Computational Neuroscience of Language Processing in the Human Brain

Epilepsy Clinical Trial

Official title:

Computational Neuroscience of Language Processing in the Human Brain

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05222594
• Other study ID #: 2020P001989
• Status: Recruiting
• Phase: N/A
• Start date: April 2, 2021
• Est. completion date: March 31, 2026

Study information

• Verified date: February 2024
• Source: Massachusetts General Hospital
• Contact: Evelina Fedorenko, PhD
• Phone: 617-258-0670
• Email: evelina9[@]mit.edu
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Language is a signature human cognitive skill, but the precise computations that support language understanding remain unknown. This study aims to combine high-quality human neural data obtained through intracranial recordings with advances in computational modeling of human cognition to shed light on the construction and understanding of speech.

Description:

The neural architecture of language is the foundation for the highest form of human interaction. Prior work has identified a network of frontal and temporal brain areas that selectively support language processing, but the precise computations that underlie our ability to extract meaning from sequences of words have remained unknown. The standard approaches in human cognitive neuroscience lack the spatial and temporal resolution necessary for precise comparisons to computational models. To bridge this gap in knowledge, neural responses to language stimuli will be collected from epileptic patients undergoing intracranial monitoring. Overall, these data will be used to identify cortical maps of different linguistic manipulations and to better understand properties of the human language network.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 40
• Est. completion date: March 31, 2026
• Est. primary completion date: March 31, 2026
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 85 Years

Eligibility

Inclusion Criteria:

• clinical indications to proceed with intracranial monitoring involving the left cerebral hemisphere, as determined by a multidisciplinary epilepsy surgery team
• the ability to comply with test directions and provide informed consent
• between ages 18 - 85

Exclusion Criteria:

• inability to understand or perform the task outlined in the protocol, or who are unwilling or unable to participate

Related Conditions & MeSH terms

• Epilepsy
• Language

Intervention

Other:
• Behavioral tasks during intracranial monitoring
Participants will listen to sentences and stories while neural data are recorded through electrodes placed for clinical purposes.

Locations

Country	Name	City	State
United States	Massachusetts General Hospital	Boston	Massachusetts

Sponsors (2)

Lead Sponsor	Collaborator
Massachusetts General Hospital	Massachusetts Institute of Technology

Country where clinical trial is conducted

United States, 

References & Publications (14)

Blank I, Balewski Z, Mahowald K, Fedorenko E. Syntactic processing is distributed across the language system. Neuroimage. 2016 Feb 15;127:307-323. doi: 10.1016/j.neuroimage.2015.11.069. Epub 2015 Dec 5. — View Citation

Blank IA, Fedorenko E. No evidence for differences among language regions in their temporal receptive windows. Neuroimage. 2020 Oct 1;219:116925. doi: 10.1016/j.neuroimage.2020.116925. Epub 2020 May 11. — View Citation

Fedorenko E, Behr MK, Kanwisher N. Functional specificity for high-level linguistic processing in the human brain. Proc Natl Acad Sci U S A. 2011 Sep 27;108(39):16428-33. doi: 10.1073/pnas.1112937108. Epub 2011 Sep 1. — View Citation

Fedorenko E, Blank IA. Broca's Area Is Not a Natural Kind. Trends Cogn Sci. 2020 Apr;24(4):270-284. doi: 10.1016/j.tics.2020.01.001. Epub 2020 Feb 20. — View Citation

Fedorenko E, Duncan J, Kanwisher N. Language-selective and domain-general regions lie side by side within Broca's area. Curr Biol. 2012 Nov 6;22(21):2059-62. doi: 10.1016/j.cub.2012.09.011. Epub 2012 Oct 11. — View Citation

Fedorenko E, Hsieh PJ, Nieto-Castanon A, Whitfield-Gabrieli S, Kanwisher N. New method for fMRI investigations of language: defining ROIs functionally in individual subjects. J Neurophysiol. 2010 Aug;104(2):1177-94. doi: 10.1152/jn.00032.2010. Epub 2010 Apr 21. — View Citation

Fedorenko E, Nieto-Castanon A, Kanwisher N. Lexical and syntactic representations in the brain: an fMRI investigation with multi-voxel pattern analyses. Neuropsychologia. 2012 Mar;50(4):499-513. doi: 10.1016/j.neuropsychologia.2011.09.014. Epub 2011 Sep 17. — View Citation

Fedorenko E, Scott TL, Brunner P, Coon WG, Pritchett B, Schalk G, Kanwisher N. Neural correlate of the construction of sentence meaning. Proc Natl Acad Sci U S A. 2016 Oct 11;113(41):E6256-E6262. doi: 10.1073/pnas.1612132113. Epub 2016 Sep 26. — View Citation

Mollica F, Siegelman M, Diachek E, Piantadosi ST, Mineroff Z, Futrell R, Kean H, Qian P, Fedorenko E. Composition is the Core Driver of the Language-selective Network. Neurobiol Lang (Camb). 2020 Mar 1;1(1):104-134. doi: 10.1162/nol_a_00005. eCollection 2020. — View Citation

Nieto-Castanon A, Fedorenko E. Subject-specific functional localizers increase sensitivity and functional resolution of multi-subject analyses. Neuroimage. 2012 Nov 15;63(3):1646-69. doi: 10.1016/j.neuroimage.2012.06.065. Epub 2012 Jul 8. — View Citation

Norman-Haignere S, Kanwisher NG, McDermott JH. Distinct Cortical Pathways for Music and Speech Revealed by Hypothesis-Free Voxel Decomposition. Neuron. 2015 Dec 16;88(6):1281-1296. doi: 10.1016/j.neuron.2015.11.035. — View Citation

Pereira F, Lou B, Pritchett B, Ritter S, Gershman SJ, Kanwisher N, Botvinick M, Fedorenko E. Toward a universal decoder of linguistic meaning from brain activation. Nat Commun. 2018 Mar 6;9(1):963. doi: 10.1038/s41467-018-03068-4. — View Citation

Shain C, Blank IA, van Schijndel M, Schuler W, Fedorenko E. fMRI reveals language-specific predictive coding during naturalistic sentence comprehension. Neuropsychologia. 2020 Feb 17;138:107307. doi: 10.1016/j.neuropsychologia.2019.107307. Epub 2019 Dec 24. — View Citation

Siegelman M, Blank IA, Mineroff Z, Fedorenko E. An Attempt to Conceptually Replicate the Dissociation between Syntax and Semantics during Sentence Comprehension. Neuroscience. 2019 Aug 10;413:219-229. doi: 10.1016/j.neuroscience.2019.06.003. Epub 2019 Jun 11. — View Citation

* Note: There are 14 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Cortical maps of linguistic responses	By using sEEG intracranial recordings of the brain, EEG power in frequency bands will reflect cortical maps of responses to different linguistic manipulations, informing the functional organization of the human language system. Power is measured in arbitrary units; higher power reflects greater activity at the investigated frequency.	Throughout intracranial monitoring period, up to approximately 10 days
Primary	Neural time-courses during naturalistic language comprehension	Time-courses of neural response to language across diverse parts of the language network. These data will be used to predict across-time variation in response strength from the properties of linguistic input.	Throughout intracranial monitoring period, up to approximately 10 days
Primary	Brain scores for diverse artificial neural network (ANN) language models	Human neural data will be compared to ANN language models to test how well these models predict human responses to language and why. There are no minimum or maximum scores. Higher values mean better model predictivity (i.e., a better match between model representations and neural responses).	Throughout intracranial monitoring period, up to approximately 10 days