Publications and Presentations

Theses

Johnson, E. C. Minimum-Error, Energy-Constrained Source Coding by Sensory Neurons. Ph. D. thesis, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, 2016. (http://hdl.handle.net/2142/95741)
Johnson, E. C. Recovery of Sparse Signals and Parameter Perturbations from Parameterized Signal Models. M. sc. thesis, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, 2013. (http://hdl.handle.net/2142/44187)

Journal Papers

Matelsky, J. K., Reilly, E. P., Johnson, E. C., Stiso, J., Bassett, D. S., Wester, B. A., & Gray-Roncal, W. (2021). DotMotif: An open-source tool for connectome subgraph isomorphism search and graph queries. Scientific Reports, 11(1), 1-14. (https://www.nature.com/articles/s41598-021-91025-5)
Johnson, E. C., Wilt, M., Rodriguez, L. M., Norman-Tenazas, R., Rivera, C., Drenkow, N., … & R. Gray-Roncal, W. (2020). Toward a scalable framework for reproducible processing of volumetric, nanoscale neuroimaging datasets. GigaScience, 9(12), giaa147. (https://academic.oup.com/gigascience/article/9/12/giaa147/6042730?login=true)
Prasad, J. A., Balwani, A. H., Johnson, E. C., Miano, J. D., Sampathkumar, V., De Andrade, V., … & Dyer, E. L. (2020). A three-dimensional thalamocortical dataset for characterizing brain heterogeneity. Scientific Data, 7(1), 1-7. (https://www.nature.com/articles/s41597-020-00692-y)
Matelsky, J., Kiar, G., Johnson, E., Rivera, C., Toma, M., & Gray-Roncal, W. Container-Based Clinical Solutions for Portable and Reproducible Image Analysis. Journal of digital imaging, 31(3), 315-320 (2018). (https://link.springer.com/article/10.1007/s10278-018-0089-4)
Kaloti A. S., Johnson E. C., Bresee C. S., Naufel S. N., Perich M. G., Jones D. L., and Hartmann M. J. Z. Representation of stimulus speed and direction in vibrissal-sensitive regions of the trigeminal nuclei: a comparison of single unit and population responses. PLoS ONE 11(7):e0158399 (2016) (http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0158399).
Johnson E. C., Jones, D. L., Ratnam, R. A Minimum-Error, Energy-Constrained Neural Code is an Instantaneous Rate Code. Journal of Computational Neuroscience, 40.2 (2016) (http://link.springer.com/article/10.1007/s10827-016-0592-x ).
Johnson E. C., Robbins, B. A., Loui, M. C. What Do Students Experience as Peer Leaders of Learning Teams? Advances in Engineering Education 4.4 (2015) (http://advances.asee.org/publication/what-do-students-experience-as-peer-leaders-of-learning-teams/).
Jones D. L., Johnson E. C., Ratnam R. A stimulus-dependent spike threshold is an optimal neural coder. Frontiers in Computational Neuroscience 9:61 (2015)(http://journal.frontiersin.org/article/10.3389/fncom.2015.00061/full).
Loui, M. C., Robbins, B. A., Johnson, E. C., Venkatesan, N. Assessment of Peer-led Team Learning in an Engineering Course for Freshmen. International Journal of Engineering Education Volume 29:6 (2013) (http://www.ijee.ie/contents/c290613.html).

