Publications

2015

B. Cheung, J. A. Livezey, A. K. Bansal, B. A. Olshausen (2015) Discovering Hidden Factors of Variation in Deep Networks. Presented at International Conference on Learning Representations 2015 Workshop. pdf

C. J. Hillar and F. T. Sommer: When can dictionary learning uniquely recover sparse data from subsamples? IEEE Transactions on Information Theory (in press) (2015)

J. Sohl-Dickstein, S. Teng, C. Rodgers, M.R. DeWeese, and N. Harper. A device for human ultrasonic echolocation. IEEE Transactions on Biomedical Engineering (in press) (2015)

S. Mobin, J. Arnemann, F. T. Sommer: Information-based learning by agents in unbounded state spaces. Advances in Neural Information Processing Systems 26, MIT Press (2015).

2014

P. R. Zulkowski and M. R. DeWeese. (2014) Optimal finite-time erasure of a classical bit. Physical Review E. 89(5):052140. pdf

G. Agarwal, I. H. Stevenson, A. Berényi, K. Mizuseki, G. Buzsáki, F. T. Sommer: Spatially distributed local fields in the hippocampus encode rat position. Science 344 (2014): 626-630. pdf Supplement

J. A. Hirsch, X. Wang, V. Vaingankar, F. T. Sommer: Inhibitory circuits in the visual thalamus. Chapter in: The New Visual Neurosciences, Eds.: Leo M. Chalupa and John S. Werner, MIT Press (2014)

A. Knoblauch, E. Koerner, U. Koerner, F. T. Sommer: Structural synaptic plasticity has high memory capacity and can explain graded amnesia, catastrophic forgetting, and the spacing effect. PLOS ONE (2014)

L. M. Martinez, M. Molano-Mazon, X. Wang, F. T. Sommer, J. A. Hirsch: Statistical wiring of thalamic receptive fields optimizes spatial sampling of the retinal image. Neuron 81 (2014) 943-956

C. Rodgers and M. R. DeWeese. Neural correlates of task switching in prefrontal cortex and primary auditory cortex in a novel stimulus selection task for rodents. Neuron (2014). pdf

F. T. Sommer: Neural oscillatons and synchrony as mechanisms for coding, communication and computation in the visual system. Chapter in: The New Visual Neurosciences, Eds.: Leo M. Chalupa and John S. Werner, MIT Press (2014)

J. Sohl-Dickstein, M. Mudigonda, M.R. DeWeese. Hamiltonian Monte Carlo Without Detailed Balance. Proceedings of the 31st International Conference on Machine Learning (Beijing) (2014). pdf

2013

T. Hromádka, A.M. Zador, and M. R. DeWeese. (2013) Up-states are rare in awake auditory cortex. Journal of Neurophysiology, 109(8):1989-95. pdf

P. King, J. Zylberberg, and M. R. DeWeese. (2013) Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1. Journal of Neuroscience, 33(13):5475–85. pdf

D. Y. Little, F. T. Sommer: Learning and exploration in action-perception loops. Frontiers in Neural Circuits, 22 March 2013 doi: 10.3389/fncir.2013.00037 online (The 2011 arXiv version of this paper: Learning in embodied action-perception loops through exploration arXiv)

D. Y. Little, F. T. Sommer: Maximal mutual information, not minimal entropy, for escaping the "Dark Room". Comment on "Whatever next? Predictive brains, situated agents, and the future of cognitive science." in Behavioral Brain Sciences 2013 Jun;36(3):220-221. doi: 10.1017/S0140525X12002415 [1]

P. R. Zulkowski, D. A. Sivak, and M. R. DeWeese. Optimal control of transitions between nonequilibrium steady states. Public Library of Science ONE. 8(12):e82754 (2013). pdf

J. Zylberberg and M. R. DeWeese. (2013) Sparse coding models can exhibit decreasing sparseness while learning sparse codes for natural images. PLoS Computational Biology. 9(8):e1003182. pdf

G. Agarval, F. T. Sommer: Measuring information in spike trains about intrinsic brain signals. Chapter in: Spike timing: Mechanisms and functions, Eds.: P. M. DiLorenzo, J. D. Victor, CRC Press - Taylor & Francis Group (2013) 137-152 Google Books

2012

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

V. Vaingankar, C. Soto-Sanchez, X. Wang, F. T. Sommer, J. A. Hirsch (2012) Neurons in the tha-lamic reticular nucleus are selective for diverse and complex visual features. Frontiers in In-tegrative Neuroscience 6:118. DOI: 10.3389/fnint.2012.00118 online

J. Zylberberg, D. Pfau, and M. R. DeWeese. (2012) Dead leaves and the dirty ground: Low-level image statistics in transmissive and occlusive imaging environments. Physical Review E, 86:066112. pdf

P. R. Zulkowski, D. A. Sivak, G. E. Crooks, and M. R. DeWeese. (2012) The geometry of thermodynamic control. Physical Review E, 86(4 Pt 1):041148. pdf

