"INTEGRO INTEGRated Psychotherapeutic InterventiOn" on the Management of Chronic Pain in Patients with Fibromyalgia: The Role of the Therapeutic Relationship.

Fibromyalgia (FM) is a chronic disease characterized by a heterogeneous set of physical and psychological conditions. The chronic experience of disability felt by patients and the impact on quality of life (QoL) of the disease may worsen the cognitive reappraisal ability and contribute to maintaining an altered pain modulation mechanism. This paper presents the study protocol of an INTEGRated psychotherapeutic interventiOn on the management of chronic pain in patients with fibromyalgia (INTEGRO). The aim of the study is to investigate the efficacy of an integrated psychotherapeutic intervention focused on pain management on QoL and pain perception, in a pilot sample of 45 FM patients with idiopathic chronic pain. The contribution of perceived therapeutic relationship (alliance) and physiological attunement, in both the patient and therapist, will be considered as possible mediators of intervention efficacy. Attachment dimensions, traumatic experiences, difficulties in emotion regulation, mindfulness attitude and psychophysiological profile will also be considered as covariates. The objectives are to evaluate longitudinally if patients will experience an increase in QoL perception (primary endpoint), pain-managing self-efficacy and emotion-regulation abilities as well as a reduction in pain intensity (secondary endpoints), considering the mediating role of perceived therapeutic alliance and physiological attunement in both the patient and therapist.

The NEVERMIND e-health system in the treatment of depressive symptoms among patients with severe somatic conditions: A multicentre, pragmatic randomised controlled trial.

Background: This study assessed the effectiveness of the NEVERMIND e-health system, consisting of a smart shirt and a mobile application with lifestyle behavioural advice, mindfulness-based therapy, and cognitive behavioural therapy, in reducing depressive symptoms among patients diagnosed with severe somatic conditions. Our hypothesis was that the system would significantly decrease the level of depressive symptoms in the intervention group compared to the control group. Methods: This pragmatic, randomised controlled trial included 425 patients diagnosed with myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants were recruited from hospitals in Turin and Pisa (Italy), and Lisbon (Portugal), and were randomly assigned to either the NEVERMIND intervention or to the control group. Clinical interviews and structured questionnaires were administered at baseline, 12 weeks, and 24 weeks. The primary outcome was depressive symptoms at 12 weeks measured by the Beck Depression Inventory II (BDI-II). Intention-to-treat analyses included 425 participants, while the per-protocol analyses included 333 participants. This trial is registered in the German Clinical Trials Register, DRKS00013391. Findings: Patients were recruited between Dec 4, 2017, and Dec 31, 2019, with 213 assigned to the intervention and 212 to the control group. The sample had a mean age of 59·41 years (SD=10·70), with 44·24% women. Those who used the NEVERMIND system had statistically significant lower depressive symptoms at the 12-week follow-up (mean difference=-3·03, p<0·001; 95% CI -4·45 to -1·62) compared with controls, with a clinically relevant effect size (Cohen's d=0·39). Interpretation: The results of this study show that the NEVERMIND system is superior to standard care in reducing and preventing depressive symptoms among patients with the studied somatic conditions. Funding: The NEVERMIND project received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 689691.

Recognizing motor imagery tasks from EEG oscillations through a novel ensemble-based neural network architecture.

Brain-Computer Interfaces (BCI) provide effective tools aimed at recognizing different brain activities, translate them into actions, and enable humans to directly communicate through them. In this context, the need for strong recognition performances results in increasingly sophisticated machine learning (ML) techniques, which may result in poor performance in a real application (e.g., limiting a real-time implementation). Here, we propose an ensemble approach to effectively balance between ML performance and computational costs in a BCI framework. The proposed model builds a classifier by combining different ML models (base-models) that are specialized to different classification sub-problems. More specifically, we employ this strategy with an ensemble-based architecture consisting of multi-layer perceptrons, and test its performance on a publicly available electroencephalography-based BCI dataset with four-class motor imagery tasks. Compared to previously proposed models tested on the same dataset, the proposed approach provides greater average classification performances and lower inter-subject variability.

fNIRS Complexity Analysis for the Assessment of Motor Imagery and Mental Arithmetic Tasks.

Conventional methods for analyzing functional near-infrared spectroscopy (fNIRS) signals primarily focus on characterizing linear dynamics of the underlying metabolic processes. Nevertheless, linear analysis may underrepresent the true physiological processes that fully characterizes the complex and nonlinear metabolic activity sustaining brain function. Although there have been recent attempts to characterize nonlinearities in fNIRS signals in various experimental protocols, to our knowledge there has yet to be a study that evaluates the utility of complex characterizations of fNIRS in comparison to standard methods, such as the mean value of hemoglobin. Thus, the aim of this study was to investigate the entropy of hemoglobin concentration time series obtained from fNIRS signals and perform a comparitive analysis with standard mean hemoglobin analysis of functional activation. Publicly available data from 29 subjects performing motor imagery and mental arithmetics tasks were exploited for the purpose of this study. The experimental results show that entropy analysis on fNIRS signals may potentially uncover meaningful activation areas that enrich and complement the set identified through a traditional linear analysis.

Effect of yoga on pulse rate variability measured from a venous pressure waveform.

The benefits of yoga have been studied in different fields, from chronic health conditions to mental disorders, showing that it can help to improve the overall health. In particular, it has been proven that yoga also improves the autonomic function. Heart rate variability (HRV) at rest is commonly used as a non-invasive measure of autonomic regulation of heart rate. Alternatively, pulse rate variability (PRV) has been proposed as a surrogate of HRV. VoluMetrix has developed a novel technology that captures venous waveforms via sensors on the volar aspect of the wrist, called NIVAband. This study aims to assess the effect of yoga in the autonomic nervous system by analyzing the PRV obtained from the NIVA signal. Temporal (statistics of the normal-to-normal intervals), spectral (power in low and high frequency bands) and nonlinear (lagged Poincaré Plot analysis) parameters are analyzed before and after a yoga session in 20 healthy volunteers. The PRV analysis shows an increase in parameters related to parasympathetic activity and overall variability, and a decrease in parameters related to sympathetic activity and mean heart rate. These results support the beneficial effect of yoga in autonomic nervous system, increasing the parasympathetic activity.

