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

• Accounting for age-related differences in the task-evoked pupil response

  2026-05-22

  articleOpen access

  The relationship between pupil size, task performance, and self-reported effort has served as a fruitful way of understanding how listeners prepare (baseline or tonic pupil size) and deploy (task-evoked or phasic pupil response) cognitive resources during a listening task. However, changes in pupil size are sensitive not only to changes in listening effort but also physiological differences, some of which may be confounded across groups. Age is one such factor: older adults’ pupil size and dynamic range tend to diminish with age (senile miosis), obscuring researchers’ ability to compare how older and younger adults prepare and deploy listening effort. To account for this age-related physiological discrepancy in pupil size, methods to normalize or scale pupil size have been proposed. Whether these methods account for physiological differences while preserving potential task-evoked differences has not yet been evaluated. The present study seeks to address this by comparing three scaling methods (baseline subtraction, luminance dynamic range scaling, and task dynamic range scaling), as well as showing the pitfalls of performing no scaling at all. To accomplish this, pupil size was recorded while normal-hearing younger and older adults listened to 60-second storybook passages in quiet. The interaction between baseline pupil size and the task-evoked pupil response was analyzed using generalized additive mixed models. The results showed that applying no scaling at all or only performing baseline subtraction resulted in significantly smaller pupil responses in older compared to younger adults, while (luminance or task) dynamic range scaling was able to account for physiological differences between groups while simultaneously capturing the dynamic relationship between baseline pupil size and the task-evoked pupil response. Overall, the results of this study suggest that whether and how to apply within-participant scaling depends on the theoretical question to be addressed and the specifics of the study design and analyses.

  PublisherDOI

• Modified-mindfulness-based stress reduction as a treatment for cognitive recovery in patients with minor stroke: a randomized controlled pilot study

  Frontiers in Neurology · 2025-08-26 · 1 citations

  articleOpen access

  Background Well-developed rehabilitation paradigms exist for post-stroke language and motor impairments. However, no such recovery program has been identified for commonly disabling cognitive deficits in patients following minor stroke. Mindfulness Based Stress Reduction (MBSR) is thought to engage the frontal lobes, improving concentration and attention, and therefore may be an effective option. Methods We prospectively enrolled a cohort of patients with subacute minor stroke and randomized them to either an 8-week online modified-MBSR course or online traditional Stroke Support Group (SSG). All patients underwent a battery of cognitive tests and measures of patient reported outcomes (PROs) pre- and post-intervention. ANOVA was used to compare changes in scores over time across both groups, along with a third group of control patients having received neither intervention ( n = 128). Results A total of 30 patients were randomized ( n = 16 for m-MBSR; n = 14 for SSG). The average age of the cohort was 65.9 years. Post-intervention, both groups demonstrated significantly improved T-scores on cognitive tasks, regardless of intervention. Compared to SSG, the m-MBSR group showed a larger degree of improvement in processing speed, executive, and global cognitive function; however, the difference between groups was not statistically significant. Engagement level was not associated with better clinical scores, though was unexpectedly low for both groups. Conclusion m-MBSR may modestly improve frontal lobe activity and demonstrates some success in increasing cognitive performance. However, further studies are needed to determine if it is more efficacious in the chronic stage of recovery when more patients are able to fully engage and actively participate.

  PublisherOA PDFDOI

• Neural Dynamics of the Processing of Speech Features: Evidence for a Progression of Features from Acoustic to Sentential Processing

  Journal of Neuroscience · 2025-01-14 · 9 citations

  articleOpen accessSenior author

  When we listen to speech, our brain's neurophysiological responses "track" its acoustic features, but it is less well understood how these auditory responses are enhanced by linguistic content. Here, we recorded magnetoencephalography responses while subjects of both sexes listened to four types of continuous speechlike passages: speech envelope-modulated noise, English-like nonwords, scrambled words, and a narrative passage. Temporal response function (TRF) analysis provides strong neural evidence for the emergent features of speech processing in the cortex, from acoustics to higher-level linguistics, as incremental steps in neural speech processing. Critically, we show a stepwise hierarchical progression of progressively higher-order features over time, reflected in both bottom-up (early) and top-down (late) processing stages. Linguistically driven top-down mechanisms take the form of late N400-like responses, suggesting a central role of predictive coding mechanisms at multiple levels. As expected, the neural processing of lower-level acoustic feature responses is bilateral or right lateralized, with left lateralization emerging only for lexicosemantic features. Finally, our results identify potential neural markers, linguistic-level late responses, derived from TRF components modulated by linguistic content, suggesting that these markers are indicative of speech comprehension rather than mere speech perception.

