Effects of Noise in a Cortical Neural Model

Recently Segev et al. (Phys. Rev. E 64,2001, Phys.Rev.Let. 88, 2002) made long-term observations of spontaneous activity of in-vitro cortical networks, which differ from predictions of current models in many features. In this paper we generalize the EI cortical model introduced in a previous paper (S.Scarpetta et al. Neural Comput. 14, 2002), including intrinsic white noise and analyzing effects of noise on the spontaneous activity of the nonlinear system, in order to account for the experimental results of Segev et al.. Analytically we can distinguish different regimes of activity, depending from the model parameters. Using analytical results as a guide line, we perform simulations of the nonlinear stochastic model in two different regimes, B and C. The Power Spectrum Density (PSD) of the activity and the Inter-Event-Interval (IEI) distributions are computed, and compared with experimental results. In regime B the network shows stochastic resonance phenomena and noise induces aperiodic collective synchronous oscillations that mimic experimental observations at 0.5 mM Ca concentration. In regime C the model shows spontaneous synchronous periodic activity that mimic activity observed at 1 mM Ca concentration and the PSD shows two peaks at the 1st and 2nd harmonics in agreement with experiments at 1 mM Ca. Moreover (due to intrinsic noise and nonlinear activation function effects) the PSD shows a broad band peak at low frequency. This feature, observed experimentally, does not find explanation in the previous models. Besides we identify parametric changes (namely increase of noise or decreasing of excitatory connections) that reproduces the fading of periodicity found experimentally at long times, and we identify a way to discriminate between those two possible effects measuring experimentally the low frequency PSD.Comment: 25 pages, 10 figures, to appear in Phys. Rev.

Uncertainty Analysis for the Classification of Multispectral Satellite Images Using SVMs and SOMs

Abstract: Classification of multispectral remotely sensed data with textural features is investigated with a special focus on uncertainty analysis in the produced land-cover maps. Much effort has already been directed into the research of satisfactory accuracy-assessment techniques in image classification, but a common approach is not yet universally adopted. We look at the relationship between hard accuracy and the uncertainty on the produced answers, introducing two measures based on maximum probability and a quadratic entropy. Their impact differs depending on the type of classifier. In this paper, we deal with two different classification strategies, based on support vector machines (SVMs) and Kohonen's self-organizingmaps (SOMs), both suitably modified to give soft answers. Once the multiclass probability answer vector is available for each pixel in the image, we studied the behavior of the overall classification accuracy as a function of the uncertainty associated with each vector, given a hard-labeled test set. The experimental results show that the SVM with one-versus-one architecture and linear kernel clearly outperforms the other supervised approaches in terms of overall accuracy. On the other hand, our analysis reveals that the proposed SOM-based classifier, despite its unsupervised learning procedure, is able to provide soft answers which are the best candidates for a fusion with supervised results

Synergic use of botulinum toxin injection and radial extracorporeal shockwave therapy in multiple sclerosis spasticity

Background and aim: In Multiple Sclerosis (MS) spasticity worsens the patient’s quality of life. Botulinum NeuroToxin TypeA (BoNT-A) is extensively used in focal spasticity, frequently combined with physical therapies. Radial extracorporeal shock waves (rESW) were already used in association with BoNTA. Considering that loss of efficacy and adverse events are determinants of BoNT-A treatment interruption, this study aimed to evaluate the possibility to prolong BoNT-A’s effect by using rESW in MS focal spasticity. Methods: Sixteen MS patients with spasticity of triceps surae muscles were first subjected to BoNT-A therapy and, four months later, to 4 sections of rESWT. Patients were evaluated before, 30, 90 days after the end of the treatments, by using Modified Ashworth Scale (MAS), Modified Tardieu Scale (MTS), and kinematic analysis of passive and active ankle ROM. Results: BoNT-A determined a significant reduction of spasticity evaluated by MAS with a reduction of positive effects after 4months (p<0.05); MTS highlighted the efficacy only 90 days after injection (p<0.05). rESWT decreased MAS values at the end and 30 days later the treatment (p<0.01); MTS values showed instead a prolonged effect (p<0.01). BoNT-A determined a gain of passive and active ankle ROM, persisting along with treatment and peaking the maximum value after rESWT (p<0.05). Conclusions: rESWT can prolong BoNT-A effect inducing a significant reduction of spasticity and improvement in passive and active ankle ROM in MS patients. The use of rESWT following BoNT-A injection is useful to avoid some limitations and to prolong the therapeutic effects of BoNT-A therapy. (www.actabiomedica.it)

Measuring GNSS ionospheric total electron content at Concordia, and application to L-band radiometers

