working groups: translation of basic science, biomarkers of stroke recovery, measurement in clinical trials and intervention development and reporting. This paper outlines the working definitions established by our group and an agreed vision for accelerating progress in stroke recovery research

When the optimal is not the best: parameter estimation in complex biological models

Background: The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values. Results: We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. Conclusions: The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system, and point to the need of a theory that addresses this problem more generally