Dear Colleagues, In collaboration with the journal Frontiers in Computational Neuroscience, we are bringing together a selected group of international experts to contribute to an open-access article collection on: Inter- and Intra-subject Variability in Brain Imaging and Decoding ( https://www.frontiersin.org/research-topics/10801/inter--and-intra-subject-v... ) We welcome you to submit your work in the field of brain imaging and decoding. Manuscripts can be submitted to this Research Topic via either of the following three journals: Frontiers in Neuroscience (Brain Imaging Methods), Frontiers in Computational Neuroscience or Frontiers in Human Neuroscience. ABOUT THIS RESEARCH TOPIC Pervasive and elusive human variability, both across and within individuals, poses a major challenge in interpreting and decoding human brain activity. Differences in brain anatomy and functionality across individuals contribute to the inter-subject variability. Within an individual, changes in neural processing, non-stationarity of brain activities, the variation of neurophysiological mechanisms, and various unknown factors might give rise to the intra-subject variability. Recently, there has been an increasing number of studies that have focused on appreciating rather than ignoring variability. Through the lens of variability, they have led to a better insight into individual differences and cross-session variations, facilitating precision functional brain mapping and decoding based on individual variability and similarity. For instance, the robustness of brain decoding has been improved by transfer learning techniques that are capable of tackling variability in data collected from different subjects across different sessions and days. On the other hand, the applicability of a neurophysiological biometric relies on its manifest inter-subject variability and minimal intra-subject variability. Critical questions, therefore, arise regarding how inter- and intra-subject variability can be observed, analyzed and modeled, what pros and cons researchers might gain from the variability, and how to deal with the variability in brain imaging and decoding. The goal of this Research Topic is to encourage researchers to examine human variability in brain imaging and decoding, with a focus on both advantages and disadvantages of inter- and intra-subject variability in mapping and modeling brain functions. We welcome empirical, theoretical and meta-analytical work and encourage authors to re-examine their datasets through the scopes of human variability rather than averaged observations and overall interpretations. Subtopics of interest include, but are not limited to: • The imaging and characteristics of inter- and intra-subject variability in neuroimaging data. • Evaluating and tracking variability within a single subject and across multiple subjects. • Obtaining neuroscientific findings from leveraging the variability in brain activities. • Enhancing the performance of brain decoding against or through variability. • Generic model learning of brain imaging • Transfer learning and model adaptation based on inter-/intra-subject variability Keywords: variability, neuroimaging, brain mapping, brain decoding, functional brain modeling, brain-computer interface, EEG, MEG, fMRI, fNIRS Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review. GUEST EDITORS Tzyy-Ping Jung, University of California, CA, United States Corey Keller, Stanford University, CA, United States Junhua Li, University of Essex, United Kingdoms Yuan-Pin Lin, National Sun Yat-sen University, Taiwan Masaki Nakanishi, University of California, CA, United States Johanna Wagner, University of California, CA, United States Chun-Shu Wei, Stanford University, CA, United States Wei Wu, Stanford University, CA, United States Yu Zhang, Stanford University, CA, United States IMPORTANT DATES 17th August 2019 – Abstract submission deadline 15th December 2019 – Manuscript submission deadline I look forward to your response. Kind Regards, Chun-Shu Wei Topic Editor, Frontiers in Computational Neuroscience On behalf of the Topic Editors. Chun-Shu Wei, Postdoctoral Fellow, Psychiatry and Behavioral Science, Stanford University cswei.tw@gmail.com | 858.380.8231 | https://sites.google.com/view/cswei/