Michael DeWeese

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

Selected manuscripts in preparation:

• ix. M. Mudigonda, J. Sohl-Dickstein, M.R. DeWeese, S. Ganguli, and B. Olshausen. Reduced Flipping in Hamiltonian Markov Chain Monte Carlo algorithms. (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 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).

• iii. B. Albanna, C. Hillar, J. Sohl-Dickstein, and M.R. DeWeese. Minimum and maximum entropy solutions for binary systems with known means and pairwise correlations. (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).

• i. A.j. Apicella and M.R. DeWeese. Circuit mechanisms that contribute to spatial tuning in primary auditory cortex. (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. 86:066112.

• 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).

• 25. N. Carlson, V.L. Ming, and M.R. DeWeese. Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus. Public Library of Science Computational Biology. 7(10):e1002250 (2012).

• 24. J. Sohl-Dickstein, P. Battaglino, and M.R. DeWeese. New method for parameter estimation in probabilistic models: Minimum probability flow. Physical Review Letters. 107(22):220601 (2011).

• 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).

• 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).

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

• 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).

• 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).

• 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).

• 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. Il 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).