Connections, Tracts, Fractals, and the Rest: A Working Guide to Network and Connectivity Studies in Neurosurgery
Open accessAbstract
Brain mapping and connectomics can probe networks that span the entire brain, producing a diverse range of outputs for probing specific clinically relevant questions. The potential for understanding the effect of focal lesions on brain function, cognition, and plasticity abounds, any one of which would likely yield more effective and safer neurosurgical strategies. However, the possibilities of advanced magnetic resonance imaging and connectomics have been somewhat underused in neurosurgery, arising from actual or perceived difficulties in either application or analysis. The present review builds on previous work describing the theoretical attractions of connectomics to deliberate on the practical details of performing high-quality connectomics studies in neurosurgery. First, the data and methods involved in deriving connectomics models will be considered, specifically for the purpose of determining the nature of inferences that can be made subsequently. Next, a selection of key analysis methods will be explored using practical examples that illustrate their effective implementation and the insights that can be gleaned. The principles of study design will be introduced, including analysis tips and methods for making efficient use of available resources. Finally, a review of the best research practices for neuroimaging studies will be discussed, including principles of open access data sharing, study preregistration, and methods for improving replicability. Ultimately, we hope readers will be better placed to appraise the current connectomics studies in neurosurgery and empowered to develop their own high-quality studies, both of which are key steps in realizing the true potential of connectomics and advanced neuroimaging analyses in general.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The brain connectomic concept benefits traditional surgical strategy by enabling a potential shift from local topography to network-guided "oncological disconnection surgery".
“The brain connectomic concept benefits traditional surgical strategy by a potential shift from focusing on local topography to a network-guided “oncological disconnection surgery” (Duffau, 2021; Hart et al., 2020).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Hart et al., 2020
Section 3c (p. 9) describes connectomics as a holistic view of brain connectivity and discusses glioblastoma analyses that reveal surgical risks beyond standard structural imaging. The pre-operative glioma example (Figure 6 caption, p. 23) also illustrates network mapping. These passages support a potential move beyond local anatomy, but they do not propose a network-guided “oncological disconnection surgery.” (LLM, conf=0.85)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060 · see citing works
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820 · see citing works
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522 · see citing works
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812 · see citing works
The minimal preprocessing pipelines for the Human Connectome Project
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J. R., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.127 · Cited by 5,253 · see citing works
Correspondence of the brain's functional architecture during activation and rest
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150 · see citing works
Mapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173 · see citing works
Exploring the brain network: A review on resting-state fMRI functional connectivity
van den Heuvel, M. P., & Hulshoff Pol, H. E. (2010) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2010.03.008 · Cited by 3,326 · see citing works
NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain
Zhang, H., Schneider, T., Wheeler-Kingshott, C. A., & Alexander, D. C. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.072 · Cited by 3,288 · see citing works
The Human Connectome: A Structural Description of the Human Brain
Sporns, O., Tononi, G., & Kötter, R. (2005) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0010042 · Cited by 3,260 · see citing works
Rhythms for cognition: communication through coherence
Fries, P. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.034 · Cited by 2,725 · see citing works
Circular analysis in systems neuroscience: the dangers of double dipping
Kriegeskorte, N., Simmons, W. K., Bellgowan, P. S. F., & Baker, C. I. (2009) · Nature Neuroscience · doi:10.1038/nn.2303 · Cited by 2,696 · see citing works
Regional homogeneity approach to fMRI data analysis.
Zang, Y., Jiang, T., Lu, Y., He, Y., & Tian, L. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2003.12.030 · Cited by 2,614 · see citing works
Jensen, J. H., Helpern, J. A., Ramani, A., Lu, H., & Kaczynski, K. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20508 · Cited by 2,488 · see citing works
Fractal dynamics in physiology: Alterations with disease and aging
Goldberger, A. L., Amaral, L. A. N., Hausdorff, J. M., Ivanov, P. C., Peng, C., & Stanley, E. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.012579499 · Cited by 2,220 · see citing works
Zou, Q., Zhu, C.-Z., Yang, Y., Zuo, X., Long, X., Cao, Q., Wang, Y., & Zang, Y. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2008.04.012 · Cited by 2,169 · see citing works
The connectomics of brain disorders
Fornito, A., Zalesky, A., & Breakspear, M. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3901 · Cited by 1,734 · see citing works
Looking into the functional architecture of the brain with diffusion MRI.
