{"id":47,"date":"2020-05-10T20:42:34","date_gmt":"2020-05-11T00:42:34","guid":{"rendered":"https:\/\/www.bme.jhu.edu\/ascharles\/brains-4\/"},"modified":"2026-05-11T14:47:50","modified_gmt":"2026-05-11T18:47:50","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.bme.jhu.edu\/ascharles\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"<p><strong style=\"font-size: inherit;\">Submitted manuscripts and preprints<\/strong><\/p>\n<ul>\n<li>S. Thomas, B. Zhu, K. Cullen, and <strong>A.S. Charles<\/strong>. Partitioning Neural Co-Variability. arxiv:2605.06995. <em>Submitted<\/em>. 2026. <a href=\"https:\/\/arxiv.org\/abs\/2605.06995\">pdf<\/a><\/li>\n<li>L. Xiang*, M. Wang*, P.O. Kanold<sup>+<\/sup>, and <strong>A.S. Charles<sup>+<\/sup><\/strong>. Precise extraction of neural motifs reveals multiscale, parallel encoding schemes in auditory cortex. <em>Submitted<\/em>. biorxiv <span class=\"highwire-cite-metadata-doi highwire-cite-metadata\">2025.08.26.67228.\u00a0 <\/span>2026. *Equal contribution. +Corresponding authors. <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2025.08.26.672281\" target=\"_blank\" rel=\"noopener\">biorxiv<\/a>\u00a0\u00a0<\/li>\n<li>N. Mudrik, A.S. Charles. Neighbor Embedding for High-Dimensional Sparse Poisson Data. arxiv:2604.16932. 2026. <em>Submitted<\/em>. <a href=\"https:\/\/arxiv.org\/abs\/2604.16932\">arxiv<\/a><\/li>\n<li>N Bertrand\u2217 , E. Yezerets\u2217 , H.L. Yap, <strong>A.S. Charles<\/strong>+ , and C.J. Rozell+ . Stable filtering for efficient dimensionality reduction of streaming manifold data. 2026. <em>Submitted<\/em>, <a href=\"https:\/\/arxiv.org\/abs\/2601.08685\">arxiv<\/a> *Equal contribution, +joint last author<\/li>\n<li>E. Yezerets, E. Yang, M. Ahrens, and <strong>A.S. Charles<\/strong>. A decomposed linear dynamical systems model for neural activity partially constrained by behavior. 2025. <em>Submitted. <\/em><a href=\"https:\/\/arxiv.org\/abs\/2603.05612\">arxiv<\/a><\/li>\n<li>S. Kumar, G.I. Coste, D. Premathilaka, R.L. Huganir, A.R. Graves, <strong>A.S. Charles<\/strong>, and M.I. Miller. Uncertainty gated min-cost flows for <em>in vivo<\/em> nanoscale synaptic plasticity tracking. 2025. <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2025.10.10.681691v1\">biorxiv<\/a><\/li>\n<li>S. Koukuntla, T. DeWeese, A. Cheng, R. Mildren, Lawrence A, A. Graves, J. Colonell, T.D. Harris, and <strong>A.S. Charles<\/strong>. SLAy-ing errors in high density electrophysiology spike sorting. biorxiv <span class=\"highwire-cite-metadata-doi highwire-cite-metadata\">2025.06.20.660590. <\/span>2025. <em>Submitted<\/em> <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2025.06.20.660590v1\">biorxiv<\/a><\/li>\n<li>E. Whang, S. Thomas, J. Yi, and <strong>A.S. Charles<\/strong>. Fast Two-photon Microscopy by Neuroimaging with Oblong Random Acquisition (NORA). <em>Submitted<\/em>. 2025. <a href=\"https:\/\/arxiv.org\/abs\/2503.15487\">arxiv<\/a><\/li>\n<li>S.S. Koukuntla, J.B. Julian, J.C. Kaminsky, M. Schottdorf, D.W. Tank, C.D. Brody, and <strong>A.S. Charles<\/strong>. Discovering shared and private geometry in multi-view data. 2025. <em>Submitted. <\/em><a href=\"https:\/\/arxiv.org\/abs\/2408.12091\">arxiv<\/a><\/li>\n<li>Z. Chen, G.I. Coste, E. Li, R.L. Huganir, A.R. Graves, and <strong>A.S. Charles<\/strong>. Automatic detection of fluorescently labeled synapses in volumetric\u00a0<em>in vivo<\/em> imaging data. <em>Submitted<\/em>. 2025 <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2025.01.22.634278v1\">biorxiv<\/a>.<\/li>\n<li>A.H. Daraie,\u00a0<strong>A.S. Charles<\/strong>, L.A. Sanchez, A. Chandler, M.A. Hays, L. Talley, S.K. Inati, K. Zaghloul, J.L. Hopp, A. Marashly, N.E. Crone, J. Gonzalez-Martinez, J.-Y. Kang, and S.V. Sarma. Seizure detection and localization using spectral entropy of the intracranial EEG network. 2024.\u00a0<em>Submitted.<\/em><\/li>\n<\/ul>\n<p><strong style=\"font-size: inherit;\">Peer-reviewed Journal and Conference Papers<\/strong><\/p>\n<ul>\n<li>N. Mudrik, Y. Chen, G. Mishne, and <strong>A.S. Charles<\/strong>. Multi-integration of labels across categories for component identification (MILCCI).<em> International Conference on Machine Learning (ICML)<\/em>. 2026<em>. <\/em><a href=\"https:\/\/arxiv.org\/abs\/2602.04270\">arxiv<\/a><\/li>\n<li>A. Estrada, G. Kang, A. Kwok, T. Broggini J. Lawlor, K. Kuchibhotla, D. Kleinfeld, G. Mishne, and <strong>A.S. Charles<\/strong>. Fast and accessible morphology-free functional fluorescence imaging analysis. <em>PLoS Computational Biology<\/em>, 2026. In Press\u00a0 <a href=\"https:\/\/www.biorxiv.org\/cgi\/content\/short\/2025.04.15.648462v1\">biorxiv<\/a>, <a href=\"https:\/\/journals.plos.org\/ploscompbiol\/article?id=10.1371\/journal.pcbi.1014038&amp;?utm_id=plos111&amp;utm_source=internal&amp;utm_medium=email&amp;utm_campaign=author\">link<\/a><\/li>\n<li>S. Moore*, Z. Wang*, Z. Zhu, R. Sun, A. Lee, <strong>A.S. Charles<\/strong>, and K.V. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual behavior. 2026. <em>Nature Communications<\/em>. In Press *Equal Contribution. <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2023.07.05.547783v1\">biorxiv<\/a><\/li>\n<li>A.H. Daraie, A. Damiani, M. Khoshkhou, L.A. Sanchez, R.J. Smith, S.H. Agashe, J.A. Gonzalez-Martinez, J. Hopp, <strong>A.S. Charles<\/strong>, S.V. Sarma, J.-Y. Kang. Artificial intelligence for adaptive neuromodulation in drug-resistant epilepsy. <em>Epilepsia<\/em>. 2026 <a href=\"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/epi.70224\">link<\/a><\/li>\n<li>R.-H. Wei, O.R. Stanley, <strong>A.S. Charles<\/strong>, and K.E. Cullen. Contextual neck muscle control enables flexible head stabilization across locomotion conditions. <em>Communications Biology<\/em>. In Press. 2026.\u00a0<\/li>\n<li>J. Xie, L.C. Voinov, N. Mudrik, G. Mishne, and <strong>A.S. Charles<\/strong>. Multiway Multislice PHATE: Visualizing hidden dynamics of RNNs through training. <em>Transactions of Machine Learning Research (TMLR). <\/em>2026. <a href=\"https:\/\/arxiv.org\/abs\/2406.01969\">arxiv<\/a><\/li>\n<li>T. Karigo and <strong>A.S. Charles<\/strong>. Towards a multi-dimensional understanding of brain states. <em>Neurobiology of Learning<\/em>.\u00a0 222(108110):1\u20139. 2025<em>.<\/em> <a href=\"http:\/\/sciencedirect.com\/science\/article\/abs\/pii\/S1074742725000917\">paper<\/a>.<\/li>\n<li>C. Bao, R. Mildren, <strong>A.S. Charles<\/strong>, and K.E. Cullen. Complex spike sorting from MEA recordings using U-net with hybrid self-attention inception blocks. <em>Journal of Neuroscience Methods.<\/em> 426(110631):1\u201313. 2025<em>. <\/em><a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2025.11.18.689109\">biorxiv.<\/a> <a href=\"https:\/\/authors.elsevier.com\/sd\/article\/S0165-0270(25)00275-4\">paper<\/a>.