Neurocognitive Mechanisms of Mindfulness: Insights from Basic Research and Translational ScienceSymposium Session 7: Monday, April 15, 2024, 10:00 am – 12:00 pm EDT, Ballroom West
Chair: Erika Nyhus1; 1Bowdoin College
Presenters: Kathryn Devaney, David Ziegler, Norman Farb, Erika Nyhus
Mindfulness meditation is the practice of becoming aware of present-moment experience with a compassionate, nonjudgmental stance (Kabat-Zinn, 1990). This seemingly simple act has had a profound impact on the world. In fact, the two most popular Mindfulness Apps, Headspace and Calm, have had over 200 million downloads. With such broad reaching impact, we’ve all heard the hype about mindfulness meditation, but what does the research show? Does mindfulness meditation really alleviate stress and improve cognition? How does mindful meditation change the brain? In this symposium, we examine the effects of mindfulness meditation on brain network activation, attention, emotion regulation, and episodic memory. To address these areas, we bring together researchers with diverse perspectives and methods, including behavioral methods employing expert meditators, in person meditation training, and mindfulness training Apps and neuroimaging methods using fMRI, EEG, and brain stimulation methods. This symposium will be of interest not only to researchers studying attention and memory, but to the general CNS audience interested in mindfulness meditation.
Highly Experienced Meditators Display Enhanced Stability in Sustained Attention Processes and Altered Resting-State Connectivity
Kathryn Devaney1; 1University of California, Berkeley
Meditation experience has previously been shown to improve performance on behavioral assessments of attention, and has been posited to effect predictive processing systems, but the neural bases of these changes are unknown. Here, we used functional magnetic resonance imaging (fMRI) to contrast cortical network activation between highly experienced focused attention Vipassana meditators and matched controls. Participants performed two attention tasks during scanning: a sustained attention task and an attention-capture oddball task (Devaney et al 2019). Meditators demonstrated increased magnitude of differential activation in the dorsal attention network (DAN) vs. default mode network (DMN) in the sustained attention task, relative to controls. A resting state functional connectivity analysis revealed a greater magnitude of anticorrelation between DAN and DMN in the meditators, compared to both our local control group and a n = 168 Human Connectome Project dataset. In contrast, attentional reorienting did not reveal attention network differences between meditators and controls. These results demonstrate, with both task- and rest-based fMRI data, increased stability in sustained attention processes in meditators without an associated attentional capture cost.
Closed-loop Digital Meditation as a Tool for Enhancing Cognition and Bolstering Neural Network Efficiency and Modularity Across the Lifespan
David Ziegler1; 1University of California, San Francisco
Given that attention is a fundamental component process of all aspects of higher order cognition, there exists a need for new methods to enhance attention abilities. A growing scientific literature supports the positive effects of real-world practices of focused-attention meditation as a means of improving sustained and selective attention. However, traditional forms of meditation can be challenging, intimidating, and expensive to learn. To help address these challenges, we developed a closed-loop, digital meditation intervention (MediTrain). This digital approach to meditation integrates key aspects of traditional meditation with a neuroplasticity-based approach to cognitive training and personalizes the experience to the real-time abilities of individuals and makes the practice available to anyone with a smartphone. I will summarize findings from a series of double-blind, randomized controlled trials (RCTs), in which we have demonstrated that MediTrain leads to improvements in sustained attention in healthy young adults, in adolescents who have experienced adverse childhood events, and in healthy older adults. In addition, MediTrain led to increased coherence of frontal theta activity in adults and led to a strengthening of functional connectivity in key cognitive control networks in both teens and older adults. We also found reductions in stress reactivity in older adults, and these stress and cognitive gains were maintained at a one-year follow up. I will conclude by previewing several ongoing studies aimed at increasing the reach of our intervention through fully mobile RCTs and by combining digital meditation with other forms of cognitive enhancement, such as noninvasive brain stimulation.
Mindful Emotion Regulation: Neural Mechanisms of Depression Vulnerability and Prophylaxis
Norman Farb1; 1University of Toronto Mississauga
Interoceptive training is a central facet of mindfulness training (MT), with the bulk of intervention practices including contemplative techniques such as breath monitoring, body scans, and yoga. Yet the mechanisms by which interoceptive mechanisms support MT benefits are still poorly understood. Two neuroimaging (fMRI) studies will be discussed. First, a large (N=85 x 2 timepoints) clinical trial of depression relapse vulnerability suggested that, in a context of provoked negative emotion, past, present, a future depression vulnerability is linked to a combination prefrontal activation and inhibition of sensory cortices, particularly the somatosensory cortex and posterior insula. Treatment response via both MT and cognitive behavioral therapies (CBT) was linked to reduced lateral prefrontal activation in a region which demonstrated a stress-evoked inhibitory relationship with sensory cortices following psychophysiological interaction (PPI) analysis. Second, neuroimaging of attention to the breath (N=22 x 2 timepoints) suggested that, relative to visual attention, training-related increases in subjective interoception (MAIA scale) were related to spared deactivation of the anterior cingulate cortex (ACC) and language regions within a broader context of cortical deactivation. PPI analysis suggested that attention to the breath also enhanced ACC connectivity with the dorsal attention network. Together, these findings support a model of mindful interoception as reversing the tendency for emotional stressors to inhibit sensory attention, which may allow practitioners to retain cognitive flexibility in the face of daily stressors.
Increases in Theta Oscillatory Activity During Episodic Memory Retrieval Following Mindfulness Meditation Training
Erika Nyhus1; 1Bowdoin College
Mindfulness meditation has been shown to improve episodic memory and increase theta oscillations which are known to play a role in episodic memory retrieval. The present study examined the effect of mindfulness meditation on episodic memory retrieval and theta oscillations. Using a longitudinal design, subjects in the mindfulness meditation experimental group who underwent 4 weeks of mindfulness meditation training and practice were compared to a waitlist control group. During the pre-training and post-training experimental sessions, subjects completed the Five Facet Mindfulness Questionnaire (FFMQ) and studied adjectives and either imagined a scene (Place Task) or judged its pleasantness (Pleasant Task). During the recognition test, subjects decided which task was performed with each word (“Old Place Task” or “Old Pleasant Task”) or “New.” FFMQ scores and source discrimination were greater post-training than pre-training in the mindfulness meditation experimental group. Electroencephalography (EEG) results revealed that for the mindfulness meditation experimental group theta power was greater post-training than pre-training in right frontal and left parietal channels and changes in FFMQ scores correlated with changes in theta oscillations in right frontal channels (n = 20). The present results suggest that mindfulness meditation increases source memory retrieval and theta oscillations in a fronto-parietal network.
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