Search results for "informatica"

Letter by Masè et al Regarding Article, "Granger Causality-Based Analysis for Classification of Fibrillation Mechanisms and Localization of Rotationa…

2020

A new Framework for the Spectral Information Decomposition of Multivariate Gaussian Processes

2021

: Different information-theoretic measures are available in the literature for the study of pairwise and higher-order interactions in multivariate dynamical systems. While these measures operate in the time domain, several physiological and non-physiological systems exhibit a rich oscillatory content that is typically analyzed in the frequency domain through spectral and cross-spectral approaches. For Gaussian systems, the relation between information and spectral measures has been established considering coupling and causality measures, but not for higher-order interactions. To fill this gap, in this work we introduce an information-theoretic framework in the frequency domain to quantify t…

GTVcut for neuro-radiosurgery treatment planning: an MRI brain cancer seeded image segmentation method based on a cellular automata model

2018

Despite of the development of advanced segmentation techniques, achieving accurate and reproducible gross tumor volume (GTV) segmentation results is still an important challenge in neuro-radiosurgery. Nowadays, magnetic resonance imaging (MRI) is the most prominent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a minimally invasive technology for dealing with inaccessible or insufficiently treated tumors with traditional surgery or radiotherapy. During a treatment planning phase, the GTV is generally contoured by experienced neurosurgeons and radiation oncologists using fully manual segmentation procedures on MR images. Unf…

Searching for repetitions in biological networks: methods, resources and tools

2013

We present here a compact overview of the data, models and methods proposed for the analysis of biological networks based on the search for significant repetitions. In particular, we concentrate on three problems widely studied in the literature: ‘network alignment’, ‘network querying’ and ‘network motif extraction’. We provide (i) details of the experimental techniques used to obtain the main types of interaction data, (ii) descriptions of the models and approaches introduced to solve such problems and (iii) pointers to both the available databases and software tools. The intent is to lay out a useful roadmap for identifying suitable strategies to analyse cellular data, possibly based on t…

Computation of Mean Cerebral Blood Flow Velocity for the Assessment of Cerebral Autoregulation: Comparison of Different Strategies

2019

Cerebral autoregulation (CA) is a complex mechanism stabilizing cerebral blood flow (CBF) against arterial pressure (AP) changes. CBF is commonly surrogated with the CBF velocity (CBFV) recorded via transcranial Doppler device from the middle cerebral artery. Most of the studies evaluating CA compute mean CBFV (MCBFV) on a beat-to-beat basis along with mean AP (MAP), but there is not a standard approach to derive MCBFV. In this study, we compare three different strategies to calculate MCBFV: i) between two consecutive diastolic points detected on the CBFV signal (MCBFVCBFV); ii) between two consecutive diastolic points detected on the AP signal (MCBFVAP); iii) between two consecutive R-wave…

Vascular resistance arm of the baroreflex: methodology and comparison with the cardiac chronotropic arm.

2020

Baroreflex response consists of cardiac chronotropic (effect on heart rate), cardiac inotropic (on contractility), venous (on venous return) and vascular (on vascular resistance) arms. Because of its measurement simplicity, cardiac chronotropic arm is most often analysed. The aim was to introduce a method to assess vascular baroreflex arm, and to characterize its changes during stress. We evaluated the effect of orthostasis and mental arithmetics (MA) in 39 (22 female, median age: 18.7 yrs.) and 36 (21 female, 19.2 yrs.) healthy volunteers, respectively. We recorded systolic and mean blood pressure (SBP and MBP) by volume-clamp method and R-R interval (RR) by ECG. Cardiac output (CO) was re…

Selection of blood pressure signal for baroreflex analysis

2020

This study aims to evaluate the strength of the causal coupling among systolic, mean and diastolic blood pressure (SBP, MBP and DBP) with heart period (RR interval) (evaluating cardiac chronotropic baroreflex arm) and peripheral vascular resistance (PVR) (evaluating vascular resistance baroreflex arm) in frequency domain using partial spectral decomposition method. We recorded beat-to-beat RR, SBP, MBP and DBP and PVR values in 39 volunteers during supine rest and head-up tilt. Our results showed that during supine rest the most dominant causal coupling was from DBP to RR in both low and high frequency bands and significantly decreased during orthostasis. The strength of spectral couplings …

Musical pitch quantization as an eigenvalue problem

2020

How can discrete pitches and chords emerge from the continuum of sound? Using a quantum cognition model of tonal music, we prove that the associated Schrödinger equation in Fourier space is invariant under continuous pitch transpositions. However, this symmetry is broken in the case of transpositions of chords, entailing a discrete cyclic group as transposition symmetry. Our research relates quantum mechanics with music and is consistent with music theory and seminal insights by Hermann von Helmholtz.

Stability-Based Model Selection for High Throughput Genomic Data: An Algorithmic Paradigm

2012

Clustering is one of the most well known activities in scien- tific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. In this beautiful area, one of the most difficult challenges is the model selection problem, i.e., the identifi- cation of the correct number of clusters in a dataset. In the last decade, a few novel techniques for model selection, representing a sharp departure from previous ones in statistics, have been proposed and gained promi- nence for microarray data analysis. Among those, the stability-based methods are the most robust and best performing in terms of predic- tion, but the slowest in terms of time. Unfortunately…

On a class of languages with holonomic generating functions

2017

We define a class of languages (RCM) obtained by considering Regular languages, linear Constraints on the number of occurrences of symbols and Morphisms. The class RCM presents some interesting closure properties, and contains languages with holonomic generating functions. As a matter of fact, RCM is related to one-way 1-reversal bounded k-counter machines and also to Parikh automata on letters. Indeed, RCM is contained in L-NFCM but not in L-DFCM, and strictly includes L-CPA. We conjecture that L-DFCM subset of RCM