  PublisherOA PDFDOI

• Neural and Behavioral Changes in Older Adults from Auditory-Cognitive Training

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-04-07 · 3 citations

  preprintOpen accessSenior authorCorresponding

  Speech perception in noisy environments is a common challenge among older adults, even for those with clinically normal hearing. Cognitive decline may be one of the contributing factors, and, as such, auditory-cognitive training may enhance speech perception in these conditions. This study aims to determine if auditory-cognitive training can improve speech-in-noise listening in normal-hearing, older adults using neural and behavioral measures, supplemented with comparisons across younger and older adults. Neural responses were obtained using magnetoencephalography (MEG) while participants listened to long, narrative passages (60 s) under four noise conditions. Neural measures employed reverse correlation using encoding and decoding models, via the temporal response function (TRF) framework, to predict neural responses and reconstruct stimulus features, respectively, with the boosting algorithm to enforce sparsity. Behavioral measures, such as working memory (reading span; RSPAN), speech perception in noise (SPIN), and nonlinguistic auditory stream segregation (stochastic figure-ground; SFG) showed improvement post-training, along with neural and subjective ratings for listening effort. Additionally, auditory-cognitive training may enhance the neural contrast between the selectively attended and unattended stimulus reconstructions, and pre-training SFG performance may predict the extent of this neuroplasticity change. These results provide promising, additional insight into the effects of auditory-cognitive training, both perceptually and neurally.

  PublisherOA PDFDOI

• Neural and Behavioral Changes in Older Adults from Auditory-Cognitive Training

  2025-07-14 · 1 citations

  articleSenior author

  Speech perception in noisy environments is a common challenge among older adults, even for those with clinically normal hearing. Cognitive decline may be one of the contributing factors, and, as such, auditory-cognitive training may enhance speech perception in these conditions. This study aims to determine if auditory-cognitive training can improve speech-in-noise listening in normal-hearing, older adults using neural and behavioral measures, supplemented with comparisons across younger and older adults. Neural responses were obtained using magnetoencephalography (MEG) while participants listened to long, narrative passages (60 s) under four noise conditions. Neural measures employed reverse correlation using encoding and decoding models, via the temporal response function (TRF) framework, to predict neural responses and reconstruct stimulus features, respectively, with the boosting algorithm to enforce sparsity. Behavioral measures, such as working memory (reading span; RSPAN), speech perception in noise (SPIN), and nonlinguistic auditory stream segregation (stochastic figure-ground; SFG) showed improvement post-training, along with neural and subjective ratings for listening effort. Additionally, auditory-cognitive training may enhance the neural contrast between the selectively attended and unattended stimulus reconstructions, and pre-training SFG performance may predict the extent of this neuroplasticity change. These results provide promising, additional insight into the effects of auditory-cognitive training, both perceptually and neurally.

  PublisherDOI

• Neural recordings of continuous speech reveal robust signatures of prediction in second language learners of English

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-11-10

  preprintOpen accessSenior authorCorresponding

  Abstract When listening to speech in their native language, speakers use prior context to anticipate upcoming phonemes, words, and concepts, integrating information at the sublexical, lexical, and sentence level. While it has been suggested that late second language learners do not predict to the same extent as native listeners, adequately evaluating this claim requires measurement of predictions at these multiple levels of representation simultaneously in natural speech. We recorded magnetoencephalography (MEG) responses from native Mandarin and Sinhala speakers listening to continuous narrative English speech. We used multivariate temporal response function (mTRF) analysis to investigate whether second language listeners demonstrate the same markers of prediction in neural data as native English speakers listening to the same stimuli. We demonstrate that late second language listeners exhibit strikingly similar responses to native speakers in sensitivity to phoneme surprisal and entropy with respect to sublexical, lexical, and sentence-level context. The few small response differences we observed appear most likely to arise from specific properties of the native languages, rather than general differences between native and second-language listening. These results provide evidence that late second-language listeners indeed leverage prediction in similar ways as native listeners in understanding continuous speech. This suggests that multivariate analyses of neural data from naturalistic listening may be vital in carefully evaluating the differences and similarities in speech prediction across populations. Significance Statement Much is still unknown about how people listening to a second language predict upcoming words and sounds. Here, we leverage neuroimaging during continuous speech and analyze responses to multiple speech language features in the signal to study the neural encoding of prediction simultaneously at multiple levels of linguistic context. We observe robust encoding of statistical properties tied to prediction at all context levels in second-language learners of English and that responses are strikingly similar between native and second language listeners. Speech language features are encoded similarly in both groups of language learners, with few differences between the native and second language listeners, indicating that second language listeners predict upcoming input similarly to native listeners.

