Claudio Gentili

Selective aberrant functional connectivity of resting state networks in social anxiety disorder.

Several functional MRI (fMRI) activation studies have highlighted specific differences in brain response in social anxiety disorder (SAD) patients. Little is known, so far, about the changes in the functional architecture of resting state networks (RSNs) in SAD during resting state. We investigated statistical differences in RSNs on 20 SAD and 20 controls using independent component analysis. A diffuse impact on widely distributed RSNs and selective changes of RSN intrinsic functional connectivity were observed in SAD. Functional connectivity was decreased in the somato-motor (primary and motor cortices) and visual (primary visual cortex) networks, increased in a network including medial prefrontal cortex which is thought to be involved in self-referential processes, and increased or decreased in the default mode network (posterior cingulate cortex/precuneus, bilateral inferior parietal gyrus, angular gyrus, middle temporal gyrus, and superior and medial frontal gyrus) which has been suggested to be involved in episodic memory, and self-projection, the dorsal attention network (middle and superior occipital gyrus, inferior and superior parietal gyrus, and middle and superior frontal gyrus) which is thought to mediate goal-directed top-down processing, the core network (insula-cingulate cortices) which is associated with task control function, and the central-executive network (fronto-parietal cortices). A relationship between functional connectivity and disease severity was found in specific regions of RSNs, including medial and lateral prefrontal cortex, as well as parietal and occipital regions. Our results might supply a novel way to look into neuro-pathophysiological mechanisms in SAD patients.

Neural correlates of spatial working memory in humans: A functional magnetic resonance imaging study comparing visual and tactile processes

Recent studies of neural correlates of working memory components have identified both low-level perceptual processes and higher-order supramodal mechanisms through which sensory information can be integrated and manipulated. In addition to the primary sensory cortices, working memory relies on a widely distributed neural system of higher-order association areas that includes posterior parietal and occipital areas, and on prefrontal cortex for maintaining and manipulating information. The present study was designed to determine brain patterns of neural response to the same spatial working memory task presented either visually or in a tactile format, and to evaluate the relationship between spatial processing in the visual and tactile sensory modalities. Brain activity during visual and tactile spatial working memory tasks was measured in six young right-handed healthy male volunteers by using functional magnetic resonance imaging. Results indicated that similar fronto-parietal networks were recruited during spatial information processing across the two sensory modalities-specifically the posterior parietal cortex, the dorsolateral prefrontal cortex and the anterior cingulate cortex. These findings provide a neurobiological support to behavioral observations by indicating that common cerebral regions subserve generation of higher order mental representations involved in working memory independently from a specific sensory modality.

Altered Effective Connectivity Network of the Amygdala in Social Anxiety Disorder: A Resting-State fMRI Study

The amygdala is often found to be abnormally recruited in social anxiety disorder (SAD) patients. The question whether amygdala activation is primarily abnormal and affects other brain systems or whether it responds “normally” to an abnormal pattern of information conveyed by other brain structures remained unanswered. To address this question, we investigated a network of effective connectivity associated with the amygdala using Granger causality analysis on resting-state functional MRI data of 22 SAD patients and 21 healthy controls (HC). Implications of abnormal effective connectivity and clinical severity were investigated using the Liebowitz Social Anxiety Scale (LSAS). Decreased influence from inferior temporal gyrus (ITG) to amygdala was found in SAD, while bidirectional influences between amygdala and visual cortices were increased compared to HCs. Clinical relevance of decreased effective connectivity from ITG to amygdala was suggested by a negative correlation of LSAS avoidance scores and the value of Granger causality. Our study is the first to reveal a network of abnormal effective connectivity of core structures in SAD. This is in support of a disregulation in predescribed modules involved in affect control. The amygdala is placed in a central position of dysfunction characterized both by decreased regulatory influence of orbitofrontal cortex and increased crosstalk with visual cortex. The model which is proposed based on our results lends neurobiological support towards cognitive models considering disinhibition and an attentional bias towards negative stimuli as a core feature of the disorder.

Differential modulation of neural activity throughout the distributed neural system for face perception in patients with Social Phobia and healthy subjects

Social Phobia (SP) is a marked and persistent fear of social or performance situations in which the person is exposed to unfamiliar people or to possible scrutiny by others. Faces of others are perceived as threatening by social phobic patients (SPP). To investigate how face processing is altered in the distributed neural system for face perception in Social Phobia, we designed an event-related fMRI study in which Healthy Controls (HC) and SPP were presented with angry, fearful, disgusted, happy and neutral faces and scrambled pictures (visual baseline). As compared to HC, SPP showed increased neural activity not only in regions involved in emotional processing including left amygdala and insula, as expected from previous reports, but also in the bilateral superior temporal sulcus (STS), a part of the core system for face perception that is involved in the evaluation of expression and personal traits. In addition SPP showed a significantly weaker activation in the left fusiform gyrus, left dorsolateral prefrontal cortex, and bilateral intraparietal sulcus as compared to HC. These effects were found not only in response to emotional faces but also to neutral faces as compared to scrambled pictures. Thus, SPP showed enhanced activity in brain areas related to processing of information about emotional expression and personality traits. In contrast, brain activity was decreased in areas for attention and for processing other information from the face, perhaps as a result of a feeling of wariness. These results indicate a differential modulation of neural activity throughout the different parts of the distributed neural system for face perception in SPP as compared to HC.

