Roberto Viviani

Changes in Prefrontal-Limbic Function in Major Depression after 15 Months of Long-Term Psychotherapy

Neuroimaging studies of depression have demonstrated treatment-specific changes involving the limbic system and regulatory regions in the prefrontal cortex. While these studies have examined the effect of short-term, interpersonal or cognitive-behavioural psychotherapy, the effect of long-term, psychodynamic intervention has never been assessed. Here, we investigated recurrently depressed (DSM-IV) unmedicated outpatients (N = 16) and control participants matched for sex, age, and education (N = 17) before and after 15 months of psychodynamic psychotherapy. Participants were scanned at two time points, during which presentations of attachment-related scenes with neutral descriptions alternated with descriptions containing personal core sentences previously extracted from an attachment interview. Outcome measure was the interaction of the signal difference between personal and neutral presentations with group and time, and its association with symptom improvement during therapy. Signal associated with processing personalized attachment material varied in patients from baseline to endpoint, but not in healthy controls. Patients showed a higher activation in the left anterior hippocampus/amygdala, subgenual cingulate, and medial prefrontal cortex before treatment and a reduction in these areas after 15 months. This reduction was associated with improvement in depressiveness specifically, and in the medial prefrontal cortex with symptom improvement more generally. This is the first study documenting neurobiological changes in circuits implicated in emotional reactivity and control after long-term psychodynamic psychotherapy.

Functional principal component analysis of fMRI data

We describe a principal component analysis (PCA) method for functional magnetic resonance imaging (fMRI) data based on functional data analysis, an advanced nonparametric approach. The data delivered by the fMRI scans are viewed as continuous functions of time sampled at the interscan interval and subject to observational noise, and are used accordingly to estimate an image in which smooth functions replace the voxels. The techniques of functional data analysis are used to carry out PCA directly on these functions. We show that functional PCA is more effective than is its ordinary counterpart in recovering the signal of interest, even if limited or no prior knowledge of the form of hemodynamic function or the structure of the experimental design is specified. We discuss the rationale and advantages of the proposed approach relative to other exploratory methods, such as clustering or independent component analysis, as well as the differences from methods based on expanded design matrices. Hum Brain Mapp 24:109–129, 2005.

Relevance of UDP-glucuronosyltransferase polymorphisms for drug dosing: A quantitative systematic review.

UDP-glucuronosyltransferases (UGT) catalyze the biotransformation of many endobiotics and xenobiotics, and are coded by polymorphic genes. However, knowledge about the effects of these polymorphisms is rarely used for the individualization of drug therapy. Here, we present a quantitative systematic review of clinical studies on the impact of UGT variants on drug metabolism to clarify the potential for genotype-adjusted therapy recommendations. Data on UGT polymorphisms and dose-related pharmacokinetic parameters in man were retrieved by a systematic search in public databases. Mean estimates of pharmacokinetic parameters were extracted for each group of carriers of UGT variants to assess their effect size. Pooled estimates and relative confidence bounds were computed with a random-effects meta-analytic approach whenever multiple studies on the same variant, ethnic group, and substrate were available. Information was retrieved on 30 polymorphic metabolic pathways involving 10 UGT enzymes. For irinotecan and mycophenolic acid a wealth of data was available for assessing the impact of genetic polymorphisms on pharmacokinetics under different dosages, between ethnicities, under comedication, and under toxicity. Evidence for effects of potential clinical relevance exists for 19 drugs, but the data are not sufficient to assess effect size with the precision required to issue dose recommendations. In conclusion, compared to other drug metabolizing enzymes much less systematic research has been conducted on the polymorphisms of UGT enzymes. However, there is evidence of the existence of large monogenetic functional polymorphisms affecting pharmacokinetics and suggesting a potential use of UGT polymorphisms for the individualization of drug therapy.

Transcranial magnetic stimulation in motor conversion disorder: a short case series.

