Watching your own brain while you (it) regulates your (its) emotions!
Posted on Dec 21, 2009 by Glyn Hallam
fMRI has long been used to look at patterns of brain activation over the course of an experiment, but a new way of processing fMRI data in almost ‘real time’ means that experiments can begin to investigate which exact cognitive processes might influences brain activity in particular areas or networks.
The technique is known as ‘neurofeedback’ and relies on a rapid automatic ‘real time’ analysis of fMRI data as they are collected from the scanner. This data will reveal which areas of the participant’s brain are particularly active during the current task. Crucially this information can then be fed back to the participants whilst still in the scanner, who can then try and influence the activity of a brain area by changing their cognition.
A fascinating study just published in NeuroImage (Johnston et al, 2010,”Neurofeedback: A promising tool for the self-regulation of emotion networks”) demonstrates how neurofeedback can be used to look at how emotion networks in the brain can be engaged and modulated.
The study looked at how participants were able to modulate areas of the brain involved in experiencing negative emotions using different cognitive strategies.
In the first part of the experiment, participants viewed a number of ‘positive’ and ‘negative’ pictures in order to find out which parts of each participants’ brains were particularly activated whilst experiencing negative emotion.
The second part of the experiment required participants to come up with strategies that would modulate the activity of these particular brain areas. It was suggested to participants that they attempt to do this using various types of emotional imagery.
During their attempts, participants were given neurofeedback about the brain activity in areas of interest: so indicating whether they should try a different strategy to change the brain activity of a particular area.
All of the participants were eventually able to successfully ‘up regulate’ the brain activity within the areas of interest. One particular area of interest was the amygdala, which has long been known to play an important role in processing of, particularly negative, emotion. Participants reported that they tried several strategies to try and change their neural activity, with the most successful strategies using negative imagery and particularly personal sad memories
The study demonstrates how participants were able to implement effective strategies for generating negative emotion and influencing neural activity within brain areas previously implicated in processing negative emotion.
It is hoped that the technique of neurofeedback could one day be used to help patients develop effective strategies for achieving desired mental states that they could use in everyday life. For example, patients with major depression could be trained on particular strategies for reducing their experience of negative emotion.
The study offers a fascinating glimpse into the way that different cognitive strategies have different effects on brain activity when it comes to controlling the experience of emotion.
The neurophysiology arm of the EROS project aims to further investigate the neural underpinnings of different strategies to regulate your own emotions, and also regulate the emotions of another person.
We are also interested in the differences between what is happening when you are doing this ‘automatically’, compared to doing it deliberately.
Finally we are interested in the ways in which people can be trained to change the ways in which they regulate their own and others people’s emotions, and how these training effects may bring about changes in patterns of brain activity. The fascinating findings from Johnson and colleagues demonstrate the way in which people can alter their emotional experience, and the way in which changes in brain activity reflect this.
Johnston, S.J., Boehm, S.G., Healy, D., Goebel, R., and Linden, D.E.J. (2010). Neurofeedback: A promising tool for the self-regulation of emotion networks. NeuroImage 49, 1066-1072.
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