Ihre Suche

BACKGROUND: Nearly half of individuals with substance use disorders relapse in the year after treatment. A diagnostic tool to help clinicians make decisions regarding treatment does not exist for psychiatric conditions. Identifying individuals with high risk for relapse to substance use following abstinence has profound clinical consequences. This study aimed to develop neuroimaging as a robust tool to predict relapse. METHODS: 68 methamphetamine-dependent adults (15 female) were recruited from 28-day inpatient treatment. During treatment, participants completed a functional MRI scan that examined brain activation during reward processing. Patients were followed 1 year later to assess abstinence. We examined brain activation during reward processing between relapsing and abstaining individuals and employed three random forest prediction models (clinical and personality measures, neuroimaging measures, a combined model) to generate predictions for each participant regarding their relapse likelihood. RESULTS: 18 individuals relapsed. There were significant group by reward-size interactions for neural activation in the left insula and right striatum for rewards. Abstaining individuals showed increased activation for large, risky relative to small, safe rewards, whereas relapsing individuals failed to show differential activation between reward types. All three random forest models yielded good test characteristics such that a positive test for relapse yielded a likelihood ratio 2.63, whereas a negative test had a likelihood ratio of 0.48. CONCLUSIONS: These findings suggest that neuroimaging can be developed in combination with other measures as an instrument to predict relapse, advancing tools providers can use to make decisions about individualized treatment of substance use disorders.

There is some evidence that neuroimaging can be used to predict relapse among abstinent methamphetamine-dependent (MD) individuals. However, it remains unclear what cognitive and neural processes contribute to relapse. This investigation examined whether insula activation during risk-taking decisions-a process shown to be disrupted in MD-is able to predict susceptibility for relapse. Sixty-eight MD enrolled in a treatment program during early abstinence completed a risk-taking task during functional magnetic resonance imaging. Sixty-three of the sixty-eight individuals were followed up 1 year after the study. Of these, 18 MD reported relapse. The 45 abstinent MD showed patterns of insula activation during risky decisions that resembled those found in prior studies of healthy controls, consisting of lower insula activation during safe decisions paired with higher activation during risky decisions. In contrast, the 18 relapsed MD showed similar insula activation during safe and risky decisions. An increase in one standard deviation in the difference in insula activation between risky and safe choices was associated with a 0.34 odds ratio for relapse at any given time. A median split of insula activation (difference between risky and safe) showed that individuals in the bottom half were two times more likely to relapse. In addition, a model that included several other brain regions increased prediction accuracy compared with insula-based model alone. These results suggest that failure to differentially activate the insula as a function of risk is a part of an altered risk-processing network associated with an increased susceptibility to relapse.

RATIONALE: Biased processing of drug-associated stimuli is believed to be a crucial feature of addiction. Particularly, an attentional bias seems to contribute to the disorder's maintenance. Recent studies suggest differential effects for stimuli associated with the beginning (BEGIN-smoking-stimuli) or the terminal stage of the smoking ritual (END-smoking-stimuli), with the former but not the later evoking high cue-reactivity. OBJECTIVE: The current study investigated the neuronal network underlying an attentional bias to BEGIN-smoking-stimuli and END-smoking-stimuli in smokers and tested the hypothesis that the attentional bias is greater for BEGIN-smoking-stimuli. METHODS: Sixteen non-deprived smokers and 16 non-smoking controls participated in an fMRI study. Drug pictures (BEGIN-smoking-stimuli, END-smoking-stimuli) and control pictures were overlaid with geometrical figures and presented for 300 ms. Subjects had to identify picture content (identification-task) or figure orientation (distraction-task). The distraction-task was intended to demonstrate attentional bias. RESULTS: Behavioral data revealed an attentional bias to BEGIN-smoking-stimuli but not to END-smoking-stimuli in both groups. However, only smokers showed mesocorticolimbic deactivations in the distraction-task with BEGIN-smoking-stimuli. Importantly, these deactivations were significantly stronger for BEGIN- than for END-smoking-stimuli and correlated with the attentional bias score. CONCLUSIONS: Several explanations may account for missing group differences in behavioral data. Brain data suggest smokers using regulatory strategies in response to BEGIN-smoking-stimuli to prevent the elicitation of motivational responses interfering with distraction-task performance. These strategies could be reflected in the observed deactivations and might lead to a performance level in smokers that is similar to that of non-smokers.

BACKGROUND: The underlying neurobiological mechanisms that account for the onset and maintenance of binge-eating disorder (BED) are not sufficiently understood. This functional magnetic resonance imaging (fMRI) study explored the neural correlates of visually induced food reward and loathing. METHOD: Sixty-seven female participants assigned to one of four groups (overweight BED patients, overweight healthy control subjects, normal-weight healthy control subjects, and normal-weight patients with bulimia nervosa) participated in the experiment. After an overnight fast, the participants' brain activation was recorded during each of the following three conditions: visual exposure to high-caloric food, to disgust-inducing pictures, and to affectively neutral pictures. After the fMRI experiment, the participants rated the affective value of the pictures. RESULTS: Each of the groups experienced the food pictures as very pleasant. Relative to the neutral pictures, the visual food stimuli provoked increased activation in the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and insula across all participants. The BED patients reported enhanced reward sensitivity and showed stronger medial OFC responses while viewing food pictures than all other groups. The bulimic patients displayed greater arousal, ACC activation, and insula activation than the other groups. Neural responses to the disgust-inducing pictures as well as trait disgust did not differ between the groups. CONCLUSIONS: This study provides first evidence of differential brain activation to visual food stimuli in patients suffering from BED and bulimia nervosa.

Cerebral reorganization may limit the effects of central nervous system tissue damage on cognition in patients with multiple sclerosis (MS). This study investigated fMRI activation patterns in patients with relapsing-remitting MS and healthy control subjects during performance of a delayed recognition task. As intended, fMRI task performance was similar in the MS and the control group, whereas neuropsychological testing revealed reduced performance in the patient group on the Paced Serial Addition Test, a reference task for the assessment of cognitive function in MS. Patients overall showed more activation in left posterior parietal cortex than healthy control subjects. Global gray matter atrophy in the patient group was associated with low PASAT scores. In a multiple regression analysis including white matter lesion load and gray matter atrophy as covariates, PASAT performance correlated with activation in left posterior parietal cortex and right anterior midfrontal gyrus, indicating a reallocation of neuronal resources to help preserve function. Global gray matter atrophy correlated with activation in bilateral prefrontal cortex, dorsal ACC and left posterior parietal cortex and, furthermore, was associated with a low degree of deactivation in rostral ACC, suggesting neural inefficiency and consistent with a reduced capacity to modulate between frontoparietal task-associated activation and 'default network' activity. The current study provides evidence that altered brain activation in MS patients has two distinct components, one related to compensatory processes and one to neural inefficiency associated with tissue damage.