Reviewing the Event Related
Electrophysiology of AD/HD.
Vicente Soto de Amesti
Student # 10391290
Brain and Cognitive Science Research Master
Cognitive Neuroscience Track
Supervisor: Ali Mazaheri
Co-Supervisor: Heleen Slagter
University of Amsterdam
Abstract
Event-related potentials (ERP) have long been used to examine characteristic brain activity associated to attention deficit/hyperactivity disorder (AD/HD). This article endeavours to review and discuss ERP investigations studying multiple aspects AD/HD information processing. The aim here is to generate a comprehensive overview of the ERP components found to be distinguishing the ADHD patients from the typical population from characteristic to AD/HD and render a clear view of the current state of the existing research. Using online search engines, multiple studies focusing on various aspects of cognitive functioning were reviewed. The most consistent finding among these studies reported was mainly, a reduced P300 component with a later latency as well as a reduced amplitude in the N200 component. We propose that future direction of research in the field of AD/HD ERPs should focus on precise clinical subtype classification and emphasize the need for standardized experimental paradigms to allow meta-analytic research.
1. Introduction:
Attention deficit/hyperactivity disorder (AD/HD) is one of the most common developmental disorders in childhood. This condition has been researched for over a century (Crichton, 1798; Still, 1902) and believed by some to be the most studied condition in children (Faraone & Biederman, 2005). As such substantial attention from the scientific community has been directed towards the clinical characterization of AD/HD leading to hundreds of experiments and publications (Barry, Johnstone, & Clarke, 2003). Scientific descriptions accompanied by a deeper understanding of this condition have refined the clinical characterisation of the disorder and, as such a large amount of research is invested in describing the underlying neural activity associated with this condition. AD/HD is a multifaceted and widespread condition characterized as a cluster of symptoms that relate to inattentive, hyperactive and impulsive behaviour. Given its prevalence in children while a lesser extent in adults AD/HD is believed by some to be a cognitive developmental problem (Bell, 2011; Kessler et al., 2006; Rostain & Ramsay, 2006).
The main objective of this review is to provide an overview of studies using Event Related Potentials (ERP) under diverse experimental paradigms to test the cognitive abilities and neural processing in AD/HD patients. We do this with the intention of generating a conceptually manageable framework regarding the underlying cognitive processes aberrant in AD/HD. To do so, we first begin by describing the diagnostic criteria used to identify and evaluate AD/HD. We review changes in the diagnostic manual throughout recent years as well discuss how inclusion criteria’s have been transformed and why. We then expose most of the relevant papers in the past 10 years
or so regarding AD/HD electrophysiology. We proceed to discuss major findings present in literature examining ERP component anomalies in AD/HD patients. We expose both auditory and visual evoked potentials as well as combine modality ERPs. We conclude by establishing most reliable differences in AD/HD ERP components as well as identifying a possible neural marker for AD/HD subtype classification. Finally areas of consistent findings are reported and future benchmarks and obstacles in AD/HD research.
The first modern description of what is currently known as AD/HD were made by Kramer, Pollnow, et al. (1932), but it was first introduced into the second edition of the Diagnostic and Statistical Manual of Mental Disorders nearly 40 years later (DSM II, 1968) under the denomination ”Hyperkinetic Reaction of Childhood”. In the past half century of research based evidence some changes in the clinical understanding of AD/HD have been made. In the current edition of the manual, AD/HD patients still are described as showing a persistent pattern of inattention and/or hyperactivity that impedes their normal functioning or development. The DSM-V, unlike some previous editions, has made alterations acknowledging that this is not a condition limited to childhood. Diagnostically, the new edition of the Diagnostics and Statistical Manual V edition (DSM-V, 2013) maintains the18 symptoms and subtypification used its previous version (DSM-IVtr) (broadly described in items 1, 2 and 3 from the American Psychiatric Association, 2013). The diagnostic criterion for AD/HD has not changed considerably in the past two decades (Johnstone, Barry, & Clarke, 2013). We interpret this fact as showing consistency in the clinical description of the condition, ultimately allowing longitudinal evaluations of the diagnosis criteria. (See annex for full DSM-V criteria)
1) Inattention: Six or more symptoms of inattention for children up to age 16, or five or more for adolescents up to 17 years and older as well as adults; symptoms of inattention have been present for at least 6 months, and they are inappropriate for developmental level
2) Hyperactivity and Impulsivity: Six or more symptoms of hyperactivity-impulsivity for children up to age 16, or five or more for adolescents 17 and older and adults; symptoms of hyperactivity-impulsivity have been present for at least 6 months to an extent that is disruptive and inappropriate for the person’s developmental level
3) In addition, the following conditions must be met:
Several inattentive or hyperactive-impulsive symptoms were present before age 12 years. Several symptoms are present in two or more setting, (e.g., at home, school or work; with friends or relatives; in other activities). There is clear evidence that the symptoms interfere with, or reduce the quality of, social,
school, or work functioning.
The symptoms do not happen only during the course of schizophrenia or another psychotic disorder. The symptoms are not better explained by another mental disorder (e.g. Mood Disorder, Anxiety Disorder, Dissociative Disorder, or a Personality Disorder).
