ABNORMAL RESTING-STATE EFFECTIVE CONNECTIVITY WITHIN THE DEFAULT MODE NETWORK IN COCAINE ADDICTION PATIENTS

Background and Aim : Effective connectivity analysis of resting-state functional magnetic resonance imaging (rsfMRI) data using spectral dynamic causal modeling (spDCM) has been widely used to investigate causal interactions between different regions. In this study we assess the effective connectivity between different components of the default mode network (DMN) including the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), and inferior parietal lobule (IPL) in cocaine addiction patients and healthy control subjects.Methods : The rsfMRI data were collected from 18 cocaine-dependent participants (age: 34.8 ± 8.7) in the NYU institute for Pediatric Neuroscience and 18 age-matched controls (age: 34.4 ± 8.9) from NewYork_a dataset of 1000 functional connectome. Pre-processing was performed using SPM12 (Statistical Parametric Mapping), includes slice-timing, head-motion correction, co-registration, segmentation, spatial smoothing and normalization. Six head motion parameters and CSF/WM signals were regressed out from the pre-processed signals filtered with in [0.009 - 0.1] HZ. To assess the effective connectivity differences between patients and controls, a fully connected model was used based on four regions of interest (mPFC, PCC, left IPL and right IPL). Mean time series was computed for each region of the two groups from the pre-processed rsfMRI data. We estimated the DCM parameters and coupling strength based on the standard variational Bayes procedures as implemented in SPM12. Then, the Bayesian reduction was used to provide more robust summary statistics for classical inference at the second level. The parameters from the best reduced model were averaged using Bayesian model averaging. Finally, the parametric empirical Bayesian model was used to investigate the commonalities and differences between the two groups. Results : Compared to controls, patients showed reduced effective connections from rIPL to lIPL, with reduced self-connection in PCC, mPFC and lIPL. However, the connection strength from PCC to lIPL showed significant increases in patients.Conclusion : Our findings suggest that the effective connectivity within the default mode network is altered in cocaine addiction patients in comparison with healthy subjects. Compared control, self-connections in DMN nodes, also coupling in the parietal cortex between left and right hemisphere are reduced in the cocaine addiction. These results confirm that in the resting state, between hemisphere connection and brain activity in the prefrontal-parietal networks are reduced in the addiction.

کلیدواژه ها:

Spectral dynamic causal modeling ، resting state fMRI ، Default mode network ، Addiction ، Effective connectivity