Resting state functional connectivity predicts neurofeedback response

Abstract

Tailoring treatments to the specific needs and biology of individual patients—personalized medicine—requires delineation of reliable predictors of response. Unfortunately, these have been slow to emerge, especially in neuropsychiatric disorders. We have recently described a real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback protocol that can reduce contamination-related anxiety, a prominent symptom of many cases of obsessive-compulsive disorder (OCD). Individual response to this intervention is variable. Here we used patterns of brain functional connectivity, as measured by baseline resting-state fMRI (rs-fMRI), to predict improvements in contamination anxiety after neurofeedback training. Activity of a region of the orbitofrontal cortex (OFC) and anterior prefrontal cortex, Brodmann area (BA) 10, associated with contamination anxiety in each subject was measured in real time and presented as a neurofeedback signal, permitting subjects to learn to modulate this target brain region. We have previously reported both enhanced OFC/BA 10 control and improved anxiety in a group of subclinically anxious subjects after neurofeedback. Five individuals with contamination-related OCD who underwent the same protocol also showed improved clinical symptomatology. In both groups, these behavioral improvements were strongly correlated with baseline whole-brain connectivity in the OFC/BA 10, computed from rs-fMRI collected several days prior to neurofeedback training. These pilot data suggest that rs-fMRI can be used to identify individuals likely to benefit from rt-fMRI neurofeedback training to control contamination anxiety.

Maintenance of Voluntary Self-regulation Learned through Real-Time fMRI Neurofeedback

“…To date, several studies show that neurofeedback training causes behavioral effects that are specific to the functional role of the targeted cortical area (Weiskopf et al, 2004; Bray et al, 2007; Caria et al, 2007; Rota et al, 2009; Shibata et al, 2011; Scharnowski et al, 2012, 2015; Robineau et al, 2014; Koush et al, 2015; Scharnowski and Weiskopf, 2015). Even more importantly, real-time fMRI neurofeedback training has also been shown to have therapeutic effects in chronic pain patients (deCharms et al, 2005; Guan et al, 2015), Parkinson’s disease (Subramanian et al, 2011), tinnitus (Haller et al, 2010), depression (Linden et al, 2012; Young et al, 2014), obsessive-compulsive disorder (Scheinost et al, 2013, 2014), spider phobia (Zilverstand et al, 2015), and addiction (Li et al, 2013; Karch et al, 2015; Kirsch et al, 2015; Hartwell et al, 2016). Especially for clinical applications of neurofeedback it is crucial that the learning effects persist beyond the initial training period and that voluntary control transfers to situations without neurofeedback information.…”

Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity?

“…In fact, a recent study found that DMN upregulation learning and down-regulation learning scores are partly determined by preneurofeedback resting-state eigenvector centrality of the PCC/PCu (Skouras & Scharnowski, 2019). Further, another study observed resting state connectivity to be predictive for neurofeedback learning success in patients with obsessive-compulsive disorder (Scheinost et al, 2014). These findings should be replicated and tested to assess whether they are generalizable.…”

Real-Time Functional Connectivity-Informed Neurofeedback of Amygdala-Frontal Pathways Reduces Anxiety

“…The outcome of an intervention is influenced by multiple factors [70], including pretreatment individual differences. The identification of markers that predict treatment response [83] and the use of repeated training sessions may increase the number of participants that respond to rt-fMRI NFTs.…”