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Macro-scale patterns in functional connectivity associated with ongoing thought patterns and dispositional traits.

Samyogita Hardikar1,2, Bronte Mckeown3, H Lina Schaare4,5

  • 1Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

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|November 20, 2024
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Summary
This summary is machine-generated.

Brain activity during wakeful rest reveals how personality traits and self-generated thoughts interact. Introverts show stronger connections between attention and default mode networks, influencing thought patterns.

Keywords:
humanmacro-scale connectivityneurosciencepersonality traitsspontaneous thoughttri-partite network

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Psychology

Background:

  • Brain activity during wakeful rest offers insights into neural organization, individual differences, and self-generated thought.
  • Disentangling neural correlates of personality traits from ongoing thoughts during rest is challenging.

Purpose of the Study:

  • To investigate the interplay between personality traits, ongoing thoughts, and brain network interactions during wakeful rest.
  • To explore if a 'tri-partite' brain network framework (ventral attention, dorsal attention, default mode) explains neural activity patterns at rest.

Main Methods:

  • Combined personality measures, indices of ongoing thoughts, and brain imaging analysis.
  • Utilized cortical gradients to map macro-scale relationships between brain systems in a low-dimensional space.

Main Results:

  • Introverted individuals exhibited greater functional alignment between the ventral attention network, somatomotor system, and default mode network.
  • Detailed self-generated thought patterns correlated with a decoupling of the dorsal attention network from the default mode network.

Conclusions:

  • Interactions between attention networks and the default mode network significantly influence ongoing thought processes during rest.
  • Integrating conscious experience perspectives is crucial for understanding resting-state brain activity patterns and their relation to traits and states.