Applying machine learning methods to avalanche forecasting

Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest neighbour methods (NN), which are known to have limitations when dealing with high dimensional data. We apply Support Vector Machines to a dataset from Lochaber, Scotland to assess their applicability in avalanche forecasting. Support Vector Machines (SVMs) belong to a family of theoretically based techniques from machine learning and are designed to deal with high dimensional data. Initial experiments showed that SVMs gave results which were comparable with NN for categorical and probabilistic forecasts. Experiments utilising the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.

Deep learning via semi-supervised embedding

We show how nonlinear embedding algorithms popular for use with shallow semi-supervised learning techniques such as kernel methods can be applied to deep multilayer architectures, either as a regularizer at the output layer, or on each layer of the architecture. This provides a simple alternative to existing approaches to deep learning whilst yielding competitive error rates compared to those methods, and existing shallow semi-supervised techniques.

Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

Anesthesia prevents auditory perceptual learning.

BACKGROUND: An auditory perceptual learning paradigm was used to investigate whether implicit memories are formed during general anesthesia. METHODS: Eighty-seven patients who had an American Society of Anesthesiologists physical status of I-III and were scheduled to undergo an elective surgery with general anesthesia were randomly assigned to one of two groups. One group received auditory stimulation during surgery, whereas the other did not. The auditory stimulation consisted of pure tones presented via headphones. The Bispectral Index level was maintained between 40 and 50 during surgery. To assess learning, patients performed an auditory frequency discrimination task after surgery, and comparisons were made between the groups. General anesthesia was induced with thiopental and maintained with a mixture of fentanyl and sevoflurane. RESULTS: There was no difference in the amount of learning between the two groups (mean +/- SD improvement: stimulated patients 9.2 +/- 11.3 Hz, controls 9.4 +/- 14.1 Hz). There was also no difference in initial thresholds (mean +/- SD initial thresholds: stimulated patients 31.1 +/- 33.4 Hz, controls 28.4 +/- 34.2 Hz). These results suggest that perceptual learning was not induced during anesthesia. No correlation between the bispectral index and the initial level of performance was found (Pearson r = -0.09, P = 0.59). CONCLUSION: Perceptual learning was not induced by repetitive auditory stimulation during anesthesia. This result may indicate that perceptual learning requires top-down processing, which is suppressed by the anesthetic.

Plastic modifications within inhibitory control networks induced by practicing a stop-signal task: an electrical neuroimaging study.

INTRODUCTION: Inhibitory control refers to our ability to suppress ongoing motor, affective or cognitive processes and mostly depends on a fronto-basal brain network. Inhibitory control deficits participate in the emergence of several prominent psychiatric conditions, including attention deficit/hyperactivity disorder or addiction. The rehabilitation of these pathologies might therefore benefit from training-based behavioral interventions aiming at improving inhibitory control proficiency and normalizing the underlying neurophysiological mechanisms. The development of an efficient inhibitory control training regimen first requires determining the effects of practicing inhibition tasks. METHODS: We addressed this question by contrasting behavioral performance and electrical neuroimaging analyses of event-related potentials (ERPs) recorded from humans at the beginning versus the end of 1 h of practice on a stop-signal task (SST) involving the withholding of responses when a stop signal was presented during a speeded auditory discrimination task. RESULTS: Practicing a short SST improved behavioral performance. Electrophysiologically, ERPs differed topographically at 200 msec post-stimulus onset, indicative of the engagement of distinct brain network with learning. Source estimations localized this effect within the inferior frontal gyrus, the pre-supplementary motor area and the basal ganglia. CONCLUSION: Our collective results indicate that behavioral and brain responses during an inhibitory control task are subject to fast plastic changes and provide evidence that high-order fronto-basal executive networks can be modified by practicing a SST.

Glucose-dependent insulinotropic polypeptide receptor knockout mice are impaired in learning, synaptic plasticity, and neurogenesis.

