Early parietofrontal network upregulation relates to future persistent deficits after severe stroke-a prospective cohort study

Winifried Backhaus, Hanna Braaß, Focko L Higgen, Christian Gerloff, Robert Schulz, Winifried Backhaus, Hanna Braaß, Focko L Higgen, Christian Gerloff, Robert Schulz

Abstract

Recent brain imaging has evidenced that parietofrontal networks show alterations after stroke which also relate to motor recovery processes. There is converging evidence for an upregulation of parietofrontal coupling between parietal brain regions and frontal motor cortices. The majority of studies though have included only moderately to mildly affected patients, particularly in the subacute or chronic stage. Whether these network alterations will also be present in severely affected patients and early after stroke and whether such information can improve correlative models to infer motor recovery remains unclear. In this prospective cohort study, 19 severely affected first-ever stroke patients (mean age 74 years, 12 females) were analysed which underwent resting-state functional MRI and clinical testing during the initial week after the event. Clinical evaluation of neurological and motor impairment as well as global disability was repeated after three and six months. Nineteen healthy participants of similar age and gender were also recruited. MRI data were used to calculate functional connectivity values between the ipsilesional primary motor cortex, the ventral premotor cortex, the supplementary motor area and the anterior and caudal intraparietal sulcus of the ipsilesional hemisphere. Linear regression models were estimated to compare parietofrontal functional connectivity between stroke patients and healthy controls and to relate them to motor recovery. The main finding was a significant increase in ipsilesional parietofrontal coupling between anterior intraparietal sulcus and the primary motor cortex in severely affected stroke patients (P <0.003). This upregulation significantly contributed to correlative models explaining variability in subsequent neurological and global disability as quantified by National Institute of Health Stroke Scale and modified Rankin Scale, respectively. Patients with increased parietofrontal coupling in the acute stage showed higher levels of persistent deficits in the late subacute stage of recovery (P <0.05). This study provides novel insights that parietofrontal networks of the ipsilesional hemisphere undergo neuroplastic alteration already very early after severe motor stroke. The association between early parietofrontal upregulation and future levels of persistent functional deficits and dependence from help in daily living might be useful in models to enhance clinical neurorehabilitative decision making.

Keywords: coupling; fMRI; functional connectivity; intraparietal sulcus; resting-state.

© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.

Figures

Graphical Abstract
Graphical Abstract
Figure 1
Figure 1
Stroke lesions and motor network ROIs. All masks of stroke lesions are displayed on the left hemisphere, overlaying a T1-weighted template in MNI space (z-coordinates below each slice). The colour intensity indicates the number of subjects of whom lesion voxels lay within the coloured region. Motor ROIs (M1, PMV, SMA, AIPS and CIPS) are displayed respective to the stroke lesions.
Figure 2
Figure 2
Functional connectivity of the ipsilesional hemisphere. Coloured lines indicate significant coupling estimates for each group (left; P <0.05, FDR-corrected for 20 tests over both groups) or significant absolute group difference for AIPS-M1 (right; P <0.05, FDR corrected for 10 tests).
Figure 3
Figure 3
Influence of ipsilesional AIPS-M1 functional connectivity on future persistent deficits after stroke. Effect plots are shown for AIPS-M1 functional connectivity (FC) of the ipsilesional hemisphere contributing to the explanation of variability in follow-up NIHSS, UEFM, MRS and BI in severe stroke patients. P-value of FC AIPS-M1 as the predictor of interest (within-model) is given (uncorrected). There were significant associations between AIPS-M1 FC at T1 and MRS and NIHSS at T2/3 with higher FC values early after stroke found in patients which are likely to show more severe persistent deficits in follow-up, independent from the initial impairment level. A similar correlation was not detected for UEFM or BI.

