Self-regulating positive emotion networks by feedback of multiple emotional brain states using real-time fMRI

Abstract

Disordered emotion regulation may affect work efficiency, induce social disharmony, and even cause psychiatric diseases. Despite recent neurocomputing advances, whether positive and negative emotion networks can be voluntarily modulated is still unknown. In the present study, we addressed this question through multivariate voxel pattern analysis and real-time functional MRI neurofeedback (rtfMRI-nf). During a sustained emotion regulation task, participants' emotional states (positive or negative) were given to them as feedback. Participants were able to increase the percentage of positive emotional states, enhancing emotion regulation network activities. Participants showed an improvement on the positive subscale of positive and negative affect scale that came close to significance. Furthermore, the activation of several emotion-related brain regions, including insula, amygdala, anterior cingulate cortex, and dorsomedial prefrontal cortex, was also increased during rtfMRI-nf training. These findings suggest that humans are able to voluntarily modulate positive emotion networks, leading to exciting applications in the treatment of various neurological and psychiatric disorders.

Control freaks: Towards optimal selection of control conditions for fMRI neurofeedback studies

“…The mental-rehearsal control condition can be implemented both inside (57,59,60,(62)(63)(64)(65)(66)(67)(68)(69)(70)(71)(72)(73)(74)(75)(76)(77)(78)(79)(80) and outside the MRI scanner (e.g., 41,81,[82][83][84]. The latter option is much easier to realize and considerably decreases associated (personnel and scanning) costs.…”

Diminished positive affect and traumatic stress: A biobehavioral review and commentary on trauma affective neuroscience

“…Attempts to elucidate the neurocircuitry underlying positive emotion more specifically have utilized experimental manipulations to induce positive emotions in participants, such as positive autobiographical memory recall ( Li et al, 2016 ; Speer et al, 2014 ), self-directed induction of compassionate feelings ( Engen and Singer, 2015 ), and presentation of humorous stimuli ( Mobbs et al, 2003 ) or sexually explicit film clips ( Greenberg et al, 2015 ), all of which have been found to up-regulate activation in the canonical reward circuit nodes of the ventromedial prefrontal cortex and ventral striatum. Thus, the intact functioning of these neuroanatomical structures appear to be crucial to the processing of general positive valence, from the most circumscribed context-bound stimuli (rewards and reward predictors) to more general internally or externally cued positive emotional states.…”

Amygdala Modulation During Emotion Regulation Training With fMRI-Based Neurofeedback

“…Among the selected studies, 13 (68.42%) were neuroscience studies (Posse et al, 2003a; Johnston et al, 2010; Zotev et al, 2011, 2014; Brühl et al, 2014; Paret et al, 2014, 2018; Koush et al, 2015; Sarkheil et al, 2015; Li et al, 2016; Marxen et al, 2016; Hellrung et al, 2018; Lorenzetti et al, 2018), and six (31.58%) are clinically focused (Young et al, 2014, 2017; Paret et al, 2016; Zotev et al, 2016, 2018; Nicholson et al, 2017). Two studies addressed Post-Traumatic Stress Disorder (Nicholson et al, 2017; Zotev et al, 2018), one study focused on Borderline Personality Disorder (Paret et al, 2016) and three studies described a sample of subjects diagnosed with Major Depressive Disorder (Young et al, 2014, 2017; Zotev et al, 2016).…”

“…Concerning the selection of participants, often, non-overlapping exclusion criteria for participants were applied among studies: (a) History of neurological or psychiatric disease, (b) not being right-handed (handedness is taken as a rough measure of hemispheric dominance to ensure sample homogeneity, and reduce confounds), (c) non-compliance with fMRI standards, such as “general contraindications against MRI examinations” (Zotev et al, 2011; Brühl et al, 2014), “general MRI exclusions/incompatibilities” (Young et al, 2014; Paret et al, 2016), which related to the “MRI safety standards” (Nicholson et al, 2017), and “physical conditions that prevent lying comfortably inside an MRI scanner” (Marxen et al, 2016); (d) alcohol/drug abuse, and (e) absence of normal or corrected-to-normal vision. Nine of the studies (47.37%) used three or more of these criteria (Zotev et al, 2011; Brühl et al, 2014; Young et al, 2014, 2017; Li et al, 2016; Marxen et al, 2016; Paret et al, 2016; Nicholson et al, 2017; Hellrung et al, 2018), four studies (21.05%) used two of the mentioned criteria (Posse et al, 2003a; Koush et al, 2015; Sarkheil et al, 2015; Lorenzetti et al, 2018), four studies (21.05%) used only one exclusion criteria (Johnston et al, 2010; Paret et al, 2014, 2018; Zotev et al, 2016) and two did not describe the applied exclusion criteria (Zotev et al, 2014, 2018). From these criteria, (a) was the most frequently used (considered in 16 of the studies−84.21%), secondly (c) (eight studies−42.11%), followed by (d) and (b) (seven studies each−36.84%), and finally (e) being the least used criterion (only four studies−21.05%).…”