The psychophysiology of selective attention and working memory in children with PPDNOS and/or ADHD Gomarus, Henriette Karin

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1 University of Groningen The psychophysiology of selective attention and working memory in children with PPDNOS and/or ADHD Gomarus, Henriette Karin IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2010 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Gomarus, H. K. (2010). The psychophysiology of selective attention and working memory in children with PPDNOS and/or ADHD Groningen: s.n. Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date:

2 The Psychophysiology of Selective Attention and Working Memory in Children with PDDNOS and/or ADHD Karin Gomarus

3 The research described in this thesis was supported by grants from the Protestants Christelijke Kinderuitzending (PCK) and by the University Medical Center Groningen 2010, H.K. Gomarus All rights reserved. No part of this publication may be reprinted or utilized in any form or by any electronic, mechanical or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without prior written permission from the copyright owner. Cover photo: Roel Arendshorst (Senegal, 2000) Handwritten cover title: Vera Lotte Arendshorst Cover design: Reyer Boxem Printed by Grafimedia (Facilitair bedrijf), Groningen

4 The Psychophysiology of Selective Attention and Working Memory in Children with PDDNOS and/or ADHD Proefschrift ter verkrijging van het doctoraat in de Medische Wetenschappen aan de Rijksuniversiteit Groningen op gezag van de Rector Magnificus, dr. F. Zwarts, in het openbaar te verdedigen op woensdag 12 mei 2010 om uur door Henriëtte Karin Gomarus geboren op 23 april 1972 te Norg

5 Promotor: Prof. dr. R.B. Minderaa Copromotores: Dr. M. Althaus Dr. A.A. Wijers Beoordelingscommissie: Prof. dr. C. Kemner Prof. dr. J.A. Sergeant Prof. dr. O.M. Tucha ISBN (printed edition): ISBN (electronic edition):

6 Voor Roel

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8 Contents Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Introduction Cortical and autonomic correlates of visual selective attention in introverted and extraverted children The effects of memory load and stimulus relevance on the EEG during a visual selective memory search task: An ERP and ERD/ERS study ERP correlates of selective attention and working memory capacities in children with ADHD and/or PDD-NOS Do children with ADHD and/or PDD-NOS differ in reactivity of alpha/theta ERD/ERS to manipulations of cognitive load and stimulus relevance? General Discussion References Samenvatting Dankwoord

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10 Chapter 1 Introduction

11 Chapter 1 Introduction Pervasive Developmental Disorder - Not Otherwise Specified (PDD-NOS) and Attention-Deficit/ Hyperactivity Disorder (ADHD) are among the most commonly diagosed childhood disorders. Although they are described as distinct psychiatric syndromes in the Diagnostic Statistical Manual of Mental Disorders (DSM-IV-TR) (American Psychiatric Association, 2000), during the diagnostic process, the clinician may often be faced with difficulties differentiating between these two disorders. The purpose of this thesis was to examine whether these developmental disorders can be differentiated from each other on the basis of two specific information processing (dis)abilities. Basic elements of human information processing In everyday life, we are exposed to a continuous stream of information reaching us from our senses and memory. Fortunately, not each part of this constant flow of information actually reaches our consciousness. It is our information processing system that determines how we deal with this continuous input and how we perceive and evaluate the world around us. As people may differ from each other in many ways, the way in which we process information from our environment may also differ from person to person. In some cases, deficits in information processing may even contribute to aberrant behavior. Two essential elements of the human information processing system that may form a bottleneck in human cognition are working memory and selective attention. These theoretical concepts will be described briefly in the next two sections. Working Memory The concept of working memory was derived from computer science and is now a widely used term in theories on human information processing. It is commonly viewed as a capacity-limited system that is used for the short-term storage and manipulation of information (Baddeley, 1986; Baddeley, 1996; Kane and Engle, 2002; Petrides, 1994; Smith and Jonides, 1999). Ever since the term became common usage, several theories have been developed on working memory, the most influential of which is the multi-component model of working memory proposed by Baddeley and 10

