About

Laura Gwilliams is an Assistant Professor of Psychology at Stanford University, with a courtesy appointment in Linguistics. She is also a member of several research institutes including the Wu Tsai Neurosciences Institute, Stanford Data Science, and the Bio-X program. Her research focuses on understanding the neural representations and operations that give rise to speech comprehension in the human brain. She combines insights from neuroscience, linguistics, and machine learning, utilizing recording techniques such as MEG, ECoG, and Neuropixels to investigate neural dynamics at different spatial scales. Her work has significantly contributed to the understanding of speech processing and language comprehension. She has explored how phonetic features are encoded in neural responses, how the brain processes language-specific and shared acoustic-phonetic features, and how hierarchical dynamic coding supports speech comprehension. Her research includes examining neural responses in individuals with language disorders such as aphasia, revealing decreased phonetic processing and mechanisms crucial for successful language understanding. Gwilliams also investigates how the brain encodes auditory word forms and coordinates hierarchical language features during natural speech comprehension, providing insights into the dynamic neural codes that support language processing in the human brain.

Research topics

• Computer Science
• Artificial Intelligence
• Cognitive psychology
• Natural Language Processing
• Medicine
• Psychology
• Neuroscience
• Linguistics
• Cognitive science
• Audiology
• Biology
• Physics

Selected publications

• On the speed of conscious perception: How soon is now?

  2025-09-27

  articleOpen accessSenior author

  Fleming and Michel propose that conscious perception is ‘slow’, with a delay of 350-450ms. But this claim is premature. Here, we will show that the speed of conscious perception remains unresolved. Examining evidence from vision and language research, we will explore how this fundamental question may ultimately be answered, to test the validity of this foundational claim.

  PublisherDOI

• Hierarchical dynamic coding coordinates speech comprehension in the human brain

  Proceedings of the National Academy of Sciences · 2025-10-17 · 14 citations

  articleOpen access1st authorCorresponding

  Speech comprehension involves transforming an acoustic waveform into meaning. To do so, the human brain generates a hierarchy of features that converts the sensory input into increasingly abstract language properties. However, little is known about how rapid incoming sequences of hierarchical features are continuously coordinated. Here, we propose that each language feature is supported by a dynamic neural code, which represents the sequence history of hierarchical features in parallel. To test this "hierarchical dynamic coding" (HDC) hypothesis, we use time-resolved decoding of brain activity to track the construction, maintenance, and update of a comprehensive hierarchy of language features spanning phonetic, word form, lexical-syntactic, syntactic, and semantic representations. For this, we recorded 21 native English participants with magnetoencephalography (MEG), while they listened to two hours of short stories in English. Our analyses reveal three main findings. First, the brain represents and simultaneously maintains a sequence of hierarchical features. Second, the duration of these representations depends on their level in the language hierarchy. Third, each representation is maintained by a dynamic neural code, which evolves at a speed commensurate with its corresponding linguistic level. This HDC preserves the maintenance of information over time while limiting destructive interference between successive features. Overall, HDC reveals how the human brain maintains and updates the continuously unfolding language hierarchy during natural speech comprehension, thereby anchoring linguistic theories to their biological implementations.

  PublisherOA PDFDOI

• Dynamics of auditory word form encoding in human speech cortex

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-05

  preprintOpen access

  When we hear continuous speech, we perceive it as a series of discrete words, despite the lack of clear boundaries in the acoustic signal. The superior temporal gyrus (STG) encodes phonetic elements like consonants and vowels, but how it extracts whole words as perceptual units remains unclear. Using high-density cortical recordings, we investigated how the brain represents auditory word forms-integrating acoustic-phonetic, prosodic, and lexical features-while participants listened to spoken narratives. Our results show that STG neural populations exhibit a distinctive reset in activity at word boundaries, marked by a brief, sharp drop in cortical activity. Between these resets, the STG consistently encodes distinct acoustic-phonetic, prosodic, and lexical information, supporting the integration of phonological features into coherent word forms. Notably, this process tracks the relative elapsed time within each word, independent of its absolute duration, providing a flexible temporal scaffolding for encoding variable word lengths. We observed similar word form dynamics in the deeper layers of a self-supervised artificial speech network, suggesting a potential convergence with computational models. Additionally, in a bistable word perception task, STG responses were aligned with participants' perceived word boundaries on a trial-by-trial basis, further emphasizing the role of dynamic encoding in word recognition. Together, these findings support a new dynamical model of auditory word forms, highlighting their importance as perceptual units for accessing linguistic meaning.