<\/li>\n<li>S. Keeley, D. Zoltowski, <strong>A. S. Charles <\/strong>and J. Pillow. Improved estimation of latent variable models from calcium imaging data. <em>eLife<\/em>, 2025. <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2025.10.17.682993v1.abstract\">biorxiv<\/a><\/li>\n<li>A. Rupasinghe, <strong>A.S. Charles<\/strong>, and J.W. Pillow. Continuous Partitioning of neuronal variability. biorxiv <span class=\"highwire-cite-metadata-doi highwire-cite-metadata\">2025.07.23.666404. <\/span>2025. <em>eLife<\/em> . <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2025.07.23.666404\" target=\"_blank\" rel=\"noopener\">biorxiv<\/a><\/li>\n<li>K. Johnson, N.A. Cruzado, Z.C. Menard, A.A. Willats, <strong>A.S. Charles<\/strong>, J.E. Markowitz, and C.J. Rozell. Bridging model and experiment in systems neuroscience with <span class=\"il\">Cleo<\/span>: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed.\u00a0<em>Journal of Neuroscience<\/em>. 2025.<\/li>\n<li><strong>A.S. Charles<\/strong>. Data mining the functional architecture of the brain&#8217;s circuitry. <em>SIAM International Conference on Data Mining (SDM). <\/em>May 2025. (Invited) <a href=\"http:\/\/arxiv.org\/abs\/2501.09684\">arxiv<\/a><\/li>\n<li>N. Mudrik, R. Ly, O. Ruebel, and <strong>A.S. Charles<\/strong>. CrEIMBO: Cross-ensemble interactions in multi-view brain observations. <em>International Conference on Learning Representations (ICLR)<\/em>. 2025. <a href=\"https:\/\/arxiv.org\/abs\/2405.17395v1\">arxiv.<\/a> (Spolight paper)<\/li>\n<li>E. Yezerets, N. Mudrik, and <strong>A.S. Charles<\/strong>. Decomposed Linear Dynamical Systems (dLDS) models reveal context-dependent dynamic connectivity in C. elegans. Communications Biology. 8(1218):1\u201317, 2025.\u00a0<a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2024.05.31.596903v1\">biorxiv.<\/a><\/li>\n<li>N. Mudrik, E. Yezerets, Y. Chen, C. J. Rozell, and <strong>A.S. Charles<\/strong>. Linocs: Lookahead inference of networked operators for continuous stability. <em>Transactions of Machine Learning Research (TMLR). <\/em>2024. <a href=\"https:\/\/arxiv.org\/pdf\/2404.18267\">pdf.\u00a0<\/a><\/li>\n<li>Y. Chen, N. Mudrik, K.A. Johnsen, S. Alagapan, <strong>A.S. Charles<\/strong>, and C.J. Rozell. Probabilistic decomposed linear dynamical systems for robust discovery of latent neural dynamics. <em>Neural Information Processing Systems (NeurIPS). <\/em>2024.<em>\u00a0<\/em><a href=\"https:\/\/arxiv.org\/pdf\/2408.16862\">arxiv<\/a><\/li>\n<li>I. Dmitrieva, S. Babkin, and <strong>A.S. Charles.<\/strong> realSEUDO for Real-time calcium imaging analysis. <em>Neural Information Processing Systems (NeurIPS). <\/em>Dec<em>. <\/em>2024. <a href=\"https:\/\/arxiv.org\/abs\/2405.15701\">arxiv<\/a><\/li>\n<li>V. Geadah, G. Barello, D. Greenidge, <strong>A.S. Charles<\/strong> and J.W. Pillow. Sparse-coding variational auto-encoders. <em>Neural Computation.<\/em> Dec. 2024.<a href=\"https:\/\/www.biorxiv.org\/content\/early\/2018\/08\/23\/399246\">\u00a0pdf<\/a><\/li>\n<li>N. Mudrik, G. Mishne, and <strong>A.S. Charles.<\/strong> SiBBlInGS: Similarity-driven building-block inference using graphs across States. <em>International Conference on Machine Learning (ICML)<\/em>. 2024. <a href=\"https:\/\/arxiv.org\/abs\/2306.04817\">pdf<\/a>.<\/li>\n<li>N. Mudrik*, Y. Chen*, E. Yezerets, C.J. Rozell, and <strong>A.S. Charles<\/strong>. Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics. <em>Journal of Machine Learning Research<\/em>. 2024. In Press. *Equal Contribution. <a href=\"https:\/\/arxiv.org\/abs\/2206.02972\">pdf<\/a>.<\/li>\n<li>C. Lamaitre, <strong>A.S. Charles<\/strong>, and S. Sarma. Exploration of a network-based EEG marker for major depressive disorder. <em>Conference of the IEEE Engineering in Medicine and Biology (EMBC)<\/em>, Orlando, FL, USA, 2024<\/li>\n<li>J. Stefanowicz, J.S. Choi, K. Wingel, J. Haggerty, <strong>A.S. Charles<\/strong>, and B. Pesaran. Widefield super-resolution feature matching of the primate cortical surface enables real-time localization. <em>Confer<\/em><em>ence of the IEEE Engineering in Medicine and Biology (EMBC)<\/em>, Orlando, FL, USA, 2024<\/li>\n<li>A. H. Daraie, <strong>A.S. Charles<\/strong>, A. Chandler, L. Sanchez, J.-Y. Kang, and S. Sarma. Localizing the seizure onset zone with bayesian learning during ieeg monitoring. <em>Conference of the IEEE Engineering <\/em><em>in Medicine and Biology (EMBC)<\/em>, Orlando, FL, USA, 2024<\/li>\n<li>C. Bao and <strong>A.S. Charles<\/strong>. Comparing spike sorting algorithms on simulated extracellular multi-electrode array recordings. <em>Proc. of the IEEE Bioinformatics and Biomedicine (BIBM)<\/em>, Istambul, Turkey, December 2023.<\/li>\n<li>X. Yuan, J.I. Colonell, A. Lebedeva, <strong>A.S. Charles<sup>+<\/sup><\/strong>, T.D. Harris<strong><sup>+<\/sup><\/strong>.\u00a0 Multi-day Neuron Tracking in High Density Electrophysiology Recordings using EMD. 2023. <em>eLife. <\/em><a href=\"https:\/\/elifesciences.org\/reviewed-preprints\/92495\">Paper<\/a> <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2023.08.03.551724v2\">biorxiv<\/a><strong> +<\/strong>Joint senior author<\/li>\n<li>G. Mishne, <strong>A.S. Charles<\/strong>. Deep and shallow data science for multi-scale optical neuroscience. <em>Photonics West.<\/em> 2024 <a href=\"https:\/\/arxiv.org\/abs\/2402.08811\">arxiv<\/a><\/li>\n<li>A. El Hady*, D. Takahashi*, R. Sun, T. Boyd-Meredith, Y. Zhang, <strong>A.S. Charles<sup>+<\/sup><\/strong>, and C.D. Brody<sup><strong>+<\/strong><\/sup>. Chronic functional ultrasound imaging for cognitive behaviors in freely moving rodents. 2023. <em>Journal of Neuroscience Methods<\/em>, *Equal contribution, <strong>+<\/strong>Joint senior author <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2022.01.29.478327v1\">biorxiv pdf<\/a><\/li>\n<li>T. Xu, A.R. Graves, G. Coste, R. Huganir, D. Bergles, <strong>A.S. Charles<sup>+<\/sup><\/strong>, and J. Sulam<strong><sup>+<\/sup><\/strong>. Cross-modality supervised image restoration enables nanoscale tracking of synaptic plasticity in living mice.\u00a0<em>Nature Methods<\/em>. 2023. \u00a0<strong>+<\/strong>Joint senior author <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2022.01.27.478042v1?rss=1\">biorxiv pdf<\/a>\u00a0<\/li>\n<li>Noga Mudrik and <strong>A. S. Charles<\/strong>. Multi-lingual DALL-E storytime, <em>IEEE Integrated STEM Education Conference (ISEC)<\/em>, March,\u00a02023 <a href=\"https:\/\/arxiv.org\/abs\/2212.11985\">arxiv<\/a><\/li>\n<li>H. Benisty, A. Song, G. Mishne, and <strong>A.S. Charles<\/strong>. Data Processing of Functional Optical Microscopy for Neuroscience. arXiv:2201.03537 <em>NeuroPhotonics. <\/em>9(4):041402. 2022. <a href=\"https:\/\/arxiv.org\/abs\/2201.03537\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, N. Cermak, R. Affan, B. Scott, J. Schiller, and G. Mishne. GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging. <span class=\"highwire-cite-metadata-journal highwire-cite-metadata\">bioRxiv\u00a0<\/span><span class=\"highwire-cite-metadata-pages highwire-cite-metadata\">2021.05.24.445514 . <em>IEEE Transactions of Signal Processing<\/em> 31:3509-3524, 2022. <a href=\"https:\/\/ieeexplore.ieee.org\/document\/9771089\">IEEE link<\/a><\/span>\u00a0<a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2021.05.24.445514v1\">pdf<\/a> <a href=\"https:\/\/github.com\/adamshch\/GraFT-analysis\">code<\/a><\/li>\n<li>J.L. Gauthier, S.A. Koay, E.H. Nieh, D.W. Tank, J.W. Pillow, and <strong>A.S. Charles<\/strong>. Detecting and Correcting False Transients in Calcium Imaging. <em>Nature Methods. <\/em>19:478-478. 