Document Type : Full Research Paper


Assistant Professor, Department of Electrical Engineering, Biomedical Engineering Lab, University of Neyshabur, Neyshabur, Iran


Parkinson’s disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Different pathological attacks in Parkinson’s disease can be investigated by directional relations in the base spontaneous fluctuations of the brain from the resting state functional magnetic resonance imaging (RS-fMRI) data. In this paper, for analyzing the directional brain network at rest, Directed Transform Function (DTF) technique with graph theory has been used in two frequency sub-bands and intra/inter group connectivities were compared by statistical analysis. The result of group comparison between PD and healthy which has been done, showed that there are more significant connections in the low frequency band in Parkinson’s disease and control group compared to high frequency band. The relation between basal ganglia and cerebellum has been disturebed in Parkinson’s disease. Furthermore, some brain regions such as left cerebellum has the most information flow in healthy group which characterized by pivotal regions which were influenced by the other brain regions, this connection became disordered in Parkinsonism.


Main Subjects

[1]     M. De Luca, C. Beckmann, N. De Stefano, P. Matthews, and S. M. Smith, "fMRI resting state networks define distinct modes of long-distance interactions in the human brain," Neuroimage, vol. 29, no. 4, pp. 1359-1367, 2006.
[2]     M. Daliri and M. Behroozi, "FMRI: clinical and research applications," OMICS J. Radiology, vol. 1, p. e112, 2012.
[3]     K. J. Friston, "Functional and effective connectivity: a review," Brain connectivity, vol. 1, no. 1, pp. 13-36, 2011.
[4]     F. Babiloni et al., "Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function," Neuroimage, vol. 24, no. 1, pp. 118-131, 2005.
[5]     B. Biswal, F. Zerrin Yetkin, V. M. Haughton, and J. S. Hyde, "Functional connectivity in the motor cortex of resting human brain using echo‐planar mri," Magnetic resonance in medicine, vol. 34, no. 4, pp. 537-541, 1995.
[6]     M. D. Greicius, B. Krasnow, A. L. Reiss, and V. Menon, "Functional connectivity in the resting brain: a network analysis of the default mode hypothesis," Proceedings of the National Academy of Sciences, vol. 100, no. 1, pp. 253-258, 2003.
[7]     Q. Gao, H. Chen, and Q. Gong, "Evaluation of the effective connectivity of the dominant primary motor cortex during bimanual movement using Granger causality," Neuroscience letters, vol. 443, no. 1, pp. 1-6, 2008.
[8]     A. K. Seth, "Causal connectivity of evolved neural networks during behavior," Network: Computation in Neural Systems, vol. 16, no. 1, pp. 35-54, 2005.
[9]     R. C. Helmich, L. C. Derikx, M. Bakker, R. Scheeringa, B. R. Bloem, and I. Toni, "Spatial remapping of cortico-striatal connectivity in Parkinson's disease," Cerebral cortex, vol. 20, no. 5, pp. 1175-1186, 2009.
[10] T. Wu, L. Wang, M. Hallett, Y. Chen, K. Li, and P. Chan, "Effective connectivity of brain networks during self-initiated movement in Parkinson's disease," Neuroimage, vol. 55, no. 1, pp. 204-215, 2011.
[11] S. Baudrexel et al., "Resting state fMRI reveals increased subthalamic nucleus–motor cortex connectivity in Parkinson's disease," Neuroimage, vol. 55, no. 4, pp. 1728-1738, 2011.
[12] T. Wu, L. Wang, Y. Chen, C. Zhao, K. Li, and P. Chan, "Changes of functional connectivity of the motor network in the resting state in Parkinson's disease," Neuroscience letters, vol. 460, no. 1, pp. 6-10, 2009.
[13] W. H. Thompson and P. Fransson, "The frequency dimension of fMRI dynamic connectivity: network connectivity, functional hubs and integration in the resting brain," NeuroImage, vol. 121, pp. 227-242, 2015.
[14] M. Daliri and M. Behroozi, "Advantages and disadvantages of resting state functional connectivity magnetic resonance imaging for clinical applications," OMICS J Radiology, vol. 3, p. e123, 2013.
[15] S. Jaeger et al., "Multiple sclerosis–related fatigue: Altered resting-state functional connectivity of the ventral striatum and dorsolateral prefrontal cortex," Multiple Sclerosis Journal, p. 1352458518758911, 2018.