References

    1. Grefkes C, Fink GR.. Reorganization of cerebral networks after stroke: New insights from neuroimaging with connectivity approaches. Brain. 2011;134(5):1264–1276.doi:10.1093/brain/awr033
    1. Rehme AK, Eickhoff SB, Rottschy C, Fink GR, Grefkes C.. Activation likelihood estimation meta-analysis of motor-related neural activity after stroke. Neuroimage. 2012;59(3):2771–2782.
    1. Koch G, Fernandez Del Olmo M, Cheeran B, et al.Focal stimulation of the posterior parietal cortex increases the excitability of the ipsilateral motor cortex. J Neurosci. 2007;27(25):6815–6822.
    1. Koch G, Cercignani M, Pecchioli C, et vivo definition of parieto-motor connections involved in planning of grasping movements. Neuroimage. 2010;51(1):300–312.
    1. Vingerhoets G. Contribution of the posterior parietal cortex in reaching, grasping, and using objects and tools. Front Psychol. 2014;5:151.
    1. Allart E, Devanne H, Delval A.. Contribution of transcranial magnetic stimulation in assessing parietofrontal connectivity during gesture production in healthy individuals and brain-injured patients. Neurophysiol Clin. 2019;49(2):115–123.
    1. Koch P, Schulz R, Hummel FC.. Structural connectivity analyses in motor recovery research after stroke. Ann Clin Transl Neurol. 2016;3(3):233–244.
    1. Rehme AK, Grefkes C.. Cerebral network disorders after stroke: Evidence from imaging-based connectivity analyses of active and resting brain states in humans. J Physiol. 2013;591(1):17–31.
    1. Buch ER, Modir Shanechi A, Fourkas AD, Weber C, Birbaumer N, Cohen LG.. Parietofrontal integrity determines neural modulation associated with grasping imagery after stroke. Brain. 2012;135(2):596–614.
    1. Wu J, Quinlan EB, Dodakian L, et al.Connectivity measures are robust biomarkers of cortical function and plasticity after stroke. Brain. 2015;138(8):2359–2369.
    1. Wang L, Yu C, Chen H, et al.Dynamic functional reorganization of the motor execution network after stroke. Brain. 2010;133(4):1224–1238.
    1. Park C, Chang WH, Ohn SH, et al.Longitudinal changes of resting-state functional connectivity during motor recovery after stroke. Stroke. 2011;42(5):1357–1362.
    1. Zhang Y, Liu H, Wang L, et al.Relationship between functional connectivity and motor function assessment in stroke patients with hemiplegia: A resting-state functional MRI study. Neuroradiology. 2016;58(5):503–511.
    1. Schulz R, Buchholz A, Frey BM, et al.Enhanced effective connectivity between primary motor cortex and intraparietal sulcus in well-recovered stroke patients. Stroke. 2016;47(2):482–489.
    1. Bönstrup M, Schulz R, Schön G, et al.Parietofrontal network upregulation after motor stroke. NeuroImage Clin. 2018;18:720–729.
    1. Schönle PW. Der Frühreha-Barthelindex (FRB) – eine frührehabilitationsorientierte Erweiterung des Barthelindex. Rehabilitation. 1995;34:69–73.
    1. Bernhardt J, Hayward KS, Kwakkel G, et al.Agreed definitions and a shared vision for new standards in stroke recovery research: The Stroke Recovery and Rehabilitation Roundtable taskforce. Neurorehabil Neural Repair. 2017;31(9):793–799.
    1. Yushkevich PA, Piven J, Hazlett HC, et al.User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. Neuroimage. 2006;31(3):1116–1128.
    1. Guder S, Frey BM, Backhaus W, et al.The influence of cortico-cerebellar structural connectivity on cortical excitability in chronic stroke. Cereb Cortex. 2020;30(3):1330–1344.
    1. Whitfield-Gabrieli S, Nieto-Castanon A.. Conn: A functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connect. 2012;2(3):125–141.
    1. Behzadi Y, Restom K, Liau J, Liu TT.. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage. 2007;37(1):90–101.
