Abstract
How do brain networks anticipate, endure, respond, and adapt to limit the consequences of a stroke? Recent studies suggest that understanding the whole process of resilience of brain networks may create new opportunities in the management of patients. The first step of resilience relates to the status of brain networks before the stroke has occurred. In healthy subjects, brain networks seem to be organized to limit the consequences of a lesion. Indeed, the anatomic location and the position of strategic nodes in the network architecture prevent major neurological deficits, even when these hubs suffer from a targeted attack. The second step in the process of resilience reflects how the brain endures the impact of stroke. Widespread changes in the organization of brain networks are triggered by the lesion. This effect can be understood as “connectional” diaschisis or “connectomal” diaschisis defined, respectively, as the changes in coupling between two nodes of a specific network or in the totality of brain connections. Clinically, the reduction in interhemispheric coupling after stroke seems to be particularly relevant. Further steps in the process of resilience include response and adaptation to the lesion. Recent evidence points to the importance of changes in network configuration during recovery. However, it remains debated whether normalization or reorganization of brain networks in a most efficient architecture will lead to a favorable outcome. Based on the concept of resilience, further studies are needed to determine how therapeutic strategies may promote an optimal architecture of brain networks to improve functional outcome.
References
Achard S, Bullmore ET. Efficiency and cost of economical brain functional networks. PLoS Comput Biol. 2007;3(2):174–83. doi:10.1371/Journal.Pcbi.0030017 (Artn E17).
Achard S, Salvador R, Whitcher B, Suckling J, Bullmore E. A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. J Neurosci. 2006;26(1):63–72. doi:10.1523/JNEUROSCI.3874-05.2006.
Alstott J, Breakspear M, Hagmann P, Cammoun L, Sporns O. Modeling the impact of lesions in the human brain. Plos Comput Biol. 2009; 5(6). doi:10.1371/Journal.Pcbi.1000408 (Artn E1000408).
Andrews RJ. Transhemispheric diaschisis—a review and comment. Stroke. 1991;22(7):943–9.
Auriat AM, Neva JL, Peters S, Ferris JK, Boyd LA. A review of transcranial magnetic stimulation and multimodal neuroimaging to characterize post-stroke neuroplasticity. Front Neurol. 2015;6:226. doi:10.3389/fneur.2015.00226.
Baron JC, Bousser MG, Comar D, Castaigne P. “Crossed cerebellar diaschisis” in human supratentorial brain infarction. Trans Am Neurol Assoc. 1981;105:459–61.
Bohlken MM, Mandl RC, Brouwer RM, van den Heuvel MP, Hedman AM, Kahn RS, Hulshoff Pol HE. Heritability of structural brain network topology: a DTI study of 156 twins. Hum Brain Mapp. 2014;35(10):5295–305. doi:10.1002/hbm.22550.
Bonilha L, Rorden C, Fridriksson J. Assessing the clinical effect of residual cortical disconnection after ischemic strokes. Stroke. 2014;45(4):988–93. doi:10.1161/STROKEAHA.113.004137 (STROKEAHA.113.004137 [pii]).
Bullmore ET, Bassett DS. Brain graphs: graphical models of the human brain connectome. Annu Rev Clin Psycho. 2011;7:113–40. doi:10.1146/Annurev-Clinpsy-040510-143934.
Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci. 2009;10(3):186–98. doi:10.1038/nrn2575.
Campo P, Garrido MI, Moran RJ, Maestu F, Garcia-Morales I, Gil-Nagel A, del Pozo F, Dolan RJ, Friston KJ. Remote effects of hippocampal sclerosis on effective connectivity during working memory encoding: a case of connectional diaschisis? Cereb Cortex. 2012;22(6):1225–36. doi:10.1093/cercor/bhr201 (bhr201 [pii]).
Carrera E. Reply: Aleksander Luria and diaschisis. Brain. 2015;138(Pt 8):e369. doi:10.1093/brain/awu402.
Carrera E, Bogousslavsky J. The thalamus and behavior—effects of anatomically distinct strokes. Neurology. 2006;66(12):1817–23. doi:10.1212/01.Wnl.0000219679.95223.4c.
Carrera E, Tononi G. Diaschisis: past, present, future. Brain. 2014;137:2408–22. doi:10.1093/brain/awu101 (awu101 [pii]).
Carter AR, Astafiev SV, Lang CE, Connor LT, Rengachary J, Strube MJ, Pope DL, Shulman GL, Corbetta M. Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke. Ann Neurol. 2010;67(3):365–75. doi:10.1002/ana.21905.
