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Duffy, Frank

Background: The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Methods: Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Results: Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Conclusions: Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.

Objective: The effect of NIDCAP (Newborn Individualized Developmental Care and Assessment Program) was examined on the neurobehavioral, electrophysiological and neurostructural development of preterm infants with severe intrauterine growth restriction (IUGR). Study Design: A total of 30 infants, 27–33 weeks gestation, were randomized to control (C; N=17) or NIDCAP/experimental (E; N=13) care. Baseline health and demographics were assessed at intake; electroencephalography (EEG) and magnetic resonance imaging (MRI) at 35 and 42 weeks postmenstrual age; and health, growth and neurobehavior at 42 weeks and 9 months corrected age (9 months). Results: C and E infants were comparable in health and demographics at baseline. At follow-up, E infants were healthier, showed significantly improved brain development and better neurobehavior. Neurobehavior, EEG and MRI discriminated between C and E infants. Neurobehavior at 42 weeks correlated with EEG and MRI at 42 weeks and neurobehavior at 9 months. Conclusion: NIDCAP significantly improved IUGR preterm infants' neurobehavior, electrophysiology and brain structure. Longer-term outcome assessment and larger samples are recommended.

Background: The experience in the newborn intensive care nursery results in premature infants’ neurobehavioral and neurophysiological dysfunction and poorer brain structure. Preterms with severe intrauterine growth restriction are doubly jeopardized given their compromised brains. The Newborn Individualized Developmental Care and Assessment Program improved outcome at early school-age for preterms with appropriate intrauterine growth. It also showed effectiveness to nine months for preterms with intrauterine growth restriction. The current study tested effectiveness into school-age for preterms with intrauterine growth restriction regarding executive function (EF), electrophysiology (EEG) and neurostructure (MRI). Methods: Twenty-three 9-year-old former growth-restricted preterms, randomized at birth to standard care (14 controls) or to the Newborn Individualized Developmental Care and Assessment Program (9 experimentals) were assessed with standardized measures of cognition, achievement, executive function, electroencephalography, and magnetic resonance imaging. The participating children were comparable to those lost to follow-up, and the controls to the experimentals, in terms of newborn background health and demographics. All outcome measures were corrected for mother’s intelligence. Analysis techniques included two-group analysis of variance and stepwise discriminate analysis for the outcome measures, Wilks’ lambda and jackknifed classification to ascertain two-group classification success per and across domains; canonical correlation analysis to explore relationships among neuropsychological, electrophysiological and neurostructural domains at school-age, and from the newborn period to school-age. Results: Controls and experimentals were comparable in age at testing, anthropometric and health parameters, and in cognitive and achievement scores. Experimentals scored better in executive function, spectral coherence, and cerebellar volumes. Furthermore, executive function, spectral coherence and brain structural measures discriminated controls from experimentals. Executive function correlated with coherence and brain structure measures, and with newborn-period neurobehavioral assessment. Conclusion: The intervention in the intensive care nursery improved executive function as well as spectral coherence between occipital and frontal as well as parietal regions. The experimentals’ cerebella were significantly larger than the controls’. These results, while preliminary, point to the possibility of long-term brain improvement even of intrauterine growth compromised preterms if individualized intervention begins with admission to the NICU and extends throughout transition home. Larger sample replications are required in order to confirm these results.