Summary: The neurophysiologic mechanisms involved in nonorganic paralysis are unclear. Because there is no established standard therapy, the authors investigated the effect of repetitive transcranial magnetic stimulation (rTMS) in four patients with nonorganic limb paralysis. Within the framework of a treatment trial, the patients were treated over a period of 5–12 weeks with rTMS applied to the contralateral motor cortex. Stimulation frequency was 15 Hz, train length 2 seconds, intertrain interval 4 seconds; daily total number of stimuli 4000. In one patient, motor function was completely restored; two patients experienced a marked improvement correlating with rTMS treatment. By contrast, one patient who had been diagnosed as a malingerer did not improve. Apart from possible favorable psychological factors that could partly explain the rTMS-associated effects, high-frequency rTMS might have enhanced or substituted an insufficient input to the motor cortex from failing frontal executive areas, and thereby opened the way to a learning process that lead to the reacquisition of limb use. rTMS may have a therapeutic effect in motor conversion disorder and may help elucidate neurophysiologic aspects of this condition. The potential benefit of rTMS in motor conversion disorder should be evaluated in larger, controlled samples.

Neural Correlates of Psychotherapy in Anxiety and Depression: A Meta-Analysis

Several studies have used neuroimaging methods to identify neural change in brain networks associated to emotion regulation after psychotherapy of depression and anxiety. In the present work we adopted a meta-analytic technique specific to neuroimaging data to evaluate the consistence of empirical findings and assess models of therapy that have been proposed in the literature. Meta-analyses were conducted with the Activation Likelihood Estimation technique, which evaluates the overlap between foci of activation across studies. The analysis included 16 studies found in Pubmed (200 foci of activation and 193 patients). Separate meta-analyses were conducted on studies of 1) depression, post-traumatic stress disorder and panic disorder investigated with rest state metabolism (6 studies, 70 patients); 2) depression, post-traumatic stress disorder and panic disorder investigated with task-related activation studies (5 studies, 65 patients); 3) the previous studies considered jointly; and 4) phobias investigated with studies on exposure-related activation (5 studies, 57 patients). Studies on anxiety and depression gave partially consistent results for changes in the dorsomedial prefrontal cortex and in the posterior cingulated gyrus/precuneus. Several areas of change in the temporal lobes were also observed. Studies on the therapy of phobia were consistent with a reduction of activity in medial temporal areas. The cluster of change in the prefrontal cortex may refer to increased recruitment of control processes, as hypothesized by influential models of emotion regulation changes due to psychotherapy. However, not all areas associated with controlled emotion regulation were detected in the meta-analysis, while involvement of midline structures suggested changes in self-related information processing. Changes in phobia were consistent with reduced reactivity to phobic stimuli.

Resting state functional connectivity in perfusion imaging: correlation maps with BOLD connectivity and resting state perfusion.

Functional connectivity is a property of the resting state that may provide biomarkers of brain function and individual differences. Classically, connectivity is estimated as the temporal correlation of spontaneous fluctuations of BOLD signal. We investigated differences in connectivity estimated from the BOLD and CBF signal present in volumes acquired with arterial spin labeling technique in a large sample (N = 265) of healthy individuals. Positive connectivity was observable in both BOLD and CBF signal, and was present in the CBF signal also at frequencies lower than 0.009 Hz, here investigated for the first time. Negative connectivity was more variable. The validity of positive connectivity was confirmed by the existence of correlation across individuals in its intensity estimated from the BOLD and CBF signal. In contrast, there was little or no correlation across individuals between intensity of connectivity and mean perfusion levels, suggesting that these two biomarkers correspond to distinct sources of individual differences.

Emotion regulation, attention to emotion, and the ventral attentional network.

