Computational Neuroscience and Multiscale Brain Modeling     


 photoJames R. Kozloski photoTim Rumbell photo

Computational Neuroscience and Multiscale Brain Modeling Publications



Self-referential forces are sufficient to explain different dendritic morphologies
H Memelli, B Torben-Nielsen, J Kozloski
Frontiers in Neuroinformatics 7(1), Frontiers Media, 2013



An Ultrascalable Solution to Large-scale Neural Tissue Simulation
J. Kozloski, J. Wagner
Front Neuroinform5, 15, 2011

Automated reconstruction of neural tissue and the role of large-scale simulation
J. Kozloski
Neuroinformatics 9(2-3), 133--142, 2011


Establishing relationships between components in simulation systems
D H Carey, J R Kozloski, H Lamehamedi, C C Peck III, R Rao
US Patent 7,756,691

A theory of loop formation and elimination by spike timing-dependent plasticity
J. Kozloski, G. A. Cecchi
Front Neural Circuits4, 7, 2010


Interoperable Model Graph Simulator for High-Performance Computing
J Kozloski, M Eleftheriou, B Fitch, C Peck
IBM Research Reports RC24811(W0906-078), 2009


Unsupervised segmentation with dynamical units
A R Rao, G A Cecchi, C C Peck, J R Kozloski
IEEE Transactions on Neural Networks 19(1), 168, IEEE, 2008

Identifying, tabulating, and analyzing contacts between branched neuron morphologies
J Kozloski, K Sfyrakis, S Hill, F Schuermann, C Peck, H Markram
IBM Journal of Research and Development 52(1/2), 43--55, IBM, 2008

Efficient segmentation in multi-layer oscillatory networks
A Ravishankar Rao, G A Cecchi, C C Peck, J R Kozloski
Neural Networks, 2008, pp. 2966--2973

Network-related challenges and insights from neuroscience
C Peck, J Kozloski, G Cecchi, S Hill, F Schuermann, H Markram, R Rao
Bio-Inspired Computing and Communication, pp. 67--78, Springer, 2008

Topological Effects of Synaptic Time Dependent Plasticity
J R Kozloski, G A Cecchi
Arxiv preprint arXiv:0810.0029, 2008

Devices, methods, and systems for accessing native neurons through artificial neural mediators (ANMS)
J R Kozloski, S Polonsky
Patent US20080299201A1
US Patent App. 11/487,810


Topographic Infomax in a Neural Multigrid
J Kozloski, G Cecchi, C Peck, A Rao
Advances in Neural Networks, ISNN 20074492, 500--509, Springer

Emergence of Topographic Cortical Maps in a Parameterless Local Competition Network
A Rao, G Cecchi, C Peck, J Kozloski
Advances in Neural Networks, ISNN 20074492, 552--561, Springer


Translation invariance in a network of oscillatory units
A R Rao, G A Cecchi, C C Peck, J R Kozloski
Proceedings of SPIE, pp. 469--477, 2006

Inference and segmentation in cortical processing
Y Liu, G A Cecchi, A R Rao, J Kozloski, C C Peck
Proceedings of SPIE, pp. 344--353, 2006

An optimization approach to achieve unsupervised segmentation and binding in a dynamical network
A R Rao, G A Cecchi, C C Peck, J R Kozloski
IEEE International Joint Conference on Neural Networks, 2006, pp. 4159--4166



A proposed method for recording intracellular signals using errors in intracellular biopolymer synthesis
J Kozloski
Society for Neuroscience, 2004


Simulation infrastructure for modeling large scale neural systems
C Peck, J Kozloski, A Rao, G Cecchi
Computational Science, ICCS, 713--713, Springer, 2003


Stereotyped position of local synaptic targets in neocortex
J Kozloski, F Hamzei-Sichani, R Yuste
Science 293(5531), 868, AAAS, 2001


Rate coding of sound features in second and third order auditory nuclei is computed from temporally structured first order spike trains
J Kozloski, JD Crawford
Society for Neuroscience Abstracts, 1998

Year Unknown

Inference and segmentation in cortical processing (Proceedings Paper)
Y Liu, G A Cecchi, A R Rao, J Kozloski, C C Peck, 0

Group Members

  • James Kozloski
  • Adam Ponzi
  • James Humble
  • Sebastien Naze
  • Sushmita Allam
  • Tim Rumbell
  • Tuan Hoang Trong
  • Vittorio Caggiano