Dr. Andreea Lazar
Singer Lab · Post-Doc
- andreea.lazar (at) esi-frankfurt.de
- Deutschordenstr. 46 · 60528 Frankfurt am Main · Germany
- +49 69 96769
The response of cortical networks to stimulation is a complicated interaction between external drive and the ongoing pattern of internally generated activity. I study how experience changes the spatio-temporal properties of cortical activity in simulated recurrent networks and data from in vivo electrophysiology. I am particularly interested in the role of spontaneous activity in neural circuits, its relevance to prediction and memory and its connection to statistical learning.
Lewis, C. M. and A.E. Lazar: Orienting Towards Ensembles: From Single Cells to Neural populations. The Journal of Neuroscience 33(1), 2–3 (2013). Schwiedrzik, C. M., C.C. Ruff, A. Lazar, F.C. Leitner, W. Singer and L. Melloni: Untangling Perceptual Memory: Hysteresis and Adaptation Map into Separate Cortical Networks. Cerebral Cortex (2012). Lazar, A., G. Pipa, and J. Triesch: Emerging Bayesian priors in a self-organizing recurrent network. Artificial Neural Networks and Machine Learning, ICANN 2011, Part II, Lecture Notes in Computer Science, Springer, 6792: 127-134 (2011). Lazar, A., G. Pipa, and J. Triesch: SORN: a self-organizing recurrent neural network. Frontiers in Computational Neuroscience, 3:23 (2009). Lazar, A., G. Pipa, and J. Triesch: Predictive coding in cortical microcircuits. Artificial Neural Networks and Machine Learning, ICANN 2008, Part II, Lecture Notes in Computer Science, Springer, 5164: 386-395 (2008). Lazar, A., G. Pipa, and J. Triesch: Fading memory and time series prediction in recurrent networks with different forms of plasticity. Neural Networks 20, 3, 312-322 (2007).