Exploratory study of the effect of brain tumors on the default mode network

Resting state functional magnetic resonance imaging (RS-fMRI) is a popular method of visualizing functional networks in the brain. One of these networks, the default mode network (DMN), has exhibited altered connectivity in a variety of pathological states, including brain tumors. However, very few studies have attempted to link the effect of tumor localization, type and size on DMN connectivity. We collected RS-fMRI data in 73 patients with various brain tumors and attempted to characterize the different effects these tumors had on DMN connectivity based on their location, type and size. This was done by comparing the tumor patients with healthy controls using independent component analysis (ICA) and seed based analysis. We also used a multi-seed approach described in the paper to account for anatomy distortion in the tumor patients. We found that tumors in the left hemisphere had the largest effect on DMN connectivity regardless of their size and type, while this effect was not observed for right hemispheric tumors. Tumors in the cerebellum also had statistically significant effects on DMN connectivity. These results suggest that DMN connectivity in the left side of the brain may be more fragile to insults by lesions.

[1]  Fenna M. Krienen,et al.  Segregated Fronto-Cerebellar Circuits Revealed by Intrinsic Functional Connectivity , 2009, Cerebral cortex.

[2]  P. Matthews,et al.  Distinct patterns of brain activity in young carriers of the APOE e4 allele , 2009, NeuroImage.

[3]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[4]  M. Greicius,et al.  Decoding subject-driven cognitive states with whole-brain connectivity patterns. , 2012, Cerebral cortex.

[5]  Kevin Murphy,et al.  Resting-state fMRI confounds and cleanup , 2013, NeuroImage.

[6]  E. Bagarinao,et al.  Evaluation of Resting State Networks in Patients with Gliomas: Connectivity Changes in the Unaffected Side and Its Relation to Cognitive Function , 2015, PloS one.

[7]  R. Thatcher,et al.  Spatial-Temporal Current Source Correlations and Cortical Connectivity , 2007, Clinical EEG and neuroscience.

[8]  D. Tucker,et al.  Functional connections among cortical regions: topography of EEG coherence. , 1986, Electroencephalography and clinical neurophysiology.

[9]  Katherine E. Prater,et al.  Distinct Cerebellar Contributions to Intrinsic Connectivity Networks , 2009, NeuroImage.

[10]  G. Chételat,et al.  [The default mode network: cognitive role and pathological disturbances]. , 2010, Revue neurologique.

[11]  Chaozhe Zhu,et al.  Hemispheric asymmetry in cognitive division of anterior cingulate cortex: A resting-state functional connectivity study , 2009, NeuroImage.

[12]  Chunshui Yu,et al.  Altered spontaneous activity in the default-mode network and cognitive decline in chronic subcortical stroke , 2014, Journal of the Neurological Sciences.

[13]  Giacomo Koch,et al.  Abnormal Asymmetry of Brain Connectivity in Schizophrenia , 2014, Front. Hum. Neurosci..

[14]  Francesca Baglio,et al.  High-Dimensional ICA Analysis Detects Within-Network Functional Connectivity Damage of Default-Mode and Sensory-Motor Networks in Alzheimer’s Disease , 2015, Front. Hum. Neurosci..

[15]  M. Jalili.  Hemispheric asymmetry of electroencephalography-based functional brain networks , 2014, Neuroreport.

[16]  Stephen M. Smith,et al.  The future of FMRI connectivity , 2012, NeuroImage.

[17]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[18]  P. Strick,et al.  Anatomical evidence for cerebellar and basal ganglia involvement in higher cognitive function. , 1994, Science.

[19]  Gian Luca Romani,et al.  Modifications of Default-Mode Network Connectivity in Patients with Cerebral Glioma , 2012, PloS one.

[20]  Manuel Graña,et al.  Impairment of functional integration of the default mode network correlates with cognitive outcome at three months after stroke , 2014, Human brain mapping.

[21]  Jeroen van der Grond,et al.  Imaging the default mode network in aging and dementia. , 2012, Biochimica et biophysica acta.

[22]  P. Strick,et al.  Cerebellar Projections to the Prefrontal Cortex of the Primate , 2001, The Journal of Neuroscience.

[23]  Stephen M. Smith,et al.  Permutation inference for the general linear model , 2014, NeuroImage.

[24]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[25]  R W Cox,et al.  Software tools for analysis and visualization of fMRI data , 1997, NMR in biomedicine.

[26]  S. Debener,et al.  Default-mode brain dysfunction in mental disorders: A systematic review , 2009, Neuroscience & Biobehavioral Reviews.

[27]  C. Rorden,et al.  Stereotaxic display of brain lesions. , 2000, Behavioural neurology.

[28]  Andrei V. Medvedev,et al.  Does the resting state connectivity have hemispheric asymmetry? A near-infrared spectroscopy study , 2014, NeuroImage.

[29]  F. Eustache,et al.  [The default mode network: cognitive role and pathological disturbances]. , 2010, Revue neurologique.

[30]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[31]  Susan Y. Bookheimer,et al.  Altered functional connectivity of the default mode network in diffuse gliomas measured with pseudo-resting state fMRI , 2013, Journal of Neuro-Oncology.