How to Catch a Blank Mind? Brain Similarities and Differences between Self- and Probe-Caught Mind Blanking
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Mind Blanking (MB) is a mental state characterized by the experience of a seemingly empty mind. This apparent emptiness challenges the theoretical view of a continuous and content-full stream of thought, leading to the question of how it is possible to capture MB events in the first place. MB research has relied largely on probe-caught experience-sampling, during which participants are interrupted at random times to report their mental state. This approach risks missing some MB events as they may occur between probes. Self-caught paradigms, on the other hand, allow participants to report MB upon spontaneously realizing it, relying on meta-awareness. To date, it is not clear whether these two methods capture the same phenomenon neuronally. Here, we investigated whether probe-caught MB (pMB) and self-caught MB (sMB) converge on their behavioral properties and brain correlates. Twenty-two participants underwent 3T fMRI scanning while performing both a pMB and a sMB experience-sampling task. We compared the behavioral properties, BOLD activations and time-varying functional connectivity (FC) across the two approaches. We found that reporting frequencies of pMB and sMB were significantly correlated across individuals, and both MB reports were uniformly distributed over time, pointing towards a behavioral convergence across approaches. However, we observed a divergence in BOLD activations, as sMB recruited significantly greater activation in the dorsal anterior cingulate cortex (dACC) compared to pMB, likely reflecting the meta-awareness and metacognitive monitoring required for self-detecting a MB. Lastly, time-varying FC analysis revealed a convergence, with both pMB and sMB FC resembling a hyperconnectivity pattern compared to other content-full mental states, pointing towards low arousal FC. Together, our results show that sMB and pMB converge on overlapping neurobehavioral correlates. This positions the self-caught method as a complementary tool for studying MB without external interruption, while highlighting the role of meta-awareness in self-report detection.