Cheng L, Wu Z, Fu Y, Miao F, Sun J, Tong S. Reorganization of functional brain networks during the recovery of stroke: a functional MRI study. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:4132–5. doi:10.1109/EMBC.2012.6346876.
Damoiseaux JS, Rombouts SA, Barkhof F, Scheltens P, Stam CJ, Smith SM, Beckmann CF. Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci U S A. 2006;103(37):13848–53. doi:10.1073/pnas.0601417103.
Feeney DM, Baron JC. Diaschisis. Stroke. 1986;17(5):817–30.
Finger S, Koehler PJ, Jagella C. The Monakow concept of diaschisis: origins and perspectives. Arch Neurol. 2004;61(2):283–8. doi:10.1001/archneur.61.2.283.
Finn ES, Shen X, Scheinost D, Rosenberg MD, Huang J, Chun MM, Papademetris X, Constable RT. Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nat Neurosci. 2015;18(11):1664–71. doi:10.1038/nn.4135.
Fornito A, Zalesky A, Breakspear M. The connectomics of brain disorders. Nat Rev Neurosci. 2015;16(3):159–72. doi:10.1038/nrn3901.
Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A. 2005;102(27):9673–8. doi:10.1073/pnas.0504136102.
Friston KJ. Functional and effective connectivity: a review. Brain Connect. 2011;1(1):13–36. doi:10.1089/brain.2011.0008.
Golestani AM, Tymchuk S, Demchuk A, Goodyear BG, Group V-S. Longitudinal evaluation of resting-state FMRI after acute stroke with hemiparesis. Neurorehabil Neural Repair. 2013; 27(2):153–163. doi:10.1177/1545968312457827.
Grefkes C, Fink GR. Connectivity-based approaches in stroke and recovery of function. Lancet Neurol. 2014;13(2):206–16. doi:10.1016/S1474-4422(13)70264-3 (S1474-4422(13)70264-3 [pii]).
Grefkes C, Nowak DA, Eickhoff SB, Dafotakis M, Kust J, Karbe H, Fink GR. Cortical connectivity after subcortical stroke assessed with functional magnetic resonance imaging. Ann Neurol. 2008;63(2):236–46. doi:10.1002/ana.21228.
Grefkes C, Nowak DA, Wang LE, Dafotakis M, Eickhoff SB, Fink GR. Modulating cortical connectivity in stroke patients by rTMS assessed with fMRI and dynamic causal modeling. Neuroimage. 2010;50(1):233–42. doi:10.1016/j.neuroimage.2009.12.029 (S1053-8119(09)01317-2 [pii]).
Griffa A, Baumann PS, Thiran JP, Hagmann P. Structural connectomics in brain diseases. Neuroimage. 2013;80:515–26. doi:10.1016/j.neuroimage.2013.04.056.
Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, Wedeen VJ, Sporns O. Mapping the structural core of human cerebral cortex. PLoS Biol. 2008;6(7):e159. doi:10.1371/journal.pbio.0060159 (07-PLBI-RA-4028 [pii]).
Honey CJ, Sporns O, Cammoun L, Gigandet X, Thiran JP, Meuli R, Hagmann P. Predicting human resting-state functional connectivity from structural connectivity. Proc Natl Acad Sci U S A. 2009;106(6):2035–40. doi:10.1073/pnas.0811168106 (0811168106 [pii]).
Jiang L, Xu H, Yu C. Brain connectivity plasticity in the motor network after ischemic stroke. Neural Plast. 2013;2013:924192. doi:10.1155/2013/924192.
Kang N, Summers JJ, Cauraugh JH. Non-Invasive Brain Stimulation Improves Paretic Limb Force Production: A Systematic Review and Meta-Analysis. Brain Stimul. 2016;. doi:10.1016/j.brs.2016.05.005.
Laney J, Adali T, McCombe Waller S, Westlake KP. Quantifying motor recovery after stroke using independent vector analysis and graph-theoretical analysis. Neuroimage Clin. 2015;8:298–304. doi:10.1016/j.nicl.2015.04.014.
Newman ME, Strogatz SH, Watts DJ. Random graphs with arbitrary degree distributions and their applications. Phys Rev E Stat Nonlin Soft Matter Phys. 2001;64(2 Pt 2):026118. doi:10.1103/PhysRevE.64.026118.
Park HJ, Friston K. Structural and functional brain networks: from connections to cognition. Science. 2013;342(6158):1238411. doi:10.1126/science.1238411.
