Machine Learning

Learning in Neural Circuits

 

Circuit diagram of the first processing stages in a cortical column.

Comparison of distributions of simple cells RFs and RFs developed by different models. Blue dots mark the column model in Lücke, Neural Comp, 2009

In this project computational models of learning in neural microcircuits are studied. The studied systems are motivated by recent data on synaptic plasticity and on on the fine-scale structure of neural circuits. We study the implications of such models for learning and compare the resulting neural response properties to experimental data.

DownloadColumns_Code.zip

Further Reading

  • C. Keck*, C. Savin*, and J. Lücke (2012).
    Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin? (online access, bibtex)
    PLoS Computational 8(3): e1002432.
    *joint first authorship


  • C. Keck, C. Savin and J. Lücke (2011).
    Input normalization and synaptic scaling - two sides of the same coin (abstract, poster)
    Proc. COSYNE.

  • C. Keck and J. Lücke (2010).
    Learning of Lateral Connections for Representational Invariant Recognition (pdf, bibtex).
    Proc. ICANN 2010, LNCS 6354, 21-30.

  • J. Bornschein, M. Henniges, G. Puertas, J. Lücke (2010)
    Binary Hidden Variables and Sparse Sensory Coding
    Frontiers Comp Neurosci, Proceedings BCCN. (online access)

  • J. Bornschein and J. Lücke (2009).
    Applications of Non-linear Component Extraction to Spectrogram Representations Of Auditory Data
    Frontiers in Compuational Neuroscience, Proc. BCCN (poster, online access).

  • J. Lücke (2009).
    Receptive Field Self-Organization in a Model of the Fine-Structure in V1 Cortical Columns (online access, bibtex).
    Neural Computation 21(10):2805-2845.

  • J. Lücke (2007).
    A Dynamical Model for Receptive Field Self-Organization in V1 Cortical Columns (bibtex).
    Proc. ICANN, Springer, LNCS 4669, 389-398

  • J. Lücke and J. D. Bouecke (2005).
    Dynamics of Cortical Columns - Self-Organization of Receptive Fields. (pdf, bibtex).
    Proc. ICANN, Springer, LNCS 3696, 31-37.

  • J. Lücke and C. von der Malsburg (2004).
    Rapid processing and unsupervised learning in a model of the cortical macrocolumn (pdf, bibtex).
    Neural Computation, 16(3):501-533.

  • J. Lücke (2004).
    Hierarchical self-organization of minicolumnar receptive fields (pdf, bibtex).
    Neural Networks 17:1377-1389.

     

Copyright notice

The papers listed above have been published after peer review in different journals. These journals remain the only definitive repository of the content. Copyright and all rights therein are usually retained by the respective publishers. These materials may not be copied or reposted without their explicit permission. Use for scholarly purposes only.