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The effect of mindfulness meditation on ERP measures of attention

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Brady, JJR 2019 , 'The effect of mindfulness meditation on ERP measures of attention', Honours thesis, University of Tasmania.

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Abstract

Mindfulness meditation refers to the non-judgmental and present focus on thoughts, feelings and experiences. Neurocognitive studies have associated processes involved in mindfulness meditation with neural networks implicit in attention. These processes are described in Attention Network Theory. The literature reflects growing support for the use of mindfulness meditation as an attentional intervention. Recent innovation has seen the development of neurofeedback devices, designed to augment the outcomes of mindfulness meditation training. However, there are few studies which have quantified these effects. The Attention Network Test is well-supported in assessing measures of attention outlined by Attention Network Theory. Accordingly, we use the Attention Network Test to compare reaction time (ms), accuracy (% correct), and N1 and P3 ERPs (μV) to quantify the effects of mindfulness meditation relative to an active electrodermal-assisted relaxation control. Results indicate no significant improvement in RT for the meditation group relative to controls, or significant corresponding N1 or P3 amplitudes. However, relating to stable reaction time measures, we find evidence of enhanced attentional network efficiency in the meditation group. These observations are paired with state and trait-based self-reports of disposition, in order to track the intervention’s manipulation. We found increased self-reported emotional regulation in both groups. Additionally, we present a case for the use of mixed models in such designs. We conclude that further research is warranted to investigate underlying mechanisms of meditation on attention, and the influence that any dispositional variation may have on training outcomes.

Item Type: Thesis - Honours
Authors/Creators:Brady, JJR
Keywords: ERP, Mindfulness Meditation, Training, Mixed Models, Neurofeedback, Muse, Attention Network Test
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Copyright 2019 the author

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