A growing number of papers have pointed out the relationship between aggressive resection of gliomas and survival prognosis. For maximum resection, the current concept of surgical decision-making is in “information-guided surgery” using multimodal intraoperative information. With this, anatomical information from intraoperative magnetic resonance imaging (MRI) and navigation, functional information from brain mapping and monitoring, and histopathological information must all be taken into account in the new perspective for innovative minimally invasive surgical treatment of glioma. Intraoperative neurofunctional information such as neurophysiological functional monitoring takes the most important part in the process to acquire objective visual data during tumor removal and to integrate these findings as digitized data for intraoperative surgical decision-making. Moreover, the analysis of qualitative data and threshold-setting for quantitative data raise difficult issues in the interpretation and processing of each data type, such as determination of motor evoked potential (MEP) decline, underestimation in tractography, and judgments of patient response for neurofunctional mapping and monitoring during awake craniotomy. Neurofunctional diagnosis of false-positives in these situations may affect the extent of resection, while false-negatives influence intra- and postoperative complication rates. Additionally, even though the various intraoperative visualized data from multiple sources contribute significantly to the reliability of surgical decisions when the information is integrated and provided, it is not uncommon for individual pieces of information to convey opposing suggestions. Such conflicting pieces of information facilitate higher-order decision-making that is dependent on the policies of the facility and the priorities of the patient, as well as the availability of the histopathological characteristics from resected tissue.