Pre-print Papers (Under Review)

Azabou, M., Azar, M. G., Liu, R., Lin, C. H., Johnson, E. C., Bhaskaran-Nair, K., … & Dyer, E. L. (2021). Mine your own view: Self-supervised learning through across-sample prediction. arXiv preprint arXiv:2102.10106. (https://arxiv.org/abs/2102.10106)
Robinson, B. S., Norman-Tenazas, R., Cervantes, M., Symonette, D., Johnson, E. C., Joyce, J., … & Gray-Roncal, W. R. (2021). Online learning for orientation estimation during translation in an insect ring attractor network. bioRxiv. (https://www.biorxiv.org/content/10.1101/2021.01.07.425323v1.abstract)
Sidhu, R. S., Johnson, E. C., Jones, D. L., & Ratnam, R. (2020). Adaptation with correlated noise predicts negative interval correlations in neuronal spike trains. bioRxiv. (https://www.biorxiv.org/content/10.1101/2020.11.30.403725v1.abstract)

Conference Papers (Peer Reviewed)

Balwani, A., Miano, J., Liu, R., Kitchell, L., Prasad, J. A., Johnson, E. C., … & Dyer, E. L. (2021, September). Multi-Scale Modeling of Neural Structure in X-Ray Imagery. In 2021 IEEE International Conference on Image Processing (ICIP) (pp. 141-145). IEEE. (https://ieeexplore.ieee.org/abstract/document/9506174)
Robinson, B., Polevoy, A., McDaniel, S., Coon, W., Scholl, C., McLean, M., & Johnson, E. (2021, July). A spiking network model for semantic representation and replay-based association acquisition. In International Conference on Neuromorphic Systems 2021 (pp. 1-8). (https://dl.acm.org/doi/abs/10.1145/3477145.3477259)
Brown, C. J., Nguyen, H. H., Thompson, M. C., Joyce, J. M., Johnson, E. C., Fifer, M. S., & Osborn, L. E. (2021, May). Simulation and analysis of neuromorphic tactile data for object interaction speed detection. In 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER) (pp. 136-139). IEEE. (https://ieeexplore.ieee.org/abstract/document/9441141)
Villafañe-Delgado, M., Johnson, E. C., Hughes, M., Cervantes, M., & Gray-Roncal, W. (2020, August). STEM Leadership and Training for Trailblazing Students in an Immersive Research Environment. In 2020 IEEE Integrated STEM Education Conference (ISEC) (pp. 1-4). IEEE. (https://ieeexplore.ieee.org/abstract/document/9280735)
Reilly, E. P., Johnson, E. C., Hughes, M. J., Ramsden, D., Park, L., Wester, B., & Gray-Roncal, W. (2020). Connecting neural reconstruction integrity (NRI) to graph metrics and biological priors. In Complex Networks XI (pp. 182-193). Springer, Cham.
Johnson, E. C., Rodriguez, L. M., Norman-Tenazas, R., Xenes, D., & Gray-Roncal, W. R. (2019, November). Transfer learning analysis of image processing workflows for electron microscopy datasets. In 2019 53rd Asilomar Conference on Signals, Systems, and Computers (pp. 1197-1201). IEEE. (https://ieeexplore.ieee.org/abstract/document/9048673)
Norman-Tenazas, R., Matelsky J., Katyal K., Johnson E., Gray-Roncal W. Worminator: A platform to enable bio-inspired (C. elegans) robotics. Cognitive and Computational Neuroscience 2018, Philadelphia, PA. (https://doi.org/10.32470/CCN.2018.1149-0)
Johnson E. C., Jones D. L., Ratnam R. Minimum squared-error, energy-constrained encoding by adaptive threshold models of neurons. In Proc. of IEEE ISIT, 2015, pp. 1337–1341 (http://ieeexplore.ieee.org/abstract/document/7282673/).
Johnson, E. C., Norton, J. S., Jun, D. M., Bretl, T., Jones, D. L. Sequential Selection of Window Length for Improved SSVEP-Based BCI Classification. In Proc. of IEEE Engineering in Medicine and Biology Society (EMBC), 2013, pp. 7060-7063 (http://ieeexplore.ieee.org/document/6611184/).
Johnson, E. C., Jones, D. L. Joint Recovery of Sparse Signals and Parameter Perturbations with Parameterized Measurement Models. In Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013, pp. 5900-5904 (http://ieeexplore.ieee.org/document/6638796/).
Johnson, E. C. and Loui, M. C. Work in progress – how do students benefit as peer leaders of learning teams? In Proc. of IEEE International Conference on Frontiers in Education Conference, 2009, pp. 645-646 (http://ieeexplore.ieee.org/document/5350637/).