2022. <a href=\"https:\/\/www.biorxiv.org\/content\/early\/2018\/11\/19\/473470\">pdf<\/a>\u00a0<\/li>\n<li>S.A. Koay, <strong>A.S. Charles<\/strong>, S.Y. Thiberge, C.D. Brody, and D.W. Tank. Sequential and efficient neural-population coding of complex task information.\u00a0<em>Neuron. <\/em>\u00a02022. <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0896627321008357\">link<\/a> <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/801654v2\">pdf<\/a><\/li>\n<li>Vogelstein, J.T., Verstynen, T., Kording, K.P., Isik, L., Krakauer, J.W., Etienne-Cummings, R., Ogburn, E.L., Priebe, C.E., Burns, R., Kutten, K. and Knierim, J.J., et al. 2022. Prospective Learning: Back to the Future. <i>arXiv preprint arXiv:2201.07372<\/i>. 2022. <a href=\"https:\/\/arxiv.org\/abs\/2201.07372\">arxiv pdf<\/a>\u00a0<\/li>\n<li>A. Song, J.L. Gauthier, J.W. Pillow, D.W. Tank, and <strong>A.S. Charles<\/strong>. Neural Anatomy and Optical Microscopy (NAOMi) Simulation for evaluating calcium imaging methods. <em>Journal of Neuroscience Methods<\/em> 358:109173, 2021. <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0165027021001084\">paper link<\/a>, <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/726174v1\">biorxiv pdf<\/a>, <a href=\"https:\/\/bitbucket.org\/adamshch\/naomi_sim\/src\/master\/\">code<\/a>, <a href=\"https:\/\/osf.io\/863j9\/\">data<\/a><\/li>\n<li>Q. She, X. Wu, B. Jelfs, <strong>A.S. Charles<\/strong>, and R.H.M. Chan. An Efficient and Flexible Spike Train Model via Empirical Bayes. <em>IEEE Transactions of Signal Processing.<\/em> 69:3236-3251. 2021. <a href=\"https:\/\/arxiv.org\/abs\/1605.02869\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, B. Falk, N. Turner, T.D. Pereira, D. Tward, B.D. Pedigo, J. Chung, R. Burns, S.S. Ghosh, J.M. Kebschull, W. Silversmith, and J.T. Vogelstein. Toward Community-Driven Big Open Brain Science: Open Big Data and Tools for Structure, Function, and Genetics. <em>Annual Review of Neuroscience<\/em> 43(1):441-464, 2020. <a href=\"https:\/\/www.annualreviews.org\/doi\/abs\/10.1146\/annurev-neuro-100119-110036\">pdf<\/a><\/li>\n<li>J. Choi, K. Kumar, M. Khazali, K. Wingel, M. Choudhury, <strong>A.S. Charles<\/strong>, and B. Pesaran. Optimal Adaptive Electrode Selection to Maximize Simultaneously Recorded Neuron Yield. <em>Neural Information Processing Systems (NeurIPS)<\/em>, Virtual, December 2020. <a href=\"https:\/\/www.biorxiv.org\/content\/10.1101\/2020.10.06.328526v1\">pdf<\/a><\/li>\n<li>N.P. Bertrand*, <strong>A.S. Charles*<\/strong>, J. Lee*, P.B. Dunn, and C.J. Rozell. Efficient tracking of sparse signals via an Earth mover&#8217;s distance regularizer. <em>IEEE Signal Processing Letters<\/em> 27:1120-1124, 2020. *Equal contribution. <a href=\"https:\/\/ieeexplore.ieee.org\/document\/9115856\">IEEE Xplore<\/a>, <a href=\"https:\/\/arxiv.org\/abs\/1806.04674\">pdf<\/a>.<\/li>\n<li>S. Gigante, <strong>A.S. Charles<\/strong>, S. Krishnaswamy, and G. Mishne. Visualizing the PHATE of Neural Networks. <em>Neural Inormation Processing Systems (NeurIPS)<\/em>, Vancouver, Canada, December 2019.<a href=\"https:\/\/arxiv.org\/abs\/1908.02831\">pdf<\/a><\/li>\n<li>G. Mishne and <strong>A.S. Charles<\/strong>. Learning spatially-correlated temporal dictionaries for calcium imaging. <em>Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)<\/em>, Brighton, UK, May 2019 (Selected for oral presentation) <a href=\"https:\/\/arxiv.org\/abs\/1902.03132\">pdf<\/a>.<\/li>\n<li><strong>A.S. Charles<\/strong>*, M. Park*, J.P. Weller, G.D. Horwitz, and J.W. Pillow. Dethroning the Fano Factor: a flexible, model-based approach to partitioning neural variability. <em> Neural Computation<\/em> 30(4):1012-1045 2018. *Joint first author. <a href=\"http:\/\/www.biorxiv.org\/content\/early\/2017\/07\/19\/165670\">pdf<\/a>. <a href=\"https:\/\/github.com\/adamshch\/flexibleModulatedPoisson\">code<\/a>.<\/li>\n<li><strong>A.S. Charles<\/strong>\u00a0and J.W. Pillow. Additive continuous-time joint partitioning of neural variability. <em>Proceedings of the Conference on Cognitive Computational Neuroscience (CCN)<\/em>, Philadelphia, PA, USA, September 2018. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/Charles_CCN2018_ACJP.pdf\">pdf<\/a>.<\/li>\n<li><strong>A.S. Charles<\/strong>, H.L. Yap, D. Lin, and C.J. Rozell. Short-term sequence memory: Compressive effects of recurrent network dynamics. <em>Proceedings of the Conference on Cognitive Computational Neuroscience (CCN)<\/em>, Philadelphia, PA, USA, September 2018. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/Charles_CCN2018_STM.pdf\">pdf<\/a>.<\/li>\n<li>N.P. Bertrand, J. Lee, <strong>A.S. Charles<\/strong>, P. Dunn, and C.J. Rozell. Sparse dynamic filtering via earth mover\u2019s distance regularization. <em>Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)<\/em>, Calgary, Alberta, Canada, April 2018 <a href=\"documents\/2018_ICASSP_emd.pdf\">pdf<\/a>.<\/li>\n<li>M. Shvartsman, N. Sudaram, M.C. Aoi, <strong>A.S. Charles<\/strong>, T. L. Wilke, and J. D. Cohen. Matrix-variate models for fMRI analysis. <em>The International Conference on Artificial Intelligence and Statistics (AISTATS)<\/em>, Playa Blanca, Lanzarote, Canary Islands, April 2018. <a href=\"https:\/\/arxiv.org\/abs\/1711.03058\">pdf(arxiv)<\/a>, <a href=\"http:\/\/proceedings.mlr.press\/v84\/shvartsman18a\/shvartsman18a.pdf\">pdf (MLR)<\/a>.<\/li>\n<li>A. Song*, <strong>A.S. Charles<\/strong>*, S.A. Koay, J.L. Gauthier, S.Y. Thiberge, J.W. Pillow, and D.W. Tank. Volumetric Two-Photon Imaging of Neurons Using Spectroscopy (vTwINS). <em> Nature Methods<\/em> 14(4):420-426, Apr. 2017. *Joint first author. <a href=\"http:\/\/biorxiv.org\/content\/early\/2016\/09\/06\/073742\">pdf<\/a>. <a href=\"https:\/\/bitbucket.org\/adamshch\/scism\/src\">code<\/a>.<\/li>\n<li><strong>A.S. Charles<\/strong>, D. Yin, and C.J. Rozell. Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks. <em>Journal of Machine Learning Research<\/em> 18(7):1-37, Jan 2017. <a href=\"http:\/\/www.jmlr.org\/papers\/volume18\/16-270\/16-270.pdf\">pdf<\/a>.<\/li>\n<li><strong>A.S. Charles<\/strong>, N.P. Bertrand, J. Lee, and C.J. Rozell. Earth-mover\u2019s distance as a tracking regulaizer. <em>Proceedings the CAMSAP<\/em>, Curacao, Dutch Antilles, December 2017. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/2017_CAMSAP_EMD.pdf\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, A. Song, S.A. Koay, D.W. Tank, and J.W. Pillow. Stochastic filtering of two-photon imaging using reweighted l<sub>1<\/sub>. <em>Proceedings of the ICASSP<\/em> New Orleans, Louisiana, March 2017. pdf.<\/li>\n<li><strong>A.S. Charles<\/strong>, A. Balavoine, and C.J. Rozell. Dynamic Filtering of Time-Varying Sparse Signals via <em>l<\/em><sub>1<\/sub> Minimization. <em>IEEE Transactions of Signal Processing 2016<\/em>, 64(21):5644-5656, November 2016. <a href=\"documents\/2016_l1methods.pdf\">pdf<\/a>.