12 Introduction Hitch (1974). A range of empirical data from experiments in cognitive psychology has contributed to further elaboration of this model (Repovs and Baddeley, 2006). In the first description of their model, Baddeley and Hitch present two slave systems that are responsible for the short-term maintenance of information while the supervisory central executive has the role of integrating and coordinating these slave systems. One slave system provides the short-term storage of phonological information by rehearsing the input in an articulatory loop. In the other slave system, the visuo-spatial sketchpad, visual and spatial information is temporarily stored. Recently, Baddeley and Hitch have added a fourth component to the model (Allen et al., 2006; Baddeley, 2000). This component, the episodic buffer, allows for the binding of information from different systems into multi-modal representations. The central executive is the most important but still the least understood component of the working memory model. In advancing the concept, Baddeley and colleagues adopted the model of attentional control by Norman and Shallice (Norman and Shallice, 1986). In the latter model, control was divided between two processes: 1) routine (automatic) control which controls behavior by patterns or schemata, and 2) the supervisory activating system (SAS) that comes into action when routine control is insufficient. The central executive in the Baddeley and Hitch model may be considered as a descendant from the SAS. Besides involvement in the functioning of the storage components of the model, it seems to be involved whenever information within the stores needs to be manipulated (Repovs and Baddeley, 2006). Evidence for a structural representation in the brain of the separate WM functions comes from neuroimaging studies. Within the prefrontal cortex (PFC), different areas appear to be associated with the temporal storage of information on the one hand and the active manipulation of information on the other. A review by Smith and Jonides (1999) of PET and fmri studies demonstrates that ventromedial regions of the PFC are involved in sustaining short-term storage, while dorsolateral regions of the PFC appear to mediate executive processes. Furthermore, with respect to temporary storage, a dissociation can be found in the activation of prefrontal areas elicited by verbal (left-hemisphere speech areas), object (ventral regions) and spatial (right premotor cortex) information. Although the concept of working memory is widely used in research on information processing in both humans and animals, there is still little consensus on the description of its actions. Notably, in a range of studies, the term working 11

13 Chapter 1 memory is used to refer to the short-term storage of information in a temporary buffer (e.g. Levy and Goldman-Rakic, 1999). Tasks that place demands on short-term memory, merely require to maintain information in the short-term buffer (Jarrold and Towse, 2006) whereas typical working memory tasks involve the active processing of material. In this thesis, the term working memory is used to refer to a system that includes both the short-term maintenance and the manipulation of information. Selective Attention Because our cognitive system is limited in capacity, only a part of the emerging stimuli can be processed and consciously perceived by us. Our attention system determines which information coming from our senses passes into working memory and furthermore facilitates retrieval of information from long term memory. The ability to process only that part of the information that is of interest while ignoring irrelevant information is commonly referred to as selective attention. In this sense, attention can be considered as a spotlight (Wachtel, 1967) that selects information for further processing. An influential theory of attention, in which neural systems mediating attentional processes are revealed, is proposed by Michael Posner (Posner & Petersen, 1990; Posner & Raichle, 1994). With the aid of a so-called cueing paradigm, he identifies three distinct anatomical networks, each playing a significant role in selective attention. In this cueing paradigm, an exogenously or endogenously presented stimulus (the cue) indicates the likely location of an upcoming target stimulus to which the subject has to respond. In the posterior attention network, the posterior parietal lobe acts to release attention from its current focus and signals the midbrain to move the spotlight of attention from its current location to the area of the cue. The thalamus selects the contents of the attended area and enhances those contents so they are given priority for processing by anterior areas that will detect targets and generate responses (Posner and Raichle, 1994, p. 167). The anterior attention system, in which the anterior cingulate gyrus (located in the anterior cingulate cortex) plays a significant role, is supposed to be involved in target detection. It selects relevant information detected by the posterior attention system for further processing. Another important aspect of attention is the maintenance of an alert state, which is regulated by the right frontal and parietal lobes making up the third attention network, the vigilance system. This system receives strong noradrenergic input from the locus 12

14 Introduction coeruleus in the medulla oblongata, which is thought to mediate arousal (e.g. Berridge and Waterhouse, 2003) and to increase the signal-to-noise ratio in the brain (e.g. Servan-Schreiber et al., 1990). Since working memory and selective attention are at the core of information processing, deficits in these areas may lead to serious problems in human functioning. Therefore, several authors have related deficits in selective attention and working memory to neurodevelopmental disorders (e.g. Belmonte and Yurgelun- Todd, 2003; Brodeur and Pond, 2001; Carter et al., 1995; Ciesielski et al., 1990; Ciesielski et al., 1995; Pennington and Ozonoff, 1996; Van der Stelt et al., 2001). The main theme of this thesis is on how the theoretical concepts of working memory and selective attention are related to the developmental disorders ADHD and PDD-NOS and whether they are differentially affected in both syndromes. Neurodevelopmental disorders: PDD-NOS and ADHD PDD-NOS PDD-NOS is a diagnosis that falls under the category of Pervasive Developmental Disorders (PDDs). Individuals with a PDD are characterized by severe and pervasive impairments in reciprocal social interaction skills, communication skills, or the presence of stereotyped behavior, interests, and activities (American Psychiatric Association, 2000). If the PDD s are placed along a continuum from mild to severe, then PDD-NOS may appear towards the less affected end of it while Autistic Disorder (AD) could be placed at the most severe end. PDD-NOS is diagnosed more often than AD with a prevalence of about 2.1 per 1000 against 1.3 per 1000 for AD (Fombonne, 2005). Furthermore, like autism, it is identified more often in boys than in girls (about 4:1). Children with PDD-NOS show autistic-like behavior in that they have difficulties interacting in a social environment. They have problems communicating adequately with others and may show stereotyped patterns in behavior, interests or activities. In social situations, their handicap emerges as a deficiency in understanding so-called social cues and in understanding what another thinks or feels. Furthermore, they adhere to regularity and get easily upset when a sudden change occurs in their daily 13