Background: Language comprehension requires decoding of complex, rapidly changing speech streams. Detecting changes of frequency modulation (FM) within speech is hypothesized as essential for accurate phoneme detection, and thus, for spoken word comprehension. Despite past demonstration of FM auditory evoked response (FMAER) utility in language disorder investigations, it is seldom utilized clinically. This report's purpose is to facilitate clinical use by explaining analytic pitfalls, demonstrating sites of cortical origin, and illustrating potential utility. Results: FMAERs collected from children with language disorders, including Developmental Dysphasia, Landau-Kleffner syndrome (LKS), and autism spectrum disorder (ASD) and also normal controls - utilizing multi-channel reference-free recordings assisted by discrete source analysis - provided demonstratrions of cortical origin and examples of clinical utility. Recordings from inpatient epileptics with indwelling cortical electrodes provided direct assessment of FMAER origin. The FMAER is shown to normally arise from bilateral posterior superior temporal gyri and immediate temporal lobe surround. Childhood language disorders associated with prominent receptive deficits demonstrate absent left or bilateral FMAER temporal lobe responses. When receptive language is spared, the FMAER may remain present bilaterally. Analyses based upon mastoid or ear reference electrodes are shown to result in erroneous conclusions. Serial FMAER studies may dynamically track status of underlying language processing in LKS. FMAERs in ASD with language impairment may be normal or abnormal. Cortical FMAERs can locate language cortex when conventional cortical stimulation does not. Conclusion: The FMAER measures the processing by the superior temporal gyri and adjacent cortex of rapid frequency modulation within an auditory stream. Clinical disorders associated with receptive deficits are shown to demonstrate absent left or bilateral responses. Serial FMAERs may be useful for tracking language change in LKS. Cortical FMAERs may augment invasive cortical language testing in epilepsy surgical patients. The FMAER may be normal in ASD and other language disorders when pathology spares the superior temporal gyrus and surround but presumably involves other brain regions. Ear/mastoid reference electrodes should be avoided and multichannel, reference free recordings utilized. Source analysis may assist in better understanding of complex FMAER findings.

Background: It has long been debated whether Asperger’s Syndrome (ASP) should be considered part of the Autism Spectrum Disorders (ASD) or whether it constitutes a unique entity. The Diagnostic and Statistical Manual, fourth edition (DSM-IV) differentiated ASP from high functioning autism. However, the new DSM-5 umbrellas ASP within ASD, thus eliminating the ASP diagnosis. To date, no clear biomarkers have reliably distinguished ASP and ASD populations. This study uses EEG coherence, a measure of brain connectivity, to explore possible neurophysiological differences between ASP and ASD. Methods: Voluminous coherence data derived from all possible electrode pairs and frequencies were previously reduced by principal components analysis (PCA) to produce a smaller number of unbiased, data-driven coherence factors. In a previous study, these factors significantly and reliably differentiated neurotypical controls from ASD subjects by discriminant function analysis (DFA). These previous DFA rules are now applied to an ASP population to determine if ASP subjects classify as control or ASD subjects. Additionally, a new set of coherence based DFA rules are used to determine whether ASP and ASD subjects can be differentiated from each other. Results: Using prior EEG coherence based DFA rules that successfully classified subjects as either controls or ASD, 96.2% of ASP subjects are classified as ASD. However, when ASP subjects are directly compared to ASD subjects using new DFA rules, 92.3% ASP subjects are identified as separate from the ASD population. By contrast, five randomly selected subsamples of ASD subjects fail to reach significance when compared to the remaining ASD populations. When represented by the discriminant variable, both the ASD and ASD populations are normally distributed. Conclusions: Within a control-ASD dichotomy, an ASP population falls closer to ASD than controls. However, when compared directly with ASD, an ASP population is distinctly separate. The ASP population appears to constitute a neurophysiologically identifiable, normally distributed entity within the higher functioning tail of the ASD population distribution. These results must be replicated with a larger sample given their potentially immense clinical, emotional and financial implications for affected individuals, their families and their caregivers.