2011

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

J. Zylberberg, J. T. Murphy, and M. R. DeWeese (2011) A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of V1 simple cell receptive fields. PLOS Computational Biology, 7(10):e1002250. pdf

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

Tosic I., Olshausen B. A. and Culpepper B. J. (2011) Learning sparse representations of depth. IEEE Journal on Selected Topics in Signal Processing, Vol. 5, No 5, pp 941 - 952, 2011. pdf

Wang X, Sommer FT, Hirsch JA: Inhibitory circuits for visual processing in thalamus. Current Opinion in Neurobiology 21 (2011) 726-733

Wang X, Vaingankar V, Soto Sanchez C, Sommer FT, Hirsch JA (2011) Thalamic interneurons and relay cells use complementary synaptic mechanisms for visual processing. Nature Neuroscience 14: 224-231

G. Isely, C. Hillar, F. T. Sommer: Decyphering subsampled data: Adaptive compressive sampling as a principle of brain communication. Advances in Neural Information Processing Systems 23. Eds: J. Lafferty and C. K. I. Williams and J. Shawe-Taylor and R.S. Zemel and A. Culotta (2011) 910-918 pdf

J. Sohl-Dickstein, P. Battaglino, and M.R. DeWeese (2011) Minimum Probability Flow Learning. Proceedings of the 28th International Conference on Machine Learning (Bellevue, WA). pdf

F. T. Sommer: Associative memory and learning. Chapter in Encyclopedia of the Sciences of Learning, Ed.: N. Seel, Springer (2011)

2010

Cadieu CF, Koepsell K (2010) Phase Coupling Estimation from Multivariate Phase Statistics. Neural Computation 22(12), pp. 3107 - 3126. pdf

Canolty RT, Ganguly K, Kennerley SW, Cadieu CF, Koepsell K, Wallis JD, Carmena JM (2010) Oscillatory phase coupling coordinates anatomically-dispersed cell assemblies. PNAS 107(40) 17356 - 17361. journal pdfsupplement

Knoblauch A, Palm G, Sommer FT (2010) Memory capacities for synaptic and structural plasticity. Neural Computation, Volume 22 (2): 289-341 pdf

Koepsell K, Wang X, Hirsch JA, Sommer FT (2010) Exploring the function of neural oscillations in early sensory systems. Focused review in Frontiers in Neuroscience 4 (1): 53-61. Frontiers in Neuroscience

Lauritzen TZ, Ales JM, Wade AR (2010) The effects of visuospatial attention measured across visual cortex using source-imaged, steady-state EEG. J. of Vision 10(14)39: 1 - 17. pdfsupplement

Tsao DY, Cadieu C, and Livingstone M (2010) Object Recognition: Physiological and Computational Insights. In Primate Neuroethology. Edited by M. Platt and A. Ghazanfar. Oxford University Press. 2010 (in press)

Wang X, Hirsch JA, Sommer FT (2010) Recoding of sensory information across the retinothalamic synapse. Journal of Neuroscience 30: 13567-13577

Canolty RT, Ganguly K, Kennerley SW, Cadieu CF, Koepsell K, Wallis JD, Carmena JM (2010) Single-neuron spike timing depends on global brain dynamics. Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00264 abstract

M.A. Silver, A.N Landau, T.Z. Lauritzen, W Prinzmetal, L.C. Robertson. Isolating human brain functional connectivity associated with a specific cognitive process. Proceedings of SPIE Volume 7527 – In press.

Culpepper B.J., Olshausen B.A. Learning transport operators for image manifolds. Advances in Neural Information Processing Systems (NIPS), 22. (2010) Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams and A. Culotta. pdf supplementary materials

2009

Kanerva P (2009). Hyperdimensional Computing: An introduction to computing in distributed representation with high-dimensional random vectors. Cognitive Computation 1(2): 139-159 link pdf

Koepsell K, Wang X, Vaingankar V, Wei Y, Wang Q, Rathbun DL, Usrey W, Hirsch J and Sommer FT (2009) Retinal oscillations carry visual information to cortex. Front Syst Neurosci 3:4 pdf

Lauritzen TZ, D’Esposito M, Heeger D and Silver MA. (2009) Top-down flow of visual spatial attention signals from parietal to occipital cortex. Journal of Vision, 9(13):18, 1-14. link

Ming, V. & Holt, L. (2009) Efficient coding in human auditory perception. J. Acoust. Soc. Am. 126.

