Computational Neuroscience of Language Processing in the Human Brain
Purpose
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.
Conditions
- Language
- Epilepsy
Eligibility
- Eligible Ages
- Between 18 Years and 85 Years
- Eligible Genders
- All
- Accepts Healthy Volunteers
- No
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
Study Design
- Phase
- N/A
- Study Type
- Interventional
- Allocation
- N/A
- Intervention Model
- Single Group Assignment
- Primary Purpose
- Basic Science
- Masking
- None (Open Label)
Arm Groups
| Arm | Description | Assigned Intervention |
|---|---|---|
|
Other Epileptic participants undergoing intracranial monitoring |
Patients with pharmaco-resistant epilepsy undergoing intracranial monitoring involving the left cerebral hemisphere. |
|
Recruiting Locations
Boston, Massachusetts 02114
More Details
- Status
- Recruiting
- Sponsor
- Massachusetts General Hospital
Detailed 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.