Wave packet evolution approach to ionization of hydrogen molecular ion by fast electrons

The multiply differential cross section of the ionization of hydrogen molecular ion by fast electron impact is calculated by a direct approach, which involves the reduction of the initial 6D Schr\"{o}dinger equation to a 3D evolution problem followed by the modeling of the wave packet dynamics. This approach avoids the use of stationary Coulomb two-centre functions of the continuous spectrum of the ejected electron which demands cumbersome calculations. The results obtained, after verification of the procedure in the case atomic hydrogen, reveal interesting mechanisms in the case of small scattering angles.Comment: 7 pages, 8 Postscript figure

Corrigendum: Computational Methods for Resting-State EEG of Patients With Disorders of Consciousness

An author name was incorrectly spelled as \u201cUrszulaMarkowska-Kacznar.\u201d The correct spelling is \u201cUrszulaMarkowska-Kaczmar.\u201d The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated

Predicting complexity perception of real world images

The aim of this work is to predict the complexity perception of real world images.We propose a new complexity measure where different image features, based on spatial, frequency and color properties are linearly combined. In order to find the optimal set of weighting coefficients we have applied a Particle Swarm Optimization. The optimal linear combination is the one that best fits the subjective data obtained in an experiment where observers evaluate the complexity of real world scenes on a web-based interface. To test the proposed complexity measure we have performed a second experiment on a different database of real world scenes, where the linear combination previously obtained is correlated with the new subjective data. Our complexity measure outperforms not only each single visual feature but also two visual clutter measures frequently used in the literature to predict image complexity. To analyze the usefulness of our proposal, we have also considered two different sets of stimuli composed of real texture images. Tuning the parameters of our measure for this kind of stimuli, we have obtained a linear combination that still outperforms the single measures. In conclusion our measure, properly tuned, can predict complexity perception of different kind of images

Anxiety disorders in headache patients in a specialised clinic: prevalence and symptoms in comparison to patients in a general neurological clinic

Data from several studies indicate an association of headache with anxiety disorders. In this study, we assessed and differentiated anxiety disorders in 100 headache patients by using the PSWQ (Penn State Worry Questionnaire) screening tool for generalised anxiety disorder (GAD) and the ACQ (Agoraphobic Cognitions Questionnaire) and BSQ (Body Sensation Questionnaire) for panic disorder (PD). Control groups were constructed: (1) on the basis of epidemiological studies on PD and GAD in the general population and (2) by including neurological patients. 37.0% of headache patients had a GAD. 27% of headache patients met the score for PD in the BSQ, 4.0% in the ACQ. Significant results were obtained in comparison to the general population (p < 0.001) and with regard to GAD in comparison with a sample of neurological patients (p < 0.005). The BSQ significantly correlated with the number of medication days (p < 0.005). The results confirm the increased prevalence of GAD in headache patients. PD seems to increase the risk of medication overuse

Recruitment and Consolidation of Cell Assemblies for Words by Way of Hebbian Learning and Competition in a Multi-Layer Neural Network

Current cognitive theories postulate either localist representations of knowledge or fully overlapping, distributed ones. We use a connectionist model that closely replicates known anatomical properties of the cerebral cortex and neurophysiological principles to show that Hebbian learning in a multi-layer neural network leads to memory traces (cell assemblies) that are both distributed and anatomically distinct. Taking the example of word learning based on action-perception correlation, we document mechanisms underlying the emergence of these assemblies, especially (i) the recruitment of neurons and consolidation of connections defining the kernel of the assembly along with (ii) the pruning of the cell assembly’s halo (consisting of very weakly connected cells). We found that, whereas a learning rule mapping covariance led to significant overlap and merging of assemblies, a neurobiologically grounded synaptic plasticity rule with fixed LTP/LTD thresholds produced minimal overlap and prevented merging, exhibiting competitive learning behaviour. Our results are discussed in light of current theories of language and memory. As simulations with neurobiologically realistic neural networks demonstrate here spontaneous emergence of lexical representations that are both cortically dispersed and anatomically distinct, both localist and distributed cognitive accounts receive partial support

Large-scale neural model for visual attention: Integration of experimental single cell and fMRI data

A computational neuroscience framework is proposed to better understand the role and the neuronal correlate of spatial attention modulation in visual perception. The model consists of several interconnected modules that can be related to the different areas of the dorsal and ventral paths of the visual cortex. Competitive neural interactions are implemented at both microscopic and interareal levels, according to the biased competition hypothesis. This hypothesis has been experimentally confirmed in studies in humans using functional magnetic resonance imaging (fMRI) techniques and also in single-cell recording studies in monkeys. Within this neurodynamical approach, numerical simulations are carried out that describe both the fMRI and the electrophysiological data. The proposed model draws together data of different spatial and temporal resolution, as are the above-mentioned imaging and single-cell results