  PublisherOA PDFDOI

• Functional Connectivity Linked to Cognitive Recovery After Minor Stroke

  Annals of Clinical and Translational Neurology · 2025-12-06

  articleOpen access

  OBJECTIVE: Patients with minor stroke exhibit slowed processing speed and generalized alterations in functional connectivity involving frontoparietal cortex (FPC). The pattern of connectivity evolves over time. In this study, we examine the relationship of functional connectivity patterns to cognitive performance, to determine neurophysiological underpinnings of improvement, and whether connectivity profiles may be useful in evaluating and predicting longer-term cognitive outcomes. METHODS: Patients hospitalized with a minor ischemic stroke (NIH Stroke Scale < 10) were neurologically evaluated approximately 1 month following discharge. A battery of neuropsychological tests was administered to assess performance across multiple cognitive domains. Functional connectivity was evaluated using resting state magnetoencephalography (MEG). Repeat evaluations were performed 3-6 months later. The Network Localized Granger Causality framework was used to estimate functional connectivity at each visit. Relationships between functional connectivity and cognitive performance at each visit were assessed using cluster-based permutation tests and mixed effects modeling. RESULTS: Forty-nine patients had available data for both follow-up visits. The average age was 62.4 years; 57% were female; 39% were Black. Mixed effects models indicated significant increases in contralesional frontoparietal beta-band connectivity across visits that corresponded to improved behavioral performance. Early reliance on the contralesional hemisphere was associated with better scores at visit 1, and continued reliance on areas within the ipsilesional hemisphere was associated with poorer performance at visit 2. DISCUSSION: Specific connectivity profiles are associated with better acute and longer-term cognitive performance and may indicate greater potential for recovery. Further studies are needed to determine if patterns are modifiable.

  PublisherDOI

• The Impacts of Two Adaptive Auditory–Cognitive Training Paradigms on Listening to Competing Talkers

  Seminars in Hearing · 2025-05-01 · 1 citations

  reviewOpen access

  Speech intelligibility among competing talkers becomes more difficult with age, even for older adults with clinically normal hearing. Recently, there has been a growing interest in the implementation of auditory-cognitive training to improve speech-in-noise recognition performance, particularly for older adults. In this study, we implemented two levels of cognitive demand in an adaptive auditory-cognitive training program that used a competing-speaker paradigm. Older adults with normal to near-normal hearing thresholds were assessed on training performance (at the individual and group level), self-reported training strategies, and far-transfer learning in a speech-perception-in-noise task. Training performance analysis revealed that some older adults, particularly those in the more demanding training, performed poorly during the auditory-cognitive training itself. Some participants in this group reported disengagement, potentially due to the low level of those individuals' self-reported satisfaction with engaging in challenging tasks in daily life. Despite these challenges, however, both groups generally improved in the far-transfer learning assessment, though there was variation among participants. Our results suggest that too-high levels of cognitive demand within the auditory-cognitive training may limit some aspects of training outcomes for speech perception in noise; however, higher cognitive demand may be beneficial for those who enjoy challenging tasks.

  PublisherOA PDFDOI

• Variational Covariance Smoothing for Dynamic Functional Connectivity Analysis

  2024-10-27

  article
  PublisherDOI

• Neural Dynamics of the Processing of Speech Features: Evidence for a Progression of Features from Acoustic to Sentential Processing

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-02-02

  preprintOpen accessSenior authorCorresponding

  When we listen to speech, our brain's neurophysiological responses "track" its acoustic features, but it is less well understood how these auditory responses are enhanced by linguistic content. Here, we recorded magnetoencephalography (MEG) responses while subjects listened to four types of continuous-speech-like passages: speech-envelope modulated noise, English-like non-words, scrambled words, and a narrative passage. Temporal response function (TRF) analysis provides strong neural evidence for the emergent features of speech processing in cortex, from acoustics to higher-level linguistics, as incremental steps in neural speech processing. Critically, we show a stepwise hierarchical progression of progressively higher order features over time, reflected in both bottom-up (early) and top-down (late) processing stages. Linguistically driven top-down mechanisms take the form of late N400-like responses, suggesting a central role of predictive coding mechanisms at multiple levels. As expected, the neural processing of lower-level acoustic feature responses is bilateral or right lateralized, with left lateralization emerging only for lexical-semantic features. Finally, our results identify potential neural markers, linguistic level late responses, derived from TRF components modulated by linguistic content, suggesting that these markers are indicative of speech comprehension rather than mere speech perception.

  PublisherOA PDFDOI

Recent grants

• NIH Grant R01DC008342

  NIH · $1.2M · 2015

• Neuroplasticity in Auditory Aging

  NIH · $16.6M · 2017–2024

• Auditory Scene Analysis and Temporal Cortical Computations

  NIH · $1.5M · 2015–2022

• NIH Grant R03DC004382

  NIH · $222k · 2003

• NCS-FO: Extracting Functional Cortical Network Dynamics at High Spatiotemporal Resolution

  NSF · $909k · 2017–2023

Frequent coauthors

• Christian Brodbeck

  McMaster University

  38 shared

• Shihab Shamma

  University of Maryland, College Park

  26 shared

• David Poeppel

  New York University

  23 shared

• Alessandro Presacco

  Children's National

  22 shared

• Joshua P. Kulasingham

  Linköping University

  20 shared

• Samira Anderson

  University of Maryland, College Park

  19 shared

• Behtash Babadi

  University of Maryland, College Park

  19 shared

• Alain de Cheveigné

  Laboratoire des Systèmes Perceptifs

  18 shared

Labs

• Simon LabPI

Education

• M.A., Ph.D., Physics

  University of California Santa Barbara

  1990

• A.B., Physics

  Princeton University

  1985