PMID- 24098860
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20131007
LR  - 20211021
IS  - 2228-7477 (Print)
IS  - 2228-7477 (Electronic)
IS  - 2228-7477 (Linking)
VI  - 3
IP  - 2
DP  - 2013 Apr
TI  - 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.
PG  - 69-78
AB  - Parkinson's disease (PD) is a progressive neurological disorder characterized by 
      tremor, rigidity, and slowness of movements. Particular changes related to 
      various pathological attacks in PD could result in causal interactions of the 
      brain network from resting state functional magnetic resonance imaging (rs-fMRI) 
      data. In this paper, we aimed to disclose the network structure of the directed 
      influences over the brain using multivariate Granger causality analysis and graph 
      theory in patients with PD as compared with control group. rs-fMRI at rest from 
      10 PD patients and 10 controls were analyzed. Topological properties of the 
      networks showed that information flow in PD is smaller than that in healthy 
      individuals. We found that there is a balanced local network in healthy control 
      group, including positive pair-wise cross connections between caudate and 
      cerebellum and reciprocal connections between motor cortex and caudate in the 
      left and right hemispheres. The results showed that this local network is 
      disrupted in PD due to disturbance of the interactions in the motor networks. 
      These findings suggested alteration of the functional organization of the brain 
      in the resting state that affects the information transmission from and to other 
      brain regions related to both primary dysfunctions and higher-level cognition 
      impairments in PD. Furthermore, we showed that regions with high degree values 
      could be detected as betweenness centrality nodes. Our results demonstrate that 
      properties of small-world connectivity could also recognize and quantify the 
      characteristics of directed influence brain networks in PD.
FAU - Ghasemi, Mahdieh
AU  - Ghasemi M
AD  - Department of Electrical and Computer Engineering, Tarbiat Modares University, 
      Tehran, Iran.
FAU - Mahloojifar, Ali
AU  - Mahloojifar A
LA  - eng
PT  - Journal Article
PL  - India
TA  - J Med Signals Sens
JT  - Journal of medical signals and sensors
JID - 101577416
PMC - PMC3788196
OTO - NOTNLM
OT  - Functional magnetic resonance imaging
OT  - graph theory
OT  - multivariate granger causality analysis
OT  - parkinson's disease
OT  - resting state
COIS- Conflict of Interest: None declared
EDAT- 2013/10/08 06:00
MHDA- 2013/10/08 06:01
PMCR- 2013/04/01
CRDT- 2013/10/08 06:00
PHST- 2012/11/19 00:00 [received]
PHST- 2013/02/17 00:00 [accepted]
PHST- 2013/10/08 06:00 [entrez]
PHST- 2013/10/08 06:00 [pubmed]
PHST- 2013/10/08 06:01 [medline]
PHST- 2013/04/01 00:00 [pmc-release]
AID - JMSS-3-69 [pii]
PST - ppublish
SO  - J Med Signals Sens. 2013 Apr;3(2):69-78.