Though relatively similar to the DSM-IV, the DSM-V diagnostic characterization of AD/HD has included some changes from its preceding edition. As in its previous edition, three main subtypes of AD/HD have been described; combined presentation (AD/HDcom), predominantly hyperactive-impulsive (AD/HDhyp) and predominantly inattentive presentation (AD/HDina). Differing to its previous edition, several modifications have been introduced. In first place, checklist items have been exemplified to facilitate lifespan applications of each criterion. Secondly, the cross-situational requirements are strengthened, demanding “several” symptoms for every setting. Thirdly, the onset age of symptom development has been extended “...inattentive or hyperactive-impulsive symptoms were present prior to the age of 12”. Fourth, subtypes are replaced with presentation specifications that map directly to the subtypes of ADHD, maintaining the AD/HD mainly hyperactive and AD/HD mainly inattentive denomination. The DSM-V allows for comorbidity in diagnosis with autism spectrum disorders like Aspergers Disease or Rett Syndrome and finally, the symptom threshold has been lowered by one symptom making the diagnostic cut-off five symptoms instead of six (DSM-V, 2013). The intent of these changes seems to reflect an effort towards better characterizing AD/HD in adult patients and accurately depicting AD/HD as a delimited clinical condition. This should help better treatment options and support patient care continuum as well as aiding in the effort to narrow an estimate of the amount of patients affected worldwide. Though AD/HD has long been considered a very common developmental disorder in children, there is significantly less agreement regarding the exact prevalence of the condition. The DSM-V recently estimated that AD/HD could affect roughly 1 out of every 20 children in the USA. On a worldwide scale, it has been suggested that non-USA children are, at least, as likely to present AD/HD symptoms as children raised in the United States (Faraone, Sergeant, Gillberg, & Biederman, 2003). If this estimation is accurate then roughly a quarter billion people worldwide are affected (250 million - 350 million). Yet figures regarding prevalence of the condition are wildly variable ranging from 2.2% to 17.8% (Skounti, Philalithis, & Galanakis, 2007), 3% to 7% of school age children (Cormier, 2008) and 2.9% for narrow AD/HD and 16.4% for broad AD/HD (Faraone & Biederman, 2005) in adults. (For a complete overview of prevalence rate studies see the Centre for Disease Control and Prevention (CDC) website. Figure 1 depicts differences in estimated prevalence rates of AD/HD by survey for the last 40 years (USA, Centre for Disease Control,
Figure 1: Timeline of AD/HD (ADD) prevalence history taken from the Centre for Disease Control and Prevention website (http://www.cdc.gov/ncbddd/ adhd/timeline.html). The figure is based on multiple studies regarding AD/HD prevalence as well as three main surveys; the United States of America National Survey of children’s Health (NSCH), the National Health Interview Survey (HNIS) and a pooling of ”other surveys”. The secondary timelines illustrate both, the diagnostic manuals used as well as the main drug course used to treat the condition at this time.
www.cdc.gov/ncbddd/adhd/data.html1).
This variability in prevalence estimates, depicted in Figure 1, could be due to different reasons. At first glance, it would seem that changes in diagnostic manuals over time, and the fact that characterisation of this condition relies primarily on behavioural descriptions and on personal assessment could explain the variability in the estimated
prevalence rates. Though these subjective behavioural based assessments could explain some of the variability in prevalence statistics across different studies and populations, it seems more relevant to look at the methodological characteristics of the studies as these factors play a far more relevant role in explaining this statistical variability. For a full review see Polanczyk, de Lima, Horta, Biederman, and Rohde (2007).
In the next section we will assess the validity of ERPs for diagnosing and establishing neural markers for AD/HD. This could ultimately help to establish better global estimates of prevalence across studies. With research methodology into human electrophysiology quickly developing, continuous improvements are being made to hardware, experimental methods and data analysis techniques, ultimately, providing better resolution and accuracy to results. As such many contradictory findings are published and replication studies are needed to gain consistency in findings. We aim to review the relevant findings in ERP research relating to AD/HD and expose areas where further investigation is needed as well as promote a comprehensive understanding of the distinct electrophysiology in ADHD.
2. Methodology
ERP studies investigating multiple aspects of AD/HD were subjected to review. Focus was set on finding, but not limited, ERP investigations published in the last decade in the general field of AD/HD electrophysiology. Studies focusing on various aspects of cognitive functioning are examined and experimental tasks including visual, auditory and combined visual/auditory elicited ERP’s are taken into account. Relevant papers were selected from online searches using Google Scholar (www.google.scholar.com) search engine and BaseSearch (www.base-search.net). Multiple search terms where used to siphon the search results; “attention deficit/hyperactivity disorder”, “ADHD”, “AD/HD”, “ERP” and “event related potential”, were among the most common. Also specific combinations of these search terms were used and more specific search terms like CNV, N100, N200, MMN, P100, etc. were also used to narrow the search results.
Recent results obtained from the online search regarded, primarily, the use of medication in ADHD and the resulting effects on patient ERPs compared to controls. These studies where not taken into account, neither where studies using fMRI or PET methodologies, nor studies applying time-frequency analysis to investigate oscillation correlation in AD/HD. Main results are presented temporally by ERP component and future research directions are discussed.
