Susan Whitfield‐Gabrieli

2 papers in the library · 88 citations · publishing 2020-2024

Papers

Real-time fMRI neurofeedback reduces auditory hallucinations and modulates resting state connectivity of involved brain regions: Part 2: Default mode network -preliminary evidence

Psychiatry Research January 14, 2020 Clemens Bauer, Kana Okano, Satrajit Ghosh et al. 87 citations

Auditory hallucinations in schizophrenia are linked to overactivity and hyperconnectivity in the default mode network and reduced anticorrelation with the central executive network. Patients were trained with real-time fMRI neurofeedback and meditation strategies to modulate these networks. The intervention reduced default mode network hyperconnectivity and increased anticorrelation between the default mode and central executive networks. Changes in individual default mode network connectivity correlated with reductions in auditory hallucination frequency and severity. This provides the first empirical evidence that meditation-enhanced neurofeedback can directly alter resting state network activity and reduce auditory hallucinations.

DOI: 10.1016/j.psychres.2020.112770 Full text Default mode network Meditation Neurofeedback Neuroscience +7

Connectome predictive modeling of trait mindfulness

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.

DOI: 10.1101/2024.07.09.602725 Mindfulness Connectome Trait Cognitive psychology +4