Statistical Signal Processing in Neuroscience Posted By: David Kennedy - Oct 1, 2008Tool/Resource: Conferences, Workshops and Meetings Call for Papers Signal processing and statistics have been playing a crucial role in neuroscience and neural engineering research. Rapid advances in solid state technology enabled simultaneous recording of many individual neurons with hundreds of microelectrode arrays, thereby accelerating the scrutiny of neural activity at an unprecedented scale. These devices are now becoming an essential constituent in brain-machine interface (BMI) systems to restore, replace, or augment damaged brain function. Nevertheless, there are numerous signal processing challenges associated with the use of this technology to address many fundamental neuroscience questions. Among these, monitoring and quantifying functional alterations of neural circuits in awake, behaving subjects remain a big challenge. Issues such as effectiveness, reliability, scalability, tradeoff between complexity and performance, and real-time processing would all require further research efforts. There is an urgent need to provide the scientific community with an opportunity to summarize the state-of-the-art use of existing signal processing theory and techniques for solving emerging problems in neuroscience, and discuss new theory and algorithms that are specifically tailored to the nature of the neurobiological environment. This special issue invites original contributions in either theory or algorithm development in the area of statistical signal processing in neuroscience. Potential topics include but are not limited to: o Detection, estimation, and classification of neural signals o Array processing and blind separation of neural sources o Statistical inference and hypothesis testing in multiple neural spike train data o Machine-learning theory and techniques for analyzing large scale neural ensembles o Information-theoretic analysis of neural data o Mixed filtering of neural signals o Neural plasticity and adaptive filtering o Decoding neural signals from sensory/motor areas of the brain o Signal processing for neuroprosthesis Authors should follow the EURASIP Journal on Advances in Signal Processing manuscript format described at the journal site http://www.hindawi.com/journals/asp/. 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: Manuscript Due January 1, 2009 First Round of Reviews April 1, 2009 Publication Date July 1, 2009 Guest Editors o Karim Oweiss, Department of Electric and Computer Engineering, Michigan State University, MI 48824-1226, USA; koweiss@msu.edu o Don Johnson, Department of Electric and Computer Engineering, Rice University, TX 77005-1892, USA; dhj@rice.edu o Jose Principe, Department of Electrical and Computer Engineering, University of Florida, FL 32611-6550, USA; principe@cnel.ufl.edu |
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