Research

Nan has broad research interests, spanning from theoretical foundations and algorithm development to practical applications in the biomedical field. Nan's primary research interest lies at the intersection of data science and neuroscience, where she harnesses advanced modeling and data-driven approaches to decode spatiotemporal dynamic processes in the brain. She mainly analyzes BOLD signals measured by fMRI but draws insights from underlying neurophysiological correlates to better understand brain functions. Her second line of work focuses on developing algorithms for the 3D reconstruction of symmetric virus particles, essential for understanding their functions. Her Ph.D. thesis delved into statistical modeling and inferences within biological datasets. She has been developing advanced theoretical approaches, computational algorithms, and analysis to investigate two distinct biological phenomena, (1) functional brain dynamics measured by functional neuroimaging data, and (2) heterogeneous virus particles involving 3D image reconstruction using cryo-EM images. Below are the main research themes and publications Nan has developed:

Modeling and inferences in causal interactions among brain networks

Investigating spatiotemporal brain dynamics across species

Assessing functional brain dynamics in neurological disorders

3D-image reconstruction from cyro-EM images: statistical characterization of virus particles

Modeling and inferences in causal interactions among brain networks

Machine learning algorithms to quantify causal interactions

[CNS 2014, ICIP 2014, EMBC 2016a, Front. Neurosci. 2017]

Introduced a generalized correlation method to estimate the directed functional connectivity in brain networks
Recovered the functional brain systems as the traditional correlation method does

[Front. Neurosci. 2017] N. Xu*, R.N. Spreng, P.C. Doerschuk, "Initial validation for the estimation of resting-state fMRI effective connectivity: A generalized correlation approach". Frontiers in Neuroscience 11:271 (2017), doi:10.3389/fnins.2017.00271. [Software]
[EMBC 2016a] N. Xu, P.C. Doerschuk, R.N. Spreng, "What are the most talkative brain regions?" The 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016. (Late-breaking research paper)
[ICIP 2014] N. Xu, R.N. Spreng, P.C. Doerschuk. "Directed interactivity of large-scale brain networks: Introducing a new method for estimating resting-state effective connectivity MRI." The 21st IEEE International Conference on Image Processing, 2014. doi:10.1109/ICIP.2014.7025712.
[CNS 2014] N. Xu, R.N. Spreng, P.C. Doerschuk, "Directed interactivity of large-scale brain networks: Introducing a new method for estimating resting-state effective connectivity MRI." Cognitive Neuroscience Society 2014 Annual Meeting, Boston, MA, April 5-8, 2014.

Discovery in neuroscience

[OHBM 2020a (oral presentation), Neuroimage 2021]

Investigated the spatial and temporal properties of the brain’s functional interactivities.
Discovered that short information transfers depict the memory consolidation process in the brain.

[Neuroimage 2021] N. Xu*, P.C. Doerschuk, S.D. Keilholz+, R.N. Spreng+ "Spatiotemporal functional interactivity among large-scale brain networks". NeuroImage 227:117628 (2021), doi:10.1016/j.neuroimage.2020.117628.
[OHBM 2020a] N. Xu, R.N. Spreng, S.D. Keilholz, "Investigation of spatiotemporal functional interactivity among large-scale brain networks." The Organization for Human Brain Mapping Annual Meeting, 2020. (Selected for oral presentation, Top 4% accepted abstract papers)

Investigating spatiotemporal brain dynamics across species

Functional brain dynamics across rodents and humans

[OHBM 2022b, Front Neurosci 2022, MSM 2023, Apert Neuro 2023, Working Paper 2]

Studied the similarities and differences in functional brains across rodents and humans, and to what extent the rodents can be used as an animal model for studying the functional connectivity of humans.
Investigating the uniformity of spatiotemporal evolution of brain activity across cortical gradients in rodents and humans.

