Annotation: What electrical brain activity tells us about brain function that other techniques cannot tell us – a child psychiatric perspective
Article first published online: 6 OCT 2006
Journal of Child Psychology and Psychiatry
Volume 48, Issue 5, pages 415–435, May 2007
How to Cite
Banaschewski, T. and Brandeis, D. (2007), Annotation: What electrical brain activity tells us about brain function that other techniques cannot tell us – a child psychiatric perspective. Journal of Child Psychology and Psychiatry, 48: 415–435. doi: 10.1111/j.1469-7610.2006.01681.x
- Issue published online: 6 OCT 2006
- Article first published online: 6 OCT 2006
- Manuscript accepted 8 June 2006
- anorexia nervosa;
- childhood-onset schizophrenia;
- developmental dyslexia;
- obsessive-compulsive disorder;
- specific language disorder;
- tic disorder
Background: Monitoring brain processes in real time requires genuine subsecond resolution to follow the typical timing and frequency of neural events. Non-invasive recordings of electric (EEG/ERP) and magnetic (MEG) fields provide this time resolution. They directly measure neural activations associated with a wide variety of brain states and processes, even during sleep or in infants. Mapping and source estimation can localise these time-varying activation patterns inside the brain.
Methods: Recent EEG/ERP research on brain functions in the domains of attention and executive functioning, perception, memory, language, emotion and motor processing in ADHD, autism, childhood-onset schizophrenia, Tourette syndrome, specific language disorder and developmental dyslexia, anxiety, obsessive-compulsive disorder, and depression is reviewed.
Results: Over the past two decades, electrophysiology has substantially contributed to the understanding of brain functions during normal development, and psychiatric conditions of children and adolescents. Its time resolution has been important to measure covert processes, and to distinguish cause and effect.
Conclusions: In the future, EEG/ERP parameters will increasingly characterise the interplay of neural states and information processing. They are particularly promising tools for multilevel investigations of etiological pathways and potential predictors of clinical treatment response.