Profile
Dong Song
Research Associate Professor
Center for Neural Engineering
Department of Biomedical Engineering

Research Topics
- Hippocampal memory prostheses
- Experimental, theoretical and computational studies of the hippocampus
- Combined mechanistic and statistical modeling of nervous systems
- Mechanisms of learning and memory
- High-density conformal multi-electrode array
- Ultraminiaturized bioelectronics systems for neural recording and stimulation
Research Overview
My main research interests are in the fields of computational neuroscience and neural engineering. The overarching goal of my research is to develop brain-like, biomimetic devices that can mimic and restore cognitive functions. Specifically, I seek to use a combined experimental, theoretical, and computational strategy to (1) understand how nervous systems such as the hippocampus perform higher-order cognitive functions, (2) build hippocampal memory prostheses that can restore memory functions lost as a consequence of diseases or injuries, and (3) develop next-generation, large-scale, multi-scale experimental-modeling methodologies to investigate complex system-level behaviors in the brain.Contact Information
University Park Campus, University of Southern California
Websites
Education
- BS 1994 Biophysics - University of Science and Technology of China, Hefei, China
- PhD 2004 Biomedical Engineering - University of Southern California, Los Angeles, USA
Selected Publications
- Song, D., Robinson, B.S., Hampson, R.E., Marmarelis, V.Z., Deadwyler, S.A., and Berger, T.W. Sparse large-scale nonlinear dynamical modeling of human hippocampus for memory prostheses. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2016, DOI: 10.1109/TNSRE.2016.2604423. Link
Robinson, B.S., Berger, T.W., and Song, D. Identification of stable spike-timing-dependent plasticity from spiking activity with generalized multilinear modeling. Neural Computation, 2016, 28:11, 2320-2351, DOI: 10.1162/NECO_a_00883.
Link- Song, D., Chan, R.H.M., Robinson, B.S., Marmarelis, V.Z., Opris, I., Hampson, R.E., Deadwyler, S.A., and Berger, T.W. Identification of functional synaptic plasticity from spiking activities using nonlinear dynamical modeling. Journal of Neuroscience Methods, 2015, 244, 123-135, DOI: 10.1016/j.jneumeth.2014.09.023. Link
Song, D., Harway, M., Marmarelis, V.Z., Hampson, R.E., Deadwyler, S.A., and Berger, T.W. Extraction and restoration of hippocampal spatial memories with nonlinear dynamical modeling. Frontiers in Systems Neuroscience, 2014, DOI: 10.3389/fnsys.2014.00097.
Link- Song, D., Wang, H., Tu, C.Y., Marmarelis, V.Z., Hampson, R.E., Deadwyler, S.A., and Berger, T.W. Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions. Journal of Computational Neuroscience, 2013, 35, 335-357. Link
Berger, T.W., Hampson, R.E., Song, D., Goonawardena, A., Marmarelis, V.Z., and Deadwyler, S.A. A cortical neural prosthesis for restoring and enhancing memory. Journal of Neural Engineering, 2011, 8, 046017.
LinkSong, D., Chan, R.H.M., Marmarelis, V.Z., Hampson, R.E., Deadwyler, S.A., and Berger, T.W. Nonlinear modeling of neural population dynamics for hippocampal prostheses. Neural Networks, 2009, 22, 1340-1351.
LinkSong, D., Marmarelis, V.Z., and Berger, T.W. Parametric and non-parametric modeling of short-term synaptic plasticity. Part I: Computational study. Journal of Computational Neuroscience, 2009, 26, 1-19.
LinkSong, D., Chan, R.H.M., Marmarelis, V.Z., Hampson, R.E., Deadwyler, S.A., and Berger, T.W. Nonlinear dynamic modeling of spike train transformations for hippocampal-cortical prostheses. IEEE Transactions on Biomedical Engineering, 2007, 54, 1053-1066.
LinkSong, D., Wang, Z., and Berger, T.W. Contribution of T-type VDCCs to TEA-induced long-term synaptic modification in hippocampal CA1 and dentate gyrus. Hippocampus, 2002, 12, 689-697.
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