Correlations of random classifiers on large data sets

Classification of large data sets by feedforward neural networks is investigated. To deal with unmanageably large sets of classification tasks, a probabilistic model of their relevance is considered. Optimization of networks computing randomly chosen classifiers is studied in terms of correlations of classifiers with network input–output functions. Effects of increasing sizes of sets of data to be classified are analyzed using geometrical properties of high-dimensional spaces. Their consequences on concentrations of values of sufficiently smooth functions of random variables around their mean values are applied. It is shown that the critical factor for suitability of a class of networks for computing randomly chosen classifiers is the maximum of sizes of the mean values of their correlations with network input–output functions. To include cases in which function values are not independent, the method of bounded differences is exploited

bilateral robot therapy based on haptics and reinforcement learning feasibility study of a new concept for treatment of patients after stroke

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Connecting Neurons to a Mobile Robot: An In Vitro Bidirectional Neural Interface

One of the key properties of intelligent behaviors is the capability to learn and adapt to changing environmental conditions. These features are the result of the continuous and intense interaction of the brain with the external world, mediated by the body. For this reason “embodiment” represents an innovative and very suitable experimental paradigm when studying the neural processes underlying learning new behaviors and adapting to unpredicted situations. To this purpose, we developed a novel bidirectional neural interface. We interconnected in vitro neurons, extracted from rat embryos and plated on a microelectrode array (MEA), to external devices, thus allowing real-time closed-loop interaction. The novelty of this experimental approach entails the necessity to explore different computational schemes and experimental hypotheses. In this paper, we present an open, scalable architecture, which allows fast prototyping of different modules and where coding and decoding schemes and different experimental configurations can be tested. This hybrid system can be used for studying the computational properties and information coding in biological neuronal networks with far-reaching implications for the future development of advanced neuroprostheses

Game theory and partner representation in joint action: toward a computational theory of joint agency

The sense of agency – the subjective feeling of being in control of our own actions – is one central aspect of the phenomenology of action. Computational models provided important contributions toward unveiling the mechanisms underlying the sense of agency in individual action. In particular, the sense of agency is believed to be related to the match between the actual and predicted consequences of our own actions (comparator model). In the study of joint action, models are even more necessary to understand the mechanisms underlying the development of coordination strategies and how the subjective experiences of control emerge during the interaction. In a joint action, we not only need to predict the consequences of our own actions; we also need to predict the actions and intentions of our partner, and to integrate these predictions to infer their joint consequences. Understanding our partner and developing mutually satisfactory coordination strategies are key components of joint action and in the development of the sense of joint agency. Here we discuss a computational architecture which addresses the sense of agency during intentional, real-time joint action. We first reformulate previous accounts of the sense of agency in probabilistic terms, as the combination of prior beliefs about the action goals and constraints, and the likelihood of the predicted movement outcomes. To look at the sense of joint agency, we extend classical computational motor control concepts - optimal estimation and optimal control. Regarding estimation, we argue that in joint action the players not only need to predict the consequences of their own actions, but also need to predict partner’s actions and intentions (a ‘partner model’) and to integrate these predictions to infer their joint consequences. As regards action selection, we use differential game theory – in which actions develop in continuous space and time - to formulate the problem of establishing a stable form of coordination and as a natural extension of optimal control to joint action. The resulting model posits two concurrent observer-controller loops, accounting for ‘joint’ and ‘self’ action control. The two observers quantify the likelihoods of being in control alone or jointly. Combined with prior beliefs, they provide weighing signals which are used to modulate the ‘joint’ and ‘self’ motor commands. We argue that these signals can be interpreted as the subjective sense of joint and self agency. We demonstrate the model predictions by simulating a sensorimotor interactive task where two players are mechanically coupled and are instructed to perform planar movements to reach a shared final target by crossing two differently located intermediate targets. In particular, we explore the relation between self and joint agency and the information available to each player about their partner. The proposed model provides a coherent picture of the inter-relation of prediction, control, and the sense of agency in a broader range of joint actions