Park CH, Chang WH, Ohn SH, Kim ST, Bang OY, Pascual-Leone A, Kim YH. Longitudinal changes of resting-state functional connectivity during motor recovery after stroke. Stroke. 2011;42(5):1357–62. doi:10.1161/STROKEAHA.110.596155 (STROKEAHA.110.596155 [pii]).
Raichle ME. Behind the scenes of functional brain imaging: a historical and physiological perspective. Proc Natl Acad Sci U S A. 1998;95(3):765–72.
Ramsey LE, Siegel JS, Baldassarre A, Metcalf NV, Zinn K, Shulman GL, Corbetta M. Normalization of network connectivity in hemispatial neglect recovery. Ann Neurol. 2016;80(1):127–41. doi:10.1002/ana.24690.
Rehme AK, Fink GR, von Cramon DY, Grefkes C. The role of the contralesional motor cortex for motor recovery in the early days after stroke assessed with longitudinal FMRI. Cereb Cortex. 2011;21(4):756–68. doi:10.1093/cercor/bhq140 (bhq140 [pii]).
Richiardi J, Altmann A, Milazzo AC, Chang C, Chakravarty MM, Banaschewski T, Barker GJ, Bokde AL, Bromberg U, Buchel C, Conrod P, Fauth-Buhler M, Flor H, Frouin V, Gallinat J, Garavan H, Gowland P, Heinz A, Lemaitre H, Mann KF, Martinot JL, Nees F, Paus T, Pausova Z, Rietschel M, Robbins TW, Smolka MN, Spanagel R, Strohle A, Schumann G, Hawrylycz M, Poline JB, Greicius MD, consortium I. Brain networks. Correlated gene expression supports synchronous activity in brain networks. Science 2015;348(6240):1241–1244. doi:10.1126/science.1255905.
Rubinov M, Sporns O. Complex network measures of brain connectivity: uses and interpretations. Neuroimage. 2010;52(3):1059–69. doi:10.1016/j.neuroimage.2009.10.003 (S1053-8119(09)01074-X [pii]).
Sami S, Miall RC. Graph network analysis of immediate motor-learning induced changes in resting state BOLD. Front Hum Neurosci. 2013;7:166. doi:10.3389/fnhum.2013.00166.
Schoffelen JM, Gross J. Source connectivity analysis with MEG and EEG. Hum Brain Mapp. 2009;30(6):1857–65. doi:10.1002/hbm.20745.
Seth AK, Barrett AB, Barnett L. Granger causality analysis in neuroscience and neuroimaging. J Neurosci. 2015;35(8):3293–7. doi:10.1523/JNEUROSCI.4399-14.2015.
Sharma N, Baron JC, Rowe JB. Motor imagery after stroke: relating outcome to motor network connectivity. Ann Neurol. 2009;66(5):604–16. doi:10.1002/ana.21810.
Sporns O, Tononi G, Kotter R. The human connectome: A structural description of the human brain. PLoS Comput Biol. 2005;1(4):245–51. doi:10.1371/Journal.Pcbi.0010042 (Artn E42).
Sporns O, Honey CJ, Kotter R. Identification and classification of hubs in brain networks. PLoS ONE. 2007;2(10):e1049. doi:10.1371/journal.pone.0001049.
Tatu L, Moulin T, Bogousslavsky J, Duvernoy H. Arterial territories of the human brain: cerebral hemispheres. Neurology. 1998;50(6):1699–708.
Thompson PM, Ge T, Glahn DC, Jahanshad N, Nichols TE. Genetics of the connectome. Neuroimage. 2013;80:475–88. doi:10.1016/j.neuroimage.2013.05.013.
Tononi G, Sporns O, Edelman GM. A measure for brain complexity: relating functional segregation and integration in the nervous system. Proc Natl Acad Sci U S A. 1994;91(11):5033–7.
Tuch DS, Reese TG, Wiegell MR, Makris N, Belliveau JW, Wedeen VJ. High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn Reson Med. 2002;48(4):577–82. doi:10.1002/mrm.10268.
van den Heuvel MP, Hulshoff Pol HE. Exploring the brain network: a review on resting-state fMRI functional connectivity. Eur Neuropsychopharmacol. 2010;20(8):519–34. doi:10.1016/j.euroneuro.2010.03.008.
van den Heuvel MP, Sporns O. Rich-club organization of the human connectome. J Neurosci. 2011;31(44):15775–86. doi:10.1523/JNEUROSCI.3539-11.2011.
