Interest in investigating the neural correlates of different meditation practices is increasing within the neuroscience community. In particular, shamatha practice, which strengthens the ability of a practitioner to sustain a concentrated, single-pointed focus of attention, is a natural focus for attention researchers within cognitive neuroscience. However, studies of the medium- and long-term effects of shamatha practice have been hindered by the lack of a real-time, neurophysiological marker or index of attentional depth. The aim of the present study is to validate a proposed index of attention, correlate it with 1st person reports of subjective experience, and determine if feedback of such an objective, real-time index can help deepen shamatha practice. Participants engaged in a visual selective attention task involving stimuli which flickered at a rate designed to produce a steady-state visual evoked potential (SSVEP). At the beginning of a trial, a cue prompted the participant to attend to either the right or left stimulus. Following the cue two stimuli flickering at different rates appear onscreen for several seconds. Since the SSVEP amplitude is modulated by attention, an index of attention can be constructed by monitoring the ratio of SSVEP amplitudes on a trial-by-trial basis. This index can be extracted in real time and fed back to the participant to provide a neurophysiological index of attentional depth which can be compared to subjective assessment of attentional depth. This study is still in a preliminary phase, but fair to good offline (not real-time) classification of the focus of attention has been obtained for several subjects. Our group now plans to implement a real-time version of this paradigm to enable real-time feedback and classification. Given our current results, our research group expects to have a real-time EEG feedback attention training system running within 6 months.

Ryan Canolty

University of California–Berkeley

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