iiinova — where your digital self keeps evolving

Cogan Lab @coganlab.bsky.social · 17/08/2026

Two new papers from the lab in Nature Human Behaviour and Nature Communications, spanning the neural mechanisms of speech production and new approaches to speech neurotechnology! 🧠 Speech plans → fluent motor sequences 🗣️ Speech BCIs across people Links below 👇 @dukebrain.bsky.social 1/3

Graphic announcing two new Cogan Lab papers. The Nature Human Behaviour paper asks how the brain turns a speech plan into fluent movement, illustrated as planning → articulation → monitoring. The Nature Communications paper asks whether a speech BCI can learn from other people, illustrated by neural activity from two individuals converging on a shared latent representation.

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Cogan Lab @coganlab.bsky.social · 26/08/2025

From Cogan Lab Journal Club with @zspald.bsky.social these decomposition acronyms are getting out of hand!

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Cogan Lab @coganlab.bsky.social · 25/08/2025

We’re happy to present @zspald.bsky.social 's work on shared neural representations of speech production across individuals! We find that patient-specific data can be aligned to a shared space that preserves speech information, enabling cross-patient speech BCIs. www.biorxiv.org/content/10.1...

Aligned neural space for speech production allows for improved decoding in micro-ECOG patients for BCI

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Cogan Lab @coganlab.bsky.social · 08/10/2024

In addition to sequences of discrete phonemes, we show that the motor cortex also tracks the transitions between phonemes (phonotactics), suggesting that speech execution combines both discrete and continuous articulatory properties. 8/10

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Cogan Lab @coganlab.bsky.social · 08/10/2024

During speech execution, we show evidence for motor sequencing by extracting sequential patterns of phonemes and find that sequencing only occurs in execution regions during speech production. 7/10

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Cogan Lab @coganlab.bsky.social · 08/10/2024

Using neural decoding models, we characterize the hierarchical relationship between syllables and phonemes and demonstrate that this relationship is temporally distinct in planning vs. execution. 6/10

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Cogan Lab @coganlab.bsky.social · 08/10/2024

Using high-resolution cortical recordings, we also show that this temporally distinct syllabic activation follows an anatomical spatial gradient from pars opercularis to pre/motor cortex that transitions in time from planning to articulation. 5/10

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Cogan Lab @coganlab.bsky.social · 08/10/2024

We identified distinct coding for syllable frames and found that this code first occurred during planning in the left-hemispheric pre-frontal cortex and was sustained during speech motor execution. 4/10

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Cogan Lab @coganlab.bsky.social · 08/10/2024

We organized speech neural activations in the high-gamma band (HG) into distinct anatomical networks that were specific to planning and execution (articulation and monitoring). These networks were active sequentially prior to and during speech production. 3/10

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Cogan Lab @coganlab.bsky.social · 08/10/2024

We performed intracranial recordings on 52 patients while they articulated pseudowords in a delayed speech repetition task. Constructed pseudowords were either monosyllabic or disyllabic and contained a fixed set of phonemes at each position within the syllable frame. 2/10

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Cogan Lab @coganlab.bsky.social · 04/10/2024

Coming to Chicago for SfN? Interested in intracranial EEG and speech and cognition? Come see the lab’s posters!

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Cogan Lab @coganlab.bsky.social · 09/11/2023

Coming to SfN 2023? Check out posters from the Cogan Lab on studying speech using intracranial neural recordings!

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Cogan Lab @coganlab.bsky.social · 06/11/2023

µECoG revealed temporal sequencing of phonemes in speech motor cortex. A non-linear recurrent model that captured the specific spatio-temporal neural patterns resulted in better decoding performance than linear techniques.

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Cogan Lab @coganlab.bsky.social · 06/11/2023

Higher spatial resolution was also required to achieve better decoding as more unique phonemes were included in the analysis.

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Cogan Lab @coganlab.bsky.social · 06/11/2023

We decoded spoken phonemes from micro-scale HG activations and found that µECoG achieved up to 57% accuracy in predicting spoken phonemes with total spoken duration of <2.5 minutes. This accurate decoding outperformed standard IEEG by 35%.

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Cogan Lab @coganlab.bsky.social · 06/11/2023

µECoG captured fine-scale spatio-temporal patterns in SMC. These spatio-temporal patterns revealed separation of both speech articulators and individual phonemes. This clustering was dependent on high-resolution sampling.

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Cogan Lab @coganlab.bsky.social · 06/11/2023

Speech neural activations in the high-gamma band (HG) were spatially specific, and our high-definition recordings demonstrated spatially discriminant neural signals at < 2 mm spacing. This micro-scale neural activations achieved 48% higher SNR compared to macro-ECoG and SEEG.

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Cogan Lab @coganlab.bsky.social · 06/11/2023

high-density ECoG arrays (4 mm). 4 patients performed a speech repetition task during their awake neurosurgery.

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Cogan Lab @coganlab.bsky.social · 16/10/2023

Do you have (or about to have) a PhD and are you interested in speech and intracranial recordings (seeg, ecog, and micro-ecog)? The Cogan Lab at Duke is looking for a postdoc! International applicants are welcome. Join us! coganlab.org/postdoc23

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Cogan Lab @coganlab.bsky.social · 25/09/2023

Some good news: our R01 has been funded! We will study the interactions between speech production and vWM using intracranial recordings. A big thank you to the whole lab and all of our collaborators. @dukebrain.bsky.social

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