1,721,045 research outputs found
Towards computational proxemics: inferring social relations from interpersonal distances
No full textCristani, M. and Paggetti, G. and Vinciarelli, A. and Bazzani, L. and Menegaz, G. and Murino, V
Waveform decoding and detection in hdEEG
No full textBrain oscillations are very powerful descriptors of both physiological and pathological brain states. In general, EEG signals consist of complex mixtures of components whose characterization provides reliable information about the neuronal activity. This study is inspired to the {\em consensus matching pursuit} (CMP) representation and proposes an effective method for the detection and modeling of interictal prototypical signal patterns in temporal lobe epilepsy. CMP allows accounting for inter-trial variability in temporal jitter, frequency and number of oscillations. In this work, we propose to generalize the approach and exploit the resulting spike representation for automatic interictal spike detection. Performance was evaluated on both synthetic and real high density EEG signals. Results show high sensitivity and specificty in spike detection as well as an accurate separation in the transient and oscillation components
Early detection of epileptic seizures by entropy-based methods
No full textThis work presents a novel method for early detection of
epileptic seizures from EEG data.
Seizure detection was accomplished in three stages: multiresolution overcomplete decomposition by the a-trous algorithm, feature extraction by computing power spectral density and sample entropy values of sub-bands and detection by using z-test and support vector machine (SVM). Results highlight large differences between the subband sample entropy values for the epileptic and the control subjects, respectively, reveling a substantial increase of such parameter during the crisis. This enables high detection accuracy and specificity especially in beta and gamma bands (16-125 Hz).
The detection performance of the proposed method
was evaluated based on the ground truth provided by the expert neurophysiologist as well as by objective indexes when two crisis had been recorded
What PLS can still do for Imaging Genetics in Alzheimer's disease
No full textIn this work we exploited Partial Least Squares (PLS) model for analyzing the genetic underpinning of grey matter atrophy in Alzheimer's Disease (AD). To this end, 42 features derived from T1-weighted Magnetic Resonance Imaging, including cortical thicknesses and subcortical volumes were considered to describe the imaging phenotype, while the genotype information consisted of 14 recently proposed AD related Polygenic Risk Scores (PRS), calculated by including Single Nucleotide Polymorphism passing different significance thresholds. The PLS model was applied on a large study cohort obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database including both healthy individuals and AD patients, and validated on an independent ADNI Mild Cognitive Impairment (MCI) cohort, including Early (EMCI) and Late MCI (LMCI). The experimental results confirm the existence of a joint dynamics between brain atrophy and genotype data in AD, while providing important generalization results when tested on a clinically heterogeneous cohort. In particular, less AD specific PRS scores were negatively correlated with cortical thicknesses, while highly AD specific PRSs showed a peculiar correlation pattern among specific subcortical volumes and cortical thicknesses. While the first outcome is in line with the well known neurodegeneration process in AD, the second could be revealing of different AD subtypes
Deep Learning in Biological Image and Signal Processing
No full textEditorial for the IEEE-SPM Special issue on Deep Learning in Biological Image and Signal Processin
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Infinite Feature Selection on Shore-Based Biomarkers Reveals Connectivity Modulation after Stroke
Full text linkConnectomics is gaining increasing interest in the scientific and clinical communities. It consists in deriving models of structural or functional brain connections based on some local measures. Here we focus on structural connectivity as detected by diffusion MRI. Connectivity matrices are derived from microstructural indices obtained by the 3D-SHORE. Typically, graphs are derived from connectivity matrices and used for inferring node properties that allow identifying those nodes that play a prominent role in the network. This information can then be used to detect network modulations induced by diseases. In this paper we take a complementary approach and focus on link as opposed to node properties. We hypothesize that network modulation can be better described by measuring the connectivity alteration directly in the form of modulation of the properties of white matter fiber bundles constituting the network communication backbone. The goal of this paper is to detect the paths that are most altered by the pathology by exploiting a feature selection paradigm. Temporal changes on connection weights are treated as features and those playing a leading role in a patient versus healthy controls classification task are detected by the Infinite Feature Selection (Inf-FS) method. Results show that connection paths with high discriminative power can be identified that are shared by the considered microstructural descriptors allowing a classification accuracy ranging between 83% and 89%
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