Our minds have a fascinating ability to wander into daydreams effortlessly, letting creativity and reflections flow naturally.
In a recent study reported in Frontiers of Human Neuroscience, researchers from the University of Arizona utilized low-intensity ultrasound technology to modify a specific brain region associated with daydreaming, memory recall, and future envisioning. This innovative approach has shown promising results in enhancing mindfulness, representing a significant breakthrough in neuroscience.
The team employed a technique called transcranial-focused ultrasound (TFUS) to target the brain’s default mode network, a collection of brain regions active during daydreaming and introspective moments.
Lead researcher Brian Lord, part of the Science Enhanced Mindfulness Lab at the university, highlighted the importance of the posterior cingulate cortex in forming personal narratives and engaging in internal reflections.
While these self-narratives are fundamental for self-awareness, they can hinder living in the present moment, especially during activities like meditation, by leading to rumination and negative thoughts.
To help individuals be more present, the team used TFUS to stimulate the brain noninvasively with millimeter precision, a method that differs from other noninvasive brain stimulation techniques by penetrating deeper into the brain and exhibiting rapid effects.
Thirty participants underwent TFUS treatment on the posterior cingulate cortex, monitored through functional magnetic resonance imaging (fMRI) to track changes in brain activity and subjective experiences pre and post-treatment.
The study revealed reduced connectivity in the brain’s default mode network post-TFUS, impacting mindfulness and self-perception, underscoring the promising applications of this technology in tailored therapeutics and mood disorder treatments.
Lord emphasized the minimal energy required for TFUS to alter brain activity, highlighting the potential for personalized medical interventions and advancements in causal modeling in neuroscience.
