Intracranial Electrophysiology & Anatomical Connectivity of Voice-Selective Auditory Cortex

颅内电生理学

• 批准号: 10747659
• 负责人: Jasmine Hect
• 金额: $ 5万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10747659
• 关键词: Acoustics; Anatomy; Anterior; Area; Auditory area; Brain; Characteristics; Childhood; Classification; Clinical; Code; Communication; Communication impairment; Complex; Cues; Data; Dedications; Development; Diffusion Magnetic Resonance Imaging; Dimensions; Distant; Electroencephalography; Electrophysiology (science); Emotions; Engineering; Epilepsy; Evaluation; Exhibits; Family; Functional Magnetic Resonance Imaging; Gender; Human; Inferior frontal gyrus; Linguistics; Measures; Mentors; Modeling; Monitor; Neurons; Noise; Operative Surgical Procedures; Participant; Pathway interactions; Patients; Pattern; Perception; Physiological; Population; Precentral gyrus; Primates; Process; Production; Property; Psycholinguistics; Publishing; Research; Research Training; Scientist; Sensory Disorders; Speech Perception; Stimulus; Structure of superior temporal sulcus; Superior temporal gyrus; Temporal Lobe; Testing; Training; Voice; Work; auditory stimulus; blood oxygenation level dependent response; frontal lobe; interest; multidisciplinary; multimodal data; multimodal neuroimaging; multimodality; neural; neural network; neuroimaging; neurophysiology; neurosurgery; nonhuman primate; novel; novel therapeutics; recruit; response; social communication; sound; structural imaging; support network; theories; tractography; training opportunity; verbal; vocalization; voice recognition; white matter

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.

提取物： 识别声音的能力是人类听觉的一项复杂技艺。对于听者来说，大脑能够 无缝地从高度可变的语音声学输入中提取复杂的语言和非语言线索。 神经影像学研究已经提出了专门用于声音感知的听觉皮层区域， 包括上级颞回（STG）和上级颞沟（STS），称为“颞音 地区”。功能性神经影像学研究也表明这些区域对发声反应最强烈 与其他灵长类动物的发声和自然声音相比， 听觉皮层对声音刺激的专门化。目前尚不清楚这些地区是否证明了 语音的真正选择性，或者更一般地说，用于处理复杂语音的频谱时间特征， 听觉刺激，如声音。语音感知网络已经部分地被神经影像学描述 研究表明，颞语音区与额下回和中央前回有连接， 然而，这些研究在生理时间尺度上表征声音区域的能力有限， 主要集中在表征额颞白色物质通路的语音感知和 生产这项研究的目的是描述局部电生理反应的声音， 时间语音区域并将描述语音的额颞结构连接性 感知网络我将利用神经群体的颅内脑电图（iEEG） 在15名接受癫痫手术评估的患者参与者中， 声音的神经表征。当参与者听一个公开的声音时，将获得神经记录。 针对iEEG研究优化的定位器刺激集，以及来自 模拟语音和其他自然声音的频谱时间特征的调制噪声，称为高斯噪声 声音模式（GSP）。声音选择性听觉皮层的额颞连接将被检查， 在招募的所有使用Voice Localizer的患者中使用临床获得的扩散张量成像（DTI）的患者， 日期（n=11），并纳入本提案（n=15）。连通性分析将揭示额叶皮层的区域 证明了与沿着STG和STS的神经元群体的连接性， 应答总之，该提案将利用多模态数据集，该数据集结合了局部皮层iEEG 在生理时间尺度上的录音和DTI结构连接分析，以批判性地检查声音 选择性听觉皮层