Le Bihan, D. (2003) · Nature Reviews Neuroscience · doi:10.1038/nrn1119 · Cited by 1,571 · see citing works
Logothetis, N. K., & Wandell, B. A. (2004) · Annual Review of Physiology · doi:10.1146/annurev.physiol.66.082602.092845 · Cited by 1,568 · see citing works
Tractography-based connectomes are dominated by false-positive connections
Maier-Hein, K. H., Neher, P., Houde, J.-C., Côté, M.-A., Garyfallidis, E., Zhong, J., Chamberland, M., Yeh, F.-C., Lin, Y.-C., Ji, Q., et al. (2016) · doi:10.1101/084137 · Cited by 1,361 · see citing works
Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging
Wedeen, V. J., Hagmann, P., Tseng, W. I., Reese, T. G., & Weisskoff, R. M. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20642 · Cited by 1,339 · see citing works
Penfield, W. G. (1950) · Digital Commons - RU (Rockefeller University) · Cited by 1,328 · see citing works
Raichle, M. E. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.01.008 · Cited by 1,111 · see citing works
Imaging structural co-variance between human brain regions
Alexander-Bloch, A., Giedd, J. N., & Bullmore, E. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3465 · Cited by 1,064 · see citing works
Recent progress and outstanding issues in motion correction in resting state fMRI
Power, J. D., Schlaggar, B. L., & Petersen, S. E. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.10.044 · Cited by 957 · see citing works
Functional connectomics from resting-state fMRI
Smith, S. M., Vidaurre, D., Beckmann, C. F., Glasser, M. F., Jenkinson, M., Miller, K. L., Nichols, T. E., Robinson, E. C., Salimi-Khorshidi, G., Woolrich, M. W., et al. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.09.016 · Cited by 952 · see citing works
Functional system and areal organization of a highly sampled individual human brain
Laumann, T. O., Gordon, E. M., Adeyemo, B., Snyder, A. Z., Joo, S. J., Chen, M.-Y., Gilmore, A. W., McDermott, K. B., Nelson, S. M., Dosenbach, N. U. F., et al. (2015) · Neuron · doi:10.1016/j.neuron.2015.06.037 · Cited by 911 · see citing works
Disease and the brain's dark energy
Zhang, D., & Raichle, M. E. (2010) · Nature Reviews Neurology · doi:10.1038/nrneurol.2009.198 · Cited by 903 · see citing works
Small-World Brain Networks Revisited
Bassett, D. S., & Bullmore, E. T. (2016) · The Neuroscientist · doi:10.1177/1073858416667720 · Cited by 840 · see citing works
Mapping Human Whole-Brain Structural Networks with Diffusion MRI
Hagmann, P., Kurant, M., Gigandet, X., Thiran, P., Wedeen, V. J., Meuli, R., & Thiran, J.-P. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000597 · Cited by 788 · see citing works
Best practices in data analysis and sharing in neuroimaging using MRI
Nichols, T. E., Das, S., Eickhoff, S. B., Evans, A. C., Glatard, T., Hanke, M., Kriegeskorte, N., Milham, M. P., Poldrack, R. A., Poline, J.-B., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4500 · Cited by 714 · see citing works
Rethinking segregation and integration: contributions of whole-brain modelling
Deco, G., Tononi, G., Boly, M., & Kringelbach, M. L. (2015) · Nature reviews. Neuroscience · doi:10.1038/nrn3963 · Cited by 658 · see citing works
Can structure predict function in the human brain?
Honey, C. J., Thivierge, J.-P., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.071 · Cited by 629 · see citing works
Brain networks and cognitive architectures
Petersen, S. E., & Sporns, O. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.027 · Cited by 553 · see citing works
Deep brain stimulation restores frontostriatal network activity in obsessive-compulsive disorder
Figee, M., Luigjes, J., Smolders, R., Valencia-Alfonso, C.-E., van Wingen, G., de Kwaasteniet, B., Mantione, M., Ooms, P., de Koning, P., Vulink, N., et al. (2013) · Nature Neuroscience · doi:10.1038/nn.3344 · Cited by 466 · see citing works
Imaging human connectomes at the macroscale
Craddock, R. C., Jbabdi, S., Yan, C.-G., Vogelstein, J. T., Castellanos, F. X., Di Martino, A., Kelly, C., Heberlein, K., Colcombe, S., & Milham, M. P. (2013) · Nature Methods · doi:10.1038/nmeth.2482 · Cited by 419 · see citing works
Making big data open: data sharing in neuroimaging
Poldrack, R. A., & Gorgolewski, K. J. (2014) · Nature Neuroscience · doi:10.1038/nn.3818 · Cited by 412 · see citing works
Direct electrical stimulation of human cortex — the gold standard for mapping brain functions?