In the framework of the project BIS - Bipolar Ionospheric Scintillation and Total Electron Content Monitoring, the ISACCO-DMC0 and ISACCO-DMC1 permanent monitoring stations were installed in 2008. The principal scope of the stations is to measure the ionospheric total electron content (TEC) and to monitor the ionospheric scintillations, using high-sampling-frequency global positioning system (GPS) ionospheric scintillation and TEC monitor (GISTM) receivers. The disturbances that the ionosphere can induce on the electromagnetic signals emitted by the Global Navigation Satellite System constellations are due to the presence of electron density anomalies in the ionosphere, which are particularly frequent at high latitudes, where the upper atmosphere is highly sensitive to perturbations coming from outer space. With the development of present and future low-frequency space-borne microwave missions (e.g., Soil Moisture and Ocean Salinity [SMOS], Aquarius, and Soil Moisture Active Passive missions), there is an increasing need to estimate the effects of the ionosphere on the propagation of electromagnetic waves that affects satellite measurements. As an example, how the TEC data collected at Concordia station are useful for the calibration of the European Space Agency SMOS data within the framework of an experiment promoted by the European Space Agency (known as DOMEX) will be discussed. The present report shows the ability of the GISTM station to monitor ionospheric scintillation and TEC, which indicates that only the use of continuous GPS measurements can provide accurate information on TEC variability, which is necessary for continuous calibration of satellite data

Automatic Classification of Seismic Signals at Mt. Vesuvius Volcano, Italy, Using Neural Networks

We present a new strategy for reliable automatic classification of local seismic signals and volcano-tectonic earthquakes (VT). The method is based on a supervised neural network in which a new approach for feature extraction from short period seismic signals is applied. To reduce the number of records required for the analysis we set up a specialized neural classifier, able to distinguish two classes of signals, for each of the selected stations. The neural network architecture is a multilayer perceptron (MLP) with a single hidden layer. Spectral features of the signals and the parameterized attributes of their waveform have been used as input for this network. Feature extraction is done by using both the linear predictor coding technique for computing the spectrograms, and a function of the amplitude for characterizing waveforms. Compared to strategies that use only spectral signatures, the inclusion of properly normalized amplitude features improves the performance of the classifiers, and allows the network to better generalize. To train the MLP network we compared the performance of the quasi-Newton algorithm with the scaled conjugate gradient method. We found that the scaled conjugate gradient approach is the faster of the two, with quite equally good performance. Our method was tested on a dataset recorded by four selected stations of the Mt. Vesuvius monitoring network, for the discrimination of low magnitude VT events and transient signals caused by either artificial (quarry blasts, underwater explosions) and natural (thunder) sources. In this test application we obtained 100% correct classification for one of the possible pairs of signal types (VT versus quarry blasts). Because this method was developed independently of this particular discrimination task, it can be applied to a broad range of other applications

Working Memory, Jumping to Conclusions and Emotion Recognition: a Possible Link in First Episode Psychosis (Fep)

Introduction A large body of literature has demonstrated that people affected by psychotic disorders show deficits in working memory, in Emotion Recognition (ER) and in data-gathering to reach a decision (Jumping To Conclusions - JTC). Aims To investigate a possible correlation between working memory, JTC and ER in FEP. Methods 41 patients and 89 healthy controls completed assessments of working memory using WAIS shortened version, JTC using the 60:40 Beads Task and ER using Degraded Facial Affect Recognition Task. Results According to the literature, cases had poorer performance in working memory tasks (Digit Span: \u3bc7,72 [ds=2,98] vs \u3bc10,14 [ds=3,10], U=865,00, p=0,00; Digit Symbol: \u3bc5,36 [ds=2,43] vs \u3bc10,05 [ds=3,10], U=455,50, p=0,00; Arithmetic: \u3bc5,46 [ds=2,76] vs \u3bc8,74 [ds=3,24], U=865,50, p=0,00; Block Design: \u3bc4,82 [ds=2,72] vs \u3bc7,60 [ds=3,18], U=912,00, p=0,00), in Beads Task (81,6% vs 51,1%, \u3c72=10,27, p=0,001, \u3bc2,53 [ds=3,57] vs \u3bc4,23 [ds=4,77], U=1171,00, p=0,006) and in DFAR (total errors: \u3bc21,62 [ds=7,43] vs \u3bc16,58 [ds=8,69], U=554,50, p=0,002). Furthermore working memory tasks in cases group correlated significantly with JTC (Digit Span: rrho=0,276, p=0,003; Digit Symbol: rrho=0,275, p=0,002; Arithmetic: rrho=0,265, p=0,003; Block Design: rrho=0,292, p=0,001), but only Digit Span with ER (rrho=-0,239; p=0,021). In addition, we found that JTC and ER were significantly associated (rrho=-0,281; p=0,004). Conclusions Data show that working memory impairments, JTC style and dysfunctions in the facial emotions recognition are phenomena strongly correlated in the group of patients. Preliminary results suggest the importance of early rehabilitation as the impairments detected may lead to difficulties in social and relational adaptation in psychotic patients

Superconductivity and spin triplet collective mode in the t-J model close to antiferromagnetic instability

To investigate relations between long-range antiferromagnetic (AF) order, superconductivity and two particle triplet collective excitations we consider a modified two dimensional t-J model at doping close to half filling. The model includes additional hopping t'' and nearest sites Coulomb repulsion V. The additional parameters allow us to control closeness of the system to the AF instability. We demonstrate the possibility of co-existence of long-range AF order and d-g-wave superconductivity. In the phase with long-range AF order we find, analytically, superconducting gaps and spin wave renormalization. We demonstrate that at approaching the point of the AF instability the spin triplet collective excitation arises with energy below the superconducting gap.Comment: 9 page

Cognitive thought diary in supportive psychology for people undergoing radiotherapy: a feasibility study.