Van Essen DC, Ugurbil K. The future of the human connectome. Neuroimage. 2012;62(2):1299–310. doi:10.1016/j.neuroimage.2012.01.032 (S1053-8119(12)00049-3 [pii]).
van Meer MP, Otte WM, van der Marel K, Nijboer CH, Kavelaars A, van der Sprenkel JW, Viergever MA, Dijkhuizen RM. Extent of bilateral neuronal network reorganization and functional recovery in relation to stroke severity. J Neurosci. 2012;32(13):4495–507. doi:10.1523/JNEUROSCI.3662-11.2012 (32/13/4495 [pii]).
von Monakow C. Die Localization im Grosshirn und der Abbau der Funktion durch korticale Herde. Germany: JF Bergmann, Wiesbaden. First published. 1914.
Wang L, Yu C, Chen H, Qin W, He Y, Fan F, Zhang Y, Wang M, Li K, Zang Y, Woodward TS, Zhu C. Dynamic functional reorganization of the motor execution network after stroke. Brain. 2010;133(Pt 4):1224–38. doi:10.1093/brain/awq043 (awq043 [pii]).
Wang GZ, Belgard TG, Mao D, Chen L, Berto S, Preuss TM, Lu H, Geschwind DH, Konopka G. Correspondence between resting-state activity and brain gene expression. Neuron. 2015;88(4):659–66. doi:10.1016/j.neuron.2015.10.022.
Watts DJ, Strogatz SH. Collective dynamics of ‘small-world’ networks. Nature. 1998;393(6684):440–2. doi:10.1038/30918.
Wedeen VJ, Hagmann P, Tseng WYI, Reese TG, Weisskoff RM. Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magnet Reson Med. 2005;54(6):1377–86. doi:10.1002/Mrm.20642.
Wedeen VJ, Wang RP, Schmahmann JD, Benner T, Tseng WY, Dai G, Pandya DN, Hagmann P, D’Arceuil H, de Crespigny AJ. Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. Neuroimage. 2008;41(4):1267–77. doi:10.1016/j.neuroimage.2008.03.036.
Westlake KP, Nagarajan SS. Functional connectivity in relation to motor performance and recovery after stroke. Front Syst Neurosci. 2011;5:8. doi:10.3389/fnsys.2011.00008.
Xu H, Qin W, Chen H, Jiang L, Li K, Yu C. Contribution of the resting-state functional connectivity of the contralesional primary sensorimotor cortex to motor recovery after subcortical stroke. PLoS ONE. 2014;9(1):e84729. doi:10.1371/journal.pone.0084729.
Yang Z, Zuo XN, McMahon KL, Craddock RC, Kelly C, de Zubicaray GI, Hickie I, Bandettini PA, Castellanos FX, Milham MP, Wright MJ. Genetic and environmental contributions to functional connectivity architecture of the human brain. Cereb Cortex. 2016;26(5):2341–52. doi:10.1093/cercor/bhw027.
Yassi N, Churilov L, Campbell BC, Sharma G, Bammer R, Desmond PM, Parsons MW, Albers GW, Donnan GA, Davis SM, Investigators E, Investigators D. The association between lesion location and functional outcome after ischemic stroke. Int J Stroke. 2015;10(8):1270–6. doi:10.1111/ijs.12537.
Zhang Y, Liu H, Wang L, Yang J, Yan R, Zhang J, Sang L, Li P, Wang J, Qiu M. Relationship between functional connectivity and motor function assessment in stroke patients with hemiplegia: a resting-state functional MRI study. Neuroradiology. 2016;58(5):503–11. doi:10.1007/s00234-016-1646-5.
Zhu Y, Bai L, Liang P, Kang S, Gao H, Yang H. Disrupted brain connectivity networks in acute ischemic stroke patients. Brain Imaging Behav. 2016;. doi:10.1007/s11682-016-9525-6.
Disclosure
The authors have nothing to disclose.
Founding
This work is supported by the Swiss National Science Foundation, the Foundation Elise et Carlo de Reuter, and the PKB Bank Foundation.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Dirren, E., Carrera, E. (2017). Resilience of Brain Networks After Stroke. In: Petrosini, L. (eds) Neurobiological and Psychological Aspects of Brain Recovery. Contemporary Clinical Neuroscience. Springer, Cham. https://doi.org/10.1007/978-3-319-52067-4_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-52067-4_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-52065-0
Online ISBN: 978-3-319-52067-4
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)