[Working Paper 2] N. Xu, L. Zhang, W-J Pan, Z. Li, K-H Chuang, S.D. Keilholz. “Uniformity in brain dynamics across rodents and humans.”
[Aperture Neuro 2023] N. Xu*, L. Zhang+, S. Larson+, Z Li, W-J Pan, K-H Chuang, S.D. Keilholz. "Rodent whole-brain fMRI data preprocessing toolbox". Aperture Neuro. 2023:1-3. doi:10.52294/001c.85075.
[MRM 2023] N. Anumba , E. Maltbie , W-J Pan, T.J LaGrow , N. Xu , S.D. Keilholz. "Spatial and spectral components of the BOLD global signal in rat rs-fMRI." Magnetic Resonance in Medicine (2023). doi: 10.1002/mrm.29824
[Front. Neurosci. 2022] N. Xu, T.J. LaGrow, N. Anumba, A. Lee, X. Zhang, B. Yousefi, Y. Bassil, G.P. Clavijo, V. Khalilzad Sharghi, E. Maltbie, L. Meyer-Baese, M. Nezafati, W-J Pan, S.D. Keilholz. "Functional connectivity of the brain across rodents and humans." Frontiers in Neuroscience (2022). doi: 10.3389/fnins.2022.816331.
[OHBM 2020b] W-J Pan, V. Khalilzad-Sharghi, E. Maltbie, X. Zhang, N. Xu, S.D. Keilholz. “Frequency-domain Correlation within Cerebral Functional Systems in Rats Authors: Introduction” The Organization for Human Brain Mapping Anual Meeting 2020.

Human brain dynamics in visual perception and attention

[OHBM 2021, CNS 2022ab, OHBM 2023, CABN 2024, Imag. Neurosci 2023]

Examined how the BOLD dynamic processes tie to the infraslow human brain activity interact with visual stimulations.
Discovered that these intrinsic dynamic processes are considerably robust in humans, but can still be modulated by different sequences of stimuli that affect the reaction time and sustained attention.

[Imaging Neuroscience 2023] N. Xu*, D.M. Smith, G. Jeno, D.T. Seeburger, E. Schumacher, S.D. Keilholz. “The interaction between random and systematic visual stimulation and infraslow quasiperiodic spatiotemporal patterns of whole brain activity.” Imaging Neuroscience 2023; 1 1–19. doi: 10.1162/imag_a_00002.
[CABN 2024] D. Seeburger, N. Xu, M. Ma, S. Larson, C. Godwin, S.D. Keilholz, E.H. Schumacher. "Time-varying functional connectivity predicts fluctuations in sustained attention in a serial tapping task." Cogn Affect Behav Neurosci 2024; 111–125. doi: 10.3758/s13415-024-01156-1
[OHBM 2023] N. Xu, D.M. Smith, G. Jeno, D.T. Seeburger, E.H. Schumacher, S.D. Keilholz. “ The interaction between visual stimulation and intrinsic infraslow whole brain activity in humans” Organization for Human Brain Mapping Annual Meeting 2023.
[CNS 2022a] D. Seeburger, N. Xu, C. Godwin, M. Ma, S.D. Keilholz, E.H. Schumacher. "Identifying the Neural Mechanisms of Zone State Performance using Time-varying Functional Connectivity Methods." Cognitive Neuroscience Society 2022 Annual Meeting. (Selected for oral presentation)
[CNS 2022b] Y-J Lee, D. Seeburger, S. Dhawan, T. Nguyen, N. Xu, M. Ma, A. Abbas, W. Majeed, G. Thompson, S.D. Keilholz, E.H. Schumacher. "Investigating the relationship between sustained attention and quasi-periodic brain activity patterns with the psychomotor vigilance task." Cognitive Neuroscience Society 2022 Annual Meeting.
[OHBM 2021] N. Xu, D.M. Smith, G. Jeno, D.T. Seeburger, E.H. Schumacher, S.D. Keilholz. “Quasiperiodic patterns and BOLD response entrained by visual stimulation in the human brain” Organization for Human Brain Mapping Annual Meeting 2021.

Assessing functional brain dynamics in neurological disorders

Brain causal dynamics in post-concussive syndromes

[OHBM 2022, ASFNR 2023, Working Paper 1]

Collaborating with Dr. Jason W. Allen group in Neuroradiology at Emory School of Medicine
Quantifying the information flow in the vestibular network for post-concussive vestibular syndrome
Identifying the spatiotemporal dynamics of the visual-vestibular system that drive different severity of post-concussive visual motion sensitivity.