15 Chapter 1 routine. Yet, their behavioral deviations are not severe enough to be indicative of autism (see also Table 1) (American Psychiatric Association, 2000). Table 1. Diagnostic criteria for Autistic Disorder and Pervasive Developmental Disorder Not Otherwise Specified, DSM-IV/TR (American Psychiatric Association, 2000) Autistic Disorder A. A total of six (or more) items from (1), (2), and (3), with at least two from (1), and one each from (2) and (3): 1. qualitative impairment in social interaction, as manifested by at least two of the following: a. marked impairment in the use of multiple nonverbal behaviors such as eye-toeye gaze, facial expression, body postures, and gestures to regulate social interaction b. failure to develop peer relationships appropriate to developmental level c. a lack of spontaneous seeking to share enjoyment, interests, or achievements with other people (e.g., by a lack of showing, bringing, or pointing out objects of interest) d. lack of social or emotional reciprocity 2. qualitative impairments in communication as manifested by at least one of the following: a. delay in, or total lack of, the development of spoken language (not accompanied by an attempt to compensate through alternative modes of communication such as gesture or mime) b. in individuals with adequate speech, marked impairment in the ability to initiate or sustain a conversation with others c. stereotyped and repetitive use of language or idiosyncratic language d. lack of varied, spontaneous make-believe play or social imitative play appropriate to developmental level 3. restricted repetitive and stereotyped patterns of behavior, interests, and activities, as manifested by at least one of the following: a. encompassing preoccupation with one or more stereotyped and restricted patterns of interest that is abnormal either in intensity or focus b. apparently inflexible adherence to specific, nonfunctional routines or rituals c. stereotyped and repetitive motor mannerisms (e.g., hand or finger flapping or twisting, or complex whole-body movements) d. persistent preoccupation with parts of objects B. Delays or abnormal functioning in at least one of the following areas, with onset prior to age 3 years: (1) social interaction, (2) language as used in social communication, or (3) symbolic or imaginative play. C. The disturbance is not better accounted for by Rett's Disorder or Childhood Disintegrative Disorder Pervasive Developmental Disorder Not Otherwise Specified (Including Atypical Autism) This category should be used when there is a severe and pervasive impairment in the development of reciprocal social interaction associated with impairment in either verbal or nonverbal communication skills or with the presence of stereotyped behavior, interests, and activities, but the criteria are not met for a specific Pervasive Developmental Disorder, Schizophrenia, Schizotypal Personality Disorder, or Avoidant Personality Disorder. For example, this category includes "atypical autism" presentations that do not meet the criteria for Autistic Disorder because of late age at onset, atypical symptomatology, or subthreshold symptomatology, or all of these. 14

16 Introduction ADHD With a prevalence of about 5-10%, Attention-Deficit/Hyperactivity Disorder (ADHD) may be considered as the most commonly diagnosed developmental disorder in school-aged children. The symptoms that children with ADHD show can be categorized into three domains, i.e. inattention, hyperactivity, and impulsive behavior. Furthermore, a distinction is made between three subtypes (American Psychiatric Association, 2000) (see Table 1.2 for a full description of the diagnostic criteria). Children of the predominantly Inattentive Type (ADHD-I) are primarily characterized by daydreaming, having difficulties organizing a task appropriately and focusing on a single task for a prolonged period of time. Children of the predominantly Hyperactive/Impulsive Type (ADHD-H) are characterized by impulsivity, restless behavior, and fidgeting. However, as attention problems are almost always present in ADHD, the occurrence of the purely hyperactive/impulsive type is the least common (Nolan et al., 2001; Wolraich et al., 1998). In the Combined Type (ADHD-C) both types of behavior are present. Table 2. Diagnostic criteria for Attention-Deficit/Hyperactivity Disorder, DSM-IV/TR (American Psychiatric Association, 2000) A. Either (1) or (2): 1. six (or more) of the following symptoms of inattention have persisted for at least 6 months to a degree that is maladaptive and inconsistent with developmental level: Inattention a. often fails to give close attention to details or makes careless mistakes in schoolwork, work, or other activities b. often has difficulty sustaining attention in tasks or play activities c. often does not seem to listen when spoken to directly d. often does not follow through on instructions and fails to finish schoolwork, chores, or duties in the workplace (not due to oppositional behavior or failure to understand instructions) e. often has difficulty organizing tasks and activities f. often avoids, dislikes, or is reluctant to engage in tasks that require sustained mental effort (such as schoolwork or homework) g. often loses things necessary for tasks or activities (e.g., toys, school assignments, pencils, books, or tools) h. is often easily distracted by extraneous stimuli i. is often forgetful in daily activities 2. six (or more) of the following symptoms of hyperactivity-impulsivity have persisted for at least six months to a degree that is maladaptive and inconsistent with developmental level: Hyperactivity a. often fidgets with hands or feet or squirms in seat b. often leaves seat in classroom or in other situations in which remaining seated is expected c. often runs about or climbs excessively in situations in which it is inappropriate (in adolescents or adults, may be limited to subjective feelings of restlessness) d. often has difficulty playing or engaging in leisure activities quietly e. is often "on the go" or often acts as if "driven by a motor" 15

