Michael DeWeese: Difference between revisions

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*27.  J. Zylberberg, D. Pfau, and M.R. DeWeese.  Dead leaves and the dirty ground: Low-level image statistics in transmissive and occlusive imaging environments. Physical Review E. (in press; Accepted Dec 4, 2012).
*27.  J. Zylberberg, D. Pfau, and M.R. DeWeese.  Dead leaves and the dirty ground: Low-level image statistics in transmissive and occlusive imaging environments. Physical Review E. (in press; Accepted Dec 4, 2012).


*26.  P.R. Zulkowski, D.A. Sivak, G.E. Crooks, and M.R. DeWeese. The geometry of thermodynamic control. Physical Review E. 86(4 Pt 1):041148 (2012).
*26.  P.R. Zulkowski, D.A. Sivak, G.E. Crooks, and M.R. DeWeese. [https://redwood.berkeley.edu/w/images/c/cb/Zulkowski_Sivak_Crooks_DeWeese_PRE_2012_reprint.pdf The geometry of thermodynamic control.] Physical Review E. 86(4 Pt 1):041148 (2012).


*25.  N. Carlson, V.L. Ming, and M.R. DeWeese. [https://redwood.berkeley.edu/w/images/4/4b/Carlson_Ming_DeWeese_Sparse_speech_ICC_PLoS_CB_2012_reprint.pdf Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus.] Public Library of Science Computational Biology. 7(10):e1002250 (2012).
*25.  N. Carlson, V.L. Ming, and M.R. DeWeese. [https://redwood.berkeley.edu/w/images/4/4b/Carlson_Ming_DeWeese_Sparse_speech_ICC_PLoS_CB_2012_reprint.pdf Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus.] Public Library of Science Computational Biology. 7(10):e1002250 (2012).

Revision as of 23:45, 9 January 2013

Here is my publication list including some preprints. Most papers are available here as PDFs.

Selected manuscripts in preparation:

  • ix. M. Mudigonda, J. Sohl-Dickstein, and M.R. DeWeese. Faster sampling from probabilistic models by reduced flipping in Hamiltonian Markov chain Monte Carlo sampling. (in preparation)
  • viii. N. Carlson, V.L. Ming, and M.R. DeWeese. Probe stimuli affect receptive field estimation of model auditory neurons optimized to represent speech efficiently. (in preparation)
  • vii. S. Marzen, J. Zylberberg, and M.R. DeWeese. The effect of natural scene statistics and oculomotor strategy on binocular disparity and ocular dominance maps. (in preparation)
  • vi. S. Corinaldi and M.R. DeWeese. A network model of task switching optimized to minimize errors predicts several counterintuitive features of human behavioral data. (in preparation).
  • v. C. Rodgers, M. Dastjerdi, and M.R. DeWeese. Task-dependent anticipatory activity in both prefrontal cortex and auditory cortex during a purely auditory selective attention task. (in preparation).

Submitted manuscripts:

  • iv. T. Hromádka, A.M. Zador, and M.R. DeWeese. Up-states are rare in awake auditory cortex. (submitted).
  • ii. J. Zylberberg and M.R. DeWeese. A model of primary visual cortex can exhibit decreasing sparseness while learning a sparse code for natural images. (submitted).

All publications:

  • 28. P. King, J. Zylberberg, and M.R. DeWeese. Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1. Journal of Neuroscience (in press).
  • 27. J. Zylberberg, D. Pfau, and M.R. DeWeese. Dead leaves and the dirty ground: Low-level image statistics in transmissive and occlusive imaging environments. Physical Review E. (in press; Accepted Dec 4, 2012).

2011-2012 Publications:

  • 23. J. Sohl-Dickstein, P. Battaglino, and M.R. DeWeese. Minimum Probability Flow Learning. Proceedings of the 28th International Conference on Machine Learning (Bellevue, WA) (2011).
  • 22. J. Zylberberg, J.T. Murphy, and M.R. DeWeese. A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of V1 simple cell receptive fields. Public Library of Science Computational Biology. 7(10):e1002250 (2011).