3. Event Related Potential (ERP) anomalies in AD/HD
Information processing occurs in the brain by the passage of electric currents through the dendrites and axons of local fields of neurons. The summation of this current flow across many neurons results in the formation of electric potentials and the induction of magnetic fields that can be non-invasively measured at the scalp. Electroencephalography (EEG) is the measurement of these electric potentials. When time-locked to a specific time marker or stimulus, ERPs can be calculated by computing the averaged electrical activity in specific regions of the brain subsequent to the onset of an event. Comparisons can be then made by analysing the average electrocortical response to different conditions or between patients and controls. The resulting activity reflects the brain’s transient time-locked response to a stimulus/event. As such, researchers have been able to examine the underlying cognitive and sensory mechanisms present in AD/HD. Event related potentials (ERPs) have been critical in establishing and discriminating typical from atypical cortical responses. Responses to specific stimuli or changes in the environment allow a temporally precise, fine-grained representation of cognitive processes time-locked to a specific event. Additionally, ERP waveforms contain characteristic amplitudes, latencies and maximum peaks that can be temporally related to the cognitive processes responding to task demands. The amplitude (uV) is normally defined as a voltage difference between the baseline preceding the stimulus and the largest positive-going peak of the ERP waveform within a latency. The latency (ms), in turn, is defined as the time from stimulus onset to the point of maximum positive amplitude within the latency window (Polich & Kok, 1995) .The functional significance and interpretation of ERP characteristics are always a relatively debated subject due to the large amount of induced variability that can exist (Olofsson, Nordin, Sequeira, & Polich, 2008). To correctly interpret ERP responses many factors must be taken into account, crucial elements to be considered are the experimental conditions of the eliciting stimulus, polarity of the waveform and the latency (Barry et al., 2003).
In AD/HD research, ERP’s have allowed researchers to establish group differences (between patients and controls) in multiple cognitive areas spanning from preparatory states to later attention driven mechanisms. Using auditory, visual and combine modalities of stimuli presentation, three main areas of ERP research related to AD/HD stand out, namely, attention, performance monitoring and inhibitory control (Johnstone et al., 2013). Specific tasks are used to research each of these processes, typical tasks include selective attention tasks (SAT), continuous performance tasks (CPT), oddball tasks (OBT), Go/Nogo tasks (G/NgT), stop signal tasks (SST), flanker
tasks, probabilistic learning tasks and even guessing tasks have been used in AD/HD research. An overview of the main areas of research is detailed in Table 1.
Table 1: Shows the main areas of EEG research investigating AD/HD as well as the modality and main tasks used in each study.
The following sections review major findings by ERP component with a special focus set on visual and auditory evoked responses. We review slow wave components like Contingent Negative Variation, as well as early ERP’s like the N100 and the P100 potential. In doing so we hope to evidence established findings at every stage of neurocognitive processing and point out major differences between AD/HD patients and normal subjects.
3.1 Contingent Negative Variation (CNV)
The contingent negative variation is a slow sustained biphasic ERP waveform. It is generated over the initial seconds in a forewarned reaction time task and responds to a
sequence of click/flash stimuli, in which the repetitive flashes are terminated by a button press. CNV in AD/HD research have been studied in order to examine preparatory processes and cortical activation in patients and normal test subjects. Active stimulus expectation is expressed by this waveform in tasks including a preparatory stimulus (S1), followed by an imperative stimulus (S2) of any modality (Leuthold, Sommer, & Ulrich, 2004). CNV develops in the anticipatory interval (between S1 and S2) after roughly about 30 paired stimuli are presented. Following this, a large negative peak is formed during stimulation that abruptly ends with the button press response (Walter, Cooper, Aldridge, McCallum, & Winter, 1964). A general model of the CNV summarises the concept to cortical arousal related to anticipatory attention, preparation, motivation, and information processing (Tecce, 1972).
The conditions of stimulation also produce CNV changes to multiple variables like stimulus withdrawal, intensity effects, stimulus content, task difficulty, the intervals between stimuli (Tecce, 1972). CNV waveforms have been established as a response to various visual and auditory selective attention tasks. The CNV is a biphasic component reaching its maximum peaks at 250ms and 500ms after a S1(warning) stimuli. Both phases, typically denominated as early CNV (CNV-e), representing expectancy and late CNV(CNV-l), indexing preparation processes can be related to distinct mechanisms (Leuthold et al., 2004; Verleger, Wauschkuhn, van der Lubbe, Jáskowski, & Trillenberg, 2000; Walter et al., 1964). The CNV can be calculated on visual and auditory tasks alike and, as such, is one of the most intensely investigated ERP’s in history.
Within AD/HD research CNV studies allow researchers to evaluate preparatory processes by examining arousal as indexed by task dependant CNV waveforms (Doehnert, Brandeis, Schneider, Drechsler, & Steinhausen, 2013). Early research results have been contradictory. A reduced CNV amplitude in AD/HD patients was not found consistently across studies. Yordanova, Dumais-Huber, and Rothenberger (1996) found no important difference in slow negative potentials between AD/HD children and controls. Henninghausen, Schulte-Korne, Warnke, and Remschmidt (2000) found that ADD children showed an attenuated frontal CNV-l amplitude support abnormal inhibitory processing in AD/HD).
