A Comparison of Working Memory in Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder
A Comparison of Working Memory in
Attention Deficit Hyperactivity Disorder and
Autism Spectrum Disorder
Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) often share behavior characteristic. In fact, many children with High Functioning Autism (HFA) are often misdiagnosed or initially diagnosed with ADHD (Corbett & Constantine, 2006). There has been an increase in ASD diagnosis over the past decade, which could be related to the increased identification of ASD in children with ADHD. Differentiating between HFA and ADHD can be challenging, however; symptom profiling using the widely accepted Diagnostic of Statistical Manual of Mental Disorders (DSM-IV) prevents clinicians from diagnosing individuals ADHD when Pervasive Developmental Disorders (PDD) is present (APA, 1994). This comparison report will first review the literature and theory on the diagnosis and working memory aspects of these two disorders and then synthesize strategies for teaching students.
Behavioral symptoms, as recorded in the Diagnostic of Statistical Manual of Mental Disorders 4th ed., DSM-IV and its text revision DSM-IVTR, are used to identify children with ADHD (APA, 2000). Eighteen symptoms are used; nine are clustered under Inattention and nine are clustered under Hyperactivity-Impulsivity. Based on these clusters, there are three subtypes of ADHD. The first is Predominantly Inattentive (ADHD-IA), showing six of the nine symptoms of inattention, but fewer than six of the symptoms of hyperactivity and impulsivity. The second is predominately Hyperactive-Impulsive, (ADHD-HI), showing the opposite pattern. The third is, ADHD Combined (ADHD-C), which shows six of the nine symptoms in both categories. In addition, persistence of the symptoms should have existed for at least six months and onset before the age of seven for some of the symptoms (APA, 2000).
ASD is a severe neurodevelopment disorder identified by distinct learning and behavioral characteristics. This disorder has biological and genetic causes that produce changes during brain development. These changes result in atypical cognitive development and social behavior. The DSM-IV provides five deficit areas as diagnostic criteria: behavior, communication, restricted interest, sensory integration and social skills (APA, 1994). These disorders are usually exhibited before the age of three years old and manifest as deficit in joint attention, eye contact, reciprocal conversation and atypical sensory and motor processing. ASD is characterized as a PDD (Corbet & Constantine, 2006).
One point of differentiation between ASD and ADHD is that it is generally agreed on that ADHD is a neurodevelopment disorder and the physiology of ADHD involves dysfunction of dopaminergic and noradrenergic pathways in the prefrontal cortex and sub-cortical areas of the brain (Martinussen & Tannock, 2006); whereas, there is much controversy regarding the neuropathological functioning of individuals with ASD. One body of research supports impairments in attention and arousal underlying some of the primary neuropathological functioning and others do not (Corbet & Constantine, 2006).
Research into the executive functions of the brain, particularly working memory has been the subject of much controversy. The executive functions of the brain, which include working memory, are described in the information processing theoretical model of learning. The information processing models for learning and language acquisition both stress the importance of attention, short-term, and working memory in the communication process (Kuder, 2008; Lerner & Kline, 2006). Attention enables the discrimination of information in short-term memory and the transfer and retrieval of information from long-term memory (Kuder, 2008). In this way, new information is related to previously stored knowledge. Working memory accepts information from the senses, processes the information, and passes it to short-term memory. Working memory capacity has been associated with differences in human performance. Working memory, which allows for simultaneous storage and processing of temporary information, has been the focus of research on children with ASD and ADHD (Ozonoff & Strayer, 2001; Steele, Minshew, Luna, & Sweeney, 2007; Williams, Goldstein, Carpenter, & Menshew, 2005; Goldberg, Mostofsky, Cutting, Mahone, Astor, Denckla, & Landa, 2005).
The information processing model for learning begins with input stimuli. This stimuli is received through the sensory register. Vision and audition are examples of input stimuli that may be passed to the sensory register. Much of the sensory input that we received is not deemed important, is not attended to, and is not passed to the sensory register. However, once the input is deemed important, it is passed to the first memory system, that is the sensory register (Lerner & Kline, 2006). At this point perception, which depends on a child’s past experience and ability to direct attention to information, is important. Sensation, attention, and perception are ongoing activities that take place when a stimulus is present. Memory begins after perception. It is the ability to store and retrieve previously experienced sensations (Lerner & Kline, 2006). The first point of storage is known as short-term memory.
