Biology subjects

Stacey, W.

Publications and source records attributed to Stacey, W..

3 recordsLinked to original sources

bioRxiv2026

Visual speech enhances phoneme separability in human superior temporal gyrus

Visual speech, such as lipreading, facilitates spoken word recognition, but the neural mechanisms underlying audiovisual speech perception remain poorly understood. Visual cues may disambiguate fine-grained articulatory features during early perceptual stages or instead integrate with speech at more categorical, phoneme-level stages. To test how speech representations are modulated by visual input, we analyzed intracranial electroencephalography (iEEG) signals recorded from 12 epilepsy patients performing an audiovisual speech perception task. Participants perceived 16 monosyllabic words presented in auditory-only, visual-only, or congruent audiovisual formats. Words were constructed from four onset consonants (/b/, /g/, /m/, /n/) and four rimes (vowel nucleus and any coda consonants). We examined event-related potentials (ERP) in superior temporal gyrus (STG) and trained support vector machine (SVM) classifiers to decode word identity from neural activity at individual electrodes. Discrete and continuous confusion matrices captured complementary changes in classification accuracy and normalized inverse classification loss, a continuous proxy for classifier confidence. Decoding performance was hierarchically evaluated at the word, phoneme, and phonetic feature levels to determine the representations affected by visual speech. Congruent audiovisual speech increased classifier confidence for phoneme-level representations and improved decoding accuracy at both the word and phoneme level, without corresponding effects on phonetic features. Time-resolved analyses further revealed earlier successful decoding for audiovisual than auditory-only speech, with audiovisual enhancement primarily observed for onset consonants rather than rimes. Together, these findings suggest that visual speech sharpens primarily categorical phoneme representations in STG, with accelerated speech processing and improved word recognition emerging as downstream consequences of phoneme-level enhancement.

neuroscience↗

bioRxiv2022

Auditory cortex encodes lipreading information through spatially distributed activity

Watching a speakers face improves speech perception accuracy. These benefits are owed, in part, to implicit lipreading abilities present in the general population. While it is established that lipreading can alter the perception of a heard word, it is unknown how information that is extracted from lipread words is transformed into a neural code that the auditory system can use. One influential, but untested, hypothesis is that visual speech modulates the population coded representations of phonetic and phonemic features in the auditory system. This model is largely supported by data showing that silent lipreading evokes activity in auditory cortex, but these activations could alternatively reflect general effects of arousal or attention, or the encoding of non-linguistic features such as visual timing information. This gap limits our understanding of how vision supports speech perception processes. To test the hypothesis that the auditory system encodes visual speech information, we acquired fMRI data from healthy adults and intracranial recordings from electrodes implanted in patients with epilepsy during auditory and visual speech perception tasks. Across both methods, linear classifiers successfully decoded the identity of silently lipread words using the spatial pattern of auditory cortex responses. Examining the time-course of classification using intracranial recordings, lipread words were classified at significantly earlier time-points relative to heard words, suggesting a predictive mechanism for facilitating speech. These results support a model in which the auditory system combines the joint neural distributions evoked by heard and lipread words to generate a more precise estimate of what was said. Significance StatementWhen we listen to someone speak in a noisy environment, watching their face can help us understand them better, largely due to automatic lipreading abilities. However, it unknown how lipreading information is transformed into a neural code that the auditory system can use. We used fMRI and intracranial recordings in patients to study how the brain processes silently lipread words and found that the auditory system encodes the identity of lipread words through spatially distributed activity. These results suggest that the auditory system combines information from both lipreading and hearing to generate more precise estimates of what is said, potentially by both activating the corresponding representation of the heard word and suppressing incorrect phonemic representations.

neuroscience↗

bioRxiv2018

Using Network Analysis to Localize the Epileptogenic Zone from Invasive EEG Recordings in Intractable Focal Epilepsy

Treatment of medically intractable focal epilepsy (MIFE) by surgical resection of the epileptogenic zone (EZ) is often effective provided the EZ can be reliably identified. Even with the use of invasive recordings, the clinical differentiation between the EZ and normal brain areas can be quite challenging, mainly in patients without MRI detectable lesions. Consequently, despite relatively large brain regions being removed, surgical success rates barely reach 60-65%. Such variable and unfavorable outcomes associated with high morbidity rates are often caused by imprecise and/or inaccurate EZ localization. We developed a localization algorithm that uses network-based data analytics to process invasive EEG recordings. This network algorithm analyzes the centrality signatures of every contact electrode within the recording network and characterizes contacts into susceptible EZ based on the centrality trends over time. The algorithm was tested in a retrospective study that included 42 patients from four epilepsy centers. Our algorithm had higher agreement with EZ regions identified by clinicians for patients with successful surgical outcomes and less agreement for patients with failed outcomes. These findings suggest that network analytics and a network systems perspective of epilepsy may be useful in assisting clinicians in more accurately localizing the EZ.\n\nAUTHOR SUMMARYEpilepsy is a disease that results in abnormal firing patterns in parts of the brain that comprise the epileptogenic network, known as the epileptogenic zone (EZ). Current methods to localize the EZ for surgical treatment often requires observations of hundreds of thousands of EEG data points measured from many electrodes implanted in a patients brain. In this paper, we used network science to show that EZ regions may exhibit specific network signatures before, during and after seizure events. Our algorithm computes the likelihood of each electrode being in the EZ and tends to agree more with clinicians during successful resections and less during failed surgeries. These results suggest that a networked analysis approach to EZ localization may be valuable in a clinical setting.

neuroscience↗