NEUROMAGNETIC INVESTIGATION OF ADULTS WITH AUTISM

自闭症是一种毁灭性的发育障碍， 大约是千分之一虽然在基因上 确定，具体异常仍有待确定， 临床表现足够分散，以暗示病理学 多重神经系统这种综合症的核心是社交能力受损 互动，严格限制的兴趣范围，以及异常 注意力（hyperattentiveness）和感觉（sensation）（通常是hyper-attentiveness） 反应性）。我们建议利用脑磁图（MEG） 感觉诱发场（EF）数据、EEG诱发电位（EP）数据，以及 MRI解剖学数据，专门解决早期皮质处理问题 的感官信息。我们将研究1）30个高功能 (IQ>50）自闭症成年人，2）30名智商和年龄匹配的FraX患者，3） 30名年龄匹配的MR受试者和4）30名年龄匹配的正常成人。 我们将具体：1）使用MEG和EEG，我们将量化 初级听觉和躯体感觉皮层对刺激的反应性 2）通过定位和量化非常高的 频率（VHF）MEG活动（600 Hz），从主要的躯体- 我们将直接测量皮层GABA能 抑制性神经元活动，我们假设这将是 缺乏自闭症受试者（并与皮质过度相关， 反应性）; 3）使用基于MEG听觉EF的拟合优度 我们将量化自闭症受试者的能力， 注意力从一个半球到另一个半球在双耳听觉 oddball任务; 4）使用100毫秒潜伏期的幅度 听觉EF（称为M100）作为听觉刺激间的函数 间隔（151），我们将计算τ，衰变的时间常数 回声记忆的痕迹，产生于赫施尔脑回我们 假设这将在自闭症患者中延长，相对于 正常、Fra-X或MR组; 5）使用基于EEG EP的度量 称为失配负波（MMN），我们假设自闭症 受试者将表现出明显的前注意力， 自动皮层特征检测过程; 6）使用MEG EF 在音调期间听觉皮层MEG α抑制的度量 记忆任务，我们假设自闭症受试者将证明， 比正常人更大的α抑制的证据，支持 增强的短期听觉记忆存储、扫描和 检索; 7）使用大脑的高分辨率MR图像，我们将 将MEG EF源与特定皮质区域相关联，以确定 基于MEG和EEG的功能异常与 观察到产生这些信号的皮层存在解剖缺陷。

Autism is a devastating developmental disorder with an incidence of approximately I in 1,000 live births. While strongly genetically determined, specific abnormalities remain to be determined, and the clinical picture is sufficiently diffuse to implicate pathology in multiple neural systems. Central to the syndrome is impaired social interaction, a severely restricted range of interests, and abnormalities of attention (hyper-attentiveness) and sensation (usually hyper- reactivity). We propose to utilize magnetoencephalographic (MEG) sensory evoked field (EF) data, EEG evoked potential (EP) data, and MRI anatomical data to specifically address early cortical processing of sensory information. We will study 1) 30 high functioning (IQ>50) autistic adults, 2) 30 IQ and age matched FraX patients, 3) 30 age matched MR subjects, and 4) 30 age matched normal adults. We will specifically: 1)Using MEG and EEG, we will quantify reactivity of primary auditory and somatosensory cortex to stimuli of varying intensity; 2) By localizing and quantifying very high frequency (VHF) MEG activity (600 Hz) from primary somato- sensory cortex we will directly measure cortical GABA-ergic inhibitory interneurone activity, which we hypothesize will be deficient in autistic subjects (and correlated with cortical hyper- reactivity); 3)Using an MEG auditory EF based goodness of fit metric, we will quantify the ability or autistic subjects to shift attention from one hemisphere to the other during a binaural auditory oddball task; 4) Using the amplitude of the 100 msec latency auditory EF (termed M100) as a function of auditory interstimulus interval (151) we will calculate tau, the time constant of the decay of the echoic memory trace, generated in Heschl's gyri. We hypothesize this will be prolonged in autistic subjects, relative to normals, Fra-X or MR groups; 5) Using the EEG EP based metric termed mismatch negativity (MMN) we hypothesize that autistic subjects will demonstrate evidence of an accentuated pre-attentive, automatic cortical feature detection processes; 6) Using an MEG EF metric of auditory cortex MEG alpha suppression during a tonal memory task, we hypothesize that autistic subjects will demonstrate evidence of greater alpha suppression than normals, supporting enhanced short term auditory memory storage, scanning and retrieval; 7) Using high resolution MR images of the brain we will relate MEG EF sources to specific cortical areas to determined if MEG and EEG based functional abnormalities are related to observed anatomical deficits in the cortex generating those signals.