EEG Processing to Discriminate Transitive-Intransitive Motor Imagery Tasks: Preliminary Evidences using Support Vector Machines.

It is known that brain dynamics significantly changes during motor imagery tasks of upper limb involving different kind of interactions with an object. Nevertheless, an automatic discrimination of transitive (i.e., actions involving an object) and intransitive (i.e., meaningful gestures that do not include the use of objects) imaginary actions using EEG dynamics has not been performed yet. In this study we exploit measures of EEG spectra to automatically discern between imaginary transitive and intransitive movements of the upper limb. To this end, nonlinear support vector machine algorithms are used to properly combine EEG-derived features, while a recursive feature elimination procedure highlights the most discriminant cortical regions and associated EEG frequency oscillations. Results show the significance of $\gamma ( 30 -45$ Hz) oscillations over the fronto-occipital and ipsilateral-parietal areas for the automatic classification of transitive-intransitive imaginary upper limb movements with a satisfactory accuracy of 70.97%.

A Case for the Interspecies Transfer of Emotions: A Preliminary Investigation on How Humans Odors Modify Reactions of the Autonomic Nervous System in Horses.

We examined the Autonomic Nervous System (ANS) activity of horses in response to human body odors (BOs) produced under happy and fear states. The ANS response of horses was analyzed in terms of Heart Rate Variability (HRV) features extracted in the frequency domain. Our results revealed that human BOs induce sympathetic and parasympathetic changes and stimulate horses emotionally, suggesting interspecies transfer of emotions via BOs. These preliminary findings open the way to measure changes in horse's ANS dynamics in response to human internal states via human BOs, and allow us to better understand unexpected animal behavior that could compromise human-horse interaction. Moreover, it becomes possible to design more effective strategies to manage animals across a range of situations in which a strict humananimal interaction is required, such as the well known Animal Assisted Therapy (AAT).

EEG Complexity Maps to Characterise Brain Dynamics during Upper Limb Motor Imagery.

The Electroencephalogram (EEG) can be considered as the output of a nonlinear system whose dynamics is significantly affected by motor tasks. Nevertheless, computational approaches derived from the complex system theory has not been fully exploited for characterising motor imagery tasks. To this extent, in this study we investigated EEG complexity changes throughout the following categories of imaginary motor tasks of the upper limb: transitive (actions involving an object), intransitive (meaningful gestures that do not include the use of objects), and tool-mediated (actions using an object to interact with another one). EEG irregularity was quantified following the definition of Fuzzy Entropy, which has been demonstrated to be a reliable quantifier of system complexity with low dependence on data length. Experimental results from paired statistical analyses revealed minor topographical changes between EEG complexity associated with transitive and tool-mediated tasks, whereas major significant differences were shown between the intransitive actions vs. the others. Our results suggest that EEG complexity level during motor imagery tasks of the upper limb are strongly biased by the presence of an object.

Relationship between cardiac vagal activity and mood congruent memory bias in major depression.

BACKGROUND: Previous studies suggest that autonomic reactivity during encoding of emotional information could modulate the neural processes mediating mood-congruent memory. In this study, we use a point-process model to determine dynamic autonomic tone in response to negative emotions and its influence on long-term memory of major depressed subjects. METHODS: Forty-eight patients with major depression and 48 healthy controls were randomly assigned to either neutral or emotionally arousing audiovisual stimuli. An adaptive point-process algorithm was applied to compute instantaneous estimates of the spectral components of heart rate variability [Low frequency (LF), 0.04-0.15 Hz; High frequency (HF), 0.15-0.4 Hz]. Three days later subjects were submitted to a recall test. RESULTS: A significant increase in HF power was observed in depressed subjects in response to the emotionally arousing stimulus (p=0.03). The results of a multivariate analysis revealed that the HF power during the emotional segment of the stimulus was independently associated with the score of the recall test in depressed subjects, after adjusting for age, gender and educational level (Coef. 0.003, 95%CI, 0.0009-0.005, p=0.008). LIMITATIONS: These results could only be interpreted as responses to elicitation of specific negative emotions, the relationship between HF changes and encoding/recall of positive stimuli should be further examined. CONCLUSIONS: Alterations on parasympathetic response to emotion are involved in the mood-congruent cognitive bias observed in major depression. These findings are clinically relevant because it could constitute the mechanism by which depressed patients maintain maladaptive patterns of negative information processing that trigger and sustain depressed mood.

Motor imagery effectiveness for mirror reversed movements.

Physical practice is known to enhance motor adaptation skills, which refer to the individual ability to compensate for environmental changes. So far, it is still unknown whether a similar effect can be observed following motor imagery (MI). Thirty-nine participants were tested during a joystick tracking task under both normal and mirror conditions (i.e., the inductive direction of the joystick was reversed), before and after a physical practice or MI training phase. Eye movements and electromyographic activity were recorded during MI. Motor performance was also evaluated after a 6 h interval during daytime. As compared to the control group, the results revealed that both MI and physical practice improved motor performance in the mirror condition, during the post-training test. Furthermore, the time to complete the task was further reduced after 6 hours, both in the normal and mirror conditions. These results demonstrate the effectiveness of MI for learning mirror-reversed movements, and for the consolidation process that follows motor adaptation.