Steven L. Meisler

Steven L. Meisler

Neuroinformaticist interested in predicting psychosis and schizophrenia, jazz vibraphonist, and wanna-be BBQ pitmaster. Previously worked on neuro-structural correlates of reading abilities.

Posts by Collection

portfolio

publications

Does data cleaning improve brain state classification?

Published in Journal of Neuroscience Methods, 2019

This paper investigates whether commonly used methods of preprocessing intracranial EEG data improve brain-state classification outcomes. In short, most methods do not improve classification outcomes, while collecting more data improves outcomes.

Recommended citation: Meisler, S. L., Kahana, M. J., & Ezzyat, Y. (2019). "Does data cleaning improve brain state classification?." Journal of neuroscience methods. 328, 108421. http://smeisler.github.io/files/MeislerEtal2019.pdf

Personalized connectome mapping to guide targeted therapy and promote recovery of consciousness in the intensive care unit

Published in Neurocritical Care, 2020

This paper describes a clinical trial framework that uses multimodal MRI data to inform and predict recovery of consciousness following pharmaceutic intervention.

Recommended citation: Edlow, B. L., Barra, M. E., Zhou, D. W., Foulkes, A. S., Snider, S. B., Threlkeld, Z. D., ... & Bodien, Y. G. (2020). "Personalized connectome mapping to guide targeted therapy and promote recovery of consciousness in the intensive care unit." Neurocritical care, 33(2), 364-375. http://smeisler.github.io/files/EdlowEtal2020.pdf

talks

teaching

BE 301 - Bioengineering Signals and Systems

Teaching assistant for undergraduate course (Fall 2016 and 2017), University of Pennsylvania, Department of Bioengineering, 2024

Course Description from Catalog: Properties of signals and systems; Examples of biological and biomedical signal and systems; Signal operations, continuous and discrete signals; Linear, time invariant systems; Time domain analysis; Systems characterized by linear constant-coefficient differential equations; Fourier analysis with applications to biomedical signals and systems; Introduction to filtering; Sampling and the sampling theorem. Examples vary from year to year, but usually include signals such as the ECG and blood pressure wave, principles of signal coding in the auditory system and cochlear implants, and simple applications in biomedical imaging.

ENM 240 - Differential Equations and Linear Algebra

Teaching assistant for undergraduate course (Fall 2017), University of Pennsylvania, Department of Engineering Mathematics, 2024

Descrtiption from Course Catalog: This course discusses the theory and application of linear algebra and differential equations. Emphasis is placed on building intuition for the underlying concepts and their applications in engineering practice along with tools for solving problems. We will also use computer simulations in MATLAB to augment this intuition.

Gen Ed 1080 - How Music Works: Engineering the Acoustical World

Teaching fellow for undergraduate course (Falls 2021-2023), Harvard University, Program in General Education, 2024

Course Description from Catalog: How does Shazam know what song is playing? Why do some rooms have better acoustics than others? How and why do singers harmonize? Do high-end musical instruments sound better than cheap ones? How do electronic synthesizers work? What processes are common in designing a device and composing a piece of music? How is music stored and manipulated in a digital form? This class explores these and related themes in an accessible way for all concentrators, regardless of technical background. The class is driven by hands-on projects to enhance your technical literacy, a critical skill for anyone designing solutions to today’s most pressing and complex issues. The projects are designed so that the creativity of students in all fields will have a role to play. Lectures, demonstrations, and guest lecturers/performers are integrated into the class to build foundational knowledge and to inspire. We will also explore wider social and historical themes related to music and acoustics. The class is approached from an engineering perspective, using music and musical instruments as the framework to introduce a broad array of concepts in physics, mathematics, and engineering. Requires no previous exposure to physics or calculus beyond the high school level.