Predicting human functional maps with neural net modeling.
Predicting human functional maps with neural net modeling.
复制标题
使用神经网络建模预测人体功能图。
DOI：
10.1002/(sici)1097-0193(1999)8:2/3
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发表时间：
1999
影响因子：
4.8
通讯作者：
Tagamets,MA
中科院分区：
文献类型：
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作者：
Horwitz,B;Tagamets,MA
在解释正电子发射断层扫描（PET）和功能性磁共振成像（fMRI）血流动力学信号的基础神经活动方面存在着巨大的困难。这些包括空间和时间分辨率的问题以及与神经元活动相关的问题（即，动作电位）到反映突触活动的血液动力学测量。此外，区域血流动力学测量对应于局部和传入突触活动的混合。为了克服这些困难，我们建议使用大规模神经生物学现实模型，其中各种空间和时间级别的数据可以通过多个学科（包括功能神经成像）进行模拟和交叉验证。延迟匹配到样本视觉任务被用来说明这种方法。Hum.脑映射8：137-142，1999.© 1999 Wiley利斯公司
Formidable difficulties exist in interpreting positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) hemodynamic signals in terms of the underlying neural activity. These include issues of spatial and temporal resolution and problems relating neuronal activity (i.e., action potentials) measured in nonhuman studies by single unit electrodes to hemodynamic measurements reflecting synaptic activity. Also, regional hemodynamic measurements correspond to a mixture of local and afferent synaptic activity. To surmount these difficulties, we propose using large‐scale neurobiologically realistic models in which data at various spatial and temporal levels can be simulated and cross‐validated by multiple disciplines, including functional neuroimaging. A delayed match‐to‐sample visual task is used to illustrate this approach. Hum. Brain Mapping 8:137–142, 1999. © 1999 Wiley‐Liss, Inc.