DEVELOPMENTAL NEUROPSYCHOLOGY, 24(2&3), 593–612 Copyright © 2003, Lawrence Erlbaum Associates, Inc.
Brain Mechanisms for Reading in Children With and Without Dyslexia: A Review of Studies of Normal Development and Plasticity Andrew C. Papanicolaou, Panagiotis G. Simos, and Joshua I. Breier Department of Neurosurgery Vivian L. Smith Center for Neurologic Research
Jack M. Fletcher and Barbara R. Foorman Department of Pediatrics University of Texas—Houston Medical School
David Francis Department of Psychology University of Houston
Eduardo M. Castillo Department of Neurosurgery Vivian L. Smith Center for Neurologic Research
Robert N. Davis Department of Neurology Vivian L. Smith Center for Neurologic Research Department of Psychology University of Houston
Requests for reprints should be sent to Andrew C. Papanicolaou, Department of Neurosurgery, University of Texas—Houston Medical School, 6431 Fannin Suite 7.154, Houston, TX 77030. E-mail:
[email protected]
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In this article we review our experience with the application of magnetic source imaging (MSI), the newest of the functional imaging methods, to the study of brain mechanisms for reading among children who read normally and among those with dyslexia. After giving a general description of MSI, we present evidence for reliable and valid maps of the brain mechanism for aural language comprehension as well as for reading. Next, we present data from 39 normal readers, 40 children with dyslexia, and 30 younger children at risk for developing a reading disability. These data show different brain activation maps for individual children with dyslexia and children at risk for dyslexia than for those of normal readers. Such differences most likely reflect aberrant brain organization underlying phonological decoding, rather than variables such as degree of effort. Finally, we present preliminary data demonstrating that the aberrant activation profiles of children with dyslexia may return to normative patterns as a result of a successful reading intervention that enables children to improve phonological decoding skills.
Listening to and comprehending words, reading words, and reading and comparing meaningless letter strings are activities that are associated with distinct profiles of brain activation. Such profiles provide us with the outlines of the various cerebral mechanisms that mediate the several cognitive and linguistic operations that each of these tasks entail. Children with dyslexia, much like normal readers, display distinct profiles of brain activation associated with a variety of reading tasks. Their profiles are indistinguishable from those of normal readers when the task involves aural presentation of words, but they differ dramatically from those of normal readers when the task entails phonological decoding. These aberrant activation profiles appear to be specific to dyslexia and are characterized by one particularly prominent feature, namely, decreased left- and increased right-hemisphere activation in certain brain regions in individuals otherwise left-dominant for language. The profiles appear to be reversible following successful training in phonological decoding, as a result of which the brain activation profiles become indistinguishable from those of normal readers. The purpose of this article is to introduce and describe the noninvasive functional imaging method used to obtain brain activation maps from individual participants, and to then 1. Summarize the reasons such maps are deemed reliable and valid in the sense that they represent brain mechanisms engaged in linguistic operations rather than other cognitive functions. Such demonstrations of validity involve maps of aural word recognition. 2. Demonstrate that, although children with dyslexia may be left-hemisphere dominant (like most normal readers) for aural word recognition, when they try to read the same words, they present a brain activation profile drastically distinct from that of normal readers engaged in the same tasks.
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3. Demonstrate that such differences in profiles during reading are (a) not due to the relatively greater difficulty that children with dyslexia experience during the reading tasks and, (b) not confined to a particular task, but are obtained on all reading tasks thus far employed. 4. Demonstrate that the brain activation profile characteristic of dyslexia is present during the initial phases of reading acquisition. 5. Demonstrate that although dyslexia is associated with what appears to be a neural signature, suggesting that it has a demonstrable neurological basis, dyslexia is not a neurological disease. Rather, it is a neurological condition that can be reversed by means of reading intervention targeting phonological decoding.
