Christian Machens

Christian Machens

Champalimaud Neuroscience Programme

Scientific Interests

  1. - models of neural data: dimensionality reduction methods, probabilistic models, etc
  2. - models of neural networks: continuous attractors, integrators, decision systems, etc.
  3. - models of behavior: reinforcement learning, bayesian learning, control theory, etc

Recent Publications

Disentangling the functional consequences of the connectivity between optic-flow processing neurons.

Weber F, Machens CK, Borst A (2012), Nature Neuroscience, in press.
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Demixed principal component analysis.

Brendel W , Romo R , Machens CK (2011), Advances in Neural Information Processing Systems 24.
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Linear readout from a neural population with partial correlation data.

Wohrer A , Romo R , Machens CK (2010), Advances in Neural Information Processing Systems 23.
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Spatio-temporal response properties of optic-flow processing neurons.

Weber F , Machens CK , Borst A (2010), Neuron 67:628-641.
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Demixing population activity in higher cortical areas.

Machens CK (2010), Frontiers in Computational Neuroscience 4(126).

A comprehensive list of publications can be found here.



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