<\/li>\n<li><strong>A.S. Charles<\/strong>, H.L. Yap, and C.J. Rozell. Short term network memory capacity via the restricted isometry property. <em>Neural Computation<\/em>, 26(6), June, 2014. <a href=\"http:\/\/arxiv.org\/pdf\/1307.7970v3\">pdf<\/a>.<\/li>\n<li><strong>A.S. Charles<\/strong> and C.J. Rozell. Spectral superresolution of hyperspectral imagery using reweighted l1 spatial filtering. <em>IEEE Journal of Geoscience and Remote Sensing Letters<\/em>, 11(3):602-606, March 2014. <a href=\"documents\/2012_HSIRW.pdf\">pdf<\/a>.<\/li>\n<li><strong>A.S. Charles<\/strong> and C.J. Rozell, Convergence of basis pursuit de-noising with dynamic filtering. <em>Proceedings of the GlobalSIP<\/em> Atlanta, Georgia, November 2014. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesRozell_globalsip2014.pdf\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, Y. Dong, and C.J. Rozell, Can random linear networks store multiple long input streams? <em>Proceedings of the GlobalSIP<\/em> Atlanta, Georgia, November 2014. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesDongRozell_globalsip2014.pdf\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong> and C.J. Rozell, Dynamic filtering of sparse signals using reweighted l1. <em>Proceedings of the ICASSP<\/em> Vancouver, Canada, May 2013. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesRozell_2013icassp.pdf\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, A. Ahmed, A. Joshi, S. Conover, C. Turnes, and M.A. Davenport. Cleaning up toxic waste: Removing nefarious contributions to recommendation systems. <em>Proceedings of the ICASSP<\/em> Vancouver, Canada, May 2013. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/ICASSP_2013_tw.pdf\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, P. Garrigues, and C.J. Rozell. A common network architecture efficiently implements a variety of sparsity-based inference problems, <em>Neural Computation<\/em>, 24(12):3317-3339, December 2012. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesGarriguesRozell_2012LCA.pdf\">pdf<\/a>.<\/li>\n<li>S. Shapero, <strong>A.S. Charles<\/strong>, C.J. Rozell, and P. Hasler. Low power sparse approximation on reconfigurable analog hardware. <em>IEEE Journal on Emerging and Selected Topics in Circuits and Systems<\/em>, 2(3):530-541, September 2012. Special Issue on Circuits, Systems and Algorithms for Compressive Sensing. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/shaperoJETCAS2012.pdf\">pdf<\/a>.<\/li>\n<li>H.L. Yap, <strong>A.S. Charles<\/strong>, and C.J. Rozell. The restricted isometry property for echo state networks with applications to sequence memory capacity. <em>Statistical Signal Processing Workshop<\/em> Ann Arbor, Michigan, August 2012. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/YapCharlesRozell_2012SSP.pdf\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, B.A. Olshausen, and C.J. Rozell. Learning sparse codes for hyperspectral images. <em>IEEE Journal of Selected Topics in Signal Processing<\/em>, 5(5):963-978, September 2011. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesOlshausenRozell_Manuscript.pdf\">pdf<\/a>. <a href=\"documents\/https:\/\/bitbucket.org\/adamshch\/scism\/src\">code<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, M.S. Asif, J. Romberg, and C.J. Rozell, Sparsity penalties in dynamical system estimation. <em>Proceedings of the CISS<\/em> Baltimore, Maryland, March 2011. (Selected for oral presentation) <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesAsifRombergRozell2011.pdf\">pdf<\/a><\/li>\n<li>M.S. Asif, <strong>A.S. Charles<\/strong>, J. Romberg, and C.J. Rozell, Estimation and dynamic updating of time-varying signals with sparse variations. <em>Proceedings of the ICASSP, <\/em>Prague, Czech Republic, May 2011. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/ACRR_KalmanCS.pdf\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, A.A. Kressner, and C.J. Rozell, Causal sparse decompositions of audio signals. <em>Proceedings of the IEEE Signal Processing (DSP) Workshop, <\/em>Sedona, AZ, January 2011. (Nominated for best student paper\/Selected for oral presentation) <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesKressnerRozell_2010.pdf\">pdf<\/a> (Nominated for best student paper)<\/li>\n<li><strong>A.S. Charles<\/strong>, B.A. Olshausen, and C.J. Rozell. Sparse coding for spectral signatures in hyperspectral images. <em>Proceedings of the Asilomar Conference on Signals, Systems and Computers<\/em>, Pacific Grove, CA, November 2010 <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesOlshausenRozell_2010.pdf\">pdf<\/a> , <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/2010AsilomarPoster_v3.pdf\">poster<\/a><\/li>\n<\/ul>\n<p><strong>Conference Abstracts<\/strong><\/p>\n<ul>\n<li>E. Yezerets, E. Yang, M. Ahrens, and <strong>A.S. Charles<\/strong>. Behavior-dlds: A decomposed linear dynamical systems model for neural activity partially constrained by behavior. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal. 2026.\u00a0<\/li>\n<li>Y. Chen*, N. Mudrik*, G. Mishne, J. Knierim, and <strong>A.S. Charles<\/strong>. Adaptive ensemble decomposition reveals context-odor coding at distinct timescales in LEC. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal. 2026. *co-first author<\/li>\n<li><strong>A.S. Charles<\/strong>, A. Rupasinghe, and J. Pillow. Continuous partitioning of neuronal variability. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal. 2026.\u00a0<\/li>\n<li>A. Lawrence, E. Yezerets, T. Harris, P. Janak, and <strong>A.S. Charles<\/strong>. Stereotypical states in anterior insula neuronal ensembles during alcohol self-administration. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal. 2026.<\/li>\n<li>P. Jiang, H. Giaffar, Z. Jin, Y. Yuan, <strong>A.S. Charles<\/strong>, and M. Aoi. Indoctrination is harder than you think: On the use and misuse of rnns as surrogates for the brain. Computational and Systems Neuroscience (CoSyNe), Lisbon, Portugal. 2026.\u00a0<\/li>\n<li>A. Daraie, L.A. Sanchez, J.A. Gonzalez-Martinez, <strong>A.S. Charles<\/strong>, J.Y. Kang, and S. Sridevi. Seizure suppression network: An intrinsic mechanism for seizure termination and novel target for neurostimulation. 4th International Conference on Artificial Intelligence in Epilepsy and Neurological Disorders, Puerto Rico. 2026.\u00a0<\/li>\n<li>N. Mudrik, R. Ly, , O. Ruebel, and <strong>A.S. Charles<\/strong>. Cross-regional ensemble interactions in multi-view brain observations (CREIMBO). Greater Baltimore Society for Neuroscience (GBSfN) Conference, Baltimore, MD. 2025.\u00a0<\/li>\n<li>E. Yezerets, E. Yang, M. Ahrens, and <strong>A.S. Charles<\/strong>. Discovering large-scale circuits in larval zebrafish via decomposed linear dynamical systems (dlds). Greater Baltimore Society for Neuroscience (GBSfN) Conference, Baltimore, MD. 2025.\u00a0<\/li>\n<li>A. Lawrence, E. Yezerets, T. Harris, <strong>A.S. Charles<\/strong>, and P.H. Janak. Dynamic single neuron and population encoding of motivational state in the anterior insula during alcohol self-administration. Greater Baltimore Society for Neuroscience (GBSfN) Conference, Baltimore, MD. 2025.