Background: Up to a third of children with Autism Spectrum Disorder (ASD) manifest regressive autism (R-ASD).They show normal early development followed by loss of language and social skills. Absent evidence-based therapies, anecdotal evidence suggests improvement following use of corticosteroids. This study examined the effects of corticosteroids for R-ASD children upon the 4 Hz frequency modulated evoked response (FMAER) arising from language cortex of the superior temporal gyrus (STG) and upon EEG background activity, language, and behavior. An untreated clinical convenience sample of ASD children served as control sample. Methods: Twenty steroid-treated R-ASD (STAR) and 24 not-treated ASD patients (NSA), aged 3 - 5 years, were retrospectively identified from a large database. All study participants had two sequential FMAER and EEG studies;Landau-Kleffner syndrome diagnosis was excluded. All subjects’ records contained clinical receptive and expressive language ratings based upon a priori developed metrics. The STAR group additionally was scored behaviorally regarding symptom severity as based on the Diagnostic and Statistical Manual IV (DSM-IV) ASD criteria list. EEGs were visually scored for abnormalities. FMAER responses were assessed quantitatively by spectral analysis. Treated and untreated group means and standard deviations for the FMAER, EEG, language, and behavior, were compared by paired t-test and Fisher’s exact tests. Results: The STAR group showed a significant increase in the 4 Hz FMAER spectral response and a significant reduction in response distortion compared to the NSA group. Star group subjects’ language ratings were significantly improved and more STAR than NSA group subjects showed significant language improvement. Most STAR group children showed significant behavioral improvement after treatment. STAR group language and behavior improvement was retained one year after treatment. Groups did not differ in terms of minor EEG abnormalities. Steroid treatment produced no lasting morbidity. Conclusions: Steroid treatment was associated with a significantly increased FMAER response magnitude, reduction of FMAER response distortion, and improvement in language and behavior scores. This was not observed in the non-treated group. These pilot findings warrant a prospective randomized validation trial of steroid treatment for R-ASD utilizing FMAER, EEG, and standardized ASD, language and behavior measures, and a longer follow-up period. Please see related article http://www.biomedcentral.com/1741-7015/12/79

Background: Attentional disorders (ADD) feature decreased attention span, impulsivity, and over-activity interfering with successful lives. Childhood onset ADD frequently persists to adulthood. Etiology may be hereditary or disease associated. Prevalence is 5% but recognition may be ‘overshadowed’ by comorbidities (brain injury, mood disorder) thereby escaping formal recognition. Blinded diagnosis by MRI has failed. ADD may not itself manifest a single anatomical pattern of brain abnormality but may reflect multiple, unique responses to numerous and diverse etiologies. Alternatively, a stable ADD-specific brain pattern may be better detected by brain physiology. EEG coherence, measuring cortical connectivity, is used to explore this possibility. Methods: Participants: Ages 2 to 22 years; 347 ADD and 619 neurotypical controls (CON). Following artifact reduction, principal components analysis (PCA) identifies coherence factors with unique loading patterns. Discriminant function analysis (DFA) determines discrimination success differentiating ADD from CON. Split-half and jackknife analyses estimate prospective diagnostic success. Coherence factor loading constitutes an ADD-specific pattern or ‘connectome’. Results: PCA identified 40 factors explaining 50% of total variance. DFA on CON versus ADD groups utilizing all factors was highly significant (p≤0.0001). ADD subjects were separated into medication and comorbidity subgroups. DFA (stepping allowed) based on CON versus ADD without comorbidities or medication treatment successfully classified the correspondingly held out ADD subjects in every instance. Ten randomly generated split-half replications of the entire population demonstrated high-average classification success for each of the left out test-sets (overall: CON, 83.65%; ADD, 90.07%). Higher success was obtained with more restricted age sub-samples using jackknifing: 2-8 year olds (CON, 90.0%; ADD, 90.6%); 8-14 year olds (CON, 96.8%; ADD 95.9%); and 14-20 year-olds (CON, 100.0%; ADD, 97.1%). The connectome manifested decreased and increased coherence. Patterns were complex and bi-hemispheric; typically reported front-back and left-right loading patterns were not observed. Subtemporal electrodes (seldom utilized) were prominently involved. Conclusions: Results demonstrate a stable coherence connectome differentiating ADD from CON subjects including subgroups with and without comorbidities and/or medications. This functional ‘connectome’, constitutes a diagnostic ADD phenotype. Split-half replications support potential for EEG-based ADD diagnosis, with increased accuracy using limited age ranges. Repeated studies could assist recognition of physiological change from interventions (pharmacological, behavioral).

