نوروفیزیولوژی نقص توجه/بیش فعالی

Recent reviews of the neurobiology of Attention-Deficit/Hyperactivity Disorder (AD/HD) have concluded that there is no single pathophysiological profile underlying this disorder. Certainly, dysfunctions in the frontal/subcortical pathways that control attention and motor behavior are implicated. However, no diagnostic criteria or behavioral/neuroimaging techniques allow a clear discrimination among subtypes within this disorder, especially when problems with learning are also considered. Two major Quantitative EEG (QEEG) subtypes have been found to characterize AD/HD. Here we review the major findings in the neurophysiology of AD/HD, focusing on QEEG, and briefly present our previous findings using a source localization technique called Variable Resolution Electromagnetic Tomography (VARETA). These two techniques represent a possible objective method to identify specific patterns corresponding to EEG-defined subtypes of AD/HD. We then propose a model representing the distribution of the neural generators in these two major AD/HD subtypes, localized within basal ganglia and right anterior cortical regions, and hippocampal, para-hippocampal and temporal cortical regions, respectively. A comprehensive review of neurochemical, genetic, neuroimaging, pharmacological and neuropsychological evidence in support of this model is then presented. These results indicate the value of the neurophysiological model of AD/HD and support the involvement of different neuroanatomical systems, particularly the dopaminergic pathways.

Attention-Deficit/Hyperactivity Disorder (AD/HD), with or without hyperactivity, still remains one of the most controversial issues in child psychiatry, especially in the endeavor to clarify the relationship between this disorder and Learning Disability (LD). The controversy begins with the operational definition of this pathology and, in general, with the terminology for classification and evaluation of children with behavioral and cognitive problems. Over time, the label for defining children who have in common some degree of inattentiveness, distractibility, impulsivity, hyperactivity, aggressiveness and learning problems has been changed repeatedly until the current definition, which distinguishes those who are predominantly inattentive (AD/HDin), or predominantly hyperactive–impulsive (AD/HDhyp), from a combined type (AD/HDcom), as a part of the same syndrome, but distinct from LD (American Psychiatric Association, 1987 and American Psychiatric Association., 1994). No current diagnostic criteria or technique allows a clear discrimination among and within these two neuropsychiatric entities, and there is considerable comorbidity between these two classes of disorders. Small sample sizes and restricted patient sampling procedures make it difficult to generalize research findings about possible pathophysiological substrates that might serve to define this population of children. Further, both are associated with an increased incidence of other psychiatric problems, such as anxiety, conduct, oppositional defiant, obsessive–compulsive or mood disorders (Biederman et al., 1991, Cantwell and Baker, 1991, Semrud-Clikeman et al., 1992, Bird et al., 1993 and Pliszka, 2000). Finally, the broad nature of interventional strategies required for these disorders suggests that a heterogeneous population of children may be subsumed under the denominations of AD/HDin, AD/HDcom and LD (Semrud-Clikeman et al., 1992, Mann et al., 1992, Barkley, 1997a and Weinberg and Brumback, 1992). Due to the difficulty of classification, epidemiological data are widely different from study to study. The prevalence of AD/HD has been estimated around 5–10% among school-aged children (Rostain, 1991, Schachar, 1991, Taylor et al., 1991, Cantwell, 2004, Scahill and Schwab-Stone, 2000 and Brown et al., 2001) and the prevalence of LD around 5% (Lyon, 1996). A review of epidemiological studies using standardized diagnostic criteria suggests that 3–6% of the school-aged population (elementary through high school) may suffer from AD/HD, although the percentage of US youth being treated for AD/HD is at the lower end of this prevalence range (Goldman et al., 1998). For the above-stated reasons, it would be of great importance to find a biological marker that could help physicians in making a differential diagnosis and selecting a treatment for children with learning and attention problems. A National Institute of Mental Health Committee has identified Quantitative Electroencephalography (QEEG) as a possible objective method to identify functional measures of child and adolescent psychopathology (Jensen et al., 1993). Compared with other methods of functional neuroimaging (PET, SPECT, fMRI), QEEG is easier to perform, less expensive, non-invasive and safer (Kuperman et al., 1990). In addition to QEEG, a new source localization method called Variable Resolution Electromagnetic Tomography (VARETA; Valdes-Sosa et al., 1996 and Bosch-Bayard et al., 2001) provides a virtual MRI representation of the EEG generators within the brain. Such localization might yield further insight into the underlying pathophysiology of AD/HD. In this paper, we summarize the major findings of neurobiological studies on AD/HD, highlighting convergent points of view about pathophysiological substrates. Consistent with these investigations, we describe our results using the VARETA method in an exploratory fashion in the two main EEG-defined subtypes of AD/HD children obtained with a QEEG analysis. We also examine the clinical role of these techniques in the evaluation of AD/HD brain dysfunction. According to our findings, we propose a neurophysiological model for AD/HD that substantially involves the dopaminergic pathways.