2010-2011 Publications:

  • 21. J. Zylberberg, and M.R. DeWeese. How should prey animals respond to uncertain threats? Frontiers in Computational Neuroscience 5:20. doi: 10.3389/fncom.2011.00020 (2011).

2009-2010 Publications:

  • 20. M.A. Olshausen and M.R. DeWeese. Applied mathematics: The statistics of style. Nature 463(7284), 1027-1028 (2010).

2008-2009 Publications:

  • 19. Y. Yang, M.R. DeWeese, G. Otazu, and A.M. Zador. Millisecond-scale differences in neural activity in auditory cortex can drive decisions. Nature Neuroscience 11, 1262-1263 (2008).

2007-2008 Publications:

  • 18. T. Hromadka, M.R. DeWeese, and A.M. Zador. Sparse representation of sounds in the unanesthetized auditory cortex. PLoS Biol. 6, 124-137 (2008).

2006-2007 Publications:

  • 17. M.R. DeWeese. Whole-Cell Recording In Vivo. Chapter 6 in Current Protocols in Neuroscience. John Wiley & Sons, Inc., pp. 6.22.1-15 (2007).
  • 16. M.R. DeWeese and A.M. Zador. Non-Gaussian membrane potential dynamics imply sparse, synchronous activity in auditory cortex. J. Neuroscience 26(47), 12206-12218 (2006).

Pre July 1, 2006 Publications:

  • 15. M.R. DeWeese and A.M. Zador. Neurobiology: Efficiency Measures. Nature 439(7079), 920-921 (2006).
  • 14. M.R. DeWeese, T. Hromádka, and A.M. Zador. Reliability and representational bandwidth in auditory cortex. Neuron 48, 479-588 (2005).
  • 13. M.R. DeWeese and A.M. Zador. Neural gallops across auditory streams. Neuron 48, 5-7 (2005).
  • 12. M.R. DeWeese and A.M. Zador. Shared and private variability in the auditory cortex. J. Neurophysiol. 92, 1840-1855 (2004).
  • 11. M.R. DeWeese and A.M. Zador. Binary coding in auditory cortex. In Advances in Neural Information Processing Systems. MIT Press, Cambridge, MA, Vol. 15, 101 (2003).
  • 10. M.R. DeWeese, M. Wehr, and A.M. Zador. Binary spiking in auditory cortex. J. Neurosci. 23, 7940-7949 (2003).
  • 9. M.R. DeWeese. An optimal preparation for studying optimization. Neuron 26, 546-548 (2000).
  • 8. M.R. DeWeese and M. Meister. How to measure the information gained from one symbol. Network 10, 325-340 (1999).
  • 7. G. Buracas, A.M. Zador, M.R. DeWeese, and T. Albright. Efficient discrimination of temporal patterns by motion-sensitive neurons in primate visual cortex. Neuron 20, 959-969 (1998).
  • 6. M.R. DeWeese and A. Zador. Asymmetric dynamics in optimal variance adaptation. Neural Computation 10, 1179-1202 (1998).
  • 5. M.R. DeWeese. Optimization principles for the neural code. Network 7, 325-331 (1996).
  • 4. M. DeWeese. Optimization principles for the neural code. In Advances in Neural Information Processing Systems. MIT Press, Cambridge, MA, Vol. 8, p. 281 (1996).
  • 3. W. Bialek and M. DeWeese. Random switching and optimal processing in the perception of ambiguous signals. Phys. Rev. Lett. 74, 3077-3080 (1995).
  • 2. M. DeWeese and W. Bialek. Information flow in sensory neurons. Nuovo Cimento A17, 733 (1995).
  • 1. W. Bialek, M. DeWeese, F. Rieke, and D. Warland. Bits and brains: information flow in the nervous system. Physica A 200, 581-593 (1993).


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