\u00a0<\/li>\n<li>P. Jiang, H. Giaffar, Z. Jin, Y. Yuan, <strong>A.S. Charles<\/strong>, and M. Aoi. Indoctrinating students is harder than you think: highly constraining rnns is no guarantee of their quality as surrogates for the brain. Society for Neuroscience (SfN) Conference, San Diego, CA. 2025.<\/li>\n<li>C. Bao, R. Mildren, <strong>A.S. Charles<\/strong>, and K.E. Cullen. Identifying complex spike activities from multi-channel electrode recording in vestibular cerebellum using a deep learning-based sorting technique. Society for Neuroscience (SfN) Conference, San Diego, CA.2025.\u00a0<\/li>\n<li>Z. Zhu, <strong>A.S. Charles<\/strong>, and K.V. Kuchibhotla. Multi-area cortical mechanisms underlying continual learning. Society for Neuroscience (SfN) Conference, San Diego, CA. 2025.<\/li>\n<li>Z. Wang, S. Moore, Z. Zhu, R. Sun, A. Lee, <strong>A.S. Charles<\/strong>, and K.V. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual behavior. Society for Neuroscience (SfN) Conference, San Diego, CA. 2025.\u00a0<\/li>\n<li>J. Lawlor, S.E. Elnozahy, F. Zhu, F. Du, T. Raam, A. Kwok, <strong>A.S. Charles<\/strong>, and K.V. Kuchibhotla. Role of the cholinergic system in early sensorimotor acquisition. Society for Neuroscience (SfN) Conference, San Diego, CA. 2025.\u00a0<\/li>\n<li>Z. Zhu, <strong>A.S. Charles<\/strong>, and K. Kuchibhotla. Multi-area cortical mechanisms underlying continual learning. Advances and Perspectives in Auditory Neuroscience (APAN). 2025.<\/li>\n<li>S. Moore, Z. Wang, Z. Zhu, R. Sun, A. Lee, <strong>A.S. Charles<\/strong>, and K. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual behavior. Advances and Perspectives in Auditory Neuroscience (APAN). 2025.\u00a0<\/li>\n<li><strong>A.S. Charles<\/strong>, E. Yezerets, S. Koukuntla, and N. Mudrik. Brain-wide data and the limits of conventional computational neuroscience. Statistical Analysis of Neural Data (SAND) Conference, New York, NY, June 2025. Selected for a talk<\/li>\n<li>L. Gomez, N. Mudrik, <strong>A.S. Charles<\/strong>, and K. Cullen. Understanding multi-sensory integration in PIVC through ensemble analysis. Statistical Analysis of Neural Data (SAND) Conference, New York, NY, June 2025<\/li>\n<li>R. Rupasinghe, <strong>A.S. Charles<\/strong>, and J.W. Pillow. Continuous partitioning of neuronal variability. Statistical Analysis of Neural Data (SAND) Conference, New York, NY, June 2025<\/li>\n<li>P. Jiang, H. Giaffar, Y. Yuan, <strong>A.S. Charles<\/strong>, and M. Aoi. Indoctrinating students is harder than you think: highly constraining RNNs is no guarantee of their quality as surrogates for the brain. Statistical Analysis of Neural Data (SAND) Conference, New York, NY, June 2025<\/li>\n<li>N. Mudrik, R. Ly, O. Rubel, and <strong>A.S. Charles<\/strong>. Modeling multi-regional and non-stationary neural dynamics via latent sub-circuits. ICLR XAI4Science Workshop. Singapore, Apr. 2025<\/li>\n<li>E. Whang, J. Yi, and <strong>A.S. Charles<\/strong>. Fast two-photon microscopy with a subsampling elliptical beam. 2025. Photonics West, San Francisco, CA<\/li>\n<li>Y. Chen, N. Mudrik, J. Kneirim, and <strong>A.S. Charles<\/strong>. LEC ensemble analysis reveals context-guided odor encoding via adaptive spatio-temporal representations. Organization for Computational Neurosceinces (CNS) Flourence, Italy, July 2025<\/li>\n<li>Z. Wang, S. Moore, Z. Zhu, J. Wang, R. Sun A. Lee, <strong>A.S. Charles<\/strong>, and K.V. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual behavior. Computational and Systems Neuroscience (CoSyNe), Montreal, Canada, March 2025<\/li>\n<li>L. Gomez, N. Mudrik, K. Cullen, and <strong>A.S. Charles<\/strong>. Understanding sensory-motor integration in the PIVC through ensemble analysis. Computational and Systems Neuroscience (CoSyNe), Montreal, Canada, March 2025<\/li>\n<li>N. Mudrik, G. Mishne, and <strong>A.S. Charles<\/strong>. Sibblings: Similarity-driven building-block inference using graphs across states. <em>ICML AI for Science Workshop,<\/em> Vienna, Austria, Jul. 2024<\/li>\n<li>N. Mudrik, Y. Chen, E. Yezerets, C.J. Rozell, and <strong>A.S. Charles<\/strong>. Decomposed linear dynamical systems (dLDS) for identifying the latent dynamics underlying high-dimensional time-series. <em>ICML Workshop on Geometry-grounded Representation Learning and Generative Modeling<\/em>, Vienna, Austria, Jul. 2024<\/li>\n<li>I. Garwood, J. Choi, K. Wingel, J. Stefanowicz, K. Chiang, A. Dubey, J. Viventi, <strong>A.S. Charles<\/strong>, and B. Pesaran. Multiregional neuronal calcium imaging during cortical electrical stimulation. <em>Simian Collective Conference<\/em>, Pittsburg, PA, USA, Sep. 2024<\/li>\n<li>S. Moore, Z. Wang, R. Sun, A. Lee, <strong>A.S. Charles<\/strong>, and K. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual behavior. <em>Advances and perspectives in Auditory Neuroscience (APAN)<\/em>, Chicago, IL, USA, Oct. 2024<\/li>\n<li>Z. Zhu, <strong>A.S. Charles<\/strong>, and K. Kuchibhotla. Multi-area cortical mechanisms underlying continual learning. <em>Advances and perspectives in Auditory Neuroscience (APAN)<\/em>, Chicago, IL, USA, Oct. 2024<\/li>\n<li>M.E. Xie, A. Negrean, L. Kinsey, G. Jaindl, <strong>A.S. Charles<\/strong>, K. Podgorski, and K. Svoboda. Measurement of input-output signals in vivo using high-speed two-photon microscopy <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Oct. 2024<\/li>\n<li>P. Jiang, <strong>A.S. Charles<\/strong>, and M. Aoi. RNN Discovery of linear dynamical systems features.\u00a0<em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Oct. 2024<\/li>\n<li>A. Estrada, G. Kang, G. Mishne, and <strong>A.S. Charles<\/strong>. Fast and accessible morphology-free calcium imaging analysis. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Oct. 2024<\/li>\n<li>Z. Zhu, <strong>A.S. Charles<\/strong>, and K. Kuchibhotla. Multi-area cortical mechanisms underlying continual learning. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Oct. 2024<\/li>\n<li>B. Pesaran, I.C. Garwood, K. Wingel, J. Haggerty, <strong>A.S. Charles<\/strong>, J. Choi, and A. Dubey. System and method for calcium imaging and electrophysiology in non-human primates. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Oct. 2024<\/li>\n<li>Z. Zhu, <strong>A.S. Charles<\/strong>, and K. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual<br \/>behavior. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Oct. 2024<\/li>\n<li>A. Rupasinghe, <strong>A.S. Charles<\/strong>, and J.W. Pillow. Continuous partitioning of neuronal variability. <em>Society<\/em><br \/><em>of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Oct. 2024<\/li>\n<li>N. Mudrik, G. Mishne, and <strong>A.S. Charles<\/strong>. Sibblings: Similarity-driven building-block inference using neural graphs across states. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>, Lisbon, Portugal, March 2024<\/li>\n<li>S. Koukuntla, T. Harris, <strong>A. S. Charles<\/strong>, and C. Brody. Unsupervised discovery of nonlinear and interpretable communication submanifolds. