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‘Neural dynamics of phoneme sequences reveal position-invariant code for content and order’ with Laura Gwilliams

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Manage episode 364677399 series 2863266
Content provided by Stephen M. Wilson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Stephen M. Wilson or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode, I talk with Laura Gwilliams, soon-to-be Assistant Professor of Psychology, Neuroscience, and Data Science at Stanford University, about her recent paper ‘Neural dynamics of phoneme sequences reveal position-invariant code for content and order’.

Gwilliams lab website

Gwilliams L, King JR, Marantz A, Poeppel D. Neural dynamics of phoneme sequences reveal position-invariant code for content and order. Nat Commun 2022; 13: 6606. [doi]

  continue reading

33 episodes

Artwork
iconShare
 
Manage episode 364677399 series 2863266
Content provided by Stephen M. Wilson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Stephen M. Wilson or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode, I talk with Laura Gwilliams, soon-to-be Assistant Professor of Psychology, Neuroscience, and Data Science at Stanford University, about her recent paper ‘Neural dynamics of phoneme sequences reveal position-invariant code for content and order’.

Gwilliams lab website

Gwilliams L, King JR, Marantz A, Poeppel D. Neural dynamics of phoneme sequences reveal position-invariant code for content and order. Nat Commun 2022; 13: 6606. [doi]

  continue reading

33 episodes

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