Journal of Neuroscience
March 12, 2014
Aaron Kucyi, Massieh Moayedi, Irit Weissman‐fogel et al.
390 citations
In patients with chronic pain, rumination—repetitive focus on discomfort—is linked to altered functional connectivity in the brain's default mode network. In a study of 17 patients with temporomandibular disorder and 17 matched healthy controls, those with chronic pain showed enhanced connectivity between the medial prefrontal cortex and other default mode network regions, including the posterior cingulate cortex and precuneus. Among patients, greater rumination about pain correlated with stronger connectivity between the medial prefrontal cortex and the posterior cingulate cortex, precuneus, retrosplenial cortex, medial thalamus, and periaqueductal gray. These results suggest that communication within the default mode network and with the descending pain modulatory system underlies the degree of rumination about chronic pain.
NeuroImage
June 25, 2014
Aaron Kucyi, Karen D. Davis
381 citations
Daydreaming is linked to how brain networks fluctuate over time, not just their average connectivity. In healthy adults, those who daydreamed more showed less stable connectivity between the posterior cingulate cortex and a part of the default mode network involved in future thinking. However, greater moment-to-moment variability in that same network's connectivity predicted more mind-wandering during a sensory task. The findings suggest that dynamic, rather than static, brain network activity reflects the conscious experience of daydreaming.
Human brain mapping
January 1, 2025
Isaac N Treves, Aaron Kucyi, Madelynn Park et al.
8 citations
Trait mindfulness—the tendency to attend to present experience non-judgmentally—is linked to better mental health, but its neural basis remains unclear. In the largest resting-state fMRI study of trait mindfulness to date, involving 367 meditation-naïve adults across three sites, no connections predicted overall trait mindfulness. However, neural models for two subscales, Acting with Awareness and Non-judging, were identified. Positive networks for these subscales involved distinct fronto-parietal and default-mode networks, while negative networks overlapped across subscales and included somatomotor, visual, and default-mode regions. Only negative networks generalized to predict subscale scores in some out-of-sample tests. Predictions negatively correlated with a mind-wandering model. The findings provide preliminary evidence for generalizable connectivity models of mindfulness facets, but incomplete generalization across sites and model overlap highlight the challenge of identifying robust brain markers.
Biological psychiatry global open science
November 1, 2024
Isaac N Treves, Hilary A Marusak, Alexandra Decker et al.
7 citations
A significant finding reveals that adolescents with higher trait mindfulness experience lower anxiety and depression symptoms. An analysis of 106 adolescents, ages 12 to 15, identified a reliable brain state characterized by hyperconnectivity, showing an intraclass correlation coefficient of 0.65. This state, marked by elevated positive connectivity between networks, was positively correlated with self-reported trait mindfulness. While most dynamic brain states were unreliable across scans, this hyperconnected state may reflect enhanced awareness and arousal in those exhibiting higher mindfulness traits.
bioRxiv : the preprint server for biology
July 4, 2024
Isaac N Treves, Hilary A Marusak, Alexandra Decker et al.
3 citations
preprint
A highly reliable brain state linked to trait mindfulness was identified in adolescents, highlighting its potential role in mental health. In a study of 106 participants aged 12 to 15, one hyperconnected state showed good reliability (ICC=0.65) and correlated positively with self-reported trait mindfulness. Adolescents exhibiting higher trait mindfulness experienced lower anxiety and depression symptoms. While most dynamic brain states were unreliable across scans, this particular state suggests that increased mindfulness may enhance awareness and arousal, offering insights into adolescent mental well-being.
bioRxiv Preprint Server
January 20, 2024
Aaron Kucyi, Nathan Anderson, Tiara Bounyarith et al.
2 citations
preprint
Mind-wandering, a common daily mental activity, varies uniquely from person to person. In three individuals who each reported hundreds of mind-wandering episodes during multiple fMRI sessions, reliable links between mind-wandering and default mode network (DMN) activation emerged when brain networks were analyzed within each person. However, the timing of spontaneous DMN activity relative to subjective reports, and the broader networks activated or deactivated during mind-wandering, differed across individuals. Whole-brain connectivity patterns that predicted mind-wandering within an individual did not fully generalize to others, and predictive models from larger datasets largely failed when applied to these densely-sampled individuals. This work demonstrates both conserved and variable neural representations of mind-wandering, highlighting the value of personalized approaches.
bioRxiv (Cold Spring Harbor Laboratory)
July 14, 2024
Isaac N. Treves, Aaron Kucyi, Madelynn Park et al.
1 citation
preprint
Trait mindfulness—the tendency to attend to present-moment experience non-judgmentally—is linked to better mental health, but its neural basis remains unclear. In the largest resting-state fMRI study of trait mindfulness to date, involving 367 adults across three samples, researchers used connectome predictive modeling to test whether brain connectivity patterns could predict mindfulness scores. No connections predicted overall trait mindfulness, but models for two subscales—Acting with Awareness and Non-judging—were identified. Positive networks for these subscales involved fronto-parietal and default-mode networks, respectively. Negative networks, which overlapped across subscales, included somatomotor, visual, and default-mode connections. Only negative networks generalized to predict subscale scores in some out-of-sample datasets, and predictions correlated negatively with a mind-wandering model. The incomplete generalization and model overlap highlight the challenge of identifying robust brain markers for mindfulness facets.