BAC KGROUND: Radiation therapy (RT ) has become one of the most widely-used and efficient treatments for cancer; nevertheless, people who undergo radiotherapy suffer the physical and psychological consequences of this stressful treatment, in addition to the psychosocial distress related to cancer. However, a Radiotherapy Unit is often a place where several patients crowd in from various hospitals with restricted timetables and, for logistic reasons, it is not easy to provide regular psychological sessions for each one. It is important to find a setting that allows us the involvement of the largest number of patients referred to the unit. In this study, we aimed to evaluate the feasibility and the effect of a brief intervention of cognitive-oriented diary on the quality of life, anxiety and depressive symptoms of patients undergoing radiotherapy (RT ), compared to a control group. METH ODS: The sample was constituted of 68 experimental subjects and 78 controls, treated with RT . Both groups were assessed with the Toronto Alexithymia Scale (TAS -20), the Hamilton Anxiety and Depression Scale (HA DS) and the EORTC -QLQ at the beginning and at the end of their RT . Experimental subjects were instructed to report emotions and thoughts before attending the RT sessions in a thought diary. RES ULTS : The experimental group showed a good adherence to the diary, a reduction in mean scores of anxiety (P<0.001), depression (P<0.001), and alexithymia (P<0.001) together with an ameliorative effect on quality of life (P<0.014), compared to control group. CONCLUSI ONS: We observed a reduction in alexithymia scores in the experimental group, together with a significant reduction in anxiety and depression symptoms and an improvement in quality of life, with a moderator role of social disparity in treatment adherence. Our outcomes suggest the opportunity to consider the diary an affordable and effective device for psychologists operating in RT units, able to be extended to the majority of patients, in a simple and replicable setting

Observing Volcanoes from the Seafloor in the Central Mediterranean Area

The three volcanoes that are the object of this paper show different types of activity that are representative of the large variety of volcanism present in the Central Mediterranean area. Etna and Stromboli are sub-aerial volcanoes, with significant part of their structure under the sea, while the Marsili Seamount is submerged, and its activity is still open to debate. The study of these volcanoes can benefit from multi-parametric observations from the seafloor. Each volcano was studied with a different kind of observation system. Stromboli seismic recordings are acquired by means of a single Ocean Bottom Seismometer (OBS). From these data, it was possible to identify two different magma chambers at different depths. At Marsili Seamount, gravimetric and seismic signals are recorded by a battery-powered multi-disciplinary observatory (GEOSTAR). Gravimetric variations and seismic Short Duration Events (SDE) confirm the presence of hydrothermal activity. At the Etna observation site, seismic signals, water pressure, magnetic field and acoustic echo intensity are acquired in real-time thanks to a cabled multi-disciplinary observatory (NEMO-SN1 ). This observatory is one of the operative nodes of the European Multidisciplinary Seafloor and water-column Observatory (EMSO; www.emso-eu.org) research infrastructure. Through a multidisciplinary approach, we speculate about deep Etna sources and follow some significant events, such as volcanic ash diffusion in the seawater

Observing Volcanoes from the Seafloor in the Central Mediterranean Area

The three volcanoes that are the object of this paper show different types of activity that are representative of the large variety of volcanism present in the Central Mediterranean area. Etna and Stromboli are sub-aerial volcanoes, with significant part of their structure under the sea, while the Marsili Seamount is submerged, and its activity is still open to debate. The study of these volcanoes can benefit from multi-parametric observations from the seafloor. Each volcano was studied with a different kind of observation system. Stromboli seismic recordings are acquired by means of a single Ocean Bottom Seismometer (OBS). From these data, it was possible to identify two different magma chambers at different depths. At Marsili Seamount, gravimetric and seismic signals are recorded by a battery-powered multi-disciplinary observatory (GEOSTAR). Gravimetric variations and seismic Short Duration Events (SDE) confirm the presence of hydrothermal activity. At the Etna observation site, seismic signals, water pressure, magnetic field and acoustic echo intensity are acquired in real-time thanks to a cabled multi-disciplinary observatory (NEMO-SN1 ). This observatory is one of the operative nodes of the European Multidisciplinary Seafloor and water-column Observatory (EMSO; www.emso-eu.org) research infrastructure. Through a multidisciplinary approach, we speculate about deep Etna sources and follow some significant events, such as volcanic ash diffusion in the seawater.Published2983A. Ambiente MarinoJCR Journalrestricte