Posts Tagged emotion regulation

[ARTICLE] Social cognition and emotion regulation: a multifaceted treatment (T-ScEmo) for patients with traumatic brain injury – Full Text

Many patients with moderate to severe traumatic brain injury have deficits in social cognition. Social cognition refers to the ability to perceive, interpret, and act upon social information. Few studies have investigated the effectiveness of treatment for impairments of social cognition in patients with traumatic brain injury. Moreover, these studies have targeted only a single aspect of the problem. They all reported improvements, but evidence for transfer of learned skills to daily life was scarce. We evaluated a multifaceted treatment protocol for poor social cognition and emotion regulation impairments (called T-ScEmo) in patients with traumatic brain injury and found evidence for transfer to participation and quality of life.

In the current paper, we describe the theoretical underpinning, the design, and the content of our treatment of social cognition and emotion regulation (T-ScEmo).

The multifaceted treatment that we describe is aimed at improving social cognition, regulation of social behavior and participation in everyday life. Some of the methods taught were already evidence-based and derived from existing studies. They were combined, modified, or extended with newly developed material.

T-ScEmo consists of 20 one-hour individual sessions and incorporates three modules: (1) emotion perception, (2) perspective taking and theory of mind, and (3) regulation of social behavior. It includes goal-setting, psycho-education, function training, compensatory strategy training, self-monitoring, role-play with participation of a significant other, and homework assignments.

It is strongly recommended to offer all three modules, as they build upon each other. However, therapists can vary the time spent per module, in line with the patients’ individual needs and goals. In future, development of e-learning modules and virtual reality sessions might shorten the treatment.

Traumatic brain injury refers to a brain lesion caused by an external mechanical force, leading not only to physical impairments and cognitive deficits, but also to changes in behavior and personality.1,2 Especially after damage to orbitofrontal and ventromedial prefrontal brain areas, deficits in social cognition can occur.3,4

According to Adolphs,5 social cognition consists of three stages: (1) the ability to perceive social information (i.e. emotional facial expressions, bodily language), (2) the capacity to process and interpret social information (i.e. theory of mind, perspective taking), and (3) the ability to adapt behavior in accordance with the situation. Babbage et al.6 estimated that 13%–39% of individuals with moderate to severe traumatic brain injury experienced emotion perception deficits and up to 70% reported low empathy.79

Deficits in social cognition often appear in the shape of socially inadequate behavior, such as disinhibited or indifferent emotional behavior.1012 Such behaviors have detrimental consequences for the ability of patients to establish and maintain social relationships, to hold jobs, and to participate in society.1,13,14 It has been found that poor theory of mind and behavioral problems significantly predict poor participation and community integration.15,16For all these reasons, it is important to provide a tailored rehabilitation treatment, in order to prevent an unfavorable outcome.

In their review of cognitive rehabilitation, Cicerone et al.17 stressed the need to provide detailed information about the theoretical base, the protocol design, and the ingredients of a treatment, as a prerequisite to analyze its effectiveness. In the current paper, we give a comprehensive description of the treatment of social cognition and emotion regulation protocol (T-ScEmo). The effectiveness of T-ScEmo was evaluated in 59 patients with traumatic brain injury. It was compared with a computerized control treatment in a randomized controlled trial.18 Compared to the control treatment, T-ScEmo resulted in significant improvements in emotion recognition, theory of mind, emphatic behavior, quality of life partner relationship, quality of life and societal participation, up to five months posttreatment. Patients with traumatic brain injury as well as their life partners were satisfied with the treatment.18 A detailed description of the T-ScEmo protocol is relevant for researchers and clinical therapists; they can use, replicate, or expand this newly developed treatment.[…]

 

Continue —-> Social cognition and emotion regulation: a multifaceted treatment (T-ScEmo) for patients with traumatic brain injury – Herma J Westerhof-Evers, Annemarie C Visser-Keizer, Luciano Fasotti, Jacoba M Spikman, 2019

 

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Figure 1. Thoughts–feelings–behavior scheme (module 2).

