Follow the links to see publications and presentations

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Published articles

[3] P. Melland, R. Curtu, and Z. Aminzare, "Spike-Adding Mechanisms in a Three-Timescale System: Insights from the FitzHugh-Nagumo Model with Periodic Forcing"  To appear in: SIAM Journal on Applied Dynamical Systems. [Arxiv].

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[2] P. Melland and R. Curtu, "Attractor-like dynamics extracted from human electrocorticographic recordings underlie computational principles of auditory bistable perception,"  Accepted in: The Journal of Neuroscience. [doi.org/10.1523/JNEUROSCI.1531-22.2023].[pdf]

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[1] P. Melland, J. Albright, and N.M. Urban, "Differentiable programming for online training of a neural artificial viscosity function within a staggered grid Lagrangian hydrodynamic scheme," Mach. Learn.: Sci. Technol. [doi.org/10.1088/2632-2153/abd644]. [pdf]

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Manuscripts in progress

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[4] P. Melland and A. Barrerio, "Multiscale and decoupled spike sorting for tetrodes."

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Poster presentations

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Exploring fast and slow neural correlates of auditory perceptual bistability with diffusion-mapped delay coordinates.  CNS 2020: virtual.

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Why is comparing neuro-computation in different species so important?  Future frameworks of theoretical neuroscience 2019: University of Texas at San Antonio .

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Dynamic neural field modeling of auditory categorization tasks.  CNS 2019: Barcelona, Spain.

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Diffusion Maps and their application to auditory streaming of triplets.  RTG parameter estimation workshop 2018: North Carolina State University.

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Invited talks

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Adding Spikes in the FitzHugh-Nagumo Model with Low-Frequency Periodic Forcing. SIAM-LS. Portland, OR.

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Artificial and biological neural networks: Using data to inform dynamic models. Computational Science Seminar. UT Dallas.

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Extracting intrinsic neural features of bistable perception with the extended DMD.

SIAM-LS. (2022)

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Incorporating data when equations are not enough. Weber State University. (2022)

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Discovering neural features of auditory bistable perception from human electrocorticography data.  Mathematics colloquium series: Southern Methodist University. (2021)

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Contributed talks

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Automatic differentiation and differentiable programming: Expanding deep learning architectures.  Math Bio seminar: The University of Iowa. (2019)

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Online machine learning enhanced artificial viscosity to suppress spurious oscillations near shocks in a staggered-grid Lagrangian scheme. Los Alamos National Laboratory: Los Alamos, NM. (2019)

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Should I wear a coat outside? Decision making in a changing environment.  (Chalk-talk) GAUSS Seminar: The University of Iowa. (2019)

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Auditory categorization: A dynamic field approach.  Math Bio seminar: The University of Iowa. (2018)

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An introduction the the Kalman filter.  Math Bio Seminar: The University of Iowa. (2018)

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Dualing objectives.  Applied Student Seminar: The University of Iowa. (2017)