Accounts of the effect of emotional information on behavioral response and current models of emotion regulation are based on two opposed but interacting processes: automatic bottom-up processes (triggered by emotionally arousing stimuli) and top-down control processes (mapped to prefrontal cortical areas). Data on the existence of a third attentional network operating without recourse to limited-capacity processes but influencing response raise the issue of how it is integrated in emotion regulation. We summarize here data from attention to emotion, voluntary emotion regulation, and on the origin of biases against negative content suggesting that the ventral network is modulated by exposure to emotional stimuli when the task does not constrain the handling of emotional content. In the parietal lobes, preferential activation of ventral areas associated with “bottom-up” attention by ventral network theorists is strongest in studies of cognitive reappraisal. In conditions when no explicit instruction is given to change ones response to emotional stimuli, control of emotionally arousing stimuli is observed without concomitant activation of the dorsal attentional network, replaced by a shift of activation toward ventral areas. In contrast, in studies where emotional stimuli are placed in the role of distracter, the observed deactivation of these ventral semantic association areas is consistent with the existence of proactive control on the role emotional representations are allowed to take in generating response. It is here argued that attentional orienting mechanisms located in the ventral network constitute an intermediate kind of process, with features only partially in common with effortful and automatic processes, which plays an important role in handling emotion by conveying the influence of semantic networks, with which the ventral network is co-localized. Current neuroimaging work in emotion regulation has neglected this system by focusing on a bottom-up/top-down dichotomy of attentional control.

Habitual emotion regulation strategies and baseline brain perfusion.

Specific emotion regulation styles like the frequent use of expressive suppression and low capacity for cognitive reappraisal has been associated with poorer mental health and a risk for depressive symptoms. Using arterial spin labeling, we investigated the effects of these regulation styles on regional cerebral blood flow (rCBF) in healthy participants during rest. Suppression scores correlated with increased rCBF in the ventral medial prefrontal cortex. Blood flow in this region was associated with elevated rCBF in other areas involved in emotional appraisal and control, and may represent neurobiological correlates of increased habitual self-monitoring as common in depression and anxiety. By linking default brain functioning to emotional styles, we provide an insight into the neurobiology of the predisposition to depression.

Executive and semantic processes in reappraisal of negative stimuli: insights from a meta-analysis of neuroimaging studies.

Neuroimaging investigations have identified the neural correlates of reappraisal in executive areas. These findings have been interpreted as evidence for recruitment of controlled processes, at the expense of automatic processes when responding to emotional stimuli. However, activation of semantic areas has also been reported. The aim of the present work was to address the issue of the importance of semantic areas in emotion regulation by comparing recruitment of executive and semantic neural substrates in studies investigating different reappraisal strategies. With this aim, we reviewed neuroimaging studies on reappraisal and we classified them in two main categories: reappraisal of stimuli (RS) and reappraisal via perspective taking (RPT). We applied a coordinate-based meta-analysis to summarize the results of fMRI studies on different reappraisal strategies. Our results showed that reappraisal, when considered regardless of the specific instruction used in the studies, involved both executive and semantic areas of the brain. When considering different reappraisal strategies separately, in contrast, we found areas associated with executive function to be prominently recruited by RS, even if also semantic areas were activated. Instead, in RPT the most important clusters of brain activity were found in parietal and temporal semantic areas, without significant clusters in executive areas. These results indicate that modulation of activity in semantic areas may constitute an important aspect of emotion regulation in reappraisal, suggesting that semantic processes may be more important to understand the mechanism of emotion regulation than previously thought.

Non-normality and transformations of random fields, with an application to voxel-based morphometry.

Parametric tests of linear models for images modeled as random fields are based like ordinary univariate tests on distributional assumptions. It is here shown that the effect of departures from assumptions in random field tests is more pronounced than in the univariate condition. Simulations are presented investigating in detail the influence of smoothing, unbalancedness and leverages on empirical thresholds. In certain conditions, significance tests may become invalid. As a case study, the existence and effect of departures from normality of gray matter probability maps, commonly used in voxel-based morphometry, is investigated, as well as the effect of different transformation strategies involving estimating the degree of transformation from the data by maximum likelihood. The best results are achieved with a voxel-by-voxel transformation, suggesting heterogeneity of distributional form across the volume for this kind of data.