Background: Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing. Methods: This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors’ discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON–CHR differences within the superior temporal gyri. Results: Variable reduction by PCA identified 40 coherence-based factors explaining 77.8 % of the total variance and 40 spectral factors explaining 95.9 % of the variance. DFA demonstrated significant CON–CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7 %; CHR, 86.4 % correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON–CHR group differences. Conclusions: CHR subjects form a cohesive group, significantly separable from CON subjects by EEG-derived indices. Symptoms of CHR may relate to altered connectivity with the posterior temporal regions but not to primary auditory processing abnormalities within these regions.

Highly penetrant mutations leading to schizophrenia are enriched for genes coding for N-methyl-D-aspartate receptor signaling complex (NMDAR-SC), implicating plasticity defects in the disease's pathogenesis. The importance of plasticity in neurodevelopment implies a role for therapies that target these mechanisms in early life to prevent schizophrenia. Testing such therapies requires noninvasive methods that can assess engagement of target mechanisms. The auditory N100 is an obligatory cortical response whose amplitude decreases with tone repetition. This adaptation may index the health of plasticity mechanisms required for normal development. We exposed participants aged 5 to 17 years with psychosis (n = 22), at clinical high risk (CHR) for psychosis (n = 29), and healthy controls (n = 17) to an auditory tone repeated 450 times and measured N100 adaptation (mean amplitude during first 150 tones − mean amplitude during last 150 tones). N100 adaptation was reduced in CHR and psychosis, particularly among participants <13 years old. Initial N100 blunting partially accounted for differences. Decreased change in the N100 amplitude with tone repetition may be a useful marker of defects in neuroplastic mechanisms measurable early in life.

Background: Previous studies suggest central nervous system involvement in chronic fatigue syndrome (CFS), yet there are no established diagnostic criteria. CFS may be difficult to differentiate from clinical depression. The study’s objective was to determine if spectral coherence, a computational derivative of spectral analysis of the electroencephalogram (EEG), could distinguish patients with CFS from healthy control subjects and not erroneously classify depressed patients as having CFS. Methods: This is a study, conducted in an academic medical center electroencephalography laboratory, of 632 subjects: 390 healthy normal controls, 70 patients with carefully defined CFS, 24 with major depression, and 148 with general fatigue. Aside from fatigue, all patients were medically healthy by history and examination. EEGs were obtained and spectral coherences calculated after extensive artifact removal. Principal Components Analysis identified coherence factors and corresponding factor loading patterns. Discriminant analysis determined whether spectral coherence factors could reliably discriminate CFS patients from healthy control subjects without misclassifying depression as CFS. Results: Analysis of EEG coherence data from a large sample (n = 632) of patients and healthy controls identified 40 factors explaining 55.6% total variance. Factors showed highly significant group differentiation (p < .0004) identifying 89.5% of unmedicated female CFS patients and 92.4% of healthy female controls. Recursive jackknifing showed predictions were stable. A conservative 10-factor discriminant function model was subsequently applied, and also showed highly significant group discrimination (p < .001), accurately classifying 88.9% unmedicated males with CFS, and 82.4% unmedicated male healthy controls. No patient with depression was classified as having CFS. The model was less accurate (73.9%) in identifying CFS patients taking psychoactive medications. Factors involving the temporal lobes were of primary importance. Conclusions: EEG spectral coherence analysis identified unmedicated patients with CFS and healthy control subjects without misclassifying depressed patients as CFS, providing evidence that CFS patients demonstrate brain physiology that is not observed in healthy normals or patients with major depression. Studies of new CFS patients and comparison groups are required to determine the possible clinical utility of this test. The results concur with other studies finding neurological abnormalities in CFS, and implicate temporal lobe involvement in CFS pathophysiology.