IEEE Transactions on Autonomous Mental Development Special Issue on
Multimodal Modeling and Analysis Informed by Brain Imaging
Call for Papers
A challenging problem facing multimedia content analysis is the semantic gap between the
high-level perception and cognition in the human brain and the low-level features embedded
in digital contents. The human brain is the ultimate recipient and assessor of multimedia
content and semantics. Deep understanding of the brain responses to multimedia will
fundamentally advance the computational strategies for multimodal representation,
classification and retrieval.
We envision a future with a seamless integration between cognitive neuroscience, a discipline
related to the principle and mechanisms of the brain, and computer science, a discipline
designing automated digital algorithms. Examples of such integration include neural network
algorithms, which could reduce the semantic gap by mimicking the neural processes in the
brain. Conversely, applications of automated computer algorithms have advanced our
understanding of the brain. In the recent years, we have witnessed the emergence of novel
brain-guided or brain-informed techniques in multimedia analysis and modeling, including
computational visual attention models, sparse representation techniques, and deep learning
techniques. These techniques have been applied to object recognition, image categorization,
image/video compression, image/video retrieval, and video summarization.
The remarkable development of neuroimaging techniques such as functional magnetic
resonance imaging (fMRI), electroencephalography (EEG) and magnetoencephalography
(MEG), has enabled us to probe the human brain in natural settings such as free viewing of
multimedia contents. This development is leading a new trend that applies neuroscience and
neuroimaging to assisting multimodal analysis and modeling. This new methodology has
considerably narrowed the gaps between the low-level multimedia features and the high-level
semantics. In parallel, neuroimaging combined with naturalistic stimuli such as films and
music also provide neuroscientist an intriguing opportunity to examine the brain circuitry
underlying natural experience. We believe that the integration of neuroimaging and
multimedia will significantly advance our understanding on how the human brain perceive,
process and assess multimodal contents, as well as developing effective algorithms for
multimedia analysis.
This special issue will focus on the synergistic combinations of cognitive brain science, brain
imaging, and multimedia analysis. It aims to capture the latest advances in the research
community working on brain imaging-informed multimedia analysis, as well as
computational model of the brain processes driven by multimedia contents. We are soliciting
original contributions for:
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Brain encoding and decoding models under natural multimedia (image/video/audio) via
fMRI and EEG
New development of brain computer interface (BCI)
Models of brain functional interaction under natural multimedia stimulus
Brain imaging informed multimedia content representation
Brain imaging informed computational models for multimedia applications
Brain imaging informed multimedia applications, including object recognition,
image/video/audio categorization, image/video/audio retrieval and summarization,
image/video/audio emotion or effective computing, and image/video/audio
recommendation
Clinical application of multimedia stimulus in brain disorders
Editors:
 Junwei Han, Northwestern Polytechnical University, junweihan2010@gmail.com
 Tianming Liu, University of Georgia, tliu@cs.uga.edu
 Christine Cong Guo, QIMR Berghofer, christine.cong@gmail.com
 Deniz Erdogmus, Northeastern University, erdogmus @ece.neu.edu
 Juyang (John) Weng, Michigan State University, weng@cse.msu.edu
Three kinds of submissions are possible:
 Regular papers, up to 15 double column pages, should describe new empirical findings
that utilize innovative methodological and/or analytic techniques.
 Correspondence papers, up to 8 double column pages, can focus on a limited set of
relevant aspects in depth.
 Survey papers, focusing on the state-of-the-art technologies and new trends and
challenges in this area. Before submitting a survey paper, the authors should contact the
guest editors.
Instructions for authors:
http://cis.ieee.org/ieee-transactions-on-autonomous-mental-development.html
We are accepting submissions through Manuscript Central at
http://mc.manuscriptcentral.com/tamd-ieee (please select “Multimodal Modeling and
Analysis Informed by Brain Imaging” as the submission type)
When submitting your manuscript, please also cc it to the editors.
Timeline:
10 October 2014:
15 February 2015:
28 February 2015:
April 2015:
Deadline for paper submission
Notification of acceptance
Final manuscript
Tentative publication date