IEEE TNN Special Issue on temporal coding

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IEEE Transactions on Neural Networks Call for Papers

Special Issue on "Temporal Coding for Neural Information Processing"

Largely motivated by neurobiological discoveries, neural network research is currently witnessing a
significant shift of emphasis towards temporal coding, which uses time as an extra degree of freedom
in neural representations. Temporal coding is passionately debated in neuroscience and related
fields, but in the last few years a large volume of physiological and behavioral data has emerged
that supports a key role for temporal coding in the brain. In neural networks, a great deal of
research is undertaken under the topics of nonlinear dynamics, oscillatory and chaotic networks,
spiking neurons, and pulse-coupled networks. Various information processing tasks are investigated
using temporal coding, including scene segmentation, figure-ground separation, classification,
learning, associative memory, inference, motor control, and communication. Progress has been made
that substantially advances the state-of-the-art of neural computing.

In many instances, however, neural models incorporating temporal coding are driven merely by the
assertion that real neurons use impulses. It is often unclear whether, and to what extent, the
temporal aspects of the models contribute to information processing capabilities. It is time to
assess the role and potential of temporal coding in terms of information processing performance by
providing a comprehensive view of the current approaches and issues to the neural networks
community. This special issue seeks to present, in a collective way, research that makes a clear
contribution to addressing information processing tasks using temporal coding. The issue is
intended not only to highlight successful use of temporal coding in neural networks but also clarify
outstanding issues for future progress.

Suggested topics include but are not limited to the following:

- Synchrony, desynchrony, and other temporal phenomena
- Encoding and decoding in the temporal domain
- Comparative issues in rate coding and temporal coding
- Cognitive aspects of temporal/spatiotemporal phenomena in neural systems
- Effects and uses of time delays
- Potential roles of chaos, randomness and noise
- Learning for temporal codes
- Temporal/spatiotemporal information processing for:
        * Perceptual processing
        * Learning, memory, and reasoning
        * Motor control
        * Communication
- Innovative applications
- Hardware implementation

The guest editors of the special issue are:

Walter Freeman, University of California, Berkeley
Robert Kozma, University of Memphis
Andrzej Lozowski, Southern Illinois University
Ali Minai, University of Cincinnati
DeLiang Wang, Ohio State University

Manuscripts will first be screened for topical relevance, and those that pass the screening process
will undergo the standard review procedure of the IEEE Transactions on Neural Networks (see the
instructions for authors for the Transactions). Paper submission deadline is May 30, 2003, and the
special issue will be published by July 2004. Papers should be submitted in PDF format via email to
the lead guest editor:

DeLiang Wang
Email: dwang@cis.ohio-state.edu
http://www.cis.ohio-state.edu/~dwang

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