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>, Lisbon, Portugal, March 2024<\/li>\n<li>A.H. Daraie, <strong>A.S. Charles<\/strong>, L.A. Sanchez, L. Talley, J.Y. Kang, and S.V. Sarma. A comprehensive seizure detection, localization and classification tool for epilepsy monitoring. <em>AI Epilepsy Conference<\/em>, Salt Lake City, Utah, USA, Mar. 2024<\/li>\n<li>N. Mudrik, G. Mishne, and <strong>A.S. Charles<\/strong>. Exploring temporal and structural variability in neural ensembles across trials and conditions. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Nov. 2023. Selected for Nanosymposium presentation<\/li>\n<li>E. Yezerets, N. Mudrik, Y. Chen, C. Rozell, and <strong>A.S. Charles<\/strong>. Decomposed linear dynamical systems for C. elegans functional connectivity. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Nov. 2023. Selected for Nanosymposium presentation<\/li>\n<li>L. Xiang, P. Kanold, and <strong>A.S. Charles<\/strong>. Unsupervised extraction of neural activity motifs encoding stimulus and choice information in mice primary auditory cortex. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Nov. 2023<\/li>\n<li>G.I. Coste, A.R. Graves, Z. Chen, T. Li, Y.T. Xu, D.E. Bergles, J. Sulam <strong>A.S. Charles<\/strong>, and R.L. Huganir. Tracking plasticity of millions of synapses induced by learning and memory in vivo. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Nov. 2023<\/li>\n<li>K. Podgorski, <strong>A.S. Charles<\/strong>, D.A. Flickinger, G. Jaindl, A. Negrean, J. Rohde, and M.E. Xie. Secondgeneration scanned line projection microscopy (SLAP2) for in vivo imaging of synaptic input. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Nov. 2023<\/li>\n<li>K. Johnsen, N. Cruzado, <strong>A.S. Charles<\/strong>, and C.J. Rozell. Enhancing the cleo experiment simulation testbed to support all-optical control, multi-channel optogenetics, and easier integration into data analysis pipelines. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Nov. 2023<\/li>\n<li>B. Pesaran, J. Choi, K. Wingel, J. Haggerty, and <strong>A.S. Charles<\/strong>. Multiregional calcium imaging of neurons in the non-human primate brain. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Nov. 2023<\/li>\n<li>S. Moore, Z. Wang, R. Sun, A. Lee, A. S. Charles, and K. Kuchibhotla. Revealing abrupt transitions from goal-directed to habitual behavior during audio-motor learning. <em>Advances and Perspecitves in Auditory Neuroscience (APAN)<\/em>, Washington DC, USA, Nov. 2023<\/li>\n<li>Y. Cheng, R. Magnard, C. Drieu, D. Garr, L.A. Castell, A. Langdon, <strong>A.S. Charles<\/strong>, D. Lee, and P.H. Janak. Chronic ethanol vapor exposure in adult rats persistently reduces behavioral flexibility in protracted withdrawal. <em>Society of Neuroscience (SfN) Conference<\/em>, Washington D.C., USA, Nov. 2023<\/li>\n<li>A.H. Daraie, L.A. Sanchez, L. Talley, <strong>A.S. Charles<\/strong>, J.Y. Kang, and S.V. Sarma. Seizure detection using entropy of source-sink nodal dynamics in the epileptic network. <em>Annual meeting of the American Epilepsy Society (AES)<\/em>, Orlando, Florida, USA, Dec. 2023<\/li>\n<li>N. Mudrik, G. Mishne, and <strong>A. S. Charles<\/strong>. Studying latent neuronal functional circuits underlying brain activity across task conditions. <em>IEEE EMBS Conference on Neural Engineering (NER)<\/em>, Baltimore, Maryland, USA, April 2023<\/li>\n<li>A. H. Daraie, L. Sanchez, K. Gunnarsdottir, J. Yi-Kang, <strong>A. S. Charles<\/strong>, and S. Sarma. A patient-specific approach for epileptic seizure prediction by tracking network dynamics using source-sink connectivity. <em>IEEE EMBS Conference on Neural Engineering (NER)<\/em>, Baltimore, Maryland, USA, April 2023<\/li>\n<li>E. Yezerets, N. Mudrik, Y. Chen, C. Rozell, and <strong>A. S. Charles<\/strong>. Decomposed linear dynamical systems for c. elegans functional connectivity. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>, Montreal, Canada, March 2023<\/li>\n<li>I. Dmitrieva, S. Babkin, and <strong>A. S. Charles<\/strong>. On-line seudo for real-time cell recognition in calcium imaging. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>, Montreal, Canada, March 2023<\/li>\n<li>S. Koukuntla, T. Harris, and <strong>A. S. Charles<\/strong>. Automatic spike sorting correction and burst detection for high-density electrophysiological recordings. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>,<br \/>Montreal, Canada, March 2023<\/li>\n<li>D. Zoltowski, <strong>A. S. Charles<\/strong>, J. Pillow, and S. Keeley. Improved estimation of latent variable models from calcium imaging data. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>, Montreal, Canada, March 2023<\/li>\n<li>S. Moore, Z. Wang, R. Sun, A. Lee, <strong>A. S. Charles<\/strong>, and K. Kuchibhotla. Revealing sudden transitions from goal-directed to habitual behavior during learning in mice. <em>Computational and Systems<\/em><br \/><em>Neuroscience (CoSyNe)<\/em>, Montreal, Canada, March 2023<\/li>\n<li>J. Haggerty, J. Choi, M. W. Choudhury, K. Wingel, B. Pesaran, and <strong>A. S. Charles<\/strong>. Mapping and localizing neurons using a robotic multiphoton microscope in NHP. <em>Society for Neuroscience (SfN)<\/em>, San Diego, California, November 2022. Selected for nanosymposium<\/li>\n<li>B. Pesaran, <strong>A. S. Charles<\/strong>, J. Choi, K. Wingel, J. Haggerty, H. Hafizi, A. Dubey, M. W. Choudhury, and R. Bakhshi. A robotic platform for multiregional calcium imaging in the non-human primate brain.<em> Society for Neuroscience (SfN)<\/em>, San Diego, California, November 2022. Selected for nanosymposium<\/li>\n<li>K. Wingel, J. Choi, M. Choudhury, <strong>A. S. Charles<\/strong>, H. Hafizi, A. Dubey, R. Bakhshi, and B. Pesaran. Multi-regional functional two photon calcium imaging in an awake behaving rhesus macaque. <em>Society for Neuroscience (SfN)<\/em>, San Diego, California, November 2022<\/li>\n<li>X. Yuan, J. Colonell, A. S. Charles, and T. Harris. Neuron tracking with chronic neuropixels 2.0 recordings from mouse visual cortex. <em>Society for Neuroscience (SfN)<\/em>, San Diego, California, November 2022<\/li>\n<li>S. Moore, Z. Wang, R. Sun, Z. Zhu, A. Lee, <strong>A. S. Charles<\/strong>, and K. Kuchibhotla. Sudden transition from goal-directed to habitual behavior during sensorimotor learning in mice. <em>Society for Neuroscience (SfN) Conference<\/em>, San Diego, California, November 2022<\/li>\n<li>T. Xu, A. Graves, G. Coste, R. Huganir, D. Bergles, <strong>A. S. Charles<\/strong>, and J. Sulam. Cross-modality supervised image restoration enables nanoscale tracking of synaptic plasticity in living mice. <em>Society for Neuroscience (SfN) Conference,<\/em> San Diego, California, November 2022<\/li>\n<li>D. Day, J. Gauthier, D. Tank, and <strong>A.S. Charles<\/strong>. Classifying transients in calcium imaging via convolutional neural nets. <em>Neuromatch Acadamy 4.0<\/em>, November 2021<\/li>\n<li>T. Xu, A. Graves, G. Coste, R. Huganir, D. Bergles, <strong>A.S. Charles<\/strong>, and J. Sulam. Cross-modality supervised image restoration enables nanoscale tracking of synaptic plasticity in living mice. <em>Neuromatch <\/em><em>Acadamy 4.0<\/em>, November 2021<\/li>\n<li>J. Choi, M. Khazali, <strong>A.S. Charles<\/strong>, and B. Pesaran. Multi-scale measurements of primate motor cortex during free reaching. <em>Brain Initiative Investigators Meeting<\/em>, June 2021<\/li>\n<li>\n<div>S. Keeley*, D. Zoltowski*, <strong>A.S. Charles<\/strong>, J.W. Pillow. Improved estimation of neural encoding models from calcium imaging data.