17 Chapter 1 f. often talks excessively Impulsivity g often blurts out answers before questions have been completed h often has difficulty awaiting turn i often interrupts or intrudes on others (e.g., butts into conversations or games) Code based on type: Attention-Deficit/Hyperactivity Disorder, Combined Type: if both Criteria A1 and A2 are met for the past 6 months Attention-Deficit/Hyperactivity Disorder, Predominantly Inattentive Type: if Criterion A1 is met but Criterion A2 is not met for the past 6 months Attention-Deficit/Hyperactivity Disorder, Predominantly Hyperactive-Impulsive Type: if Criterion A2 is met but Criterion A1 is not met for the past 6 months Coding note: For individuals (especially adolescents and adults) who currently have symptoms that no longer meet full criteria, "In Partial Remission" should be specified. Comorbidity In the DSM-IV-TR (American Psychiatric Association, 2000), PDD-NOS and ADHD are described as clearly distinct syndromes. However, in clinical practice, it may be difficult to discriminate the two disorders (Clark et al., 1999; Jensen et al., 1997) with ADHD characteristics often being observed in children with PDD-NOS and vice versa. Scientific evidence for these observations is growing. For example, deviant social behavior, which is a core symptom of PDD-NOS, has also been demonstrated in many clinically referred children with ADHD (e.g. Clark et al., 1999; Santosh and Mijovic, 2004) as well as in children ascertained from the general population meeting DSM-criteria for ADHD (Reiersen et al., 2007). Likewise, an increasing number of studies has shown that in a large number of children diagnosed with PDD-NOS, traits of ADHD are present, i.e. hyperactivity or inattentiveness (De Bruyn et al., 2007; Goldstein and Schwebach, 2004; Sturm et al., 2004; Volkmar et al., 1997). These studies suggest an overlap in problem behavior that may complicate differential diagnosis. The social problems that are sometimes seen in children with ADHD may be engendered by the ADHD-related behavior they typically demonstrate. For example, poor impulse control, acting before taking notice of another person s thoughts and feelings (Lahey et al., 1987), and difficulties with stopping behavior once it has started may lead to various problems during play and social interaction. Furthermore, when a child has difficulties maintaining attention during a conversation with an adult, it may miss parts of instructions and, as a result, may be accused of not willing to listen or not being open for conversation. The apparent overlap in symptomatology 16

18 Introduction between ADHD and PDD-NOS may, however, be caused by differing underlying mechanisms (Jensen et al., 1997) which is the subject of investigation of this thesis. Information processing in PDD and ADHD Working memory in PDD It is well known that people with autism adhere strongly to daily routines. They often show distress when things unexpectedly take a different course. As long as events take place according to a fixed schedule, they can rely on a more or less automatic control system. However, when a sudden change occurs, this automatic processing is no longer sufficient and a more controlled way of processing is needed (Norman and Shallice, 1986). It is especially in social situations that autistic people feel uncomfortable. These situations are constantly subject to change and many events may occur more or less in parallel. This complexity requires high flexibility and the ability to process and integrate several types of information. In other words, social situations impose high demands on working memory capacity. It is probably this call upon working memory capacity that is especially demanding for people with autism spectrum disorders. For example, when presented with an increasing amount of social cues, autistic children have been demonstrated to become less able to interpret social situations (Pierce et al., 1997). The children probably had less spare capacity left to process these additional social cues. In sum, the nature of the specific difficulties that children with PDD-NOS encounter in daily life points to a less efficient use of working memory capacity. However, as will be summarized in the introduction of Chapter 4, experimental studies that were specifically conducted on working memory in children with pervasive developmental disorder show contradicting results, leaving the question of a possible deficit in working memory partly unresolved. Selective attention in ADHD Apart from overly active behavior, poor impulse control and being fidgety, children with ADHD often show high distractibility and have problems in selective attention when faced with competing stimuli. Due to this presumed difficulty of ignoring 17