[Working Paper 1] N. Xu, J.L. Smith, J. Allen+, S.D. Keilholz+. “Spatiotemporal interactions in visual-vestibular networks affected by different severity of post-concussive vestibular syndromes.”
[OHBM 2022] N. Xu, J.L. Smith, J. Allen+, S.D. Keilholz+. “Dynamic spatiotemporal interactions in vestibular networks affected by concussive syndromes ” The Organization for Human Brain Mapping Annual Meeting 2022.
[ASFNR 2023] A. Trofimova, J. Smith, N. Xu, S. Keilholz, R. Gore, J.W. Allen. Hyperconnected” Vestibular State in Subacute and Chronic Post-Concussive Vestibular Dysfunction Using Dynamic Whole Brain Functional Connectivity Analysis. The 16th Annual Meeting of the American Society of Functional Neuroradiology; 2023 October 7; Boston, MA, USA.

3D-image reconstruction from cyro-EM images: statistical characterization of virus particles

Machine learning algorithms & Scientific computing

[SRS2014, SPIE2015, ICIP 2015, EMBC2016b, IEEE TIP 2019, SISC 2021]

- Derived and computed a complete set of real-valued basis functions of polyhedral groups for characterizing stochastic biological object
- Developed algorithm which enabled a realistic description on ensembles of biological objects: it is the statistics of the ensemble have symmetry, not the individual instances
- Results eliminated long-standing distortions in space-varying variance calculations associated with symmetry axes of all existing reconstruction methods (see video).

[SISC 2021] N. Xu*, P.C. Doerschuk, "Computation of real-valued basis functions which transform as irreducible representations of the polyhedral groups". SIAM Journal on Scientific Computing 43:6 (2021), doi: 10.1137/20M1318183 (arXiv). [Software]
[IEEE TIP 2019] N. Xu, P.C. Doerschuk, "Reconstruction of stochastic 3-D signals with symmetric statistics from 2-D projection images motivated by cryo-electron microscopy". IEEE Transactions on Image Processing, 28:11 (2019), doi: 10.1109/TIP.2019.2915631 (arXiv).
[EMBC 2016b] N. Xu, P.C. Doerschuk. "Statistical characterization of ensembles of symmetric virus particles: 3-D stochastic signal reconstruction from electron microscope images." The 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016. doi: 10.1109/EMBC.2016.7591598. (EMBS Student Paper Competition Finalist, Top 0.4% accepted papers)
[ICIP 2015] N. Xu, P.C. Doerschuk. "Reconstruction for stochastic 3-D signals with symmetric statistics in noise: electron microscopy of virus particles." The 22nd IEEE International Conference on Image Processing, 2015. doi: 10.1109/ICIP.2015.7351039. (1 of Top 127 papers recognized as "Top 10%"; 1 of Top 34 papers demonstrated in the "Show & Tell" session)
[SPIE 2015] N. Xu, Y. Gong, Q. Wang, Y. Zheng, P.C. Doerschuk. "Characterizing heterogeneity among virus particles by stochastic 3D signal reconstruction." SPIE Optics + Photonics 2015. doi: 10.1117/12.2193791SPIE 2015.
[SRS 2014] N. Xu, Yunye Gong, Yili Zheng, Qiu Wang, Peter C. Doerschuk. "3-D statistical characterization of the heterogeneity of biological macromolecular complexes by electron microscopy." Optical Society of America, Signal Recovery and Synthesis, 2014.doi: 10.1364/SRS.2014.STu3F.4.

Discovery in structural virology

[JSB2018]

Demonstrated allosteric changes in the capsid peptide caused by the binding of the viral protease for HK97
Demonstrated for the first time the space-varying anisotropy of the fluctuations in the electron scattering intensity for a virus-like particle (VLP) from bacteriophage HK97

[JSB 2018] N. Xu, D. Veesler, P.C. Doerschuk and J. E. Johnson, "Allosteric effects in bacteriophage HK97 procapsids revealed directly from covariance analysis of cryo-EM data". Journal of Structural Biology 202:2 (2018), doi: 10.3389/fnins.2017.00271.

Nan has extensive software engineering experience, especially in Matlab, Mathematica, and C. The virus image reconstruction problem is a "big data" problem as over 100,000 electron microscope images were reconstructed and analyzed all at once! Nan was also experienced with C++, Java, R, and Python.

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