Glucose-dependent insulinotropic polypeptide (GIP) is a key incretin hormone, released from intestine after a meal, producing a glucose-dependent insulin secretion. The GIP receptor (GIPR) is expressed on pyramidal neurons in the cortex and hippocampus, and GIP is synthesized in a subset of neurons in the brain. However, the role of the GIPR in neuronal signaling is not clear. In this study, we used a mouse strain with GIPR gene deletion (GIPR KO) to elucidate the role of the GIPR in neuronal communication and brain function. Compared with C57BL/6 control mice, GIPR KO mice displayed higher locomotor activity in an open-field task. Impairment of recognition and spatial learning and memory of GIPR KO mice were found in the object recognition task and a spatial water maze task, respectively. In an object location task, no impairment was found. GIPR KO mice also showed impaired synaptic plasticity in paired-pulse facilitation and a block of long-term potentiation in area CA1 of the hippocampus. Moreover, a large decrease in the number of neuronal progenitor cells was found in the dentate gyrus of transgenic mice, although the numbers of young neurons was not changed. Together the results suggest that GIP receptors play an important role in cognition, neurotransmission, and cell proliferation.

Learning from failure - rationale and design for a study about discontinuation of randomized trials (DISCO study).

BACKGROUND: Randomized controlled trials (RCTs) may be discontinued because of apparent harm, benefit, or futility. Other RCTs are discontinued early because of insufficient recruitment. Trial discontinuation has ethical implications, because participants consent on the premise of contributing to new medical knowledge, Research Ethics Committees (RECs) spend considerable effort reviewing study protocols, and limited resources for conducting research are wasted. Currently, little is known regarding the frequency and characteristics of discontinued RCTs. METHODS/DESIGN: Our aims are, first, to determine the prevalence of RCT discontinuation for specific reasons; second, to determine whether the risk of RCT discontinuation for specific reasons differs between investigator- and industry-initiated RCTs; third, to identify risk factors for RCT discontinuation due to insufficient recruitment; fourth, to determine at what stage RCTs are discontinued; and fifth, to examine the publication history of discontinued RCTs.We are currently assembling a multicenter cohort of RCTs based on protocols approved between 2000 and 2002/3 by 6 RECs in Switzerland, Germany, and Canada. We are extracting data on RCT characteristics and planned recruitment for all included protocols. Completion and publication status is determined using information from correspondence between investigators and RECs, publications identified through literature searches, or by contacting the investigators. We will use multivariable regression models to identify risk factors for trial discontinuation due to insufficient recruitment. We aim to include over 1000 RCTs of which an anticipated 150 will have been discontinued due to insufficient recruitment. DISCUSSION: Our study will provide insights into the prevalence and characteristics of RCTs that were discontinued. Effective recruitment strategies and the anticipation of problems are key issues in the planning and evaluation of trials by investigators, Clinical Trial Units, RECs and funding agencies. Identification and modification of barriers to successful study completion at an early stage could help to reduce the risk of trial discontinuation, save limited resources, and enable RCTs to better meet their ethical requirements.

MP2RAGE provides new clinically-compatible correlates of mild cognitive deficits in relapsing-remitting multiple sclerosis.

Despite that cognitive impairment is a known early feature present in multiple sclerosis (MS) patients, the biological substrate of cognitive deficits in MS remains elusive. In this study, we assessed whether T1 relaxometry, as obtained in clinically acceptable scan times by the recent Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) sequence, may help identifying the structural correlate of cognitive deficits in relapsing-remitting MS patients (RRMS). Twenty-nine healthy controls (HC) and forty-nine RRMS patients underwent high-resolution 3T magnetic resonance imaging to obtain optimal cortical lesion (CL) and white matter lesion (WML) count/volume and T1 relaxation times. T1 z scores were then obtained between T1 relaxation times in lesion and the corresponding HC tissue. Patient cognitive performance was tested using the Brief Repeatable Battery of Neuro-psychological Tests. Multivariate analysis was applied to assess the contribution of MRI variables (T1 z scores, lesion count/volume) to cognition in patients and Bonferroni correction was applied for multiple comparison. T1 z scores were higher in WML (p < 0.001) and CL-I (p < 0.01) than in the corresponding normal-appearing tissue in patients, indicating relative microstructural loss. (1) T1 z scores in CL-I (p = 0.01) and the number of CL-II (p = 0.04) were predictors of long-term memory; (2) T1 z scores in CL-I (β = 0.3; p = 0.03) were independent determinants of long-term memory storage, and (3) lesion volume did not significantly influenced cognitive performances in patients. Our study supports evidence that T1 relaxometry from MP2RAGE provides information about microstructural properties in CL and WML and improves correlation with cognition in RRMS patients, compared to conventional measures of disease burden.

