Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan, Italy.
Centre of Epilepsy Surgery "C. Munari", Department of Neuroscience, Niguarda Hospital, Milan, Italy.
Sci Data. 2020 Apr 28;7(1):127. doi: 10.1038/s41597-020-0467-x.
Precisely localizing the sources of brain activity as recorded by EEG is a fundamental procedure and a major challenge for both research and clinical practice. Even though many methods and algorithms have been proposed, their relative advantages and limitations are still not well established. Moreover, these methods involve tuning multiple parameters, for which no principled way of selection exists yet. These uncertainties are emphasized due to the lack of ground-truth for their validation and testing. Here we present the Localize-MI dataset, which constitutes the first open dataset that comprises EEG recorded electrical activity originating from precisely known locations inside the brain of living humans. High-density EEG was recorded as single-pulse biphasic currents were delivered at intensities ranging from 0.1 to 5 mA through stereotactically implanted electrodes in diverse brain regions during pre-surgical evaluation of patients with drug-resistant epilepsy. The uses of this dataset range from the estimation of in vivo tissue conductivity to the development, validation and testing of forward and inverse solution methods.
精确定位脑电图记录的脑活动源是研究和临床实践的基本程序和主要挑战。尽管已经提出了许多方法和算法,但它们的相对优势和局限性仍未得到很好的确立。此外,这些方法涉及调整多个参数,而对于这些参数,目前还没有确定的选择方法。由于缺乏验证和测试的基准,这些不确定性被强调了。在这里,我们提出了 Localize-MI 数据集,这是第一个包含来自活体人脑内精确已知位置的脑电图记录的电活动的公开数据集。在对耐药性癫痫患者进行术前评估期间,通过立体定向植入的电极,以 0.1 至 5 mA 的强度递送电刺激双相电流,记录高密度脑电图。该数据集的用途包括估计体内组织电导率、开发、验证和测试正、逆解方法。