Computational and Mathematical Methods in Medicine

Methodological Advances in Brain Connectivity


Publishing date
18 May 2012
Status
Published
Submission deadline
18 Nov 2011

Lead Editor

1Department of Physics and Biotechnology, University of Trento, Mattarello, 38122 Trento, Italy

2Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain

3J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611-6131, USA

4Department of Mathematical, Physical and Computational Sciences, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece


Methodological Advances in Brain Connectivity

Description

In recent years, neuroscience has recognized that the concept of brain connectivity is central for the understanding of the synergic behavior of cerebral regions which constitute distributed structural and functional networks. Brain connectivity refers to the description of how brain areas interact, encompassing different and interrelated aspects such as anatomical links (structural connectivity), statistical dependencies (functional connectivity), or causal interactions (effective connectivity). As such, the study of brain connectivity has become central both for the investigation of neurophysiological processes typically engaged in cognitive and perceptive processing and for the assessment of a wide variety of neurological disorders.

The main focus of this special issue is on analytical and computational techniques for the investigation of brain connectivity through data analysis, modeling, and integration. Indeed, the fast advancement of multichannel data acquisition technology and processing capability has fostered the development of sophisticated approaches to the study of brain networks. These approaches include multivariate analysis of linear stochastic processes, complexity analysis of nonlinear dynamical systems, principal and independent component analysis, graph theory, structural equation modeling, dynamic causal modeling, and Granger causality analysis. These methodologies have been applied to brain signals acquired in different modalities such as electroencephalography, magnetoencephalography, and functional and diffusion magnetic resonance imaging.

In this context, the special issue will bring together experts from the fields of computational and experimental neuroscience to summarize recent developments and to advance new ideas on various aspects of brain connectivity. Potential topics include, but are not limited to:

  • Inference of causality from time series analysis
  • Inference of causality from graphical models
  • Inference of synchronization from dynamical systems analysis
  • Statistical techniques for measuring connectivity
  • Effective and functional connectivity
  • Structural/anatomical connectivity
  • Multimodal neuroimaging for discovering connectivity
  • Topology of brain networks
  • Connectivity as a tool for assessing clinical disorders and cognitive behaviors

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/cmmm/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2012
  • - Article ID 492902
  • - Editorial

Methodological Advances in Brain Connectivity

Luca Faes | Ralph G. Andrzejak | ... | Dimitris Kugiumtzis
  • Special Issue
  • - Volume 2012
  • - Article ID 912729
  • - Research Article

Fundamental Dynamical Modes Underlying Human Brain Synchronization

Catalina Alvarado-Rojas | Michel Le Van Quyen
  • Special Issue
  • - Volume 2012
  • - Article ID 402341
  • - Research Article

Localizing True Brain Interactions from EEG and MEG Data with Subspace Methods and Modified Beamformers

Forooz Shahbazi Avarvand | Arne Ewald | Guido Nolte
  • Special Issue
  • - Volume 2012
  • - Article ID 303601
  • - Research Article

Causal Information Approach to Partial Conditioning in Multivariate Data Sets

D. Marinazzo | M. Pellicoro | S. Stramaglia
  • Special Issue
  • - Volume 2012
  • - Article ID 635103
  • - Research Article

Quantification of Effective Connectivity in the Brain Using a Measure of Directed Information

Ying Liu | Selin Aviyente
  • Special Issue
  • - Volume 2012
  • - Article ID 140513
  • - Research Article

Measuring Connectivity in Linear Multivariate Processes: Definitions, Interpretation, and Practical Analysis

Luca Faes | Silvia Erla | Giandomenico Nollo
  • Special Issue
  • - Volume 2012
  • - Article ID 910380
  • - Research Article

An Analytical Approach to Network Motif Detection in Samples of Networks with Pairwise Different Vertex Labels

Christoph Schmidt | Thomas Weiss | ... | Lutz Leistritz
  • Special Issue
  • - Volume 2012
  • - Article ID 697610
  • - Research Article

Statistical Analysis of Single-Trial Granger Causality Spectra

Andrea Brovelli
  • Special Issue
  • - Volume 2012
  • - Article ID 451938
  • - Research Article

Enhancing the Signal of Corticomuscular Coherence

Cristiano Micheli | Christoph Braun
  • Special Issue
  • - Volume 2012
  • - Article ID 476324
  • - Research Article

Computational Models of Neuron-Astrocyte Interactions Lead to Improved Efficacy in the Performance of Neural Networks

Alberto Alvarellos-González | Alejandro Pazos | Ana B. Porto-Pazos

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