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Investigating the effects of focused attention (mantra) meditation on mismatch negativity: Insights into sensory and
Chandan Srivastava1, Jamie A O'Reilly2, Rashmi Gupta1
1Cognitive and Behavioural Neuroscience Laboratory, Department of Humanities and Social Sciences, Indian Institute of Technology Bombay, Powai, Mumbai, 400076, Maharashtra, India.
Abstract:
Over the past fifty years, research has enhanced our understanding of meditation and its effects on cognition. Meditation is particularly promising due to its long-term (trait) effects, which persist outside meditation sessions. Advances in neuroimaging have enabled the study of these effects using neural markers such as mismatch negativity (MMN), which reflects the involuntary shift of attention to unexpected acoustic changes. This shift is modulated by attentional control, a key area where focused attention (FA) meditation training offers improvements. However, studies investigating the trait effects of FA meditation on MMN have produced mixed results, with previous research introducing confounds from short-term (state) effects that may influence trait-specific assessments. Furthermore, most research has focused on breath-based FA meditation, overlooking other prominent forms of FA meditation that might differentially modulate MMN, as per recent studies. The current study, therefore, examines mantra meditation, a widely practiced form of FA meditation, with an adequately powered sample to address the mixed findings in the literature. The study employs an intensity oddball paradigm instead of commonly used frequency oddball paradigms to assess whether MMN arises from higher-order cognitive processes or sensory adaptation. The findings reveal similar MMN amplitude in experts and novices, suggesting that MMN may be insensitive to meditation expertise or influenced by the enhanced attentional skills of novices. Additionally, a unidirectional polarity shift in event-related potential to deviant stimuli suggests that meditation effects on MMN are likely to be interpreted in the context of higher-order deviance detection mechanism.
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