Wearable monitoring for mood recognition in bipolar disorder based on history-dependent long-term heart rate variability analysis.

Current clinical practice in diagnosing patients affected by psychiatric disorders such as bipolar disorder is based only on verbal interviews and scores from specific questionnaires, and no reliable and objective psycho-physiological markers are taken into account. In this paper, we propose to use a wearable system based on a comfortable t-shirt with integrated fabric electrodes and sensors able to acquire electrocardiogram, respirogram, and body posture information in order to detect a pattern of objective physiological parameters to support diagnosis. Moreover, we implemented a novel ad hoc methodology of advanced biosignal processing able to effectively recognize four possible clinical mood states in bipolar patients (i.e., depression, mixed state, hypomania, and euthymia) continuously monitored up to 18 h, using heart rate variability information exclusively. Mood assessment is intended as an intrasubject evaluation in which the patients states are modeled as a Markov chain, i.e., in the time domain, each mood state refers to the previous one. As validation, eight bipolar patients were monitored collecting and analyzing more than 400 h of autonomic and cardiovascular activity. Experimental results demonstrate that our novel concept of personalized and pervasive monitoring constitutes a viable and robust clinical decision support system for bipolar disorders recognizing mood states with a total classification accuracy up to 95.81%.

Mood recognition in bipolar patients through the PSYCHE platform: Preliminary evaluations and perspectives

BACKGROUND Bipolar disorders are characterized by a series of both depressive and manic or hypomanic episodes. Although common and expensive to treat, the clinical assessment of bipolar disorder is still ill-defined. OBJECTIVE In the current literature several correlations between mood disorders and dysfunctions involving the autonomic nervous system (ANS) can be found. The objective of this work is to develop a novel mood recognition system based on a pervasive, wearable and personalized monitoring system using ANS-related biosignals. MATERIALS AND METHODS The monitoring platform used in this study is the core sensing system of the personalized monitoring systems for care in mental health (PSYCHE) European project. It is comprised of a comfortable sensorized t-shirt that can acquire the inter-beat interval time series, the heart rate, and the respiratory dynamics for long-term monitoring during the day and overnight. In this study, three bipolar patients were followed for a period of 90 days during which up to six monitoring sessions and psychophysical evaluations were performed for each patient. Specific signal processing techniques and artificial intelligence algorithms were applied to analyze more than 120 h of data. RESULTS Experimental results are expressed in terms of confusion matrices and an exhaustive descriptive statistics of the most relevant features is reported as well. A classification accuracy of about 97% is achieved for the intra-subject analysis. Such an accuracy was found in distinguishing relatively good affective balance state (euthymia) from severe clinical states (severe depression and mixed state) and is lower in distinguishing euthymia from the milder states (accuracy up to 88%). CONCLUSIONS The PSYCHE platform could provide a viable decision support system in order to improve mood assessment in patient care. Evidences about the correlation between mood disorders and ANS dysfunctions were found and the obtained results are promising for an effective biosignal-based mood recognition.

Efficacy of Psychotherapies for Borderline Personality Disorder: A Systematic Review and Meta-analysis