  PublisherOA PDFDOI

• Human cortical dynamics of auditory word form encoding

  Neuron · 2025-11-07 · 5 citations

  articleOpen access

  We perceive continuous speech as a series of discrete words, despite the lack of clear acoustic boundaries. The superior temporal gyrus (STG) encodes phonetic elements like consonants and vowels, but it is unclear how whole words are encoded. Using high-density cortical recordings and spoken narratives, we investigated how the human brain represents auditory word forms. STG activity exhibits a distinctive reset at word boundaries, marked by a sharp drop in cortical activity. Between resets, STG encodes acoustic-phonetic, prosodic, and lexical features, supporting integration of phonological features into coherent word forms. This process tracks the relative elapsed time within words, independent of absolute duration, providing a flexible encoding of variable word lengths. Similar dynamics were found in deeper layers of a self-supervised artificial speech network. Finally, a bistable word perception task revealed trial-by-trial STG responses to perceived word boundaries. Together, these findings support a new dynamical model of auditory word forms.

  PublisherDOI

• Dynamics of Pitch Perception in the Auditory Cortex

  Journal of Neuroscience · 2025-02-05 · 8 citations

  articleOpen accessSenior author

  The ability to perceive pitch allows human listeners to experience music, recognize the identity and emotion conveyed by conversational partners, and make sense of their auditory environment. A pitch percept is formed by weighting different acoustic cues (e.g., signal fundamental frequency and interharmonic spacing) and contextual cues (expectation). How and when such cues are neurally encoded and integrated remains debated. In this study, 28 participants (16 female) listened to tone sequences with different acoustic cues (pure tones, complex missing fundamental tones, and tones with an ambiguous mixture), placed in predictable and less predictable sequences, while magnetoencephalography was recorded. Decoding analyses revealed that pitch was encoded in neural responses to all three tone types in the low-to-mid auditory cortex and sensorimotor cortex bilaterally, with right-hemisphere dominance. The pattern of activity generalized across cue types, offset in time: pitch was neurally encoded earlier for harmonic tones (∼85 ms) than pure tones (∼95 ms). For ambiguous tones, pitch emerged significantly earlier in predictable contexts than in unpredictable. The results suggest that a unified neural representation of pitch emerges by integrating independent pitch cues and that context alters the dynamics of pitch generation when acoustic cues are ambiguous.

  PublisherOA PDFDOI

• Shared and language-specific phonological processing in the human temporal lobe

  Nature · 2025-11-19 · 1 citations

  articleOpen access

  Abstract All spoken languages are produced by the human vocal tract, which defines the limited set of possible speech sounds. Despite this constraint, however, there exists incredible diversity in the world’s 7,000 spoken languages, each of which is learned through extensive experience hearing speech in language-specific contexts 1 . It remains unknown which elements of speech processing in the brain depend on daily language experience and which do not. In this study, we recorded high-density cortical activity from adult participants with diverse language backgrounds as they listened to speech in their native language and an unfamiliar foreign language. We found that, regardless of language experience, both native and foreign languages elicited similar cortical responses in the superior temporal gyrus (STG), associated with shared acoustic–phonetic processing of foundational speech sound features 2,3 , such as vowels and consonants. However, only during native language listening did we observe enhanced neural encoding in the STG for word boundaries, word frequency and language-specific sound sequence statistics. In a separate cohort of bilingual participants, this encoding of word- and sequence-level information appeared for both familiar languages in the same individual and in the same STG neural populations. These results indicate that experience-dependent language processing involves dynamic integration of both shared acoustic–phonetic and language-specific sequence- and word-level information in the STG.

  PublisherDOI

• Measuring Naturalistic Speech Comprehension in Real Time

  2025-11-21

  articleOpen accessSenior author

  Speech comprehension has been described as an effortless and robust process; yet, in real-world contexts, it is common for a listener to misunderstand what was said, or fail to derive meaning entirely. Typically, methods of measuring speech comprehension are applied `post-hoc' - that is, after the comprehension has happened. This approach fails to capture comprehension as it is happening, which has limited the field's understanding of the cognitive processes involved in real-time comprehension. To overcome these challenges, we designed and tested a novel method of measuring real-time speech comprehension during naturalistic listening. We built a slider device that synchronizes with experimental software and provides millisecond read-out. In three experiments, participants listened to audiobook segments while providing continuous comprehension ratings using the slider. To vary comprehension success, we presented speech segments at speed factors 1-5 times faster than normal. We validated the time-resolved slider data against established speech comprehension assessment methods. Overall, our findings validate our novel time-resolved comprehension measure and demonstrate that it is possible to derive an online behavioral measure of real-time speech comprehension. We also confirmed numerous limitations of static post-hoc assessments, including challenges of multi-choice question design, and the confounding of potential effects due to recency bias and comprehension for summarization. The measure proposed here overcomes the constraints of static post-hoc assessments, and can be effectively integrated with neuroimaging techniques, offering a valuable tool for future research on dynamic processes during naturalistic listening.