Monaci G, Vandergheynst P, Sommer FT (2009) Learning bimodal structure in audio-visual data. IEEE Transactions on Neural Networks 20:1898-1910 pdf

Para LC, Beck JM, Bell AJ (2009) On the maximization of information flow between spiking neurons. Neural Computation, in press

Huth A, Cadieu CF, Dale CL, Weber D, Pantazis D, Darvas F, Leahy R, Simpson GV, Koepsell K (2009) Detecting functional connectivity in networks of phase-coupled neural oscillators, Poster presentation, Computational and Systems Neuroscience. doi: 10.3389/conf.neuro.06.2009.03.258 abstract

Charles CF, Koepsell K (2009) A multivariate phase distribution and its estimation, Poster presentation, Computational and Systems Neuroscience. doi: 10.3389/conf.neuro.06.2009.03.260 abstract

Cadieu C.F., Olshausen B.A., (2009) Learning Transformational Invariants from Natural Movies. Advances in Neural Information Processing Systems (NIPS), 21:209-216, 2009. D. Koller and D. Schuurmans and Y. Bengio and L. Bottou, MIT Press, Cambridge, MA. pdf [Movies: Figure 2 wmv / mov , 4a avi / mov , 4b avi / mov , 4c avi / mov , 4d avi / mov ]

Olshausen, B., C. Cadieu, and D.K. Warland. (2009) Learning Real and Complex Overcomplete Representations from the Statistics of Natural Images, Proc. SPIE 7446, 74460S, 2009. link

2008

Koepsell K, Sommer FT (2008) Information transmission in oscillatory neural activity. Biological Cybernetics 99:403–416 abstract pdf

Rozell CJ, Johnson DH, Baraniuk RG, Olshausen BA (2008) Sparse Coding via Thresholding and Local Competition in Neural Circuits. Neural Computation, 20:2526-2563 pdf

Teeters JL, Harris KD, Millman KJ, Olshausen BA, Sommer FT (2008) Data sharing for computational neuroscience. Neuroinformatics 6:47-55 pdf

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). pdf

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

Garrigues P.J., El Ghaoui L., An Homotopy Algorithm for the Lasso with Online Observations. Advances in Neural Information Processing Systems 21 (NIPS 2008). pdf

Monaci G., Sommer F. T. and Vandergheynst P., Learning Sparse Generative Models of Audiovisual Signals, Proc. of European Conf. on Signal Processing (EUSIPCO08), 2008 pdf

2007

Rehn M, Sommer FT (2007) A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. J. Comp. Neurosci. 22 (2): 135-146. pdf

Sommer FT (2007) Bunte Theorien für graue Zellen. Gehirn und Geist, Juni 70-76

Wang X, Wei Y, Vaingankar V, Wang Q, Koepsell K, Sommer FT, Hirsch JA (2007) Feedforward excitation and inhibition evoke dual modes of firing in the cat’s visual thalamus during naturalistic viewing. Neuron 55 (2007) 465-478. pdf See also the preview about this paper: P. Reinagel: The inner life of bursts. Neuron 55: 339-341

Garrigues P.J. Olshausen B.A. (2007) Learning Horizontal Connections in a Sparse Coding Model of Natural Images. To appear in Advances in Neural Information Processing Systems 20 (NIPS 2007) pdf

Olshausen, B., C. Cadieu, J. Culpepper, and D.K. Warland. (2007) Bilinear Models of Natural Images, Proc. SPIE Int. Soc. Opt. Eng. 6492, 649206, February 2007. pdf

2006

Bethge M (2006) Factorial coding of natural images: how effective are linear models in removing higher-order dependencies? J. Opt. Soc. Am. A, 23(6): 1253-1268.

Rehn M, Sommer FT (2006) Storing and restoring visual input with collaborative rank coding and associative memory. Neurocomputing 69 (10-12) 1219-1223 pdf

Sommer FT, Kanerva P (2006) Can neural models of cognition benefit from the advantages of connectionism? Behavoral and Brain Sciences 29 (1) 86-87 pdf

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). pdf

2005

George D, Sommer FT (2005) Computing with inter-spike inverval codes in networks of integrate and fire neurons. Neurocomputing 65-66, 414 - 420. pdf

Johnson JS, Olshausen BA (2005) The recognition of partially visible natural objects in the presence and absence of their occluders. Vision Research, 45, 3262-3276. pdf

Johnson JS, Olshausen BA (2005) The earliest EEG signatures of object recognition in a cued-target task are postsensory. Journal of Vision, 5, 299-312. link

Martinez LM, Wang Q, Reid RC, Pillai C, Alonso J-M, Sommer FT, Hirsch JA (2005) Receptive field structure varies with layer in the primary visual cortex. Nature Neuroscience 8 , 372 - 379 pdf

Olshausen BA, Field DJ (2005) How close are we to understanding V1? Neural Computation, 17, 1665-1699. pdf

Sommer FT, Wennekers T (2005) Synfire chains with conductance-based neurons: internal timing and coordination with timed input. Neurocomputing 65-66, 449 - 454. pdf

Bell A.J., Parra L.C. (2005) Maximising Sensitivity in a Spiking Network, Advances in Neural Information Processing Systems 17, Saul L.K. and Weiss Y. and Bottou L., MIT Press, Cambridge, MA pdf

Redwood Neuroscience Institute

An incomplete list of publications from the Redwood Neuroscience Institute (2002-2004) is available here.