Shared Microstructural Features of Behavioral and Substance Addictions Revealed in Areas of Crossing Fibers

Abstract

Background Similarities between behavioral and substance addictions exist. However, direct neurobiological comparison between addictive disorders is rare. Determination of disorder-specificity (or lack thereof) of alterations within white-matter microstructures will advance understanding of the pathophysiology of addictions. Methods We compared white-matter microstructural features between individuals with gambling disorder (GD; n=38), cocaine-use disorder (CUD; n=38) and healthy comparison (HC; n=38) participants, as assessed using diffusion-weighted magnetic resonance imaging (dMRI). To provide a more precise estimate of diffusion within regions of complex architecture (e.g., cortico-limbic tracts), analyses were conducted using a crossing-fiber model incorporating local-orientation modeling (tbss_x). Anisotropy estimates for primary and secondary fiber orientations were compared using ANOVAs corrected for multiple comparisons across space using threshold-free cluster enhancement (pFWE<.05). Results A main effect of group on anisotropy of secondary fiber orientations within the left internal capsule, corona radiata, forceps major and posterior thalamic radiation, involving reduced anisotropy among GD and CUD participants in comparison to HC participants. No differences in anisotropy measures were found between GD and CUD individuals. Conclusions This is the first study to compare diffusion indices directly between behavioral and substance addictions and the largest dMRI study of GD. Our findings indicate similar white-matter microstructural alterations across addictions that cannot be attributed solely to exposure to drugs or alcohol and thus may be a vulnerability mechanism for addictive disorders.

White-matter crossing-fiber microstructure in adolescents prenatally exposed to cocaine

“…As in our prior work, (Yip, 2016b), FSL software was used to analyze the dMRI data. Tract-based spatial statistics (TBSS) procedures were used, which incorporate both diffusion-tensor and crossing-fiber models (Jbabdi et al, 2010; Reveley et al, 2015; Smith et al, 2006b).…”

“…Tract-based spatial statistics (TBSS) procedures were used, which incorporate both diffusion-tensor and crossing-fiber models (Jbabdi et al, 2010; Reveley et al, 2015; Smith et al, 2006b). Voxel-wise statistical analysis of the FA data was carried out using TBSS (Tract-Based Spatial Statistics, (Smith et al, 2006a), part of FSL (Smith et al, 2004), as was done in our previous work (Yip, 2016b). First, FA images were created by fitting a tensor model to the raw diffusion data using FSL’s Diffusion Toolbox (FDT) (Behrens et al, 2007; Behrens et al, 2003).…”

“…This technique provides estimates of anisotropy for different fiber orientations (e.g., primary (F1) and secondary (F2) orientations) that may be interpreted within regions of complex architecture (regions containing more than one fiber orientation per voxel; estimated to include up to 90% of white-matter-containing voxels (Jeurissen et al, 2013)) with less ambiguity than traditional measures such as FA and other tensor-based indices (Baumgartner et al, 2015; Reveley et al, 2015). This crossing-fiber approach has recently been used to study adults with addictions (Savjani et al, 2014; Yip, 2016b) and is proposed to be a more comprehensive examination of white matter. This model will provide a comprehensive examination of white matter that is suitable for a population in which differences in white matter from prenatally non-exposed youth may be subtle.…”

A preliminary longitudinal study of white matter alteration in cocaine use disorder subjects

“…Though there exist exceptions (e.g., Kelly et al, 2011), the majority of previous DTI studies (Moeller et al, 2005; 2007; Lim et al, 2002; 2008; Ma et al, 2009; 2015; Lane et al, 2010; Romero et al, 2010; Xu et al, 2010; Bell et al, 2011; Nakamura-Palacios, 2016; Yip et al, 2016) have reproducibly shown that cocaine use disorder (CocUD) is associated with white matter alterations, with consistent findings in the corpus callosum (Moeller et al, 2005; 2007; Ma et al, 2009; 2005; Lane et al, 2010; Xu et al, 2010; Bell et al, 2011). The white matter alterations found in CocUD may be related to impulsivity (Moeller et al, 2005), decision-making (Lane et al, 2010), treatment outcomes (Xu et al, 2010), or abstinence duration (Bell et al, 2011).…”

Tecnologías de la Información y la Comunicación (TIC): abuso de Internet, videojuegos, teléfonos móviles, mensajería instantánea y redes sociales mediante el MULTICAGE-TIC

“…Un buen número de trabajos neurocientíficos ha encontrado que, como en el caso de la adicción a sustancias, los déficits en el funcionamiento de la corteza prefrontal son elementos centrales de las adicciones comportamentales que explican la pérdida de control superior sobre la conducta problema (Blum et al, 2015;Brand, Young y Laier, 2014; de Ruiter, Oosterlaan, Veltman, van den Brink y Goudriaan, 2012) y que pueden encontrarse similitudes importantes entre ambas modalidades en estructuras cerebrales como la sustancia blanca (Yip et al, 2016).…”