Newer studies, however, have found more consistency in results, typically reporting reduced amplitudes in early CNV. Perchet, Revol, Fourneret, Mauguiére, and Garcia-Larrea (2001) measured the slow negative waveform (typically attributed to CNV) that precedes presentation of a target stimuli in their “no-cue” condition. They found a significantly reduced, “virtually absent”, CNV waveforms in their AD/HD group. In the same line of investigation, Valko et al. (2009) found weaker CNV in AD/HD
patients compared to their matched controls (both adults and children) they proposed as well that the AD/HD related ERP’s showed more prominent activations at posterior scalp sites in children, while in adults, a more pronounced anterior scalp activation was found. They further the discussion and make a parallel between prominent topographic changes of both ERP markers with development. In this same line, although Benikos and Johnstone (2009) also found evidence of atypical orienting/preparing processes indexed by reduced CNV-e and CNV-l amplitudes, they propose that energetic factors (arousal, effort and activation) might play grater roles in generating these differential results between patients and controls. Given these propositions, the authors entice future research to consider these additional factors into explicative models of AD/HD.
Pre-emptive motor and responses have also been examined in children with AD/HD by examining the CNV. McLoughlin et al. (2010) also found a reduced CNV amplitude in ADHD patients. The proposed interpretation of this result was to understand the reduction as a reflection of abnormal preparatory processing expressed by a differential anticipation and preparation process to the upcoming stimulus. In line with these results, a longitudinal study showed the CNV to be significantly smaller in adults that had been previously diagnosed with ADHD, while other ERP components showed a normalisation accompanying development from childhood to adulthood (Doehnert et al., 2013).
Though earlier studies found some opposing results in regards to the CNV evidenced in AD/HD, later studies examining preparatory processes in AD/HD have consistently found a reduction in this component for AD/HD subjects.
3.2 Brain Stem Auditory Evoked Potentials
The BAEP (Brainstem Auditory Evoked Potential) has typically been used to examine the integrity of auditory pathways in sound processing. As such it serves as a tool for characterizing the electrophysiological phenomenon of neural excitation, transmission across the auditory pathway in the brainstem (Vaney, Anjana, & Khaliq, 2011). The BAEP or auditory brainstem response (ABR) waveforms are enumerated from I to V, where wave I is believed to represent activity in the auditory nerve; waves II and III are typically associated with activity in the cochlea and superior olivary nuclei and finally waves IV and V are related with activity in the lateral leminiscus and inferior colliculus (Stockard, Stockard, & Sharbrough, 1980).
Although research has revealed much about BAEP’s in general, very few studies have examined auditory integrity via the BAEP’s in AD/HD. Lahat et al. (1995) provide one of the only comprehensive BAEP studies regarding AD/HD. They provide evidence of bigger latencies in waveforms III and IV in ADD patients. They find I-III
wave and I-V wave transitions times were slower in ADD as well. Puente, Ysunza, Pamplona, Silva-Rojas, and Lara (2002) found that the brainstem transmission was significantly longer in children with ADHD and the latency of the posterior P300 components was also significantly longer in children with ADHD. They present data to support the idea that ADHD patients present abnormal brainstem transmission. The found that mean conduction times (between I-III and I-V) where significantly longer in ADHD patients compared to controls.
In later investigations opposing evidence was presented. In a double blind study, Schochat, Scheuer, and Andrade (2002) found no significant difference in the BAEP of AD/HD children compared to controls. They did, however observe the absence of a P300 in about half their subjects as well as an effect of methylphenidate (Ritalin) on the P300 amplitude. A newer study (Vaney et al., 2011) tests the auditory brain response (ABR) in AD/HD children. Their results oppose those of Lahat et al. (1995) as well. Vaney et al. (2011) found no difference in BAEP/ABR between AD/HD and control groups supporting the notion that the auditory integrity is not compromised in AD/HD.
Considering the methodological refinements and hallmarks of EEG in the past 25 years (like the discovery of the average event related potentials, the broad frequency band quantitative integration of EEG oscillations, or the computerized functional brain mapping) presented by Lazarev, (2006) it seems wise to consider the possibility of disregarding earlier evidence of differences in BAEP and establish that the auditory processing is not a pivotal factor causing AD/HD. Given the nature of the results presented so far, clearly more research is needed in this area.
3.3 The N100 and N200
The N1 negative deflection occurring at around 100ms after the apparition of an unpredictable auditory stimulus (Näätänen & Picton, 1987). This component has been associated with early attention mechanisms (Näätänen & Winkler, 1999; Rinne, Sarkka, Degerman, Schroger, & Alho, 2006) it is thought to represent the detection of changes in sensory input (Horvath, Winkler, & Bendixen, 2008) and early extraction of initial sensory information from the auditory stimulus (Näätänen & Winkler, 1999). Commonly assessed under a single stimulus passive listening task or within an odd-ball paradigm, the N1 is normally distributed frontally through the midline of the scalp with its generators typically associated to neural populations within the motor and frontal areas in the brain cortex (Näätänen & Picton, 1987). While the amplitude of the negative deflection of this component can be influenced by multiple factors, the unpredictability of the stimuli and abruptness of auditory changes are known to
significantly increase N1 amplitudes (Butler, 1968). Also task irrelevant factors like the age of the participant (Shibasaki & Miyazaki, 1992) have an effect on the max peak in this component. Due to this, the age of participant in studies should be controlled for within clinical studies. Within AD/HD research this is not always the case, and as such conflicting results have been provided as to the N1 component in ADHD patients.