19 Chapter 1 irrelevant information, selective attention has emerged as a frequent subject of investigation in these children using a wide range of paradigms. For example, ADHD children s performance on a traditional neuropsychological task as the Stroop Color- Naming rather consistently points to a selective attention deficit (see, for a review, Barkley et al., 1992; Carter et al., 1995). However, results from other paradigms as the visual search paradigm (e.g. Hazell et al., 1999; Karatekin and Asarnow, 1998; Mason et al., 2003) or two-channel visual selective attention tasks (Jonkman et al., 2004; Jonkman et al., 1997; Satterfield et al., 1994; Van der Stelt et al., 2001) are mixed. Thus, although the behavioral symptoms of ADHD may suggest a deficit in selective attention, the results from experimental studies are not conclusive and further research might be necessary to shed more light on this issue. Discriminating PDD-NOS and ADHD with respect to working memory and selective attention In order to examine whether working memory and selective attention are differentially affected in PDD-NOS and ADHD, studies of working memory in ADHD and studies of selective attention in autism spectrum disorders should also be considered. However, a short review of such studies (see the introductions to Chapters 4 and 5 for a more extensive summary) learns that these show mixed results too. For a better understanding, it was considered necessary to carry out an experiment in which groups of children with both kinds of neurodevelopmental disorders took part, thereby making use of a task paradigm appealing to both working memory and selective attention. Only then, a direct comparison could be made between children with PDD- NOS and with ADHD regarding these information processing capacities. The number of studies making such direct comparisons between these groups has grown over the last few years (Corbett et al., 2009; Geurts et al., 2004; Happé et al., 2006; Nydén et al., 1999; Ozonoff and Jensen, 1999; Sinzig et al., 2008). These studies used various distinct tasks in order to examine various aspects of the so-called executive functions. Executive functioning (EF) is generally used as an umbrella term for higher cognitive abilities such as planning, impulse control, set-shifting and working memory. Separate EF studies on either ADHD or ASD suggested a deficiency in these abilities to be a core deficit in both ADHD (Barkley, 1997; Castellanos and 18

20 Introduction Tannock, 2002; Pennington and Ozonoff, 1996) and ASD (Hughes et al., 1994; Ozonoff et al., 1991). The notion that EF would be affected in both disorders while they differ in behavioral phenotype, has raised the question whether there still might be differences in the cognitive underpinnings of EF that are affected in each disorder (Ozonoff and Jensen, 1999). By comparing groups with these different psychopathological conditions on a number of EF tasks, several authors sought to find different executive profiles in task performance which might still point to distinct underlying cognitive deficits at a more micro-analytic level. Ozonoff and Jensen (1999) found some evidence for a double dissociation in that children with autism demonstrated decreased performance in planning and cognitive flexibility while children with ADHD could be characterized by deficient inhibition. However, these results could not be replicated by Nydén and colleagues (1999). The study by Geurts and co-workers (Geurts et al., 2004) also showed impaired inhibition in ADHD while children with high functioning autism (HFA) displayed inferior performance on a wider range of EF tasks. In the study by Happé (2006), at last, no differences were found with respect to cognitive flexibility between these groups. In the same study, the ADHD group displayed a significant impairment in response selection/inhibition on a Go/No Go task while the autism groups performed worse on response selection/monitoring in a so-called cognitive estimates task adapted from Shallice and Evans (Shallice and Evans, 1978). All together, these studies, in which direct comparisons were made between children with ADHD and children with ASD, supply some evidence for differences in cognitive profile between children with ADHD on the one hand and children with autism spectrum disorder on the other. However, the results are not convincing and most of them need replication before statements concerning unequivocal differences can be made. In the greater part of the studies cited above, typical neuropsychological EF tasks were used to assess higher cognitive functioning. However, while it is recognized that working memory is a critical component of tasks that have been developed to assess executive functioning (Pennington and Ozonoff, 1996), the outcome of these tests may reflect the product of multiple underlying processes among which perception, inhibition, motor execution and working memory. As a consequence, it is difficult to point out in which stage of information processing the bottleneck might be when performance is impaired. An accurate interpretation of the results may therefore be difficult. A more refined way to asses cognitive functioning is 19

21 Chapter 1 to manipulate task demands that load on specific stages in information processing while reaction times are measured. The effects of such manipulations on reaction time may give more insight into the separate cognitive processes that are addressed by the task at hand. In this manner, these so-called reaction time paradigms allow for a more thorough examination of the various stages of information processing. In the studies described in this thesis, such paradigms were employed in order to examine processes of both selective attention and working memory. In addition, psychophysiological measures were used to study brain processes underlying an overt response. In this sense, the high temporal resolution of EEG event-related potentials (ERPs) enables us to study stages in information processing that take place before an overt response is made. Another method, the method of eventrelated (de-)synchronization in spectral energy of specific EEG rhythms (ERD/ERS) was also applied and will be explained below. The task-related brain dynamics that are reflected by this latter technique are longer lasting than ERP phenomena and may be more related to the subject s neurophysiological state. Psychophysiological measures ERPs The electroencephalogram (EEG) represents electrical activity of (postsynaptic) potentials produced by a large number of neurons and can be recorded with the aid of electrodes attached on the surface of the scalp. Event-related potentials (ERPs) are small, transient changes in brain activity that are time locked to a specific event. They are presumed to reflect the perceptual, motor and/or cognitive processes related to the processing of that event. Because of their small amplitudes and the presence of background noise, ERPs can hardly be discerned in the ongoing EEG. Therefore, in cognitive electroencephalographic research, an averaging procedure is applied to a range of predefined time segments in the EEG that are time-locked to the occurrence of an event. By the summation of these time segments, the random noise is averaged to zero leaving the time-locked ERP visible. The resulting ERP provides a very high time resolution, in the range of milliseconds, and consists of a number of positive and negative deflections that are time-locked to the stimulus. These properties make the method of ERPs an excellent means to study 20