The neuronal monocarboxylate transporter MCT2: its regulation by BDNF and its role in learning and memory

Glucose has been considered the major, if not the exclusive, energy substrate for the brain. But under certain physiological and pathological conditions other substrates, namely monocarboxylates (lactate, pyruvate and ketone bodies), can contribute significantly to satisfy brain energy demands. These monocarboxylates need to be transported across the blood-brain barrier or out of astrocytes into the extracellular space and taken up into neurons. It has been shown that monocarboxylates are transported by a family of proton-linked transporters called monocarboxylate transporters (MCTs). In the central nervous system, MCT2 is the predominant neuronal isoform and little is known about the regulation of its expression. Noradrenaline (NA), insulin and IGF-1 were previously shown to enhance the expression of MCT2 in cultured cortical neurons via a translational mechanism. Here we demonstrate that the well known brain neurotrophic factor BDNF enhances MCT2 protein expression in cultured cortical neurons and in synaptoneurosome preparations in a time- and concentrationdependent manner without affecting MCT2 mRNA levels. We observed that BDNF induced MCT2 expression by activation of MAPK as well as PI3K/Akt/mTOR signaling pathways. Furthermore, we investigated the possible post-transcriptional regulation of MCT2 expression by a neuronal miRNA. Then, we demonstrated that BDNF enhanced MCT2 expression in the hippocampus in vivo, in parallel with some post-synaptic proteins such as PSD95 and AMPA receptor GluR2/3 subunits, and two immediate early genes Arc and Zif268 known to be expressed in conditions related to synaptic plasticity. In the last part, we demonstrated in vivo that a downregulation of hippocampal MCT2 via silencing with an appropriate lentiviral vector in mice caused an impairment of working memory without reference memory deficit. In conclusion, these results suggest that regulation of neuronal monocarboxylate transporter MCT2 expression could be a key event in the context of synaptic plasticity, allowing an adequate energy substrate supply in situations of altered synaptic efficacy. - Le glucose représente le substrat énergétique majeur pour le cerveau. Cependant, dans certaines conditions physiologiques ou pathologiques, le cerveau a la capacité d'utiliser des substrats énergéiques appartenant à la classe des monocarboxylates (lactate, pyruvate et corps cétoniques) afin de satisfaire ses besoins énergétiques. Ces monocarboxylates doivent être transportés à travers la barrière hématoencéphalique mais aussi hors des astrocytes vers l'espace extracellulaire puis re-captés par les neurones. Leur transport est assuré par une famillle de transporteurs aux monocarboxylates (MCTs). Dans le système nerveux central, les neurones expriment principalement l'isoforme MCT2 mais peu d'informations sont disponibles concernant la régulation de son expression. Il a été montré que la noradrénaline, l'insuline et l'IGF-1 induisent l'expression de MCT2 dans des cultures de neurones corticaux par un mécanisme traductionnel. Dans cette étude nous démontrons dans un premier temps que le facteur neurotrophique BDNF augmente l'expression de MCT2 à la fois dans des cultures de neurones corticaux et dans les préparations synaptoneurosomales selon un décours temporel et une gamme de concentrations propre. Aucun changement n'a été observé concernant les niveaux d'ARNm de MCT2. Nous avons observé que le BDNF induisait l'expression de MCT2 par l'activation simultanée des voies de signalisation MAPK et PI3K/Akt/mTOR. De plus, nous nous sommes intéressés à une potentielle régulation par les micro-ARNs de la synthèse de MCT2. Ensuite, nous avons démontré que le BDNF induit aussi l'expression de MCT2 dans l'hippocampe de la souris en parallèle avec d'autres protéines post-synaptiques telles que PSD95 et GluR2/3 et avec deux « immediate early genes » tels que Arc et Zif268 connus pour être exprimés dans des conditions de plasticité synaptique. Dans un dernier temps, nous avons démontré qu'une diminution d'expression de MCT2 induite par le biais d'un siRNA exprimé via un vecteur lentiviral dans l'hippocampe de souris générait des déficits de mémoire de travail sans affecter la mémoire de référence. En conclusion, ces résultats nous suggèrent que le transporteur aux monocarboxylates neuronal MCT2 serait essentiel pour l'apport énergétique du lactate pour les neurones dans des conditions de haute activité neuronale comme c'est le cas pendant les processus de plasticité synaptique.