Conference Presentations (Sometimes Peer Reviewed)

Brown, M., Johnson, E. C., Matelsky, J. K., Dewey, B. E., Cowley, H., Duerr, A., … & Gray-Roncal, W. R. (2019, March). Toward a Reproducible Framework for Evaluating Neuroimaging Algorithms for Clinical Research. In ACTRIMS Forum 2019. ACTRIMS.
Johnson, E., Wilt, M., Norman-Tenazas, R., Rodriguez, L., Downs, J., Reilly, E., Hughes, M., Matelksy, J., Drenkow, N., Rivera, C., Wester, B., Dyer, E., Kording, K., Gray Roncal, W. A framework for pipeline optimization and deployment for large neuroscience datasets. SFN 2018. San Diego, CA.
Johnson, E. C., Lee, D. H., Jones, D. L., Aronoff, J., Ratnam, R. A Neural Timing Code Improves Speech Perception in Vocoder Simulations of Cochlear Implant Sound Coding. PS 21. ARO Midwinter Meeting, 2017. Baltimore, MD.
Bresee, C. S., Bush, N. E., Kaloti, A. S., Johnson, E. C., Naufel, S. N., Perich, M. G., Jones, D. L., Hartmann, M. J. Z. Evidence for tuning to stimulus directionality in the responses of neurons with multi-whisker receptive fields in spinal trigeminal nucleus interpolaris. Program No. 706.16/S17. 2015 Neuroscience Meeting Planner. Chicago, IL: Society for Neuroscience, 2015. Online.
Johnson, E. C., Jones, D. L., Ratnam, R. An optimal neural encoding model predicts anti-correlated spike-trains in the p-type afferents of a weakly electric fish. Program No. 90.09/AA17. 2015 Neuroscience Meeting Planner. Chicago, IL: Society for Neuroscience, 2015. Online.
Johnson, E. C., Jones, D. L., Ratnam, R. A Minimum-Error, Energy-Constrained Neural Encoder Predicts an Instantaneous Spike-Rate code. BMC Neuroscience 2015, 16(Suppl 1):P201
Johnson, E. C., Jones, D. L., Ratnam, R. Encoding of sensory signals by an energy-constrained neural source encoding mechanism. Program No. 372.18/VV82. 2014 Neuroscience Meeting Planner. Washington, DC: Society for Neuroscience, 2014. Online.
Maduram, A., Johnson, E. C., Catanho, M., Rubakhin, S., Jones, D. L., Gillete, R., Sweedler, J. Morphological and electrophysiological parameters of spatially complex networks of peripheral sensory neurons formed in microfluidic devices. Program No. 520.27. 2011 Neuroscience Meeting Planner. Washington, DC: Society for Neuroscience, 2011. Online.
Vega Leonel, J. C. M., Catanho, M. J., Quinn, C. J., Johnson, E. C., Jones, D. L., Coleman, T. P., Leckband, D. E., Kong, H. Electrophysiological and neuronal localization techniques for cultured aplysia neurons. Program No. 873.12. 2011 Neuroscience Meeting Planner. Washington, DC: Society for Neuroscience, 2011. Online.
Johnson, E. C. and Wah, E. 2008. Data Visualization and Analysis of CIC Graduate Student TeraGrid Resource Usage. In Proc. of IEEE International Conference on Escience, 2008, pp. 354-355.
Wah, E., Johnson E. C., Auvil, L., Thakkar, U., Hwu, W., Kirk, D., Dunning, T., Glotzer, S. Visualization and Analysis of GPU Summer School Applicants and Participants. In Proc. of IEEE International Conference on Escience 2008, pp. 362-363.