22 Introduction psychological and neural sub-processes involved in complex perceptual, cognitive, or motor tasks. As a result of extensive research - which generally has been conducted on healthy adults - it is now possible to relate distinct ERP components to different stages of information processing, e.g. processes related to orienting, early perception, selective attention, target detection and evaluation, search processes etc. This knowledge is now widely applied to research in psychopathology in both adults and children in order to study possible deficiencies in information processing. Although the amount of ERP research in healthy children is far less extensive than in adults, promising results are reported with respect to ERP characteristics in children. For example, a developmental study by Van der Stelt and colleagues has demonstrated that ERPs in children have longer latencies and may differ in amplitude and scalp distribution from those of adults (Van der Stelt et al., 1998). ERD/ERS An external or internally paced event can also induce rhythmic changes in brain activity. These changes can be made visible with the method of ERD/ERS. Here, an event-related change in power of a given frequency band is expressed as the percentage of the power in a specified reference period that is considered unaffected by the event. A decrease of power is called event-related desynchronization (ERD) (Pfurtscheller, 1977; Pfurtscheller and Aranibar, 1977) while an increase is referred to as event-related synchronization (ERS) (Pfurtscheller, 1992). In the averaging procedure of the ERP, non-phase locked activity is cancelled out, while with the method of ERD/ERS, this activity can be maintained because the amplitudes are squared before averaging (Bastiaansen and Hagoort, 2003). In addition, as ERD/ERS reveals longer lasting event-related changes than ERPs, ERD/ERS may reflect brain dynamics that are more related to the subject s neurophysiological state. The frequency bands that have acquired most attention in ERD/ERS research are the theta (4-8 Hz) and alpha (8-10 Hz) bands which have been found to be sensitive to variations in task demands (for reviews, see Bastiaansen and Hagoort, 2003; and Klimesch, 1999) such as attention and memory load. 21

23 Chapter 1 Interpreting ERP deflections and ERD/ERS in children The meaning that can be ascribed to an ERP deflection as well as to ERD/ERS is strongly dependent on the cognitive demands that are imposed by the task at hand. Much knowledge on the interpretation of these task-related measures has been derived from adult studies using a wide range of task paradigms. This knowledge has become more and more applied to studies in clinical samples of both adults and children. However, some caution should be taken in generalizing adult findings to child studies as it is known that the immature brain is subject to developmental changes in information processing. Consequently, as compared to the mature brain, it may show differences in electrophysiological responses to incoming stimuli which may be related to cognitive growth or brain maturation (Ridderinkhof and Van der Stelt, 2000). A comprehensive developmental study by Van der Stelt and colleagues (1998) for example, demonstrated that ERPs may change in latency onset, amplitude and scalp distribution with increasing age. Aim and outline of this thesis The aim of the present thesis is to shed more light on possible differences in the information processing capacities of selective attention and working memory between children with PDD-NOS on the one hand and children with ADHD on the other. To this end, groups of school-aged children with different types of psychopathology related to these developmental disorders as well as a healthy control group carried out reaction time tasks while their EEG was recorded. Whereas much knowledge about psychophysiological correlates of working memory and selective attention has been derived from studies in healthy adults, studies in healthy children are far smaller in number. Therefore, prior to examining children with developmental psychopathology, the first two studies in this thesis were conducted on groups of healthy children. The study described in Chapter 2 uses a visuo-spatial selective attention task in order to examine whether the manipulation of selective attention shows differential effects in children categorized as either introverted or extraverted. It was thought that the psychophysiological correlates of attention processes that were derived from this task, would also supply useful tools for studying these processes in children diagnosed with ADHD and/or PDD-NOS. However, in a subsequent pilot study on 22

24 Introduction children with developmental psychopathology, the spatial cueing of this task induced too many eye movements in these children, making it impossible to derive reliable ERPs. Therefore, this paradigm was considered unsuitable for the investigation of our hypotheses and a different task paradigm was developed. Chapter 3 describes a study in which a non-spatial selective attention task is used to examine the effects of selective attention and memory load on ERPs and ERD/ERS in a group of healthy control children. The outcome of this study shows that this task provides a useful paradigm for the study of selective attention and working memory in children with developmental disorders. It further supplies a framework within which the group comparisons described in the next two studies could be carried out. In Chapters 4 and 5, group comparisons are made between healthy controls, children with PDD-NOS, ADHD, and a group of children showing symptoms of both disorders. Chapter 4 uses the method of ERPs whereas the study in Chapter 5 employs ERD/ERS in order to find additional information to the former study. Although in the past, several authors have used event-related potentials to investigate processes of selective attention and working memory in children with ADHD (Jonkman et al., 2000; e.g. Jonkman et al., 1997; Van der Stelt et al., 2001) and autism spectrum disorder (e.g. Ciesielski et al., 1990; Ciesielski et al., 1995; Hoeksma et al., 2004) separately, to our knowledge, a direct comparison between these groups with respect to ERPs has not been carried out before. Finally, Chapter 6 presents a discussion of the results. 23

