Recent studies have shown that aging, psychiatric and neurologic diseases, and dopaminergic blockade all result in altered brain network efficiency. We investigated the efficiency of human brain functional networks as measured by fMRI in individuals with idiopathic Parkinson's disease (N=14) compared to healthy age-matched controls (N=15). Functional connectivity between 116 cortical and subcortical regions was estimated by wavelet correlation analysis in the frequency interval of 0.06-0.12 Hz. Efficiency of the associated network was analyzed, comparing PD to healthy controls. We found that individuals with Parkinson's disease had a marked decrease in nodal and global efficiency compared to healthy age-matched controls. Our results suggest that algorithmic approach and graph metrics might be used to identify and track neurodegenerative diseases, however more studies will be needed to evaluate utility of this type of analysis for different disease states.
"Using each individual data set of the normalized BOLD signal time course, Pearson's correlation coefficients was calculated between each pair the 62 ROIs, resulting in a symmetric 62 × 62 correlation matrix. Applying the cost-threshold approach on the 62 × 62 correlation matrix, we first checked the cost, which indicated small-world network property, showing global efficiency is less than random network but greater than a regular lattice network , and local efficiency is more than random network (Achard et al., 2006; Achard and Bullmore, 2007; Skidmore et al., 2011; Carbonell et al., 2014), in the HV and PD patients, respectively. Cost efficiency (global efficiency – cost) was calculated to see the economical cost, while maximizing the cost efficiency during the task, the HV and PD patients, respectively. "
[Show abstract][Hide abstract] ABSTRACT: The basal ganglia (BG) are thought to be involved in the integration of multiple sources of information, and their dysfunction can lead to disorders such as Parkinson's disease (PD). PD patients show motor and cognitive dysfunction with specific impairments in the internal generation of motor actions and executive deficits, respectively. The role of the BG, then, would be to integrate information from several sources in order to make a decision on a resulting action adequate for the required task. Reanalyzing the data set from our previous study (Martinu et al., 2012), we investigated this hypothesis by applying a graph theory method to a series of fMRI data during the performance of self-initiated (SI) finger movement tasks obtained in healthy volunteers (HV) and early stage PD patients. Dorsally, connectivity strength between the medial prefrontal areas (mPFC) and cortical regions including the primary motor area (M1), the extrastriate visual cortex, and the associative cortex, was reduced in the PD patients. The connectivity strengths were positively correlated to activity in the striatum in both groups. Ventrally, all connectivity between the striatum, the thalamus, and the extrastriate visual cortex decreased in strength in the PD, as did the connectivity between the striatum and the ventrolateral PFC (VLPFC). Individual response time (RT) was negatively correlated to connectivity strength between the dorsolateral PFC (DLPFC) and the striatum and positively correlated to connectivity between the VLPFC and the striatum in the HV. These results indicate that the BG, with the mPFC and thalamus, are involved in integrating multiple sources of information from areas such as DLPFC, and VLPFC, connecting to M1, thereby determining a network that leads to the adequate decision and performance of the resulting action.
Frontiers in Neuroscience 07/2014; 8(8):187. DOI:10.3389/fnins.2014.00187 · 3.66 Impact Factor
"To date, there are very few studies of PD employing graph theoretical framework for fMRI data analysis. Skidmore et al. found reduced whole-brain global efficiency in PD (Skidmore et al., 2011). Compared to healthy controls, 14 PD patients included in the study demonstrated reduced local efficiency (nodal level) in the precentral regions, primary and secondary visual cortex. "
[Show abstract][Hide abstract] ABSTRACT: Cognitive impairment is a common non-motor feature of Parkinson’s disease (PD). The current study aimed to investigate resting state fMRI correlates of cognitive impairment in PD from a large-scale network perspective, and to assess the impact of dopamine deficiency on these networks. Thirty PD patients with resting state fMRI were included from the Parkinson’s Progression Marker Initiative (PPMI) database. Eighteen patients from this sample were also scanned with 123I-FP-CIT SPECT. A standardized neuropsychological battery was administered, evaluating verbal memory, visuospatial, and executive cognitive domains. Image preprocessing was performed using an SPM8-based workflow, obtaining time-series from 90 regions-of-interest (ROIs) defined from the AAL brain atlas. The Brain Connectivity Toolbox was used to extract nodal strength from all ROIs and modularity of the cognitive circuitry determined using the meta-analytical software Neurosynth. Brain-behavior covariance patterns between cognitive functions and nodal strength were estimated using Partial Least Squares. Extracted latent variable scores were correlated with performances in the three cognitive domains and striatal dopamine transporter binding ratios (SBR) using linear modeling. Finally, influence of nigrostriatal dopaminergic deficiency on modularity of the "cognitive network" was analyzed. Less severe executive impairment was associated with increased dorsal fronto-parietal cortical processing and inhibited subcortical and primary sensory involvement. This pattern was positively influenced by the relative preservation of nigrostriatal dopaminergic function. The pattern associated with better memory performance favored prefronto-limbic processing, and did not reveal associations with presynaptic striatal dopamine uptake. SBR ratios were negatively associated with modularity of the "cognitive network", suggesting integrative effects of the preserved nigrostriatal dopamine system on this circuitry.
Frontiers in Systems Neuroscience 04/2014; 8(1):45. DOI:10.3389/fnsys.2014.00045
[Show abstract][Hide abstract] ABSTRACT: The brain is the characteristic of a complex structure. By representing brain function, measured with EEG, MEG, and fMRI, as an abstract network, methods for the study of complex systems can be applied. These network studies have revealed insights in the complex, yet organized, architecture that is evidently present in brain function. We will discuss some technical aspects of formation and assessment of the functional brain networks. Moreover, the results that have been reported in this respect in the last years, in healthy brains as well as in functional brain networks of subjects with a neurological or psychiatrical disease, will be reviewed.
European neuropsychopharmacology: the journal of the European College of Neuropsychopharmacology 11/2012; 23(1). DOI:10.1016/j.euroneuro.2012.10.010 · 4.37 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.