Brain Connectivity: Recent Advances in Experimental and Computational Approaches

Call for Papers

Brain connectivity represents a multifaceted concept in neuroscience which is central for an understanding of the neurophysiological processes underlying perception and cognition. Also many neurological disorders appear as a consequence of a malfunction of neuronal signaling pathways as well as related neuronal communication networks. Brain connectivity refers to concepts like structural connectivity, describing anatomical connections between neurons, in contrast to functional and effective connectivity. The whole connectome of the brain will be considered in this special issue on all levels, be it macroscopic, mesoscopic, or microscopic. Underlying such concepts is a fundamental understanding of how information is processed in brain. Modeling brain function is thus intimately related with connectivity analysis.

The special issue will focus on computational techniques and analytical models for the investigation of brain connectivity and information processing as well as on related experimental techniques, especially multichannel data acquisition and multimodal functional imaging and concomitant data processing techniques like data integration and image fusion. Computational techniques involve dynamic causal modeling, Granger causality analysis, exploratory matrix factorization techniques, multidimensional EMD, graphical models, multivariate analysis of stochastic processes, complexity analysis of nonlinear dynamical systems, and so forth. Modeling information processing most often focusses on visual pathways but could include also other sensual modalities.

The special issue will bring together experts from the fields of computational intelligence, machine learning, neuroinformatics, and experimental neuroscience to discuss recent developments and propose new ideas about all aspects of brain connectivity. Potential topics include, but are not limited to:

• Multimodal functional imaging for connectivity analysis
• Diffusion tensor imaging and tractography
• Structural connectivity
• Functional or effective connectivity
• The interplay of diverse brain areas during processing of visual perception
• Graphical models of brain networks
• Synchronization in dynamical neuronal networks
• Causality via graphical models
• Causality via time series analysis
• Fusing neurocomputational modeling and connectivity analysis
• Neurological disorders via connectivity analysis

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/cin/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:

Lead Guest Editor

• Elmar W. Lang, Computational Intelligence and Machine Learning Group, Institute of Biophysics, University of Regensburg, 93040 Regensburg, Germany

Guest Editors

• Mark Greenlee, Institute of Psychology, University of Regensburg, 93040 Regensburg, Germany
• Gustavo Deco, Computational Neuroscience Group, Department of Technology, Universitat Pompeu Fabra, 08003 Barcelona, Spain
• Heiko Neumann, Vision and Perception Science Lab, Institute of Neural Information Processing, Faculty of Engineering and Computer Sciences, Ulm University, 89069 Ulm, Germany