Data_Sheet_2_Toward a Compassionate Intersectional Neuroscience: Increasing Diversity and Equity in Contemplative Neuroscience.PDF

Mindfulness and compassion meditation are thought to cultivate prosocial behavior. However, the lack of diverse representation within both scientific and participant populations in contemplative neuroscience may limit generalizability and translation of prior findings. To address these issues, we propose a research framework called Intersectional Neuroscience which adapts research procedures to be more inclusive of under-represented groups. Intersectional Neuroscience builds inclusive processes into research design using two main approaches: 1) community engagement with diverse participants, and 2) individualized multivariate neuroscience methods to accommodate neural diversity. We tested the feasibility of this framework in partnership with a diverse U.S. meditation center (East Bay Meditation Center, Oakland, CA). Using focus group and community feedback, we adapted functional magnetic resonance imaging (fMRI) screening and recruitment procedures to be inclusive of participants from various under-represented groups, including racial and ethnic minorities, gender and sexual minorities, people with disabilities, neuropsychiatric disorders, and/or lower income. Using person-centered screening and study materials, we recruited and scanned 15 diverse meditators (80% racial/ethnic minorities, 53% gender and sexual minorities). The participants completed the EMBODY task – which applies individualized machine learning algorithms to fMRI data – to identify mental states during breath-focused meditation, a basic skill that stabilizes attention to support interoception and compassion. All 15 meditators’ unique brain patterns were recognized by machine learning algorithms significantly above chance levels. These individualized brain patterns were used to decode the internal focus of attention throughout a 10-min breath-focused meditation period, specific to each meditator. These data were used to compile individual-level attention profiles during meditation, such as the percentage time attending to the breath, mind wandering, or engaging in self-referential processing. This study provides feasibility of employing an intersectional neuroscience approach to include diverse participants and develop individualized neural metrics of meditation practice. Through inclusion of more under-represented groups while developing reciprocal partnerships, intersectional neuroscience turns the research process into an embodied form of social action.

正念与慈悲冥想被认为可培育亲社会行为。然而，沉思神经科学领域中，科研人员群体与受试者群体均缺乏多样性代表性，这可能会限制既往研究结果的可推广性与转化应用。为解决上述问题，我们提出一种名为交叉神经科学（Intersectional Neuroscience）的研究框架，该框架调整研究流程以更充分纳入代表性不足的群体。交叉神经科学通过两大核心路径将包容性流程嵌入研究设计：其一，与多样化受试者群体开展社区合作；其二，采用个体化多元神经科学方法以适配神经多样性。我们与美国加州奥克兰市东湾冥想中心（East Bay Meditation Center）合作，对该框架的可行性进行了验证。借助焦点小组调研与社区反馈，我们对功能磁共振成像（functional magnetic resonance imaging, fMRI）的筛查与招募流程进行了调整，以纳入来自各类代表性不足群体的受试者，包括少数种族与族裔群体、性别与性少数群体、残障人士、神经精神疾病患者及低收入人群。依托以受试者为中心的筛查流程与研究材料，我们共招募并完成扫描的15名多样化冥想参与者中，80%为少数种族与族裔群体，53%为性别与性少数群体。受试者完成了EMBODY任务——该任务将个体化机器学习算法应用于fMRI数据，以识别专注呼吸冥想过程中的心理状态。专注呼吸是一项基础技能，可稳定注意力以支持内感受与慈悲觉知。所有15名冥想参与者的独特脑活动模式均被机器学习算法以显著高于随机水平的准确率识别。这些个体化脑活动模式被用于解码每位冥想者在10分钟专注呼吸冥想过程中的内部注意力焦点。上述数据被用于构建冥想过程中的个体水平注意力特征档案，例如用于关注呼吸、思绪游离或进行自我参照加工的时间占比。本研究验证了采用交叉神经科学方法纳入多样化受试者，并构建冥想练习的个体化神经指标的可行性。通过纳入更多代表性不足群体并构建互惠合作关系，交叉神经科学将研究流程转化为一种具身化的社会行动形式。