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Jonathan Simon

Jonathan Simon

University of Maryland, College Park · Biology

Active 1985–2026

h-index51
Citations10.6k
Papers18741 last 5y
Funding$23.3M1 active

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Jonathan Simon is a professor in the Department of Biology at the University of Maryland, with joint appointments in the Department of Electrical and Computer Engineering and the Institute for Systems Research. His research program focuses on identifying and describing neural computations performed in the brain’s auditory system, aiming to shed light on brain function and discover algorithms unknown to engineering. His work investigates neural computations across multiple hierarchical levels, including macroscopic brain activity observable with magnetoencephalography (MEG), small neural networks, and individual neurons, with a particular emphasis on neural processes that utilize the temporal characteristics of sounds. Simon’s research explores how the brain performs critical and rapid computations necessary for functions such as spatial hearing and speech processing, especially under adverse conditions. His work also develops new ideas in neural signal processing and computational neuroscience. He has contributed to understanding cortical responses to continuous speech, neural tracking of speech intelligibility, and neural dynamics involved in speech feature processing. His research aims to bridge neuroscience and engineering by uncovering neural algorithms and mechanisms underlying auditory perception.

Research topics

  • Computer Science
  • Psychology
  • Speech recognition
  • Artificial Intelligence
  • Biology
  • Neuroscience
  • Audiology
  • Medicine

Selected publications

  • Continuous speech processing

    Current Opinion in Physiology · 2020-07-28 · 152 citations

    articleOpen accessSenior authorCorresponding
    PublisherOA PDFDOI

  • Eelbrain, a Python toolkit for time-continuous analysis with temporal response functions

    eLife · 2023-11-29 · 82 citations

    articleOpen accessSenior author

    Even though human experience unfolds continuously in time, it is not strictly linear; instead, it entails cascading processes building hierarchical cognitive structures. For instance, during speech perception, humans transform a continuously varying acoustic signal into phonemes, words, and meaning, and these levels all have distinct but interdependent temporal structures. Time-lagged regression using temporal response functions (TRFs ) has recently emerged as a promising tool for disentangling…

    PublisherDOI

  • High gamma cortical processing of continuous speech in younger and older listeners

    NeuroImage · 2020 · 64 citations

    Senior authorCorresponding

    Neural processing along the ascending auditory pathway is often associated with a progressive reduction in characteristic processing rates. For instance, the well-known frequency-following response (FFR) of the auditory midbrain, as measured with electroencephalography (EEG), is dominated by frequencies from ∼100 Hz to several hundred Hz, phase-locking to the acoustic stimulus at those frequencies. In contrast, cortical responses, whether measured by EEG or magnetoencephalography (MEG), are typi…

    DOI

  • Effects of aging on cortical representations of continuous speech

    Journal of Neurophysiology · 2023-04-25 · 35 citations

    articleOpen accessSenior authorCorresponding

    We observed age-related changes in cortical temporal processing of continuous speech that may be related to older adults' difficulty in understanding speech in noise. These changes occur in both timing and strength of the speech representations at different cortical processing stages and depend on both noise condition and selective attention. Critically, their dependence on noise condition changes dramatically among the early, middle, and late cortical processing stages, underscoring how aging d…

    PublisherOA PDFDOI

  • Neural tracking measures of speech intelligibility: Manipulating intelligibility while keeping acoustics unchanged

    Proceedings of the National Academy of Sciences · 2023-11-30 · 25 citations

    articleOpen accessSenior author

    Neural speech tracking has advanced our understanding of how our brains rapidly map an acoustic speech signal onto linguistic representations and ultimately meaning. It remains unclear, however, how speech intelligibility is related to the corresponding neural responses. Many studies addressing this question vary the level of intelligibility by manipulating the acoustic waveform, but this makes it difficult to cleanly disentangle the effects of intelligibility from underlying acoustical confound…

    PublisherOA PDFDOI

Recent grants

Frequent coauthors

Labs

  • Simon LabPI

Education

  • M.A., Ph.D., Physics

    University of California Santa Barbara

    1990

  • A.B., Physics

    Princeton University

    1985

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