Predicting Neurofeedback and BCI Performance Using Sensory Processing Sensitivity Scores

Abstract

Neurofeedback is a biofeedback method allowing individuals to self-regulate neural activity, such as via EEG, to influence their cognitive and emotional functioning. Alpha brainwaves (8-12 Hz), associated with relaxed wakefulness, are a common target - their augmentation shows promise for treatment of conditions like depression and anxiety. However, predicting individual success in neurofeedback training or brain-computer interface (BCI) control remains challenging [1]. Some people appear to be non-responders, as they fail to gain sufficient control. Predicting response success is crucial for optimizing intervention efficacy and generalizability of applications.

Simultaneously, Sensory Processing Sensitivity (SPS) has emerged in psychological research as a heritable trait characterized by deeper processing and heightened reactivity to stimuli, present in 20-30% of the population. Individuals with high SPS may exhibit greater interoceptive awareness [2].

We hypothesize a link between an individual's ability for successful BCI interaction and the presence of the SPS trait. Drawing on evidence suggesting high SPS individuals possess good interoceptive abilities and deep stimulus processing, we propose this trait may predict neurofeedback and/or successful BCI interaction, which we will proxy by a motor imagery task (a task that requires individuals to imagine movements without actually exhibiting them). Existing research links various known predictors of performance to traits typical for high SPS individuals.

Building on this potential link, this pilot study investigates whether SPS or its constituent components (Aesthetic Sensitivity, Low Sensory Threshold, and Ease of Excitation), are associated with individual differences in alpha neurofeedback and motor imagery task performance. We hypothesize that SPS scores might correlate with performance in these tasks. We explore whether SPS can serve as a predictor of training success and whether it could be useful in identifying individuals who may be non-responders or exhibit poorer performance.

Healthy adult participants, without a history of psychiatric or neurological disorders, scoring high and low on the SPS trait (measured by the SPS questionnaire [3]) will engage in alpha neurofeedback training following contemporary protocols and complete a motor imagery task. This study, limited by its small sample size inherent to a pilot design, aims to test the feasibility of using SPS as a predictor of performance in these tasks. Should a significant effect be found, it would warrant further investigation into the neurobiological basis of SPS and its broader influence on performance across diverse BCI and neurofeedback paradigms.

References

[1] O. Alkoby, A. Abu-Rmileh, O. Shriki, and D. Todder, “Can We Predict Who Will Respond to Neurofeedback? A Review of the Inefficacy Problem and Existing Predictors for Successful EEG Neurofeedback Learning”, Neuroscience, vol. 378, pp. 155–164, May 2018. doi: 10.1016/j.neuroscience.2016.12.050.

[2] E. N. Aron, A. Aron, and J. Jagiellowicz, “Sensory Processing Sensitivity: A Review in the Light of the Evolution of Biological Responsivity”, Pers Soc Psychol Rev, vol. 16, no. 3, pp. 262–282, Aug. 2012. doi: 10.1177/1088868311434213.

[3] E. N. Aron and A. Aron, “Sensory-Processing Sensitivity and Its Relation to Introversion and Emotionality”, Journal of personality and social psychology, vol. 73, no. 2, p. 345, 1997.