Executive functions such as attention, inhibition, and working memory are associated with the prefrontal cortex and subcortical regions of the brain (Martinussen & Tannock, 2006). This theoretical model lays a ground work for comparing research on ASD and ADHD and working memory.
The central executive coordinates a number of subsystems. Two of these subsystems are the articulatory loop, and the visuospatial sketchpad. The articulatory loop, composed of phonological memory holds speech based materials for brief periods and the articulatory control process by which information is refreshed through rehearsal. Verbal information that is presented either auditorally or visually is remembered by translating the sensory input into a representational form (Williams, et al., 2005). This area is referenced in our model as Verbal Working Memory (VWM). The visuospatial sketchpad is responsible for the manipulation and temporary storage of visual information including spatial locations. This area is referenced in our model as Spatial Working Memory (SWM), (Williams, et al., 2005).
Literature suggest that working memory dysfunction, a core deficit in autism, inhibits the retention of information in the VWM or the SWM sufficiently enough to solve problems. However other studies suggest that the deficit is only in the SWM (Williams, et. al., 2005). VWM and SWM have been the focus of several research studies on children with ASD (Williams, et al., 2005; Steel, Minshew, Luna & Sweeney, 2007; Goldberg, Mostofsky, Ozonoff & Strauer, 2001) and comparisons with children with ADHD (Cutting, Mahone, Astor, Denckla, & Landa, 2005). Based on these research studies there is evidence that the VWM is not seriously impaired in autism (Ozonoff, Strayer, 2001; Williams, et. al., 2005; Steely, et. al., 2007), and is more impaired in ADHD (Goldberg, et. al., 2005). The opposite is true of SWM. Children with ADHD are not impacted as greatly as children with ASD. It is important to look at the assessment tools used to measure VWM and SWM in order to relate these findings to the education acquisition for children with HFA and ADHD.
In one test on VWM, the subjects are presented with an item and asked if it matches an item that was presented previously, one back, or prior to the previous item, two back. Several items are presented at a time for increased complexity. Subjects were required to hold in working memory the items from the previous trials continually updating VWM and use the information to decide if a match, or a mismatch had occurred. The critical measure was reaction time and accuracy. In another test of VWM that uses audio cues, the subjects are asked to recall randomly mixed sequence of letter and numbers (e.g., 6 L that are read aloud by the examiner (Williams et. al., 2005).
In one test of SWM, follow the leader, ten cubes are presented in fixed location, and the subject must tap the cubes in the same order that the examiner taped the cubes. The number of taps are increased in order to increase the complexity (William, et. al., 2005). In another study, subjects are shown one, three, or five shapes simultaneously on a computer screen. The shapes were removed and one of the shapes was represented in the center of the screen. The subject had to touch the location on the screen where the shape being shown was previously presented (Ozonoff & Strayer, 2001). The delay between the presentation of the shapes was increased during the testing. The critical measurements were reaction time and accuracy.
In another test six colored boxes were presented on the screen. The subjects had to locate the three hidden items that were hidden behind the boxes. They were instructed to search each box but never return to a box they had previously searched. After each selection the locations of the colored boxes were rotated (Ozonoff & Strayer, 2001). The subjects had to hold in memory the color of the boxes that had already been selected and use that information to select subsequent boxes. The critical factor was the number of times subjects selected boxes that had been previously chosen (Ozonoff & Strayer, 2001). In another study the boxes were not rotated until after all the tokens were found, however, there were more boxes presented and the strategies that subjects used to avoid selecting previously selected boxes was also measured (Steel et., al., 2007). The outcome of these tests was that the greater the demand on SWM the lower the performance level for the ASD subjects when compared to the control groups.
The explicit teaching of working memory strategies and time accommodations are needed for HFA and ADHD students. For educators of HFA and ADHD students these studies point to the need to chunk information into manageable sizes and decrease time lag between dependent chucks of information. ADHD students are better able to strategically organize information than HFA students, however both populations can improve SWM by using tools such as story maps and visual organizers. These tools also increase working memory capacity by scaffolding information to paper. One reading comprehension strategy is to read the question first, write it, and then refer back to it until an answer is found while reading the passage. Additional time to employ these strategies is a necessary accommodation. ADHD and HFA students can be taught to self accommodate their SWM and VWM deficits so as to achieve academic success.
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