[16] S. Herrera, P. D. Butler, V. Zemon, D. C. Javitt, and M. J. Hoptman, "S250. Associations Between Contrast Processes and Resting-State Functional Connectivity in Patients With Schizophrenia and Healthy Controls," Biological Psychiatry, vol. 83, no. 9, p. S445, 2018.
[17] T. J. Silk, C. Malpas, A. Vance, and M. A. Bellgrove, "The effect of single-dose methylphenidate on resting-state network functional connectivity in ADHD," Brain imaging and behavior, vol. 11, no. 5, pp. 1422-1431, 2017.
[18] B. L. Klaassens, J. van Gerven, J. van der Grond, F. de Vos, C. Möller, and S. A. Rombouts, "Diminished Posterior Precuneus Connectivity with the Default Mode Network Differentiates Normal Aging from Alzheimer's Disease," Frontiers in aging neuroscience, vol. 9, p. 97, 2017.
[19] M. P. Lopez-Larson et al., "Abnormal functional connectivity between default and salience networks in pediatric bipolar disorder," Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, vol. 2, no. 1, pp. 85-93, 2017.
[20] M. D. Greicius et al., "Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus," Biological psychiatry, vol. 62, no. 5, pp. 429-437, 2007.
[21] J. Fang et al., "Impaired brain network architecture in newly diagnosed Parkinson’s disease based on graph theoretical analysis," Neuroscience letters, vol. 657, pp. 151-158, 2017.
[22] M. Ghasemi, A. Mahloojifar, M. Zarei, and A. Ferdosi-makan, "Changes of localized spontaneous activity and connectivity in resting state fMRI data of Parkinson disease," in Biomedical Engineering and Sciences (IECBES), 2010 IEEE EMBS Conference on, 2010, pp. 325-329: IEEE.
[23] J. Wang, X. Zuo, and Y. He, "Graph-based network analysis of resting-state functional MRI," Frontiers in systems neuroscience, vol. 4, p. 16, 2010.
[24] D. S. Bassett and E. Bullmore, "Small-world brain networks," The neuroscientist, vol. 12, no. 6, pp. 512-523, 2006.
[25] S. Hayasaka and P. J. Laurienti, "Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data," Neuroimage, vol. 50, no. 2, pp. 499-508, 2010.
[26] D. S. Bassett and E. T. Bullmore, "Small-world brain networks revisited," The Neuroscientist, vol. 23, no. 5, pp. 499-516, 2017.
[27] W. Liao et al., "Small-world directed networks in the human brain: multivariate Granger causality analysis of resting-state fMRI," Neuroimage, vol. 54, no. 4, pp. 2683-2694, 2011.
[28] M. Ghasemi and A. Mahloojifar, "Directed Transform Function approach for functional network analysis in resting state fMRI data of Parkinson disease," in Biomedical Engineering (ICBME), 2012 19th Iranian Conference of, 2012, pp. 223-228: IEEE.
[29] M. Ghasemi and A. Mahloojifar, "Disorganization of equilibrium directional interactions in the brain motor network of Parkinson's disease: new insight of resting state analysis using Granger causality and graphical approach," Journal of medical signals and sensors, vol. 3, no. 2, p. 69, 2013.
[30] S. M. Smith et al., "Advances in functional and structural MR image analysis and implementation as FSL," Neuroimage, vol. 23, pp. S208-S219, 2004.
[31] M. Behroozi, M. R. Daliri, and H. Boyaci, "Statistical analysis methods for the fMRI data," Basic and Clinical Neuroscience, vol. 2, no. 4, pp. 67-74, 2011.
[32] A. C. Kelly, L. Q. Uddin, B. B. Biswal, F. X. Castellanos, and M. P. Milham, "Competition between functional brain networks mediates behavioral variability," Neuroimage, vol. 39, no. 1, pp. 527-537, 2008.
[33] E. Bullmore and O. Sporns, "Complex brain networks: graph theoretical analysis of structural and functional systems," Nature Reviews Neuroscience, vol. 10, no. 3, p. 186, 2009.
[34] R. Caslake, J. N. Moore, J. C. Gordon, C. E. Harris, and C. Counsell, "Changes in diagnosis with follow-up in an incident cohort of patients with parkinsonism," Journal of Neurology, Neurosurgery & Psychiatry, vol. 79, no. 11, pp. 1202-1207, 2008.
[35] A. Galvan and T. Wichmann, "Pathophysiology of parkinsonism," Clinical Neurophysiology, vol. 119, no. 7, pp. 1459-1474, 2008.
[36] H. Akaike, "A new look at the statistical model identification," IEEE transactions on automatic control, vol. 19, no. 6, pp. 716-723, 1974.
[37] H. Yu, D. Sternad, D. M. Corcos, and D. E. Vaillancourt, "Role of hyperactive cerebellum and motor cortex in Parkinson's disease," Neuroimage, vol. 35, no. 1, pp. 222-233, 2007.
[38] A. K. Seth, "A MATLAB toolbox for Granger causal connectivity analysis," Journal of neuroscience methods, vol. 186, no. 2, pp. 262-273, 2010.