The Management of Metastatic Triple-Negative Breast Cancer: An Integrated and Expeditionary Approach

An Intersectional Neuroscience Approach for Disadvantageous Populations: Meditation Practice as a Possible Support Option for Women with Breast Cancer?

Author(s): Katarzyna Rygiel *

Pp: 129-138 (10)

DOI: 10.2174/9789815196023123010012

* (Excluding Mailing and Handling)

Abstract

Mindfulness and compassion meditation have a positive impact on cognition, mood, behavior, and general health, based on recent studies in neuroscience. However, the research methodology is still insufficient to determine and measure different mental states during meditation, especially in minority populations. Intersectional Neuroscience, which is an innovative research model, may provide some solutions since it adapts modern research procedures to include disadvantageous groups of participants (e.g., ethnic minorities, patients with chronic diseases, like cancer, heart disease, or depression). Evaluating Multivariate Maps of BODY Awareness (EMBODY) is a task designed to accommodate diverse neural structures and functions, using the multi-voxel pattern analysis (MVPA) classifiers, with functional magnetic resonance imaging (fMRI). The EMBODY task applies individualized artificial intelligence algorithms to the fMRI data, in order to identify mental states during breath-focused meditation, a basic skill that stabilizes attention. This chapter describes a potential application of the Intersectional Neuroscience (IN) approach to developing useful metrics of meditation practice, including participants from disadvantageous groups. Hopefully, these findings can be explored in-depth, and possibly applied to patients with triple-negative breast cancer (TNBC), in the future. 


Keywords: Breath-focused meditation, Community-based participatory research (CBPR), Compassion meditation, Functional magnetic resonance imaging (fMRI), Intersectional neuroscience (IN), Mindfulness, Mindfulness-based interventions (MBI).

Related Journals
Related Books
© 2024 Bentham Science Publishers | Privacy Policy