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Related Concept Videos

Traumatic Memory01:20

Traumatic Memory

225
Emotionally traumatic events often lead to memories that are exceptionally vivid and enduring, sometimes persisting with remarkable clarity throughout an individual's life. A classic example of this phenomenon is a person who survives a car accident. Even years later, they may recall every detail of the event with startling accuracy — the screeching of the tires, the jarring impact, and the acrid smell of burning rubber. Such vividness contrasts sharply with how an individual...
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Network Specificity in Predicting Childhood Trauma Characteristics Using Effective Connectivity.

Shufei Zhang1,2, Wei Zheng3,4, Zezhi Li3,4

  • 1Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52425 Jülich, Germany.

Alpha Psychiatry
|July 9, 2025
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Summary

Childhood maltreatment impacts brain development. Effective connectivity within the default mode network (DMN) shows promise in predicting maltreatment severity in adults.

Keywords:
childhood maltreatmentdefault mode networkeffective connectivityfeature selectionregression dynamic causal modeling

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Brain Imaging

Background:

  • Childhood maltreatment (CM) is a significant stressor affecting brain development.
  • Previous research focused on functional connectivity, leaving dynamic effective connectivity (EC) less understood.

Purpose of the Study:

  • To investigate the relationship between brain effective connectivity (EC) and childhood maltreatment severity.
  • To identify specific brain networks whose EC patterns can predict CM severity.

Main Methods:

  • Resting-state fMRI data from 215 adults were analyzed using dynamic causal modeling for whole-brain EC estimation.
  • Regression models, including LASSO, were used to predict Childhood Trauma Questionnaire (CTQ) scores based on EC features.
  • EC features were selected based on correlation thresholds (5%, 10%, 20%) and validated.

Main Results:

  • Whole-brain EC showed a marginal association with predicting CM severity (CTQ scores).
  • Effective connectivity within the default mode network (DMN) significantly predicted CTQ scores.
  • DMN-specific EC features consistently showed predictive power across different selection thresholds.

Conclusions:

  • Brain effective connectivity can reflect individual differences in childhood maltreatment severity.
  • The default mode network (DMN) emerges as a key predictor in the context of CM.