Satterfield, Schell, and Nicholas (1994) reported that the N1 components in their mid-aged AD/HD group (children from 7 to 9 years old) showed a reduced amplitude. This reduction was not seen, however, at any other age group in their study. Sable et al. (2013) present results aligning with these early findings. They report a reduced N1 component in college students with ADHD. Using streams of tone with different inter train interval (ITI) they determined that unlike older ADHD patients who display a typical N1 amplitude followed by a reduced attenuation of the N1 component (Fabiani, Low, Wee, Sable, & Gratton, 2006), young adults seem to maintain the same level of N1 amplitude throughout stimulation. These results suggest a heightened level of excitability in patients compared to controls. The N1 amplitude reduction, in the framework of an auditory NoGo tasks is typically related to abnormal early processing of sensorial input, representing a distinctive initial extraction of perceptual/sensory information (Casale et al., 2008). This finding can be viewed as a reduction in the mechanisms scaling the level of “amplification” of incoming information in tough ADHD adults.
Contrary results have been provided reporting increases in the N1 amplitudes (Johnstone, Barry, Markovska, Dimoska, & Clarke, 2009; Prox, Dietrich, Zhang, Emrich, & Ohlmeier, 2007). Prox et al. (2007) show significantly increased N1/N2 amplitudes for AD/HD patients in a Go/Nogo auditory task. These results support the theory that AD/HD patients must inhibit their reactions more strongly than healthy controls leading to greater N1 components. In the same line, Johnstone et al. (2009) found increases in the N1 and N2 component using a combined auditory/visual oddball tasks, they relate their results to an overly effortful processing mechanism that is required to overcome sensory processing deficits in AD/HD patients.
The suggested inability to correctly scale the level of incoming stimulation seems to be in line with the idea of additional resources required to compensate processing deficits. A misguided scaling of auditory input levels, as measured in a listening task, could lead to more effortful processing of relevant auditory stimuli, as in the framework of a Go/Nogo task.
Within an oddball task undergoing active attending conditions the N2 component is thought to represent a specific mismatch detection process relevant for accurate
sensory discrimination. This negative going deflection reaches its maximum peak between 200ms and 350ms following the onset of a stimulus that deviates in form or context of prevailing stimuli (Hoffman, 1990; Patel & Azzam, 2005).
Within Go/nogo tasks the N200 has been an important tool in investigating executive control (Kopp et al. 1996), specifically, inhibitory executive functions (Heil et al. 2000).
Several different studies have presented evidence of abnormal sensory/cognitive processing in patients with AD/HD. Initial results showed an enhanced N250 component in hyperkinetic children. The N2 component was normalised by methylphenidate, but not by a placebo in hyperkinetic patients. (Prichep et al. 1976). Newer results contradict earlier ones in regards to the N2 component. Johnstone and Barry (1996) found a smaller N2 component for non-targets in ADHD children compared to matched healthy controls. They interpreted this as reflecting attentional compensation mechanisms.
In newer studies, Pliszka et al. (2000) used a Stop-Signal task experimental setup to find a manifestly reduced N2 waveform over the right inferior frontal scalp for the AD/HD children. They attributed the reduction to abnormalities in inhibitory control processes. Lazzaro et al. (2001) found a similar N2 amplitude reduction over the midline of the scalp in their AD/HD group. They interpret these deficits in response selection and initiation of motor responses as an abnormality in the dopaminergic activity of pre-frontal cortical activity in ADHD children. Dimoska et al. (2003) also found a diminished N2 in AD/HD children compared to controls. They interpret their finding as disturbed inhibition when reacting to auditory stop signals.
3.4 P200
The P2 component, classically utilised in a visual search task, has indeed an auditory elicitation as well. It has been defined as a positive deflection presenting itself roughly 200ms after stimulus presentation. It has a peak latency between 130 and 210 ms and its distribution is localised mainly over parietal and central areas of the cortex (Kropotov et al. 2005). Subsequent to the N1 component, the P2 amplitude is independent from changes in the N1 amplitude suggesting a degree of independence between both components (Ross and Tremblay 2009). Besides polarity and timing, the main difference between the N1 and P2 is referred to as the vertex amplitude which is found to be significantly larger for target than non-target stimuli and for rapid attention switching task (Furutsuka, T., 1989). This independence implies separate processes governing the elicitation of the P2 and N1 component. The P2 is typically thought to represent inhibition of sensory input from further processing demands
(Hegerl and Juckel 1993) or the inhibition specific incoming information contending for attention and further processing (Oades 1998). Initially Oades et al. (1996) found very large P2 components, with an anterior shifted maximum, in ADHD patients as well as in people suffering from Tourette syndrome. In a follow up study study (Oades et al. 1996) implemented a three tone oddball task to an AD/HD patient and control group. Their results evidenced significantly larger P2 amplitudes in AD/HD patients to both standard and deviant stimuli. Regarding the latency of this component, the AD/HD group P2 latency was found to be shorter for both standard and deviant stimuli and stronger across the right hemisphere of the brain.
Johnstone et al., 2001 report similar results when testing the effects of age on the topographical distribution of ERPs elicited from a two-tone oddball task. They found a large P2 amplitude to target stimuli in AD/HD inattentive subjects compared to their normal control group. This effect however was only found in 8-16 year old patients and not in any older groups. Latencies for their AD/HD combined group (8 - 18 years old) proved longer than controls and showed important topographic differences across all age groups compared to controls. These results were not found in and other group. Authors interpret this as representing a qualitatively unique brain pattern across their age groups.
