Loading...
Model Based Analysis of tDCS Effects on Brain Networks in Methamphetamine Addicts
Hariri, Ali | 2015
891
Viewed
- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 47325 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Fatemizadeh, Emadodin; Ekhtiari, Hamed
- Abstract:
- Despite intensive scientific investigations, drug addiction treatment outcomes have not significantly improved in more than 30 years. The addicted human brain can be conceptualized as a set of networks that spatially and temporally interact with each other in an abnormal way. Over the past several decades, neuroimaging techniques have contributed important novel insights into the neuroplastic alterations that result from drug dependence. Also functional connectivity magnetic resonance imaging (fcMRI) has emerged as a powerful tool for mapping large-scale networks in the human brain. On the other hand, transcranial direct current stimulation (tDCS) has been reintroduced as a noninvasive brain stimulation tool suited to alter cortical excitability and activity via the application of weak direct current. In addition, tDCS-induced effects might modulate functional connectivity between segregated cortical areas. Therefore it would be a reasonable hypothesis that, tDCS could make effective modulation on the abnormal organization of functional large scale networks in drug dependents. In this study, these possible effects of anodal tDCS supplied over right dorsolateral prefrontal cortex (rDPLFC) on resting state networks are studied. Large-scale brain networks such as default mode network (DMN), executive control network (ECN) and saliency network (SN) have pivotal role in addiction medicine. These networks are monitored using functional MRI (fMRI) before and after brain stimulation. Fifteen male right handed abstinent methamphetamine dependents were recruited after giving written informed.The experiment was a randomized double blinded sham controlled crossover study. All subjects received two types of DC stimulation (real and sham) in two separate days. Each subject was counterbalanced across in two stimulation types and two separates days with one week interval as a wash out period. Neither subjects nor investigator were aware of stimulation type. The resting-state fMRI acquired before and after real/sham stimulation. In order to extract the networks, 4D functional images were processed by FSL 5.0.4 and AFNI software. Our processing method is seed based correlation. In order to identify significant clusters for desired networks (Monte Carlo simulated correction; a = 0.05 voxel-wise p<0.01, cluster size>726 mm3), we applied one sample t-test for each conditions (before (baseline 1) and after (P-active) real tDCS, before (baseline 2) and after (P- sham) sham tDCS). To find effect of tDCS on the three resting state networks, the contrasts (P-active > baseline1) > (P-sham > baseline2) were examined by two-sample paired t-test. The results were considered statistically significant by Monte Carlo stimulation algorithm (a = 0.05, voxel-wise p<0.05, cluster size >4089 mm3). The analysis show that, DMN, ECN and SN were significantly modulated after real tDCS. This study shows real tDCS on the rDLPFC lead to significant reconfigured large-scale networks functional connectivity. In detail definition, DMN activation was scaled down where ECN and SN were increased. We speculate these alterations may explain the decrease self-report craving in methamphetamine users after anodal stimulation. Given that changes in the intrinsic activity of brain networks of methamphetamine users can be obtained by tDCS, we can ensure this method have a robust effect on the treatment of the addiction
- Keywords:
- Electrical Stimulation ; Functional Magnetic Resonance Imaging (FMRI) ; Model-Based Reasoning ; Transcranial Direct Current Stimulation (tDCS) ; Resting State Brain ; Functional Networks ; Methamphtamine
- محتواي کتاب
- view