Neural oscillations facilitate the functioning of the human brain in spatial and temporal dimensions at various frequencies. These oscillations feature a universal frequency architecture that is governed by brain anatomy, ensuring frequency specificity remains invariant across different measurement techniques. Initial magnetic resonance imaging (MRI) methodology constrained functional MRI (fMRI) investigations to a singular frequency range, thereby neglecting the frequency characteristics inherent in blood oxygen level-dependent oscillations. With advancements in MRI technology, it has become feasible to decode intricate brain activities via multi-band frequency analysis (MBFA). During the past decade, the utilization of MBFA in fMRI studies has surged, unveiling frequency-dependent characteristics of spontaneous slow oscillations (SSOs) believed to base dark energy in the brain. There remains a dearth of conclusive insights and hypotheses pertaining to the properties and functionalities of SSOs in distinct bands. We surveyed the SSO MBFA studies during the past 15 years to delineate the attributes of SSOs and enlighten their correlated functions. We further proposed a model to elucidate the hierarchical organization of multi-band SSOs by integrating their function, aimed at bridging theoretical gaps and guiding future MBFA research endeavors.
Integrative neurocybernetic modeling in the era of large-scale neuroscience
Champalimaud Centre for the Unknown（Champalimaud 未知中心）；Janelia Research Campus（Janelia 研究campus）；Harvard University（哈佛大学）；Yale University（哥伦比亚大学）；École Polytechnique Fédérale de Lausanne (EPFL)（瑞士联邦理工学院）；RyvivyR Inc（RyvivyR 公司）
Non-invasive biomarkers of fetal brain development reflecting prenatal stress: an integrative multi-scale multi-species perspective on data collection and analysis
Triple Configuration of Brain Networks Based on Recurrent Neural Networks: The Synergistic Effects of Exogenous Stimuli, Task Demands, and Spontaneous Activity
School of Future Technology, University of Chinese Academy of Sciences（中国科学院大学未来技术学院）
Emergent complexity and rhythms in evoked and spontaneous dynamics of human whole-brain models after tuning through analysis tools
Univ. of Milan（米兰大学）；Università Campus Bio-Medico di Roma（罗马生物医学大学）；Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma（意大利国家核物理研究所罗马分部）；Center for Data Science, New York University（纽约大学数据科学中心）；Institute for Advanced Simulation (IAS-6), Jülich Research Centre（于利希研究中心高级模拟研究所（IAS-6））
EEG-to-fMRI synthesis of task-evoked and spontaneous brain activity: addressing issues of statistical significance and generalizability
Institute for Systems and Robotics – Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Portugal（里斯本系统与机器人研究所及生物工程系，里斯本技术学院，里斯本大学，葡萄牙）；Electrical and Computer Engineering Department, Carnegie Mellon University（电气与计算机工程系，卡内基梅隆大学）
Adversarial dictionary learning for a robust analysis and modelling of spontaneous neuronal activity
University of Crete（克里特大学）；Foundation for Research and Technology Hellas（希腊研究与技术基金会）；Brigham and Women’s Hospital（布莱根妇女医院）；Harvard Medical School（哈佛医学院）；Boston VA Research Institute（波士顿退伍军人事务研究所）；Jamaica Plain Veterans Administration Hospital（牙买加平原退伍军人管理局医院）
Update on the multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs: auditory, sensory and high-frequency sensory evoked potentials
Multi-Scale Graph Theoretical Analysis of Resting-State fMRI for Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Healthy Controls
University of Bojnord（博季努尔德大学）；Munster Technological University（芒斯特理工大学）