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26 Chapter 2 Cortical and autonomic correlates of visual selective attention in introverted and extraverted children Monika Althaus, H. Karin Gomarus, Albertus A. Wijers, Lambertus J.M. Mulder, José L. van Velzen, Ruud B. Minderaa The study described in this chapter has been published in the Journal of Psychophysiology,19:1, 35-49, 2005

27 Abstract We investigated the performance on a selective attention task in two Groups of 8- to 12-year-old healthy children being characterized as extraverted and introverted, respectively. During task performance EEG-activity was recorded to investigate differential effects on a specific selection-related potential, the N2b. Cardiac activity was recorded continuously before, during and after task performance. Spectral energy was computed for three distinguishable frequency bands corresponding with a low (LF) mid- (MF) and high (HF) frequency component in heart rate variability (HRV). The extraverted children were found to show greater perceptual sensitivity in response to irrelevant information. They also exhibited a greater N2b-component while showing significantly greater decreases in, particularly, the LF- and MF-power of HRV during task performance as compared to baseline periods. The magnitude of the N2b and the task-related decreases in LF-power of HRV were found to correlate significantly with the degree of extraversion and task performance, as well as with each other. The findings are discussed in the light of how selective attention and changes in physiological state may be related to the children s temperament. Key words: selective attention, introversion, extraversion, children, ERPs, autonomic responsiveness.

28 Selective Attention in Introverted and Extraverted Children Introduction In everyday life we are continuously exposed to many events occurring in our environment. Because of our limited information processing capacity these events cannot all be processed simultaneously to be perceived and consciously experienced by us. By orienting to only a small sample of the incoming information, we exclude most of the input reaching our peripheral receptor organs. This ability of the human information processing system, to process only that part of the information that may be relevant in a given situation, is commonly referred to as selective attention. People differ in the way they are able to select relevant information from the vast number of stimuli they are exposed to. Introverted subjects have been suggested to have a narrower focus of attention than extraverted subjects (Stenberg et al., 1990). This narrower range of attention has been assumed to result in less extensive processing of stimuli that are not directly relevant to the primary task. Consequently, task-irrelevant or distracting information should be more easily ignored. This difference in selective processing has been explained by H.J. Eysenck s (1967) arousal theory of introversion-extraversion. According to this theory introverts are more easily aroused than extraverts with the consequence of reaching an optimal level of arousal more easily. The increased level of arousal in introverted people is supposed to lead to a narrower range of cue utilization and enhanced selective attention. Extraverts, on the other hand, should tend to seek stimulation in order to increase their level of arousal (Eysenck, 1981; Eysenck, 1982). When arousal is low, attention is easily displaced leading to higher distractibility (Posner and Raichle, 1994). Under more demanding task conditions, however, the arousal level is supposed to increase. The introvert is then inclined to become overaroused leading to a decrease in performance, whereas the extravert might reach a near to optimum level of arousal leading to improved performance. Better attentional performances are expected to be found in extraverts if processing demands are high, habituation to the task is low, and inter-stimulus intervals are short (Stenberg et al., 1990). Prior to the study of differences in selective attention between children with externalizing and internalizing behavior problems, we investigated selective attention and its psychophysiological correlates in two groups of healthy, normally intelligent children who were judged to be introverted and extraverted, respectively. More 27

29 Chapter 2 specifically, the objective was to investigate the relationship between a specific selection-related potential in the EEG, changes in autonomic state, and the performance of a selective attention task in these two groups of children. Theoretical background Evidence for changes in arousal affecting selectivity, i.e. the efficiency of orienting to relevant inputs alone, has come from investigations into the interactions between the three distinguishable attention systems that have been postulated by Posner and colleagues (Posner, 1993; Posner and Petersen, 1990; Posner and Raichle, 1994; Turken and Swick, 1999; Webster and Ungerleider, 1998) as well as from studies on the participation of the locus coeruleus (LC) in cortically mediated attentional processes (Aston-Jones et al., 1999; Foote et al., 1991). Changes in activity of the locus coeruleus, this structure being described by Posner and colleagues to form an essential part of the vigilance system, have been suggested to contribute to the production of a behavioral state in which novel sensory stimuli are more effectively processed. This behavioral state has been postulated to be a necessary precondition for the elicitation of long latency, P3-like, event-related EEG potentials (Foote et al., 1991). In this context it is important to note that the authors of the LC studies pointed to the particular role of the peripheral sympathetic system, which should be activated in parallel with the central LC system (Aston-Jones et al., 1999). Physiological Measures Selectivity of attention in humans has previously been studied by using a visual attention task in which subjects have to attend to cued (relevant) information and ignore uncued (irrelevant) information (Posner, 1980). When measuring EEG, a difference has been observed between the ERPs evoked by, respectively, relevant and irrelevant stimuli. A stable ERP-component related to selective attention has turned out to be the N2b, a long latency difference potential reflecting a negativity when averaged responses to irrelevant stimuli are subtracted from averaged responses to relevant stimuli (Lange et al., 1998; Näätänen and Gaillard, 1983; Okita et al., 1985; Smid et al., 1999). This negativity appears between about ms after the appearance of the stimulus to be attended to and reaches its maximum at 28