As for the P2 as a differentiating charactereristics between AD/HD subtypes, results have been conflicting. Initial results (Statterfield et al., 1984) were unable to distinguish hyperactive from control groups. Johnstone et al., (2001) were also unable to find any differences in P2 latency between the AD/HD inattentive group and controls. Oades et al. 1996 did report differences in the latency of this component between groups but due to the DSM diagnostic understanding of the time in which this study was performed, no subtype differentiation was made.
3.5 MMN
Mismatch negativity (MMN) is a change specific ERP component that allows the evaluation of a pre-attentive auditory sensory processing. This component is an electrophysiological response to changes in any constant stream of auditory perception. Auditory MMN usually peaks at 150-200 ms from the onset for a deviating sound with an amplitude of approximately −3μ V (Licht and Horsley, 1998) and is elicited even in the absence of attention (Näätänen, Gaillard, & Mantysalo, 1978). Responding as a mismatch detection mechanism this particular component can arise from omitting and expected auditory stimulus as well as by the presentation of a deviant tone within a stream of standard tones (for a full review see Näätänen et al. (2005)). Leun, Ritterc, and Achimd (2000) provide a detailed review and characterise MMN as likely to represent an automatic change-detection process. Due to this it has
been thought to represent an integrated representation of auditory events (Näätänen & Winkler, 1999).
Though some discussion has arisen from the relative similarity to the N100 component, it has been distinguished from the N100 due evidence showing that different generators elicit a mismatch response (Alho 1995), that temporally it appears later than the N100 (Alho and Näätänen 1995) and the fact that the MMN can be elicited by stimulus omissions (Yabe et al. 1998) suggest that the MMN and the N100 represent distinct processes. Perhaps due to the controversies surrounding the MMN, literature evaluating MMN in AD/HD patients is relatively scarce. Kremner et al. (1996) reported a smaller MMN response in ADHD children using speech stimuli compared to controls, but the difference only approached significance corresponding to a trend in ADHD patients’ ERPs (p < .08). Winsberg et al. (1993) used small sample sizes (6 AD/HD and 5 controls) and also reported smaller MMN in a ADHD group of children.
In one newer study, Rothenberger (2000) found attenuated MMN waves, but only in ADHD patients with comorbid conduct disorders. Upon further analysis a significant overall effect of smaller amplitude of the MMN waveforms was observed in the ADHD groups (including groups with comorbid conditions) compared to normal controls, but no further distinctions were made.
In other studies evaluating differences between reading disabled, AD/HD and normal control children, Huttunen et al (2007) reported only a significant difference in the lateralization of the MMNs between the reading disabled and control group. The MMNs of the reading disabled group was larger over the left hemisphere, while those of the control group appeared larger over the right hemisphere. Due to the fact that the definition criteria and overlap of the AD/HD group with the purely reading disabled group might have affected the results a second experiment using four groups (controls, children with reading disabilities, AD/HD children and children with both AD/HD and reading disabilities) was performed (Huttunun et al. 2008). In this study the purely AD/HD group showed significantly early peak latencies of the MMN curves over channel Fz.
3.6 P300
The P3 waveform is a highly investigated component as it is elicited in decision making processes. The earliest reports of the P300 component date back to the mid 60’s (Chapman and Bragdon 1964). In this study the authors reported for the first time that ERP’s to visual stimuli differ depending on the relevance of the particular stimuli. Some authors go as far as stating that the discovery of this component enticed the use of ERP’s to study the neural underpinnings of cognition (Polich 2006). In the case of
the P3, unlike previously discussed ERPs, this component is regarded as a endogenous component (Donchin and Spencer 2000) in the sense that its elicitation does not depend solely on the stimulus and its characteristics, but on a person’s reaction to said stimulus. This parieto-central positivity, occurring 300ms post stimulus onset time, occurs when subjects can detect an informative, task-relevant, stimulus (Picton 1992). Typically appearing as a response to an oddball task (Johnson et al., 1978 and Pritchard, 1981), the P3 component has now been segregated in two separate sub components; the P3a and P3b (depicted in Figure 2).
Polich (2007) proposed a cognitive model in which the P3a represents a stimulus driven frontal attention mechanisms during task processing. The P3b subcomponent, on the other hand, originates from temporal-parietal activity that is typically associated with attentional processes and appears to be related to memory processing. Lazzaro et al. (1997) examined the P3 in of seventeen ADHD male patient with mean age of 13,6 years old and found no significant P3 differences between non-medicated ADHD patients and controls in an oddball task. In this study, never the less, the attentional/cognitive necessities of the task may not have resulted as deficits in information processing and hence, no ERP was elicited. Also, the relatively high mean age of their ADHD group could be problematic. This reduction in the amplitude of P3b to task-relevant stimuli has been consistently found (Barry et al., 2003; Brandeis et al., 2002), but opposed findings have been found in past years. Tsai, Hung, and Lu
Figure 2Schematic of single, oddball and three tone auditory tasks for eliciting the P300. The oddball task can present two or three different stimuli within a random stream of tones that occur with different rates (target = T, standard = S). The three-stimulus
(2012), initially found that their ADHD patients to have a longer P3 latency and lower P3 amplitude than normal control children. When subjects were pooled into different age groups (6 - 7 years; 8 - 9 years; 10 - 11 years; and 12 - 13 years old) their results were slightly different. The latency of P3 was increased in all age groups regarding normal controls and the amplitude of the P3 was smaller in children with ADHD over the age of ten.
