Dimensional brain-behavior relationships in children with attention-deficit/hyperactivity disorder
Camille Chabernaud1, Maarten Mennes, Clare Kelly
1Phyllis Green and Randolph Cowen Institute for Pediatric Neuroscience at the New York University Child Study Center, Langone Medical Center, New York, New York, USA.
Biological Psychiatry
|October 7, 2011
Summary
Dimensional measures of psychiatric symptoms reveal brain-behavior links beyond categorical diagnoses like ADHD. These relationships are influenced by the presence of ADHD, suggesting a complex interplay in psychiatric disorders.
Area of Science:
- Neuroscience
- Psychiatry
- Genetics
Background:
- Psychiatric disorders are increasingly viewed dimensionally, not categorically.
- Integrating dimensional approaches into current diagnostic frameworks is challenging.
- Resting state functional magnetic resonance imaging (RSFMRI) can explore brain-behavior relationships.
Purpose of the Study:
- To investigate if dimensional psychiatric symptomatology captures brain-behavior relationships missed by categorical diagnoses.
- To determine if attention-deficit/hyperactivity disorder (ADHD) modifies dimensional brain-behavior associations.
Main Methods:
- RSFMRI scans were acquired from children with and without ADHD.
- Dimensional measures included parent-rated Child Behavior Checklist (CBCL) Internalizing and Externalizing scores.
- Default Network (DN) resting state functional connectivity (RSFC) was analyzed.
Main Results:
- Significant associations between DN RSFC and both internalizing and externalizing scores were found, irrespective of diagnosis.
- Increased internalizing scores correlated with stronger positive intra-DN RSFC.
- Increased externalizing scores correlated with reduced negative RSFC between DN and task-positive regions.
Conclusions:
- Categorical diagnostic boundaries may be insufficient for understanding psychiatric disorder pathophysiology.
- Psychiatric illness is not merely an extreme of typical function; dimensional and categorical assessments are crucial.
- Understanding neural underpinnings requires integrating both dimensional and categorical clinical data.
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