\u00a0<em>Brain Initiative Investigator&#8217;s Meeting<\/em>, June, 2020. *Equal contribution\u00a0<\/div>\n<\/li>\n<li><strong>A.S. Charles<\/strong>, N. Cermak, J. Shiller, and G. Mishne. Calcium imaging analysis with graph filtered temporal dictionary learning. <em>Society for Neuroscience (SfN)<\/em>, Chicago, Illinois, October 2019<\/li>\n<li><strong>A.S. Charles<\/strong> and J. W. Pillow. Continuous-time partitioning of neural variability. <em>Society for Neuroscience (SfN) Conference<\/em>, Chicago, Illinois, October 2019<\/li>\n<li>G. Mishne, N. Cermak, J. Shiller, and <strong>A.S. Charles<\/strong>. Spatially-filtered temporal dictionary learning for calcium imaging analysis. <em>Signal Processing with Adaptive Sparse Structured Representations (SPARS)<\/em>, Toulouse, France, June 2019<\/li>\n<li>G. Mishne, B. Scott, S. Thiberge, N. Cermak, J. Schiller, D.W. Tank, and <strong>A.S. Charles<\/strong>. Graph-filtered temporal dictionary learning for calcium imaging analysis. <em>Computational Neuroscience Meeting (CNS), <\/em> Barcelona, Spain, July 2019 (Selected for oral presentation)<\/li>\n<li>J.L. Gauthier, S.A. Koay, E. Nieh, D.W. Tank, J.W. Pillow, and <strong>A.S. Charles<\/strong>. Sparse-coding variational auto-encoders. <em>Computational and Systems Neuroscience (CoSyNe), <\/em> Lisbon, Portugal, July 2019<\/li>\n<li>G. Mishne, B. Scott, S. Thiberge, N. Cermak, J. Schiller, D.W. Tank, and <strong>A.S. Charles<\/strong>. Temporal dictionary learning for calcium imaging analysis. <em>Computational and Systems Neuroscience (CoSyNe), <\/em> Lisbon, Portugal, July 2019<\/li>\n<li>G. Barello, <strong>A.S. Charles<\/strong>, and J.W. Pillow. Sparse-coding variational auto-encoders. <em>Computational and Systems Neuroscience (CoSyNe), <\/em> Lisbon, Portugal, July 2019<\/li>\n<li><strong>A.S. Charles<\/strong>, H. L. Yap, D. Yin, and C. J. Rozell. Rigorous guarantees on sequence memory capacity in recurrent neural networks using randomized dimensionality reduction. <em> Theoretical Foundation of Deep Learning<\/em>, Atlanta, Georgia, October 2018<\/li>\n<li>J.L. Gauthier, <strong>A.S. Charles<\/strong>, D.W. Tank, and J.W. Pillow. Robust identification and removal of falsetransients in calcium fluorescence imaging data. <em>Society for Neuroscience (SfN), <\/em> San Diego, California, September 2018<\/li>\n<li>M. Shvartsman, N. Sudaram, M.C. Aoi, <strong>A.S. Charles<\/strong>, T.L. Wilke, and J.D. Cohen. Matrix-normal models for fMRI analysis. <em>Organization for Human Brain Mapping (OHBM), <\/em> Singapore, June 2018<\/li>\n<li>M. Shvartsman, N. Sudaram, M.C. Aoi, <strong>A.S. Charles<\/strong>, T.L. Wilke, and J.D. Cohen. Matrix-normal models for fMRI analysis. <em>Computational and Systems Neuroscience (CoSyNe), <\/em> Denver, Colorodo, March 2018<\/li>\n<li>J. Lee, <strong>A.S. Charles<\/strong>, N.P. Bertrand, and C.J. Rozell. An optimal transport tracking regularizer. <em>Neural Information Processing Systems (NIPS) Workshops, <\/em> Long Beach, California, December 2017<\/li>\n<li>M. Shvartsman, N. Sudaram, M.C. Aoi, <strong>A.S. Charles<\/strong>, T.L. Wilke, and J.D. Cohen. Matrix-variate models for fMRI analysis. <em>Neural Information Processing Systems (NIPS) Workshops, <\/em> Long Beach, California, December 2017<\/li>\n<li>A. Song, <strong>A.S. Charles<\/strong>, S.Y. Thiberge, J.L. Gauther, S.A. Koay, J.W. Pillow, and D.W. Tank. Volumetric two-photon imaging via stereoscopy and two-photon calcium imaging simulator. <em> Emerging Tools for Acquisition and Interpretation of Whole-Brain Functional Data, <\/em> Ashburn, Virginia, November 2017<\/li>\n<li>J.L. Gauthier, <strong>A.S. Charles<\/strong>, D.W. Tank, and J.W. Pillow. Robust estimation of calcium transients by modeling contamination. <em>SFN<\/em> Washington DC., June 2017.<\/li>\n<li>A. Song, <strong>A.S. Charles<\/strong>, D.W. Tank and J.W. Pillow. A two-photon microscopy simulation framework for optimizing optics and benchmarking cell-finding algorithms. <em>SFN<\/em> Washington DC., June 2017.<\/li>\n<li><strong>A.S. Charles<\/strong>, A. Song, S.A. Koay, J.L. Gauthier, S.Y. Thiberge, D.W. Tank, and J.W. Pillow. Adaptive orthogonal basis pursuit for volumetric two-photon microscopy. <em>Signal Processing with Adaptive Sparse Structured Representations (SPARS)<\/em>\u00a0Lisbon, Portugal, June 2017.<\/li>\n<li><strong>A.S. Charles<\/strong>, D. Yin, and C.J. Rozell. Compression of multiple input streams into recursive neural networks. <em>Signal Processing with Adaptive Sparse Structured Representations (SPARS)<\/em>\u00a0Lisbon, Portugal, June 2017.<\/li>\n<li><strong>A.S. Charles<\/strong>, J. Lee, N.P. Bertrand, and C.J. Rozell. Dynamic filtering with earth mover&#8217;s distance regularization. <em>Signal Processing with Adaptive Sparse Structured Representations (SPARS) <\/em>\u00a0Lisbon, Portugal, June 2017.<\/li>\n<li><strong>A.S. Charles<\/strong> and J.W. Pillow. Continuous-time partitioning of binned spike counts. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>\u00a0Salt Lake City, Utah, February 2017.<\/li>\n<li>J.L. Gauthier, <strong>A.S. Charles<\/strong>, J.W. Pillow, and D.W. Tank. Robust estimation of calcium transients by modeling contamination. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>\u00a0Salt Lake City, Utah, February 2017.<\/li>\n<li>A. Song, <strong>A.S. Charles<\/strong>, J.L. Gauthier, S.A. Koay, D.W. Tank, and J.W. Pillow. Two-photon microscopy simulation for optics optimization and benchmarking. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>\u00a0Salt Lake City, Utah, February 2017.<\/li>\n<li><strong>A.S. Charles<\/strong>, H.L. Yap, D. Yin, and C.J. Rozell. Short-term sequence memory in recurrent networks. <em>Neural Information Processing Systems<\/em> (<em>NIPS) Workshops<\/em> Barcelona, Spain, December 2016.<\/li>\n<li>N.P. Bertrand, H.L. Yap, <strong>A.S. Charles<\/strong>, and C.J. Rozell. Efficient randomized filtering for dimensionality reduction in electrophysiology data. <em>Neural Information Processing Systems<\/em> (<em>NIPS)<\/em><em>\u00a0Workshops<\/em> Barcelona, Spain, December 2016.<\/li>\n<li>A. Song, <strong>A.S. Charles<\/strong>, S.Y. Thiberge, J.L. Gauthier, S.A. Koay, J.W. Pillow, and D.W. Tank. Two-photon imaging of neurons using stereoscopy (TwINS). <em>SfN<\/em> San Diego, California, December 2016.<\/li>\n<li><strong>A.S. Charles<\/strong> and C.J. Rozell, Learning a dynamics dictionary for time-varying sparse signals. <em>Signal Processing with Adaptive Sparse Structured Representations (SPARS)<\/em>\u00a0Cambridge, United Kingdom, July 2015.<\/li>\n<li><strong>A.S. Charles<\/strong> and C.J. Rozell, Robust estimation of sparse time-varying signals. <em>Information Theory and Applications<\/em> La Jolla, California, February 2015.<\/li>\n<li>C.J. Rozell, M. Zhu, <strong>A.S. Charles<\/strong>, H.L. Yap, and M. Norko, The role of sparsity in visual perception. <em>Biologically Inspired Cognitive Architectures (BICA).