McPherson and Salamat (2004), also tested ADHD young adults and matched controls in an auditory oddball task, but in this instance, using different ISIs. ADHD P3 amplitudes were reduced and the latencies were delayed relative to the normal controls. Additionally the differences in timing between the P3a and P3b in the group with ADHD were also significantly longer. Furthermore authors proposed that the greater max peaks separation between the P3a and P3b in ADHD patients is indicative of a lag in processing that occurs between recognising that there is a difference between the stimuli and posteriorly detecting the task.
3.7 Later Components
Late ERP components, commonly denominated “slow-wave" components have also been found to be abnormal in AD/HD patients. These late ERP components have been associated with anticipatory motor mechanisms and resource investment. Holcomb et al. (1986) produce evidence to support the notion that the parietal positive slow-wave, occurring between 600ms and 900ms post stimulus onset, is smaller in AD/HD patients, regardless of the sub-classification. In later slow-wave components, namely 900ms-1200ms, there does seem to be differences. This group presents results showing that this later slow-wave is smaller in AD/HD without hyperactivity compared to the AD/HD with hyperactivity group. These results, however, could be a due to a carry-over effect from the P3 component with similar attributes. Satterfield et al. (1990), on the other hand, have reported between-channel effects in the slow-wave potentials in AH/HD patients. They report a slow positive potential, 400ms-600ms, that was smaller in attend conditions compared to non-attend ones. This difference was not found, nevertheless, in later slow positive potentials, 600ms-800ms.
3.8 Visual Evoked Potentials
Diverse visual presentation tasks have been used to examine multiple aspects of visual processing in AD/HD. Group differences have been observed in evoked responses to
visual stimuli. To examine early stages of visual processing the N1, N3 and P1 component seem to provide the best account for evaluating discrimination (the N100), selection (P150), memory retrieval (the N300) and context updating processes (P300 also referred to as the P450wm). Perchet et al (2001) found no difference in the amplitude or latency of the P1 in a cued target visual task between AD/HD patients and control groups. This interpretfinding as reflecting no differences in AD/HD childrens top-down attention mechanisms that act as sensory control over the flow of visual information. Opposing these findings, Smith et al (2004) reported the N1 component evidenced amplitude reductions in frontal sites of AD/HD children in light of a Go/Nogo task. Nazari et al (2010) found a delayed P1 and N2 latency, and lower P1 amplitude for Nogo trials in AD/HD children compared to controls. Additionally the P1 latency was also shifted for NoGo versus a Go condition. This important decrease in early processing was found in ADHD children specifically in the NoGo condition. In the same study researchers also ran a SwLORETA (PalmeroSoler et al. 2007 for a full methodological description) to perform the source localisation study and suggest an early deficit in visual sensory integration was specific to the occipital cortex in children with ADHD. As found in studies performed earlier, Benikos et al (2009) describe that N1 amplitudes were not consistent between conditions for AD/HD patients. They showed reduced N1 in fast conditions while an enhancement in medium speed conditions was found compared to controls. The AD/HD group in this study evidenced a similar atypical ERP response pattern to modulation in the N2, but the opposite for the P2, namely an over-activation in rapid presentation of stimuli and an underactivation in the mid speed conditions (Benikos et al 2009). Inoue et al (2010) found an effect of a preceding trial on brain activity during a similar visual Go/Nogo task. Response inhibition was definitely greater for nogo-switch than for nogo-repeat suggesting an influence of the preceding stimuli on the processing of the present one, but not different between patients and controls. No significant alteration was found in the amplitud of the N100 component of children with AD/HD. Moreover, all between-group comparison showed significantly reduced amplitudes to the NoGo N2 in the AD/HD group compared to the control one. In summary, the effect of preceding response execution on the NoGo N2 component was evidently altered in the AD/HD children. In further investigations Lopez et al (2006) presented evidence showing late differential cortical responses to initially suppressed irrelevant stimuli. The N1-P1 amplitudes where modulated by the physical location of the on-screen stimulus and showed no evidence for any type of group differences at this time. Typical flanker tasks have also been used to study the N2 component. Here tasks require participants to respond to an array of items (letters, numbers or images), with particular items corresponding to a left or right-handed response and distractors included in the stimuli. Within flanker tasks, the N200 component it typically seen in response to incompatible trials (BBABB) within a stream of compatible ones. Sunohara et al
(1999) show significantly faster N2 latencies in AD/HD in their patient and methylphenidate placebo patient group, but not in their control group. This finding is associated to abnormal stimulus classification processes and interpreted as representing differential attention to stimulus features. Satterfield et al (1994) present data to support these findings reporting smaller visual N2 amplitudes to attended targets. These findings, in conjunction with a P3b abnormalities found in this study are suggestive of deficiencies in two independent cognitive processes thought to be crucial to how normal controls perceive, learn, and remember. In the later P3 component relevant differences are found in other investigations as well. Dhar et al (2008) also report no difference in the P1 component of AD/HD children, but they do report a P3 difference between invalid and valid conditions in AD/HD and co-morbid AD/HD/dyslexia patients. This is in line with the previously discussed Lopez et al (2006) results on the P300 positivity being evoked, in AHDH children, by peripheral stimuli only. Johnstone et al (2009) test Barkley’s behavioural inhibition hypothesis for AD/HD. Barkley (1997) proposes a theoretical model linking four main executive functions to effective execution, namely (1) working memory, (2) self-regulation of affect, motivation and arousal, (3) internalization of speech, and (4) reconstitution. This proposed model... In testing this hypothesis, Johnstone et al (2009) report that the AD/HD group showed reduced Go/ Nogo P2 mean amplitud. Also, they report a significantly more anterior distribution of the Go/Nogo P3 component compared to controls. In their Flanker task experiement, the AD/HD group showed delayed N1 and P2 component with a dramatically reduced N2 waveform to incongruent stimuli. They report an enhanced N2 amplitude to neutral stimuli, as well as increased P3 to Incongruent stimuli in AD/HD patients. They concluded that, at least, in the Go/Nogo behavioural inhibition task and their flanker interference control task children with AD/HD were not equally impaired, challenging the model put forward by Barkley (1997). P2 latency is found diminished in AHDH children. This finding is interpreted as representing impulsivity. Oades et al (1998) proposed that larger amplitudes in the P200 are suggestive of deregulated contextual information processing while the N2 would be understood as a mismatch detector.
