Ernst Niebur PhD

Professor of Neuroscience




Camille Simon Chane, Ernst Niebur, Ryad Benosman, and Sio-Hoi Ieng. An event-based implementation of saliency-based visual attention for rapid scene analysis. arXiv preprint arXiv:2401.05030, 2024.

Christopher Taylor, Macauley Smith Breault, Daniel Dorman, Patrick Greene, Pierre Sacre, Aaron Sampson, Ernst Niebur, Veit Stuphorn, Jorge González-Martínez, and Sridevi Sarma. Exploration
of large-scale brain networks during gambling. Brain Sciences, in press, 2024.
 
Aaron L. Sampson, You-Ping Yang, Marius Usher, Dino Levy, Ernst Niebur, and Veit Stuphorn. The role of attention in multi attribute decision making. bioRxiv, 2023.
 
Takeshi Uejima, Elena Mancinelli, Ernst Niebur, and Ralph Etienne-Cummings. The influence of stereopsis on visual saliency in a proto-object based model of selective attention. Vision Research, 212:108304, 2023.

Omar A Hafez, Benjamin Escribano, Rouven L Ziegler, Jan J Hirtz, Ernst Niebur, and Jan Pielage.  The cellular architecture of memory modules in Drosophila supports stochastic input integration.  eLife, 12:e77578, March 2023.

Suman Ghosh, Giulia D’Angelo, Arren Glover, Massimiliano Iacono, Ernst Niebur, and Chiara Bartolozzi. Event-driven proto-object based saliency in 3D space to attract a robot’s attention. Scientific Reports, 12(7645), 2022.

J. Molin, C. Thakur, E. Niebur, and R. Etienne-Cummings. A neuromorphic proto-object based dynamic visual saliency model with a hybrid implementation. IEEE Transactions on Biomedical Circuits and Systems, 15(3):580–594, 2021.

J. Molin, C. Thakur, E. Niebur, and R. Etienne-Cummings. A neuromorphic proto-object based dynamic visual saliency model with a hybrid implementation. IEEE Transactions on Biomedical Circuits and Systems, 15(3):580–594, 2021.

Seah Chang, Ernst Niebur, and Howard E. Egeth. Standing out in a small crowd: The role of display size in attracting
attention. Visual Cognition, 29(9):587–91, 2021.

Varun Chokshi, Bryce D. Grier, Andrew Dykman, Crystal L. Lantz, Ernst Niebur, Elizabeth M.  Quinlan, and Hey-Kyoung
Lee. Naturalistic spike trains drive state-dependent homeostatic plasticity in superficial layers of visual cortex. Frontiers in
Synaptic Neuroscienc e, 13:18, 2021.

Takeshi Uejima, Ernst Niebur, and Ralph Etienne-Cummings. Proto-object based saliency model with texture
detection channel. Frontiers in Computational Neuroscience, 14(541581):1–18, 2020.

Moshe Glickman, Orian Sharoni, Dino J Levy, Ernst Niebur, Veit Stuphorn, and Marius Usher. The formation of preference in risky choice. PLoS Computational Biology, 15(8):e1007201, 2019.

Brian Hu, Rüdiger von der Heydt, and Ernst Niebur. Figure-ground organization in natural scenes: Performance of a recurrent neural model compared with neurons of area V2. eNeuro, pages ENEURO–0479–18, 2019.

Pierre Sacré, Matthew S. D. Kerr, Sandya Subramanian, Zachary Fitzgerald, Kevin Kahn, Matthew A. Johnson, Ernst Niebur, Uri T. Eden, Jorge A. Gonzalez-Martinez, John T. Gale, and Sridevi V. Sarma. Risk-taking bias in human decision-making is encoded via a right-left brain push-pull system. Proc Natl Acad Sci USA, 116(4):1404–1413, 2019.

Daniel M Jeck, Michael Qin, Howard Egeth, and Ernst Niebur. Unique objects attract attention even when faint. Vision research, 160:60–71, 2019.

Yao Xu, Chun-Hui Zhang, Ernst Niebur, and Jun-Song Wang. Analytically determining frequency and amplitude of spontaneous alpha oscillation in Jansen’s neural mass model using the describing function method. Chinese Physics B, 27(4):048701, 2018.

 

Daniel M. Jeck, Michael Qin, Howard Egeth, and Ernst Niebur. Attentive pointing in natural scenes correlates with other measures of attention. Vision Research, 135:54–64, 2017.

Brian Hu and Ernst Niebur. A recurrent neural model for proto-object based contour integration and figure-ground segregation. Journal of computational neuroscience, 43(3):227–242, 2017

Grant Gillary, Rudiger von der Heydt, and Ernst Niebur. Short term depression and transient mem- ory in sensory cortex. Journal of computational neuroscience, 43(3):273–294, 2017.

Chetan Singh Thakur, Jamal Molin, Tao Xiong, Jie Zhang, Ernst Niebur, and Ralph Etienne-Cummings. Neuromorphic visual saliency implementation using stochastic computation. In IEEE International Symposium on Circuits and Systems (ISCAS 2017), Baltimore, MD USA, May 2017. Elsevier (CP)

Gillary, G. and Niebur, E.. (2016) The Edge of Stability: Response Times And Delta Oscillations in Balanced Networks. PLoS Comput Biol, 12(9):e1005121. [pdf]

Gomez-Ramirez, M., Hysaj, K., Niebur, E. (2016) Neural mechanisms of selective attention in the somatosensory system. Journal of Neurophysiology, 116(3):1218–1231. [pdf]
 
Wagatsuma,N., von der Heydt, R.,Niebur, E. (2016) Spike Synchrony Generated by Modulatory Common Input through NMDA-type Synapses. Journal of Neurophysiology, 116(3):1418–1433. [pdf]
 
Wang, J., Xia, X., Hu, J., Niebur, E. (2016)  Regulating activity in a neural mass model through interaction of excitatory and inhibitory feedback: a bifurcation study. Scientific Reports.
 