Borchers, S., Himmelbach, M., Logothetis, N. K., & Karnath, H. (2011) · Nature reviews. Neuroscience · doi:10.1038/nrn3140 · Cited by 402 · see citing works
From 1/f noise to multifractal cascades in heartbeat dynamics
Ivanov, P. C., Amaral, L. A. N., Goldberger, A. L., Havlin, S., Rosenblum, M., Stanley, E., & Struzik, Z. R. (2001) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/1.1395631 · Cited by 402 · see citing works
Integrated strategy for improving functional connectivity mapping using multiecho fMRI
Kundu, P., Brenowitz, N. D., Voon, V., Worbe, Y., Vértes, P. E., Inati, S. J., Saad, Z. S., Bandettini, P. A., & Bullmore, E. T. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1301725110 · Cited by 399 · see citing works
Clinical applications of the functional connectome
Castellanos, F. X., Di Martino, A., Craddock, R. C., Mehta, A. D., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.083 · Cited by 312 · see citing works
Building connectomes using diffusion MRI: why, how and but
Sotiropoulos, S. N., & Zalesky, A. (2019) · NMR in Biomedicine · doi:10.1002/nbm.3752 · Cited by 290 · see citing works
Default mode contributions to automated information processing
Vatansever, D., Menon, D. K., & Stamatakis, E. A. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1710521114 · Cited by 281 · see citing works
Network-Level Structure-Function Relationships in Human Neocortex
Mišić, B., Betzel, R. F., de Reus, M. A., van den Heuvel, M. P., Berman, M. G., McIntosh, A. R., & Sporns, O. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw089 · Cited by 277 · see citing works
Fractional Gaussian noise, functional MRI and Alzheimer's disease
Maxim, V., Sendur, L., Fadili, J. M., John Suckling, A., Gould, R. L., Howard, R. J., & Bullmore, E. T. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.10.044 · Cited by 270 · see citing works
Resting developments: a review of fMRI post-processing methodologies for spontaneous brain activity
Margulies, D. S., Böttger, J., Long, X., Lv, Y., Kelly, C. A. M., Schäfer, A., Goldhahn, D., Abbushi, A., Milham, M. P., Lohmann, G., et al. (2010) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-010-0228-5 · Cited by 242 · see citing works
Wiring cost and topological participation of the mouse brain connectome
Rubinov, M., Ypma, R. J. F., Watson, C., & Bullmore, E. T. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1420315112 · Cited by 219 · see citing works
FATCAT: (An Efficient) Functional And Tractographic Connectivity Analysis Toolbox
Taylor, P. A., & Saad, Z. S. (2013) · Brain Connectivity · doi:10.1089/brain.2013.0154 · Cited by 211 · see citing works
Mapping Connectivity Damage in the Case of Phineas Gage
Van Horn, J. D., Irimia, A., Torgerson, C. M., Chambers, M. C., Kikinis, R., & Toga, A. W. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037454 · Cited by 196 · see citing works
Modeling the outcome of structural disconnection on resting-state functional connectivity
Cabral, J., Hugues, E., Kringelbach, M. L., & Deco, G. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.007 · Cited by 182 · see citing works
Theoretical neuroanatomy and the connectivity of the cerebral cortex
Sporns, O., Tononi, G., & Edelman, G. M. (2002) · Behavioural Brain Research · doi:10.1016/s0166-4328(02)00157-2 · Cited by 144 · see citing works
The modular organization of human anatomical brain networks: Accounting for the cost of wiring
Betzel, R. F., Medaglia, J. D., Papadopoulos, L., Baum, G. L., Gur, R. C., Gur, R. E., Roalf, D. R., Satterthwaite, T. D., & Bassett, D. S. (2017) · Network Neuroscience · doi:10.1162/netn_a_00002 · Cited by 144 · see citing works
Vassal, M., Charroud, C., Deverdun, J., Bars, E. L., Molino, F., Bonnetblanc, F., Boyer, A., Dutta, A., Herbet, G., Moritz‐Gasser, S., et al. (2016) · Journal of neurosurgery · doi:10.3171/2016.4.jns152484 · Cited by 136 · see citing works
Wink, A. M., Bullmore, E. T., Barnes, A., Bernard, F., & John Suckling, A. (2008) · Human Brain Mapping · doi:10.1002/hbm.20593 · Cited by 128 · see citing works
fMRI Functional Connectivity Applied to Adolescent Neurodevelopment
Ernst, M., Torrisi, S., Balderston, N. L., Grillon, C., & Hale, E. A. (2015) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-032814-112753 · Cited by 104 · see citing works
John Suckling, A., Wink, A. M., Bernard, F., Barnes, A., & Bullmore, E. T. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2008.06.037 · Cited by 98 · see citing works
Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain
Aerts, H., Schirner, M., Jeurissen, B., Roost, D. V., Achten, E., Ritter, P., & Marinazzo, D. (2018) · eNeuro · doi:10.1523/eneuro.0083-18.2018 · Cited by 86 · see citing works
Avena‐Koenigsberger, A., Mišić, B., Hawkins, R. X. D., Griffa, A., Hagmann, P., Goñi, J., & Sporns, O. (2016) · Brain Structure and Function · doi:10.1007/s00429-016-1238-5 · Cited by 78 · see citing works
Hart, M. G., Ypma, R. J. F., Romero-Garcia, R., Price, S. J., & Suckling, J. (2016) · Journal of Neurosurgery · doi:10.3171/2015.4.jns142683 · Cited by 74 · see citing works
Self-citationBuck, S. (2015) · Science · doi:10.1126/science.aac8041 · Cited by 72 · see citing works
Laing, R. J. C. (1998) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.64.2.284 · Cited by 64 · see citing works
Connectome analysis for pre-operative brain mapping in neurosurgery
Hart, M. G., Price, S. J., & Suckling, J. (2016) · British Journal of Neurosurgery · doi:10.1080/02688697.2016.1208809 · Cited by 58 · see citing works
Self-citationBrain Mapping: From Neural Basis of Cognition to Surgical Applications
Kubben, P. (2012) · Europe PMC (PubMed Central) · Cited by 47 · see citing works
Gracia-Tabuenca, Z., Moreno, M. B., Barrios, F. A., & Alcauter, S. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.051 · Cited by 40 · see citing works
Romero-García, R., Erez, Y., Oliver, G., Owen, M., Merali, S., Poologaindran, A., Morris, R. C., Price, S. J., Santarius, T., John Suckling, A., et al. (2020) · World Neurosurgery · doi:10.1016/j.wneu.2020.01.085 · Cited by 18 · see citing works
Self-citationExtraoperative electrical mapping
Winkler, P. (2011) · Springer eBooks · doi:10.1007/978-3-7091-0723-2_7 · Cited by 4 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Zhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R. E., Yeh, C.-H., Zhao, T., & O’Donnell, L. J. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2021.118870 · Cited by 302 · see citing works
“The brain connectomic concept benefits traditional surgical strategy by a potential shift from focusing on local topography to a network-guided “oncological disconnection surgery” (Duffau, 2021; Hart et al., 2020).”
BackgroundA Network-Based Approach to Glioma Surgery: Insights from Functional Neurosurgery
Samuel, N., Vetkas, A., Pancholi, A., Sarica, C., Loh, A., Germann, J., Harmsen, I. E., Tasserie, J., Milano, V. C., Yamamoto, K., et al. (2021) · Cancers · doi:10.3390/cancers13236127 · Cited by 30 · see citing works
Bigler, E. D., & Allder, S. J. (2021) · Neurorehabilitation · doi:10.3233/nre-218023 · Cited by 10 · see citing works
Magnani, M., Rustici, A., Zoli, M., Tuleasca, C., Chaurasia, B. K., Franceschi, E., Tonon, C., Lodi, R., & Conti, A. (2024) · Life · doi:10.3390/life14010136 · Cited by 10 · see citing works
A Self-Similarity Logic May Shape the Organization of the Nervous System
Guidolin, D., Tortorella, C., De, R., & Agnati, L. F. (2024) · Advances in neurobiology · doi:10.1007/978-3-031-47606-8_10 · Cited by 4 · see citing works
Surgeon’s Eyes on the Relevant Surgical Target
DIVITIIS, O. D., d’Avella, E., Fabozzi, G. L., Cavallo, L. M., & Solari, D. (2023) · Acta neurochirurgica. Supplementum · doi:10.1007/978-3-031-36084-8_2 · Cited by 1 · see citing works
Neural network-based neurosurgical device discovery and prototypes
Tan, B., Li, G., Sun, J. P., & Chen, Y. (2025) · Elsevier eBooks · doi:10.1016/b978-0-323-90509-1.00035-7
- Authors
- Hart, M. G., Romero-Garcia, R., Price, S. J., Santarius, T., & Suckling, J.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Hart, Michael G.
- Venue
- World Neurosurgery
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 140
- Pages
- 389-400
- ISSN
- 1878-8750 (ISSN-L)
- OpenAlex
- W3014706026
- Cited by
- 7
- References
- 66
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 1 · 2022: 1 · 2021: 2
- FWCI
- 0.13
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- World Neurosurgery (publishedVersion)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Funders
- Guarantors of Brain
- Brain Tumour Charity (GN-000335)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- connectomics, brain networks, neurosurgery, brain mapping, focal brain lesions, neuroplasticity, research design, open data sharing, replicability, advanced neuroimaging
- MeSH terms
- Brain, Humans, Magnetic Resonance Imaging, Nerve Net, Neural Pathways, Neurosurgical Procedures, Neuroimaging, Connectome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
