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.

摘要： 识别声音的能力是人类听觉的一项复杂的壮举。对于听者来说，大脑能够 从高度可变的声音输入中无缝提取复杂的语言和非语言线索。 神经影像学研究提出听觉皮层专门负责声音感知的区域， 包括颞上回（STG）和颞上沟（STS），简称“颞声” 功能性神经影像学研究还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，同一物种的发声和自然声音，进一步表明 听觉皮层对声音声刺激的专门化。目前尚不清楚这些地区是否表现出 语音的真正选择性，或者更一般地用于处理复杂的频谱时间特征 听觉刺激，例如声音。神经影像学已经部分描述了语音感知网络 研究并表明颞发声区表现出与额下回和中央前回的连通性， 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，并且 主要集中于表征言语感知和基础的额颞叶白质通路 生产。拟议的研究旨在表征对声音的局部电生理反应 颞部语音区域并将描述语音的额颞叶结构连接 感知网络。我将利用神经群体的颅内脑电图 (iEEG) 对 15 名接受癫痫手术的患者参与者进行人类听觉皮层评估，以检查 声音的神经表征。当参与者聆听已发布的声音时，将获取神经录音 针对 iEEG 研究优化的定位器刺激集，以及来自 模仿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)。将检查声音选择性听觉皮层的额颞叶连接 在所有使用语音定位器的患者中使用临床获得的弥散张量成像 (DTI) 的患者 日期（n=11）并包含在本提案中（n=15）。连接性分析将揭示额叶皮层区域 展示了沿着 STG 和 STS 与神经元群的连接性，具有最大的语音选择性 回应。该提案将共同利用与局部皮质 iEEG 相结合的多模式数据集 生理时间尺度的录音和 DTI 结构连接分析，以严格检查声音 选择性听觉皮层。