Hu, B., Kane-Jackson, R., Niebur, E., (2016) A proto-object based saliency model in threedimensional space. Vision Research, 119:42–49. [pdf]
 
Gomez-Ramirez,M., Trzcinski, N.K.,Mihalas, S., Niebur, E., Hsiao, S.S. (2014) Temporal correlation mechanisms and their role in feature selection: a single-unit study in primate somatosensory cortex. PLoS Biol, 12(11):e1002004:1–16. [pdf]
 
Ramenahalli,S.,Mihalas, S., Niebur, E. (2014) Local spectral anisotropy is a valid cue for figure-ground organization in natural scenes. Vision Research, 103:116–126. [pdf]
 
Russell, A.F., Mihalas, S.,von der Heydt, R., Niebur, E., Etienne-Cummings, R. (2014)  A model of proto-object based saliency. Vision Research, 94:1–15. [pdf]
 
Le Callet, P., Niebur, E. (2013) Visual Attention and Applications in Multimedia Technologies. IEEE Proceedings, 101(9):2058–67. [pdf]
 
Chen, X.,  Mihalas, S., Niebur, E., Stuphorn, V. (2013)  Mechanisms underlying the influence of saliency on value-based decisions. Journal of vision, 13(12):18. [pdf]
 
Jimenez, N.D., Mihalas, S., Brown, R., Niebur, E., Rubin, J. (2013)  Contractive Dynamics in Generalized Integrate-and-Fire Neurons. SIAM Journal on Applied Dynamical Systems, 12(3):1474–1514. [pdf]

Dong Y, Mihalas S, Kim SS, Yoshioka T, Bensmaia S, Niebur E. (2013) A simple model of mechanotransduction in primate glabrous skin. Journal of Neurophysiology 109(5):1350-1359. [pdf]

Dong, Y., Mihalas, S., Russell, A., Etienne-Cummings, R., & Niebur, E. Estimating parameters of generalized integrate-and-fire neurons from the maximum likelihood of spike trains. Neural Computation 2011 Nov;23(11):2833-67. Epub 2011 Aug 18. [pdf]

Mihalas, S., Dong, Y., von der Heydt, R., & Niebur, E. (2011a). Mechanisms of perceptual organization provide auto-zoom and auto-localization for attention to objects. Proceedings of the National Academy of Sciences, 108 (18), 7583.[pdf]

Dong, Y., Mihalas, S., & Niebur, E. (2011). Improved integral equation solution for the first passage time of leaky integrate-and-fire neurons. Neural Computation, 23 (2), 421–34. [pdf] 

Millman, D., Mihalas, S., Kirkwood, A., & Niebur, E. (2010). Self-organized criticality occurs in non-conservative neuronal networks during Up states. Nature Physics, 6 (10), 801–805. [pdf] 

van Schaik, A., Jin, C., McEwan, A., Hamilton, T., Mihalas, S., & Niebur, E. (2010). A log-domain implementation of the Mihalas-Niebur neuron model. In Circuits and Systems (ISCAS), Proceedings of the 2010 IEEE International Symposium on, pp. 4249–4252. IEEE. 

Russell, A., Orchard, G., Dong, Y., Mihalas, S., Niebur, E., Tapson, J., & Etienne-Cummings, R. (2010). Optimization methods for spiking neurons and networks. IEEE Transactions on Neural Networks, 21 (12), 1950–62. [pdf]

Niebur E.  (2009)  Temporal tagging of attended objects.  Proc Natl Acad Sci U S A. 2009 Feb 24;106(8):2479-80. [LINK]

Masciocchi, C., Mihalas, S., Parkhurst, D., & Niebur, E. (2009). Everyone knows what is interesting: Salient locations which should be fixated. Journal of Vision, 9 (11), 1–22. [pdf]

Mihalas, S. & Niebur, E. (2009). A generalized linear integrate-and-fire neural model produces diverse spiking behavior. Neural Computation, 21 (3), 704–18. [pdf]

Deppmann, C. D., Mihalas, S., Sharma, N., Lonze, B. E., Niebur, E., & Ginty, D. D. (2008). A model for neuronal competition during development.  Science, 320 (5874), 369–73. [pdf]

Dong, Y., Mihalas, S., Qiu, F., von der Heydt, R., & Niebur, E.  (2008). Synchrony  and the binding problem in macaque visual cortex. Journal of Vision, 8 (7), 1–16. [pdf]

Mikula, S. & Niebur, E. (2008). Exact solutions for rate and synchrony in recurrent networks of coincidence detectors. Neural Computation, 20 (11), 2637–61. [pdf]

Ray, S., Hsiao, S. S., Crone, N. E., Franaszczuk, P. J., & Niebur, E. (2008a).  Effect of stimulus intensity on the spike-local field potential relationship in the secondary somatosensory cortex. J. Neurosci., 28 (29), 7334–43. [pdf]