4. Conclusions
Within the realm of auditory evoked potentials, the oddball task seems to provide the most reliable and reproducible ERP effect in the literature. Main findings seem to be directed at establishing differences between ADHD patients and controls regarding auditory attention (figure from Johnstone et al., 2001), and are best for visual inspection of distribution features. These differences show promise in distinguishing DSM-IV, and concordantly DSM-V, subtypes of ADHD, and as such could be useful neural markers in correctly diagnosing specific AD/HD subtypes. As for general
AD/HD diagnosis using ERPs, some attempts have been made with relative success. Robaey et al. (1997) correctly classified 79\% of AD/HD children on the basis of their P3 latency in the right parieto-occipital region, but also misclassified three normal and two control children.
Visual evoked potential also show differences in most components mentioned in this review, but the genesis of deficiencies in ADHD is still obscure. It is not clear if the differences noted are a result of specific online problems in information processing or if the differences discussed are a reflection of early cognitive processing deficiencies that are manifested later in time.
Several methodological issues have also been identified with past investigation into AD/HD. Typically issues relate to small sample sizes and differently distinguished experimental groups. The fact that diagnostic criteria have evolved and been rethought throughout the past years also bring to question the ability to generalise these results. Also, many studies use combined modality of stimulus presentation (Barry et al.; 2003, Satterfield et al.; 1994) differences in stimuli, like intensity, frequency and modality, could also introduce ERP differences that pertain more to methodological variability than to strictly ADHD specific differences.
Future research in this field has many obstacles to overcome, the first being developing ERP methodologies to permit an adequate distinction of AD/HD subtypes. By specifying methods and relating ERP results to AD/HD subtypes a promising applied field of ERP research could blossom. In the same line, ERP research in AD/HD must deal with the issue of comorbidity with other conditions. To date this problem in AD/HD ERP research has not been addressed properly, only few studies have considered this problem. To correctly conduct experiments where this issue is controlled would require four experimental groups (pure AD/HD, AD/HD+comorbid, pure comorbid and control) to permit the separation of the purely AD/HD results, but as we have seen, sample sized tend to be an issue in this line of research.
Finally, a valid point is raised by Barry et al (2003) regarding the locus of ERP differences in AD/HD and their origin. Do differences in later components arise from earlier stages of information processing or are these late differences independent of earlier ones? Research directed at resolving the question of timing anomalies in information processing in AD/HD is clearly warranted and could contribute important advances in the understanding of the functional basis of AD/HD.
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Annexes
National Center on Birth Defects and Developmental Disabilities Division of Human Development and Disability
Is it ADHD?
Attention Deficit/Hyperactivity Disorder ADHD)
Symptom Checklist
Deciding if a child has ADHD is a several step process. There is no single test to diagnose ADHD, and many other problems, like anxiety, depression, and certain types of learning disabilities, can have similar symptoms.
The American Psychiatric Association's Diagnostic and Statistical Manual, Fifth edition (DSM-5) is used by mental health professionals to help diagnose ADHD. It was released in May 2013 and replaces the previous version, the text revision of the fourth edition (DSM-IV-TR). This diagnostic standard helps ensure that people are appropriately diagnosed and treated for ADHD. Using the same standard across communities will help determine how many children have ADHD, and how public health is impacted by this condition.
There were some changes in the DSM-5 for the diagnosis of ADHD: symptoms can now occur by age 12 rather than by age 6; several symptoms now need to be present in more than one setting rather than just some impairment in more than one setting; new descriptions were added to show what symptoms might look like at older ages; and for adults and adolescents age 17 or older, only 5 symptoms are needed instead of the 6 needed for younger children.
The criteria are presented in shortened form. Please note that they are provided just for your information. Only trained health care providers can diagnose or treat ADHD.
If a parent or other adult is concerned about a child’s behavior, it is important to discuss these concerns with the child’s health care provider.
