Empathy to emotional voices and the use of real-time fMRI to enhance activation of the anterior insula

Highlights

• Participants in the NF group only learned to up-regulate their AI activity in response to auditory stimuli.

• Negative relationship found between individuals' empathic traits and up-regulation abilities.

• Participants increased AI activity better when listening to positive, compared to negative valenced, auditory stimuli.

Abstract

The right anterior insula (AI), known to have a key role in the processing and understanding of social emotions, is activated during tasks that involve the act of empathising. Neurofeedback provides individuals with a visualisation of their own brain activity, enabling them to regulate and modify this activity. Following previous research investigating the ability of individuals to up-regulate right AI activity levels through neurofeedback, we investigated whether this could be similarly accomplished during an empathy task involving auditory stimuli of human positive and negative emotional expressions. Twenty participants, ten with feedback from right anterior insula and ten with feedback from a sham brain region, participated in two sessions that included sixteen neurofeedback runs and four transfer runs. Results showed that for the second session participants in the right AI neurofeedback group demonstrated better ability to up-regulate their right AI compared to the control group who received sham feedback. Examination of the relationship between individual participants’ empathic traits and their ability to up-regulate right AI activity showed that participants low on empathic traits produced a greater increase in activation of right AI by the end of training. Moreover, the response to positively valenced audio stimuli was greater than for negatively valenced stimuli. These results have implications for therapeutic training of empathy in populations with limited empathic response.

Introduction

The underlying neural mechanisms of emotion have been the focus of much research, with neuroimaging revealing the anterior insula (AI) to be the most consistently activated region in studies of emotion (Kober et al., 2008). Social emotions, specifically empathy - the ability to identify other people's emotions and respond to these appropriately with one's own emotions - have also been found to activate the AI region (Lamm and Singer, 2010). Further support for a link between empathy and AI activity comes from autism spectrum disorders (ASD), which frequently involve abnormalities in social and communication development. The right AI has been shown to be hypoactive in autistic individuals during social processing tasks (Di Martino et al., 2009), suggesting a dysfunctional right AI in autistic people produces difficulties in social awareness.

Neurofeedback using real time fMRI (rt-fMRI) is a technique that aims to allow voluntary control of brain function through monitoring metabolic activity in the brain (as denoted by the blood oxygenation-dependent level (BOLD) signal) and visually relaying it back to the participant in real-time (Ruiz et al., 2013). The resulting readout is used by participants to either up- or down-regulate activity levels in a specific brain region using cognitive strategies. If these learned techniques can be used by participants outside the scanner, then they have the potential to manifest beneficial behavioural changes in these individuals (Paret et al., 2014). Real time fMRI has been examined as an intervention in several conditions, including attention deficit hyperactivity disorder (ADHD), depression and phobias (Zilverstand et al., 2017; Linden et al., 2012; Zilverstand et al., 2015, respectively).

Real time neurofeedback has also been utilised in emotion research as a method of emotion regulation. The ability of humans to empathise with others has been trialled as a mechanism to help participants gain control over brain activation patterns. In particular, one study explored the affective aspect of empathy, and demonstrated participants’ abilities at increasing BOLD responses in key regions implicated in these traits (Moll et al., 2014). Similarly, the ability of participants to self-regulate their amygdala BOLD activity was investigated by Zotev et al. (2011), by contemplating positive autobiographical memories. The researchers found that BOLD signal was significantly increased by the end of the training, and as well as this, these effects were seen in transfer runs later on, which lacked any neurofeedback. More recently, one research group found rt-fMRI neurofeedback not only allowed participants to up-regulate their amygdala activity, but also helped most participants in the experimental group to meet conventional criteria for remission by the end of the study via a decrease in the depressive symptoms displayed (Young et al., 2014, 2017).

Previous research has found rt-fMRI neurofeedback techniques to be successful at up-regulating activity levels of the AI in healthy individuals (Caria et al., 2007; Lawrence et al., 2014). Participants are asked to employ various cognitive strategies to increase their AI BOLD signal, such as using emotional imagery (Berman et al., 2013), or responding to aversive visual stimuli (Veit et al., 2012). A further study found that individuals who managed to increase their AI activity went on to assign more ratings that are negative to aversive pictures post-training. These ratings were in direct correlation with AI activation, demonstrating a behavioural effect of increased emotional engagement (Caria et al., 2010). Further, participants that managed to up-regulate AI activity went on to exhibit stronger empathic responses to painful stimuli, a behavioural effect that was also apparent two days after the training (Yao et al., 2016). One limitation of previous research involves the methods used to elicit these empathic responses. It could be said that simply asking participants to recall emotional memories may create methodological issues, as it is impossible to measure, quantify, and compare emotional memories between participants. Further, the use of visual stimuli to elicit emotional responses, in between visually displaying the NFB signal, poses a problem due to the fact that these two things are not done at the same time. By supplying an alternative stimuli modality, this problem could be overcome, and both stimuli and NFB signal could be administered at the same time. Moreover, the right insula has been shown to respond more strongly than left insula to emotional stimuli of crying and laughing (Sander and Scheich, 2005) and thus the use of such auditory stimuli could reveal new understanding of insula function.

The aim of the present research was to determine whether participants can, using rt-fMRI neurofeedback, learn to up-regulate and enhance right-AI activity levels through empathising in response to auditory stimuli. Although this area has previously been explored using visual inputs, to our knowledge, no study has made use of auditory stimuli. Furthermore, we seek to determine whether an individual's intrinsic empathy levels affect their ability to enhance activity in their right-AI and whether right-AI activity can be up-regulated in the absence of a visual readout. Finally, we are interested in determining whether the type of auditory stimuli heard in the experiment, either positively- or negatively-valenced, affected participants' up-regulating abilities. It is important to note that we are not exploring a case of pure neurofeedback as participants will be learning to up-regulate in the presence of an audio signal and an empathy task and thus up-regulation can be considered an enhancement of the untrained response.