Intracranial Electrophysiology & Anatomical Connectivity of Voice-Selective Auditory Cortex
Intracranial Electrophysiology & Anatomical Connectivity of Voice-Selective Auditory Cortex
批准号:
10747659
负责人:
Jasmine Hect
金额:
$5.0万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-01 至 2027-06-30
关键词:
AcousticsAnatomyAnteriorAreaAuditory areaBrainCharacteristicsChildhoodClassificationClinicalCodeCommunicationCommunication impairmentComplexCuesDataDedicationsDevelopmentDiffusion Magnetic Resonance ImagingDimensionsDistantElectroencephalographyElectrophysiology (science)EmotionsEngineeringEpilepsyEvaluationExhibitsFamilyFunctional Magnetic Resonance ImagingGenderHumanInferior frontal gyrusLinguisticsMeasuresMentorsModelingMonitorNeuronsNoiseOperative Surgical ProceduresParticipantPathway interactionsPatientsPatternPerceptionPhysiologicalPopulationPrecentral gyrusPrimatesProcessProductionPropertyPsycholinguisticsPublishingResearchResearch TrainingScientistSensory DisordersSpeech PerceptionStimulusStructure of superior temporal sulcusSuperior temporal gyrusTemporal LobeTestingTrainingVoiceWorkauditory stimulusblood oxygenation level dependent responsefrontal lobeinterestmultidisciplinarymultimodal datamultimodal neuroimagingmultimodalityneuralneural networkneuroimagingneurophysiologyneurosurgerynonhuman primatenovelnovel therapeuticsrecruitresponsesocial communicationsoundstructural imagingsupport networktheoriestractographytraining opportunityverbalvocalizationvoice recognitionwhite matter
中文摘要
ABTRACT:
英文摘要
ABTRACT:
The ability to recognize voice is an intricate feat of human audition. For the listener, the brain is able to
seamlessly extract complex linguistic and non-linguistic cues from highly variable vocal acoustic input.
Neuroimaging studies have proposed specialized regions of auditory cortex dedicated to voice perception,
including superior temporal gyrus (STG) and superior temporal sulcus (STS), referred to as “temporal voice
areas”. Functional neuroimaging studies also demonstrate these areas respond most strongly to vocalizations
of the same-species compared to other primate vocalizations and natural sounds, further suggesting
specialization of auditory cortex for vocal acoustic stimuli. It remains unknown if these regions demonstrate
true selectivity for voice, or more generally function to process the spectrotemporal features of complex
auditory stimuli, such as voice. The voice perception network has been partially described by neuroimaging
studies and suggests temporal voice areas exhibit connectivity to inferior frontal gyrus and precentral gyrus,
however these studies are limited in their ability to characterize voice areas at physiologic timescales and have
largely focused on characterizing frontotemporal white matter pathways underlying speech perception and
production. The proposed research aims to characterize local electrophysiologic responses to voice in
temporal voice areas and will describe the frontotemporal structural connectivity of the voice
perception network. I will leverage intracranial electroencephalography (iEEG) from neural populations
across human auditory cortex in 15 patient-participants undergoing epilepsy surgery evaluation to examine the
neural representation of voice. Neural recordings will be acquired while participants listen to a published Voice
Localizer stimulus set optimized for iEEG research, as well as an engineered acoustic stimulus set from
modulated noise that mimick the spectrotemporal features of voice and other natural sounds, called Gaussian
Sound Patterns (GSPs). Frontotemporal connectivity of voice-selective auditory cortex will be examined across
patients using clinically-acquired diffusion tensor imaging (DTI) in all patients with Voice Localizer recruited to
date (n=11) and included in this proposal (n=15). Connectivity analyses will reveal regions of frontal cortex
demonstrating connectivity to neuronal populations along STG and STS with the greatest voice-selective
responses. Together this proposal will leverage a multimodal dataset that marries local cortical iEEG
recordings at physiologic timescales and DTI structural connectivity analysis to critically examine voice
selective auditory cortex.
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