Mapping genetic factors for resistance to Soil-borne cereal mosaic virus (SBCMV) in durum wheat

Article first published online: 8 FEB 2014OBJECTIVE: In an unselected group of women with signs of preterm labour, maintenance tocolysis is not effective in the prevention of preterm birth and does not improve neonatal outcome. Among women with signs of preterm labour, those who are fetal fibronectin positive have an increased risk of preterm birth. We investigated whether maintenance tocolysis with nifedipine would delay delivery and improve neonatal outcome in women with threatened preterm labour and a positive fetal fibronectin status. STUDY DESIGN: Women with a singleton pregnancy in threatened preterm labour (24(+0) to 33(+6)  weeks) with a positive fetal fibronectin test were randomised to nifedipine or placebo. Study medication was continued until 36 completed weeks' gestation. The primary endpoint was prolongation of pregnancy of seven days. Secondary endpoints were gestational age at delivery and length of NICU admission. RESULTS: Of the 60 participants, 29 received nifedipine and 31 placebo. Prolongation of pregnancy by >7 days occurred in 22/29 (76%) in the nifedipine group and 25/31 (81%) in the placebo group (relative risks, RR 0.94 [0.72-1.2]). Gestational age at delivery was 36.1 ± 5.1 weeks for nifedipine and 36.8 ± 3.6 weeks for placebo (P = 0.027). Length of NICU admission [median (interquartile ranges, IQR)] was 27 (24-41) days and 16 (8-37) days in nifedipine and placebo groups, respectively (P = 0.17). CONCLUSION: In women with threatened preterm labour who are fetal fibronectin positive, maintenance tocolysis with nifedipine does not seem to prolong pregnancy, nor reduce length of NICU admission.Emma Parry, Carolien Roos, Peter Stone, Lynsey Hayward, Ben Willem Mol and Lesley McCowa

Induction chemotherapy followed by alternating chemo-radiotherapy in stage IV undifferentiated nasopharyngeal carcinoma

In locally advanced undifferentiated nasopharyngeal carcinoma (UNPC), concomitant chemo-radiotherapy is the only strategy that gave better results over radiation alone in a phase III trial. Adding effective chemotherapy to a concomitant chemo-radiotherapy programme may be a way to improve the results further. 30 patients with previously untreated T4 and/or N2–3 undifferentiated nasopharyngeal carcinoma were consecutively enrolled and initially treated with 3 courses of epidoxorubicin, 90 mg/m2, day 1 and cisplatin, 40 mg/m2, days 1 and 2, every 3 weeks. After a radiological and clinical response assessment patients underwent 3 courses of cisplatin, 20 mg/m2/day, days 1–4 and fluorouracil, 200 mg/m2/day, days 1–4, i.v. bolus, (weeks 1, 4, 7) alternated to 3 courses of radiation (week 2–3, 5–6, 8–9–10), with a single daily fractionation, up to 70 Gy. WHO histology was type 2 in 30% and type 3 in 70% of the patients. 57% had T4 and 77% N2–3 disease. All the patients are evaluable for toxicity and response. All but one received 3 courses of induction chemotherapy. Toxicity was mild to moderate in any case. At the end of the induction phase 10% of CRs, 83.3% of PRs and 6.7% of SD were recorded. All the patients but one had the planned number of chemotherapy courses in the alternating phase and all received the planned radiation dose. One patient out of 3 developed grade III–IV mucositis. Haematological toxicity was generally mild to moderate. At the final response evaluation 86.7% of CRs and 13.3% of PRs were observed. At a median follow-up of 31 months, 13.3% of patients had a loco-regional progression and 20% developed distant metastases. The 3-year actuarial progression-free survival and overall survival rates were 64% and 83%. Induction chemotherapy followed by alternating chemo-radiotherapy is feasible and patients' compliance optimal. This approach showed a very promising activity on locally advanced UNPC and merits to be investigated in phase III studies. © 2000 Cancer Research Campaign http://www.bjcancer.co