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11-03 Identifying cognitive and affective markers within an integrative neuroscience model of ADHD

Published online by Cambridge University Press:  24 June 2014

DF Hermens ,
MR Kohn ,
SD Clarke ,
CR Clark ,
E Gordon  and
LM Williams
DF Hermens
Affiliation:
The Brain Dynamics Centre, Westmead Millennium Institute, Westmead Hospital and Western Clinical School, University of Sydney, Australia Brain Resource International Database, Brain Resource Company
MR Kohn
Affiliation:
The Brain Dynamics Centre, Westmead Millennium Institute, Westmead Hospital and Western Clinical School, University of Sydney, Australia Adolescent Medicine, CRASH, Westmead Hospital, Westmead, Australia Children's Hospital at Westmead, Westmead, Australia
SD Clarke
Affiliation:
The Brain Dynamics Centre, Westmead Millennium Institute, Westmead Hospital and Western Clinical School, University of Sydney, Australia Adolescent Medicine, CRASH, Westmead Hospital, Westmead, Australia Children's Hospital at Westmead, Westmead, Australia
CR Clark
Affiliation:
Cognitive Neuroscience Unit, Flinders University, Adelaide, Australia
E Gordon
Affiliation:
The Brain Dynamics Centre, Westmead Millennium Institute, Westmead Hospital and Western Clinical School, University of Sydney, Australia Brain Resource International Database, Brain Resource Company
LM Williams
Affiliation:
The Brain Dynamics Centre, Westmead Millennium Institute, Westmead Hospital and Western Clinical School, University of Sydney, Australia Brain Resource International Database, Brain Resource Company
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Abstract

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Type
Abstracts from ‘Brainwaves’— The Australasian Society for Psychiatric Research Annual Meeting 2006, 6–8 December, Sydney, Australia
Information
Acta Neuropsychiatrica , Volume 18 , Issue 6 , December 2006 , pp. 339
Copyright
Copyright © 2006 Blackwell Munksgaard

Background:

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, often allied with conduct and emotional problems. Our integrative model of ADHD explores fronto-limbic-striatal networks and arousal regulation to understand poor inhibitory function in ADHD. This model provides the basis to develop new and objective assessment tools that complement subjective clinical scales in diagnostic and treatment decisions. Our objective was to identify the combination of cognitive and brain function markers that distinguish ADHD. We also evaluated these markers in response to stimulants treatment.

Methods:

About 175 patients with ADHD (6–16 years) tested before and after stimulant treatment were compared with 175 matched controls using the standardized Brain Resource protocols. Testing included batteries of cognitive tests and psychophysio-logical measures of brain function [EEG, event-related potentials (ERPs)] in response to cognitive- and emotion-related tasks.

Results:

Multivariate analyses showed a profile of cognitive and brain function markers that distinguished ADHD (90% sensitivity, 71% specificity, 0.76 positive predictive power, 0.88 negative predictive power). This profile comprised errors of impulsivity and intrusion, with raised slow-wave EEG, altered ERPs during inhibition and emotion processing, and autonomic dysregulation. While cognitive, EEG and inhibition-related ERP markers ‘normalized’ following stimulants, the emotion ERP marker did not. Autonomic markers distinguished subgroups of treatment responders.

Conclusions:

These findings support an integrative model of ADHD, in which impulsivity and poor inhibition are associated with dysregulation of brain function and arousal. The markers provide a platform for objective assessment to support diagnostic and treatment decisions. This work is being extended to examine whether these markers capture comorbid features of ADHD and differential response to nonstimulants.