The diagnostic category AD/HD, as defined by APA, seems not to fit with the real heterogeneity of the symptoms exhibited in AD/HD and must be explained by multiple specific causes. Even though the intent of DSM-IV is to provide hierarchically organized categories of mental disorders that aid clinicians in differential diagnosis, certain criteria are too restrictive. In regard to AD/HD and LD, these are considered two mutually exclusive and non-overlapping entities. By this definition, a child cannot simultaneously meet criteria for AD/HD and LD. It is clear that AD/HD is a heterogeneous disorder. Therefore, it cannot be conceptualized as only one disease entity with a very narrow phenotype and a distinct etiology. Rather, it is believed to constitute a spectrum of disorders that subsume different subtypes of a larger population of children with attention and learning problems. To date, AD/HD is diagnosed solely on the basis of patterns of observable behavior. It has been difficult to identify specific biochemical or neurophysiological tests that may contribute to more accurate diagnosis. Identifying a biological measure that could aid in this distinction would help to refine diagnostic criteria and may provide more specific diagnostic tests for AD/HD and LD. QEEG may prove to be the most clinically relevant imaging technique for use in children with attention and learning problems. Indeed, it can play an important role in the evaluation and treatment selection of AD/HD. Compared to other methods of functional neuroimaging (SPECT, PET, fMRI), QEEG has the advantage that it is non-invasive, easier to perform and safer, as well as less expensive. The clinical applications of this technique in diagnosing AD/HD may also provide information about the underlying physiological processes. By combining individual abnormal QEEG features together, the neurometric method can create multivariate discriminant functions that have a sensitivity, specificity and accuracy level much higher than univariate features alone. In addition to its diagnostic usefulness, an initial neurometric QEEG screening may aid in treatment selection (Chabot et al., 1999 and Chabot et al., 2001). Finally, the emergence of EEG biofeedback treatment techniques offers a direct application of QEEG for determining QEEG biofeedback treatment parameters and may offer effective treatment that is not medication oriented (Lubar, 1991). The QEEG results can then be confirmed by VARETA analysis of the raw data. Thus, Neurometric QEEG analysis together with the VARETA technique could be useful not only in recognizing the different subtypes and in predicting the treatment response of AD/HD children, but also by helping us to better understand the biological basis of this disorder. Our findings involving the localization of QEEG frequency abnormality mainly to the right frontal/basal ganglia and hippocampal/temporal regions are in agreement with current neuroanatomical theories of attention processes. The different QEEG/VARETA subtypes may reflect parallel distributed neural systems involved in attentional performance. Altogether, we believe that our findings justify not only the clinical utilization of QEEG in the initial screening and treatment evaluation stages of AD/HD and LD children (Prichep and John, 1990, Chabot and Serfontein, 1996, Chabot et al., 1996 and Chabot et al., 1999), but also can aid in the detection of organicity as the cause of brain dysfunction in children presenting with learning and attention problems (Chabot et al., 2001). Finally, QEEG-based models may help explain the pathophysiology of these disorders.