Importance Borderline personality disorder (BPD) is a debilitating condition, but several psychotherapies are considered effective. Objective To conduct an updated systematic review and meta-analysis of randomized clinical trials to assess the efficacy of psychotherapies for BPD populations. Data Sources Search terms were combined for borderline personality and randomized trials in PubMed, PsycINFO, EMBASE, and the Cochrane Central Register of Controlled Trials (from database inception to November 2015), as well as the reference lists of earlier meta-analyses. Study Selection Included were randomized clinical trials of adults with diagnosed BPD randomized to psychotherapy exclusively or to a control intervention. Study selection differentiated stand-alone designs (in which an independent psychotherapy was compared with control interventions) from add-on designs (in which an experimental intervention added to usual treatment was compared with usual treatment alone). Data Extraction and Synthesis Data extraction coded characteristics of trials, participants, and interventions and assessed risk of bias using 4 domains of the Cochrane Collaboration Risk of Bias tool (independent extraction by 2 assessors). Outcomes were pooled using a random-effects model. Subgroup and meta-regression analyses were conducted. Main Outcomes and Measures Standardized mean differences (Hedges g) were calculated using all outcomes reported in the trials for borderline symptoms, self-harm, suicide, health service use, and general psychopathology at posttest and follow-up. Differential treatment retention at posttest was analyzed, reporting odds ratios. Results Thirty-three trials (2256 participants) were included. For borderline-relevant outcomes combined (symptoms, self-harm, and suicide) at posttest, the investigated psychotherapies were moderately more effective than control interventions in stand-alone designs (g = 0.32; 95% CI, 0.14-0.51) and add-on designs (g = 0.40; 95% CI, 0.15-0.65). Results were similar for other outcomes, including stand-alone designs: self-harm (g = 0.32; 95% CI, 0.09-0.54), suicide (g = 0.44; 95% CI, 0.15-0.74), health service use (g = 0.40; 95% CI, 0.22-0.58), and general psychopathology (g = 0.32; 95% CI, 0.09-0.55), with no differences between design types. There were no significant differences in the odds ratios for treatment retention (1.32; 95% CI, 0.87-2.00 for stand-alone designs and 1.01; 95% CI, 0.55-1.87 for add-on designs). Thirteen trials reported borderline-relevant outcomes at follow-up (g = 0.45; 95% CI, 0.15-0.75). Dialectical behavior therapy (g = 0.34; 95% CI, 0.15-0.53) and psychodynamic approaches (g = 0.41; 95% CI, 0.12-0.69) were the only types of psychotherapies more effective than control interventions. Risk of bias was a significant moderator in subgroup and meta-regression analyses (slope &bgr; = −0.16; 95% CI, −0.29 to −0.03; P = .02). Publication bias was persistent, particularly for follow-up. Conclusions and Relevance Psychotherapies, most notably dialectical behavior therapy and psychodynamic approaches, are effective for borderline symptoms and related problems. Nonetheless, effects are small, inflated by risk of bias and publication bias, and particularly unstable at follow-up.

Characterization of Depressive States in Bipolar Patients Using Wearable Textile Technology and Instantaneous Heart Rate Variability Assessment

The analysis of cognitive and autonomic responses to emotionally relevant stimuli could provide a viable solution for the automatic recognition of different mood states, both in normal and pathological conditions. In this study, we present a methodological application describing a novel system based on wearable textile technology and instantaneous nonlinear heart rate variability assessment, able to characterize the autonomic status of bipolar patients by considering only electrocardiogram recordings. As a proof of this concept, our study presents results obtained from eight bipolar patients during their normal daily activities and being elicited according to a specific emotional protocol through the presentation of emotionally relevant pictures. Linear and nonlinear features were computed using a novel point-process-based nonlinear autoregressive integrative model and compared with traditional algorithmic methods. The estimated indices were used as the input of a multilayer perceptron to discriminate the depressive from the euthymic status. Results show that our system achieves much higher accuracy than the traditional techniques. Moreover, the inclusion of instantaneous higher order spectra features significantly improves the accuracy in successfully recognizing depression from euthymia.

Speech analysis for mood state characterization in bipolar patients

Bipolar disorders are characterized by an unpredictable behavior, resulting in depressive, hypomanic or manic episodes alternating with euthymic states. A multi-parametric approach can be followed to estimate mood states by integrating information coming from different physiological signals and from the analysis of voice. In this work we propose an algorithm to estimate speech features from running speech with the aim of characterizing the mood state in bipolar patients. This algorithm is based on an automatic segmentation of speech signals to detect voiced segments, and on a spectral matching approach to estimate pitch and pitch changes. In particular average pitch, jitter and pitch standard deviation within each voiced segment, are estimated. The performances of the algorithm are evaluated on a speech database, which includes an electroglottographic signal. A preliminary analysis on subjects affected by bipolar disorders is performed and results are discussed.

Effects of visual experience on the human MT+ functional connectivity networks: an fMRI study of motion perception in sighted and congenitally blind individuals

Human middle temporal complex (hMT+) responds also to the perception of non-visual motion in both sighted and early blind individuals, indicating a supramodal organization. Visual experience, however, leads to a segregation of hMT+ into a more anterior subregion, involved in the supramodal representation of motion, and a posterior subregion that processes visual motion only. In contrast, in congenitally blind subjects tactile motion activates the full extent of hMT+. Here, we used fMRI to investigate brain areas functionally connected with the two hMT+ subregions (seeds) during visual and tactile motion in sighted and blind individuals. A common functional connectivity network for motion processing, including bilateral ventral and dorsal extrastriate, inferior frontal, middle and inferior temporal areas, correlated with the two hMT+ seeds both in sighted and blind individuals during either visual or tactile motion, independently from the sensory modality through which the information was acquired. Moreover, ventral premotor, somatosensory, and posterior parietal areas correlated only with the anterior but not with the posterior portion of hMT+ in sighted subjects, and with both hMT+ seeds in blind subjects. Furthermore, a correlation between middle temporal and occipital areas with primary somatosensory seeds was demonstrated across conditions in both sighted and blind individuals, suggesting a cortico-cortical pathway that conveys non-visual information from somatosensory cortex, through posterior parietal regions, to ventral extrastriate cortex. These findings expand our knowledge about the development of the functional organization within hMT+ by showing that distinct patterns of brain functional correlations originate from the anterior and posterior hMT+ subregions as a result of visual experience.