  PublisherDOI

• Neural Phoneme Processing in Children with and without Dyslexia

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-14

  preprintOpen access

  Abstract This study investigates the neural dynamics of phoneme processing in 7-year-old children with and without dyslexia (25;9 ♂), using EEG recordings collected during continuous speech listening. By applying temporal generalization to phonetic descriptor decoding, we can disentangle whether potential phoneme processing deficits are due to the maintenance of phonemes in verbal short-term memory and/or inferred differences in phonetic processing speed, both of which are thought to be impaired in dyslexia. We investigated whether phonetic processing depends on the phoneme’s position or its lexical competition. Our results reveal two key findings that may help explain the challenges faced by children with dyslexia. First, these children exhibit reduced decoding accuracy for word-onset phonemes, suggesting disruptions in either predictive, word-level anticipatory mechanisms or in the intrinsic rhythmic processing aligned with word boundaries. Second, they exhibit increased decoding accuracy for non-onset phonemes with low lexical competition approximately 400 ms after phoneme onset. This pattern suggests that children with dyslexia retain linguistically less relevant sounds longer in verbal short-term memory and process them more slowly compared to their typical reading peers. Together, these findings suggest that dyslexia is characterized by altered phonetic encoding strategies, specifically inefficient prioritization of relevant phonological information. This work provides new insight into the neural mechanisms underlying phonological deficits and contributes to a deeper understanding of the cognitive basis of dyslexia. Significance statement Dyslexia is associated with difficulties in phonological processing. Investigating EEG during continuous speech listening, we show that children with dyslexia exhibit weaker encoding of word-onset phonemes and prolonged processing of less informative phonemes. These altered encoding strategies suggest inefficient prioritization of linguistic information, offering new insight into the neural basis of dyslexia.

  PublisherOA PDFDOI

• The Text Aphasia Battery (TAB): A Clinically-Grounded Benchmark for Aphasia-Like Deficits in Language Models

  ArXiv.org · 2025-11-25

  preprintOpen accessSenior author

  Large language models (LLMs) have emerged as a candidate "model organism" for human language, offering an unprecedented opportunity to study the computational basis of linguistic disorders like aphasia. However, traditional clinical assessments are ill-suited for LLMs, as they presuppose human-like pragmatic pressures and probe cognitive processes not inherent to artificial architectures. We introduce the Text Aphasia Battery (TAB), a text-only benchmark adapted from the Quick Aphasia Battery (QAB) to assess aphasic-like deficits in LLMs. The TAB comprises four subtests: Connected Text, Word Comprehension, Sentence Comprehension, and Repetition. This paper details the TAB's design, subtests, and scoring criteria. To facilitate large-scale use, we validate an automated evaluation protocol using Gemini 2.5 Flash, which achieves reliability comparable to expert human raters (prevalence-weighted Cohen's kappa = 0.255 for model--consensus agreement vs. 0.286 for human--human agreement). We release TAB as a clinically-grounded, scalable framework for analyzing language deficits in artificial systems.

  PublisherOA PDFDOI

• Speech prosody enhances the neural processing of syntax

  Communications Biology · 2024-06-20 · 17 citations

  articleOpen access

  Human language relies on the correct processing of syntactic information, as it is essential for successful communication between speakers. As an abstract level of language, syntax has often been studied separately from the physical form of the speech signal, thus often masking the interactions that can promote better syntactic processing in the human brain. However, behavioral and neural evidence from adults suggests the idea that prosody and syntax interact, and studies in infants support the notion that prosody assists language learning. Here we analyze a MEG dataset to investigate how acoustic cues, specifically prosody, interact with syntactic representations in the brains of native English speakers. More specifically, to examine whether prosody enhances the cortical encoding of syntactic representations, we decode syntactic phrase boundaries directly from brain activity, and evaluate possible modulations of this decoding by the prosodic boundaries. Our findings demonstrate that the presence of prosodic boundaries improves the neural representation of phrase boundaries, indicating the facilitative role of prosodic cues in processing abstract linguistic features. This work has implications for interactive models of how the brain processes different linguistic features. Future research is needed to establish the neural underpinnings of prosody-syntax interactions in languages with different typological characteristics.

  PublisherOA PDFDOI

Frequent coauthors

• Jean-Rémi King

  Université Paris Sciences et Lettres

  63 shared

• Alec Marantz

  New York University

  38 shared

• David Poeppel

  New York University

  30 shared

• Saskia Haegens

  New York State Psychiatric Institute

  16 shared

• Charles E. Schroeder

  University of Toronto

  12 shared

• Yael M. Cycowicz

  New York State Psychiatric Institute

  12 shared

• Luca Iemi

  Columbia University

  12 shared

• Liina Pylkkänen

  New York University

  11 shared

Labs

• Vice Provost for Student AffairsPI

Awards & honors

• Neuroscience Fellowship Award, Klingenstein Philanthropies (…
• Early Career Award, Whitehall Foundation (2024)
• Glushko Dissertation Prize, Cognitive Science Society (2021)