[Comp-neuro] [journals] CfP: Special Issue on Inter- and Intra-subject Variability in Brain Imaging and Decoding

Chun-Shu Wei cswei.tw at gmail.com
Wed Jul 17 00:57:08 CEST 2019


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-variability-in-brain-imaging-and-decoding
)

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 at gmail.com | 858.380.8231 | https://sites.google.com/view/cswei/
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