Using Electrophysiological Methods to Understand Neural Mechanisms of, and Treatment Effects in, Mental Illness in Children and Adolescents
- Sponsored by:
- National Institute of Mental Health
In September 2009, the NIMH convened a multidisciplinary workshop to discuss the role of electrophysiology in understanding the brain mechanisms underlying mental illness in children and adolescents. The meeting was organized around different domains of functioning, including: auditory processing/language; social information processing; emotion regulation; and, attention/inhibition. In addition, one session specifically examined the use of electrophysiology to examine treatment effects in children and adolescents with mental illness. Participants discussed major trends, methodological challenges, and opportunities.
The first part of each session briefly highlighted the most promising research using electrophysiology to understand the particular domain of functioning under discussion. A series of talks on particular aspects that required special attention when studying children followed, such as the need to understand typical development. Methodological considerations were then addressed, with a special focus on new methods of analysis that could further elucidate the brain mechanisms underlying the particular domain or the disorders under study. Each session was followed by a period of discussion.
Current Research Using Electrophysiological Tools
Presentations focused on results from recent and on-going studies that have shown the utility of these tools to:
- track language development from infancy onwards;
- reveal the developmental trajectory of auditory and sensory evoked responses and abnormalities of these trajectories in autism spectrum disorders;
- understand the functional significance of delayed maturation of white matter tracts in autism spectrum disorders;
- predict conversion from the prodromal stage of schizophrenia to psychosis;
- elucidate the abnormal attentional processes in individuals with attention deficit hyperactivity disorder.
In addition, similar to imaging genetics as used with functional magnetic resonance imaging (fMRI), electroencephalography (EEG) and magnetoencephalography (MEG) can be used to associate an endophenotype with one of the putative genotypes for a particular disorder. The participants agreed that there is considerable evidence to support the important contribution that these tools can make to our understanding of the neural substrates of mental illness, our ability to predict the course and/or the development of mental illness, and to elucidate treatment effects and efficacy of interventions.
Participants agreed that a major advantage of these tools is that they provide a direct measure of brain activity, unlike the indirect measures obtained with fMRI. Participants indicated that an important area for development is cross-methodological studies using both fMRI and electrophysiology. The two tools are complementary in many ways, and can provide a broader knowledge of brain functioning when used together than when used separately. While fMRI highlights parallel processing (where activation is occurring) electrophysiology captures aspects of serial processing (when activation is occurring).
During the workshop, presentations highlighted the potential of electrophysiological tools to provide real-time monitoring of activity within brain circuits on a millisecond-by-millisecond basis, which may be crucial to detecting the types of disruptions that are likely to occur in mental disorders. As technological developments continue to make EEG more portable, it will be possible to collect data using new experimental paradigms, and to analyze the data using sophisticated methods capable of capturing trial-to-trial variability, which is much more informative about brain processes than averaging is.
Despite this promise, participants were concerned about a widespread belief that electrophysiological signals are unrelated to underlying brain activity. This misconception may exist because current data collection and data analytic techniques have used relatively little of the abundant information EEG and MEG data can provide, and that minimal information has been correlated to a very limited aspect of the mental disorder being studied. For instance, one commonly used data analytic method averages the signals in order to collapse the data into two dimensions (e.g., time and amplitude measurements of event related potentials [ERP]). These data are then related to behaviors assessed in highly controlled settings in the laboratory, which cannot capture the full spectrum of dysfunction in a disorder. Thus, it is difficult to grasp the significance of the electrophysiological signals and their relationship to complex behavior.
Workshop participants identified a number of areas in pediatric studies of psychopathology that require further improvement, including training to help researchers understand the physiological basis of these tools, and efforts to develop methodological best practices, including experimental design and data analysis.
Participants agreed that electrophysiological tools have the potential to identify individuals at greatest risk for mental illness and, in this way, may provide an important window into the effectiveness of early intervention in preventing or altering the course of mental illnesses. Studies delineating typical development are critically important to understanding the abnormal processes associated with mental disorders in children and adolescents. A major advantage of EEG/MEG is that many of the experimental paradigms can be used in very young children—unlike fMRI, which typically requires the cooperation of the individual being studied.
Another important area of future study is the reliability of the electrophysiological signals and the validity of their relationship to behavioral phenotypes. This effort will require innovative mobile devises to collect data in real-life situations and to synchronize complex data sets from many different sources—e.g., interactive eye tracking, gaze scene tracking, recording, psychophysiology, EEG, and motion capture. Critical also are large, normative, preferably longitudinal, developmental EEG datasets linked to behavioral phenotypes available through data-sharing portals similar to those presently available for MRI data. Another area ripe for further study is the use of electrophysiological tools in cross-species translational studies to yield potential targets for novel pharmacological and behavioral interventions.
In addition, all recognized the need for greater outreach and education regarding the nature of electrophysiological tools and their potential to further our understanding of the mechanisms of mental disorders.
For more information, please contact Marjorie Garvey, M.B., B.Ch., 301-443-5944.