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[ARTICLE] Emotion Regulation Using Virtual Environments and Real-Time fMRI Neurofeedback – Full Text

Neurofeedback (NFB) enables the voluntary regulation of brain activity, with promising applications to enhance and recover emotion and cognitive processes, and their underlying neurobiology. It remains unclear whether NFB can be used to aid and sustain complex emotions, with ecological validity implications. We provide a technical proof of concept of a novel real-time functional magnetic resonance imaging (rtfMRI) NFB procedure. Using rtfMRI-NFB, we enabled participants to voluntarily enhance their own neural activity while they experienced complex emotions. The rtfMRI-NFB software (FRIEND Engine) was adapted to provide a virtual environment as brain computer interface (BCI) and musical excerpts to induce two emotions (tenderness and anguish), aided by participants’ preferred personalized strategies to maximize the intensity of these emotions. Eight participants from two experimental sites performed rtfMRI-NFB on two consecutive days in a counterbalanced design. On one day, rtfMRI-NFB was delivered to participants using a region of interest (ROI) method, while on the other day using a support vector machine (SVM) classifier. Our multimodal VR/NFB approach was technically feasible and robust as a method for real-time measurement of the neural correlates of complex emotional states and their voluntary modulation. Guided by the color changes of the virtual environment BCI during rtfMRI-NFB, participants successfully increased in real time, the activity of the septo-hypothalamic area and the amygdala during the ROI based rtfMRI-NFB, and successfully evoked distributed patterns of brain activity classified as tenderness and anguish during SVM-based rtfMRI-NFB. Offline fMRI analyses confirmed that during tenderness rtfMRI-NFB conditions, participants recruited the septo-hypothalamic area and other regions ascribed to social affiliative emotions (medial frontal / temporal pole and precuneus). During anguish rtfMRI-NFB conditions, participants recruited the amygdala and other dorsolateral prefrontal and additional regions associated with negative affect. These findings were robust and were demonstrable at the individual subject level, and were reflected in self-reported emotion intensity during rtfMRI-NFB, being observed with both ROI and SVM methods and across the two sites. Our multimodal VR/rtfMRI-NFB protocol provides an engaging tool for brain-based interventions to enhance emotional states in healthy subjects and may find applications in clinical conditions associated with anxiety, stress and impaired empathy among others.

Introduction

Neurofeedback (NFB) is a novel application of brain-computer interfaces that aids real-time voluntarily regulation of brain activity. Mounting evidence shows that NFB has promising effects to enhance behavior, cognitive and emotional processes in normative samples (1–5). NFB has also been preliminary used to restore aberrant neurobiology and symptoms in neurological conditions (e.g., stroke, traumatic brain injury) and in psychopathology (e.g., ADHD, autism, depression, addiction) (1–7). Real-time functional magnetic resonance imaging (rtfMRI) based NFB has the potential to provide insight in understanding the mechanisms of psychological states (8–10). These include affiliative emotions (11) underpinned by deep brain nuclei (12, 13) the activity of which is unlikely to be robustly measured via surface electroencephalography.

rtfMRI NFB tools can be used to study the causal mechanisms of complex emotions and to inform evidence-based personalized interventions to enhance and recover aberrant emotional states (and their neural substrates) in normative and clinical samples. One key practical human challenge of fMRI studies includes participants being distracted and experiencing difficulties to feel valid psychological states in the scanner environment, particularly when trying to sustain complex emotions.

Recent studies have combined immersive virtual environments with multiple sensory modalities to deliver psychological/cognitive interventions, and to enhance their effectiveness via engaging and motivating individuals to practice (14–16).

Only two proof of concept studies have combined rt-NFB with virtual environments as brain computer interfaces (BCI). An electroencephalography-based NFB study computed brain activity from about 500 participants collectively, during an interactive game of relaxation and concentration over one night (16), where individual’s level of brain activity could not be discerned. A separate rtfMRI-NFB paradigm used a virtual fire interface to up-regulate and down-regulate brain activity in eight healthy participants—but this was devoid of any emotional states and far from multimodal and immersive (17).

It remains untested whether rt-NFB platforms integrating multisensory virtual environments can successfully recruit complex emotions and sustain these emotions long and strong enough to probe their underlying neural correlates. Such a platform can advance NFB applications, via (i) increasing the ecological validity of rtfMRI-NFB experiments, and their relevance for the daily experiences of emotions outside of experimental settings, (ii) adapting NFB interfaces to the individual and target population so these are more relatable, engaging and effective in generating and sustaining complex emotions that maximize the success of rtfMRI-NFB interventions (18–20).

This study aims to demonstrate the feasibility of an engaging rtfMRI-NFB interface that can be individually tailored and, specifically, to provide a proof of concept for a rtfMRI-NFB integrating a virtual environment as a BCI and musical stimuli using both local (region of interest, ROI) and distributed (support vector machine, SVM) analyses. The FRIEND Engine Framework system (21) was enhanced and adapted for this aim. We recruited healthy young adults performing rtfMRI-NFB during complex emotion experiences, including tenderness—a positive affiliative emotion – and anguish—a self-reflective negative emotion (11, 13, 22–25).