30 Selective Attention in Introverted and Extraverted Children centro-frontal positions. The N2b has been found in paradigms using several different selection features, e.g. color, location, or size. Hence, it appears to be unrelated to the type of selection cue (Wijers, 1989). Using a visual (color) selective attention paradigm in a developmental study comparing different age groups within the range of 7 to 24 years, Van der Stelt and colleagues (1998) could show that the N2b component had a later onset in children and young adolescents (7 to 15 year) while it also appeared to be more frontally distributed as compared to older adolescents and young adults who showed a more central distribution of this component. In general, the magnitude of the N2b has repeatedly been described as being related to both the difficulty of a discrimination task and the subject s efficiency in task performance (Kasai et al., 1999; Lorist et al., 1995; Mulder et al., 1989; Potts et al., 2002; Senkowski and Herrmann, 2002). Measures of the individual s autonomic state and his autonomic responsiveness to an attention-demanding task can be derived from the cardiac signal. Spectral analysis of the fluctuations in inter-beat interval (IBI) times reveals three different components of heart rate variability (HRV) within three distinguishable frequency bands. The power of the various components is expected to be differentially affected by changes in parasympathetic and sympathetic activity. There is a high frequency (HF) component, which can be observed within a frequency band ranging from 0.15 to 0.40 Hz. This component corresponds to the individual s dominant respiration frequency and, thus, has been associated with respiratory sinus arrhytmia (RSA). Parasympathetic (vagal) autonomic activity has been assumed to be the major contributor to fluctuations in the high frequency band, and withdrawal of vagal activity has been shown to produce a decrease in the power of this component in particular (e.g. Akselrod et al., 1985; Grossman, 1992; Porges and Byrne, 1992). A second component is found at about 0.10 Hz within a range from 0.07 to 0.14 Hz, called the mid-frequency (MF) band. This component is supposed to reflect the activity of the baroreflex, by means of which short term fluctuations in blood pressure are adjusted. Both, parasympathetically as well as sympathetically driven changes are supposed to modulate the power of HRV in the mid-frequency band (e.g. Mulder et al., 1995b; Pagani et al., 1992; Saul, 1990). Decreases of HRV in this band have been shown to be a sensitive index of the amount of mental effort invested in an attention-demanding task (e.g. Aasman et al., 1988; Althaus et al., 1998; Althaus et al., 1999; Redondo and Valle-Inclan, 1992). 29

31 Chapter 2 A third component reflecting slower changes in heart rate is found within a low frequency (LF) band ranging from 0.02 to 0.06 Hz. Fluctuations in this range arise from vasomotor activity involved in the regulation of body temperature (Kitney, 1975) and renin-angiotensin system activity (Akselrod et al., 1985). Decreases in the power of this component have also been found in attention-demanding situations (Althaus et al., 1998; Jorna, 1992; Mulder, 1992). Changes in LF-power are also assumed to be affected by both, parasympathetically and sympathetically mediated changes in autonomic activity (e.g. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996). Hypotheses We investigated whether two groups of healthy, normally intelligent children who were judged to be introverted and extraverted, respectively, differ in (1) their way of performing a selective attention task, (2) their attention-related cortical responses to relevant vs. irrelevant information, and (3) their cardiac responsiveness to the task demands. To this end cardiac and EEG-activity was recorded from sixteen 8-to 12- year-old children while they performed a visual selective attention task. Heart rate was recorded continuously during two periods of rest preceding and following task performance, respectively, as well as during task performance. From the different types of errors made in response to relevant and irrelevant information we computed two types of parameters derived from signal detection theory (Green and Swets, 1966) reflecting the children s perceptual sensitivity (d ) and their decision bias (β), respectively. Changes in perceptual sensitivity have previously been associated with phasic changes in the individual s level of arousal, while changes in decision criterion have been associated with changes in readiness to respond, this being dependent on the individual s tonic activation level (Broadbent, 1971; Sanders, 1983). The dependent measures of our comparisons, therefore, were, (1) d and β in response to both relevant and irrelevant information as well as reaction times (RT) in response to relevant information, (2) the above-described N2b component as a cortical index of selective attention, while (3) autonomic responsiveness to the task demands was operationalized by computing rest-task differences (RTDs) in IBI times as well as in the spectral power of HRV obtained for the three frequency bands presented above. 30