<\/em> Cambridge, Massachusetts, November 2014.<\/li>\n<li><strong>A.S. Charles<\/strong>, C.J. Rozell, and N. Tufillaro, Sparsity based spectral super-resolution and applications to water color. <em>IEEE International Geoscience and REmote Sensing Symposium (IGARSS)<\/em> Quebec, Canada, May 2014. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/IGARSS2014.pdf\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong> and C.J. Rozell. Stochastic filtering via reweighted l1. <em>Signal Processing with Adaptive Sparse Structured Representations (SPARS)<\/em>, Lausanne, Switzerland, July 2013. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/SPARS13_abstract1.pdf\">pdf<\/a>, <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/spars13_poster.pdf\">poster<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, H.L. Yap, and C.J. Rozell. Using compressed sensing to study sequence memory capacity in networked systems. <em>Signal Processing with Adaptive Sparse Structured Representations (SPARS)<\/em>, Lausanne, Switzerland, July 2013 <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/esn_spars13.pdf\">pdf<\/a><\/li>\n<li>A.A. Kressner, <strong>A.S. Charles<\/strong>, and C.J. Rozell. Causal locally competitive algorithm for the sparse decomposition of audio signals. <em>IEEE Womens Workshop on Communications and Signal Processing<\/em>, Banf, Canada, July 2012<\/li>\n<li><strong>A.S. Charles<\/strong>, H.L. Yap, , and C.J. Rozell. Short term memory in neural networks via the restricted isometry property. <em>Computational Neuroscience Meeting Workshop on Methods of Information Theory in Computational Neuroscience<\/em>, Atlanta, GA, July 2012<\/li>\n<li>H.L. Yap, <strong>A.S. Charles<\/strong>, and C.J. Rozell, Short-term memory capacity in recurrent Networks via compressed sensing. <em>Challenges in Geometry, Analysis and Computation: High-Dimensional Synthesis<\/em>, Yale University, June 2012 <a href=\"documents\/HIDIMabstract.txt\">abstract<\/a><\/li>\n<li>C.J. Rozell and <strong>A.S. Charles<\/strong>. Spectral super-resolution of hyperspectral images. <em>SIAM Conference on Imaging Science<\/em>, Philadelphia, PA, May 2012<\/li>\n<li>C.J. Rozell and <strong>A.S. Charles<\/strong>. Recursive estimation of dynamic signals with sparsity models via re-weighted l1 minimization. <em>Janelia Farm Conference on Machine Learning, Statistical Inference, and Neuroscience<\/em>, Ashburn, VA, May 2012<\/li>\n<li><strong>A.S. Charles<\/strong>, H.L. Yap, and C.J. Rozell, Short-term memory capacity in recurrent Networks via compressed sensing. <em>Janelia Farm Conference on Machine Learning,Statistical Inference and Neuroscience<\/em>, Ashburn, Virginia, 2012 <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/Janelia_poster2012.pdf\">poster<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, H.L. Yap, and C.J. Rozell, Short-term memory capacity in recurrent Networks via compressed sensing. <em>Computational and Systems Neuroscience (CoSyNe)<\/em>, Salt Lake City, Utah, 2012 <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesYapRozell_STMinLNN.pdf\">pdf<\/a>, <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/COSYNE2012_poster.pdf\">poster<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>, B.A. Olshausen, and C.J. Rozell. Learning sparse codes for hyperspectral images. <em>Duke Workshop on Sensing and Analysis of High-Dimensional Data (SAHD)<\/em>, Durham, NC, July 2011 <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/2011Duke_Poster_v1.pdf\">poster<\/a><\/li>\n<li><strong>A.S. Charles<\/strong> and C.J. Rozell, A hierarchical re-weighted-l1 approach for dynamic sparse signal estimation. <em>Signal Processing with Adaptive Sparse Structured Representations (SPARS)<\/em>, Edinburgh, Scotland UK, 2011 (Selected for oral presentation) <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2019\/02\/CharlesRozell_2011.pdf\">pdf<\/a>, <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2020\/01\/2011SPARS11_Presentation.pdf\">slides<\/a><\/li>\n<\/ul>\n<p><strong>Other publications<\/strong><\/p>\n<ul>\n<li><strong>A.S. Charles<\/strong>, Interpreting Deep Learning: The Machine Learning Rorschach Test? <em>Society for Industrial and Applied Mathematics (SIAM) News<\/em>, Jul. 2018. <a href=\"https:\/\/sinews.siam.org\/Details-Page\/interpreting-deep-learning-the-machine-learning-rorschach-test\">link<\/a>, <a href=\"https:\/\/arxiv.org\/abs\/1806.00148\">extended pdf<\/a><\/li>\n<li>M. Shvartsman, N. Sundaram, M.C. Aoi, <strong>A.S. Charles<\/strong>, T.C. Wilke, and J.D. Cohen. Matrix-normal models for fMRI analysis. <em>arXiv:1711.03058<\/em> Nov. 2017. <a href=\"https:\/\/arxiv.org\/abs\/1711.03058v1\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>. Dynamics and correlations in sparse signal acquisition. <em>PhD thesis<\/em>, Georgia Institute of Technology, 2015. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2020\/07\/charles_thesis.pdf\">pdf<\/a><\/li>\n<li><strong>A.S. Charles<\/strong>. Adjustable Subband Allocation Algorithm for Critically Sampled Subband Adaptive Filters. <em>Master&#8217;s Thesis.<\/em> The Cooper Union for the Advancement of Science and Art. April 2009. <a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/wp-content\/uploads\/2020\/07\/MastersThesis.pdf\">pdf<\/a><\/li>\n<\/ul>\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Submitted manuscripts and preprints S. Thomas, B. Zhu, K. Cullen, and A.S. Charles. Partitioning Neural Co-Variability. arxiv:2605.06995. Submitted. 2026. pdf L. Xiang*, M. Wang*, P.O. Kanold+, and A.S. Charles+. Precise extraction of neural motifs reveals multiscale, parallel encoding schemes in auditory cortex. Submitted. biorxiv 2025.08.26.67228.\u00a0 2026. *Equal contribution. +Corresponding authors. biorxiv\u00a0\u00a0 N. Mudrik, A.S. Charles. &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/www.bme.jhu.edu\/ascharles\/publications\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Publications&#8221;<\/span><\/a><\/p>\n","protected":false},"author":18,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"iawp_total_views":951,"footnotes":""},"class_list":["post-47","page","type-page","status-publish","hentry","entry"],"_links":{"self":[{"href":"https:\/\/www.bme.jhu.edu\/ascharles\/wp-json\/wp\/v2\/pages\/47","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.bme.jhu.edu\/ascharles\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.bme.jhu.edu\/ascharles\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.bme.jhu.edu\/ascharles\/wp-json\/wp\/v2\/users\/18"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bme.jhu.edu\/ascharles\/wp-json\/wp\/v2\/comments?post=47"}],"version-history":[{"count":129,"href":"https:\/\/www.bme.jhu.edu\/ascharles\/wp-json\/wp\/v2\/pages\/47\/revisions"}],"predecessor-version":[{"id":1436,"href":"https:\/\/www.bme.jhu.edu\/ascharles\/wp-json\/wp\/v2\/pages\/47\/revisions\/1436"}],"wp:attachment":[{"href":"https:\/\/www.bme.jhu.edu\/ascharles\/wp-json\/wp\/v2\/media?parent=47"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}