    1. Murphy K, Birn RM, Handwerker DA, Jones TB, Bandettini PA.. The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced? Neuroimage. 2009;44(3):893–905.
    1. Wu P, Zeng F, Li YX, et al.Changes of resting cerebral activities in subacute ischemic stroke patients. Neural Regen Res. 2015;10(5):760–765.
    1. Hallquist MN, Hwang K, Luna B.. The nuisance of nuisance regression: Spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity. Neuroimage. 2013;82:208–225.
    1. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2019.
    1. Benjamini Y, Hochberg Y.. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc Ser B. 1995;57(1):289–300.
    1. Koch PJ, Hummel FC.. Toward precision medicine. Curr Opin Neurol. 2017;30(4):388–397.
    1. 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):756–768.
    1. Alstott J, Breakspear M, Hagmann P, Cammoun L, Sporns O.. Modeling the impact of lesions in the human brain. In: Friston KJ, ed. PLoS Comput Biol. 2009;5(6):e1000408.
    1. Schulz R, Koch P, Zimerman M, et al.Parietofrontal motor pathways and their association with motor function after stroke. Brain. 2015;138(7):1949–1960.
    1. Welniarz Q, Dusart I, Roze E.. The corticospinal tract: Evolution, development, and human disorders. Dev Neurobiol. 2017;77(7):810–829.
    1. Schulz R, Park C-H, Boudrias M-H, Gerloff C, Hummel FC, Ward NS.. Assessing the integrity of corticospinal pathways from primary and secondary cortical motor areas after stroke. Stroke. 2012;43(8):2248–2251.
    1. Liu J, Wang C, Qin W, et al.Corticospinal fibers with different origins impact motor outcome and brain after subcortical stroke. Stroke. 2020;51(7):2170–2178.
    1. Baldwin MKL, Cooke DF, Goldring AB, Krubitzer L.. Representations of fine digit movements in posterior and anterior parietal cortex revealed using long-train intracortical microstimulation in macaque monkeys. Cereb Cortex. 2018;28(12):4244–4263.
    1. Rathelot J-A, Dum RP, Strick PL.. Posterior parietal cortex contains a command apparatus for hand movements. Proc Natl Acad Sci. 2017;114(16):4255–4260.
    1. Innocenti GM, Caminiti R, Rouiller EM, et al.Diversity of cortico-descending projections: Histological and diffusion MRI characterization in the monkey. Cereb Cortex. 2019;29(2):788–801.
    1. Nioche C, Cabanis EA, Habas C.. Functional connectivity of the human red nucleus in the brain resting state at 3T. Am J Neuroradiol. 2009;30(2):396–403.
    1. Tscherpel C, Hensel L, Lemberg K, et al.The differential roles of contralesional frontoparietal areas in cortical reorganization after stroke. Brain Stimul. 2020;13(3):614–624.
    1. Baldassarre A, Ramsey L, Hacker CL, et al.Large-scale changes in network interactions as a physiological signature of spatial neglect. Brain. 2014;137(12):3267–3283.
    1. Nyffeler T, Vanbellingen T, Kaufmann BC, et al.Theta burst stimulation in neglect after stroke: Functional outcome and response variability origins. Brain. 2019;142(4):992–1008.
    1. Schulz R, Gerloff C, Hummel FC.. Non-invasive brain stimulation in neurological diseases. Neuropharmacology. 2013;64:579–587.
    1. Zhou RJ, Hondori HM, Khademi M, et al.Predicting gains with visuospatial training after stroke using an EEG measure of frontoparietal circuit function. Front Neurol. 2018;9:597
    1. Abela E, Missimer J, Wiest R, et al.Lesions to primary sensory and posterior parietal cortices impair recovery from hand paresis after stroke. PLoS One. 2012;7(2):e31275.
    1. Kim RG, Cho J, Ree J, et al.Sensory-parietal cortical stimulation improves motor recovery in severe capsular infarct. J Cereb Blood Flow Metab. 2016;36(12):2211–2222.
    1. Bonkhoff AK, Espinoza FA, Gazula H, et al.Acute ischaemic stroke alters the brain’s preference for distinct dynamic connectivity states. Brain. 2020;143(5):1525–1540.

Source: PubMed

3
Abonneren