We also aimed to validate the functional anatomy of these complex emotions during rtfMRI-NFB. After the real-time data was collected, we ran offline fMRI data analyses to verify the effects of the real-time neurofeedback task on brain activity using standard preprocessing and statistical analysis methods.

We hypothesized that participants would voluntary change the color of a virtual environment in the BCI during rtfMRI-NFB using the activity of the following regions: (i) for the tenderness condition, the septo-hypothalamic area (when using ROI-based rtfMRI-NFB method) and other brain areas ascribed to positive affiliative emotions i.e., medial orbitofrontal areas (when using SVM-based rtfMRI-NFB method) (11, 25–27); and (ii) for the anguish condition, the amygdala (during the ROI-based fMRI-NFB method) and also lateral prefrontal cortices implicated in negative affect (e.g., anguish, fear, anxiety, negative mood, stress, psychological pain), and in psychopathologies where negative affect is a feature [e.g., depression and generalized anxiety disorder (28–32)] (during SVM-based rtfMRI-NFB).

Materials and Methods

Participants

We used a single subject, repeated measures design with two identical assessments on two consecutive days, counterbalanced by rtfMRI-NFB method (i.e., ROI and SVM). We recruited eight psychiatrically and neurologically healthy postgraduate research students, free of psychoactive medication and with normal or corrected-to-normal vision. Four participants were recruited from the D’Or Institute for Research and Education (IDOR) in Rio de Janeiro, Brazil (approved by the Ethics and Scientific committees of the Copa D’Or Hospital, Rio de Janeiro, Brazil – No 922.218). To validate the protocol in a different scanner and institution, we also recruited four participants from the Monash Biomedical Imaging (MBI) at Monash University in Melbourne, Australia (MUHREC CF15/1756 – 2015000893). All volunteers provided written informed consent prior to study participation.

Design of the Neurofeedback BCI

Supplementary video 1 and Figure 1 show the BCI used for the rt-fMRI NFB. The BCI comprised a virtual environment as a medium to convey sensory feedback to participants in real time, in association with ongoing tenderness, anguish and neutral emotional states. The virtual environment was created by editing the Unity 3D asset Autumnal Nature Pack (Unity 3D, https://assetstore.unity.com/packages/3d/environments/autumnal-nature-pack-3649) and displayed a first-person navigation at walking speed through hills and cornfields, with a total duration of 10′8″ (Supplementary Video 1). The virtual environment was prepared to alternate between different trial types: neutral (30″), tenderness (46″) and anguish (46″).

The trial types were displayed via changes in the base color hues of the virtual environment and via specific music excerpts. Music excerpts were fixed for each trial type, and not influenced by current neural/psychological states (no music for Neutral, mild, gentle music for Tenderness and eerie, distorted music for Anguish). Music excerpts were selected from 20 audio tracks, all normalized using the root mean square feature of Audacity software (Audacity, http://www.audacityteam.org). The audio tracks were previously rated to have comparable volume, pace, and rhythm. For the rtfMRI-NFB task runs, four excerpts for tenderness and four excerpts for anguish were played.

Neutral trials were characterized by a normal colored virtual landscape displayed in the BCI with no background music. Tenderness trials were characterized by a change in the color of the virtual landscape to orange and were accompanied by tenderness music excerpts. Anguish trials commenced when the color of the environment turned to purple hues and were accompanied by anguish music excerpts.

Neurofeedback Task

Task Practice Outside the MRI

For training purposes, we recorded a video showing a sample of the virtual environment. The video lasted as long as one run of the rtfMRI-NFB task (10′ 8″) and was used by participants to practice tenderness, anguish and neutral states before the MRI. With this practice, participants could learn which music tracks and VR color changes in the BCI corresponded to tenderness, anguish and neutral trials.

Neurofeedback Interface

As shown in Figure 1, instead of a classic thermometer, the color of the virtual environment was used as BCI changed in real time with increased engagement of the neural activity/pattern corresponding to distinct target emotional states—orange for tenderness trials, purple for anguish trials and natural light tones for neutral trials. Participants were instructed to experience tenderness or anguish as intensely as possible in the respective trials and to increase the intensity of their emotion to turn in real time, the color of the virtual environment BCI to as orange as possible during tenderness trials, and as purple as possible during anguish trials, which increased in turn the corresponding neural activity/pattern.

FIGURE 1

Figure 1. Color hue modulation of the virtual environment during rtfMRI-NFB. The color hue changes from baseline neutral trials to a more intense orange and purple as participants increasingly engage target brain regions for tenderness and anguish trials.

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via Frontiers | Emotion Regulation Using Virtual Environments and Real-Time fMRI Neurofeedback | Neurology

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