GENERAL DESCRIPTION OF THE METHOD OF MAGNETOENCEPHALOGRAPHY (MEG) MEG, otherwise known as magnetic source imaging (MSI), is a completely noninvasive method of functional brain imaging, akin to quantitative electroencephalography and complementary to other functional imaging methods, such as functional magnetic resonance imaging and positron emission tomography. It consists of first recording, on the head surface, the magnetic flux associated with electrical currents in activated sets of neurons (Lewine, 1990; Papanicolaou, 1998; Papanicolaou & Tarkka, 1996). Second, the locations of such sets of neurons (also referred to as activity sources) are estimated. Third, the locations of these sources are projected onto structural images of the brain, which allows for visualization of the activated brain regions. MEG has undergone a rapid evolution during the past few years and is a very successful method for mapping the primary sensory (Nakasato et al., 1997; Ruohonen et al., 1996; Seki et al., 1996; Sobel et al., 1993) and association cortices (Rogers, Basile, Papanicolaou, & Eisenberg, 1993; Rogers et al., 1991; Simos, Basile, & Papanicolaou, 1997). The procedures for imaging the brain mechanisms of simple and higher functions with MEG can be summarized as follows. Stimuli are known to evoke brain activity soon after they impinge on the sensory receptors. One basic aspect of such activity is the intra- and extracellular flow of ions, which generates electrical currents and magnetic fields. Repetitive presentation of stimuli results in repeated evocation of the same currents and magnetic fields that, when recorded on the head surface and averaged, result in the well-known evoked potentials (EPs) and their magnetic counterparts, the evoked fields (EFs). The distribution of EFs on the head surface lends itself—much more readily than the distribution of the EPs—to estimates of the location and extent of activation of their sources in the brain.
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EFs, much like EPs, are waveforms representing temporal variations in brain activity, evoked by the presentation of stimuli. Some of these variations are observed consistently across various experimental conditions and are referred to as components. There are two basic types of components: (a) early, extending up to 150–200 ms following stimulus onset, and (b) late, lasting several hundred milliseconds. Early components have been shown to reflect activation of primary sensory cortices (Nakasato et al., 1997; Ruohonen et al., 1996; Seki et al., 1996; Sobel et al., 1993). Late components have been shown to reflect activation of the association cortex (Rogers et al., 1991; Rogers et al., 1993; Simos et al., 1997). Early components can be used to construct images of brain mechanisms of simple sensory functions, whereas the late components are used for constructing maps of higher cortical functions, such as language. In our laboratory, all MEG recordings are made with a multichannel neuromagnetometer (4-D Neuroimaging, Magnes WH2500) consisting of 148 magnetometers arranged to cover the entire head. This instrument is housed in a magnetically shielded chamber used for reducing environmental magnetic noise that interferes with the recordings of biological signals. The typical recording session (during which the participants must remain immobile while lying on a bed with their head inside the helmet-like container of magnetometers) rarely exceeds 10 min. Thus, repeated measurements for the purpose of establishing the reliability of the results are feasible, as is testing of restless or very young children. The four experiments described later involved a number of different linguistic tasks. More detailed descriptions of the specific tasks are provided below, but there were several features shared by all tasks. Each task involved the use of an Apple Macintosh Powerbook computer running Superlab Pro (version 1.76). In tasks that required a yes–no response, participants were instructed to lift their index finger when two stimuli were comparable (or identical, depending on the task) but to not respond if they were not. The responding hand was counterbalanced across participants within each experimental task. All auditory stimuli were delivered binaurally through two 5-m-long plastic tubes terminating in ear inserts at an intensity of 80 dB SPL at the participant’s outer ear. All visual stimuli were projected through an LCD projector on a white screen located about 1.5 m in front of the participant and subtending 1.0–4.0 and 0.5 degrees of horizontal and vertical visual angle, respectively. For all tasks that involved rhyming or matching of two stimuli, event-related magnetic fields were always recorded to the first stimulus of each pair. This recording ensured that the brain activity recorded corresponded to the operations of interest (e.g., phonological decoding) but did not reflect the additional cognitive operations that matching of the stimuli might have entailed. For all tasks that involved pronunciation of printed material (e.g., letter sounds), event-related magnetic fields were recorded as the relevant stimuli were presented, but before the participant read the stimuli aloud. This procedure ensured
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TABLE 1 Children’s Demographic Information Study 1 Word Recognition Visual
Group n M Age
Auditory
Study 2 Pseudoword Reading
Study 3 Letter sound knowledge
Ch. w/ Ch. w/o Ch. w/ Ch. w/o Ch. w/ Ch. w/o Not At Dyslexia Dyslexia Dyslexia Dyslexia Dyslexia Dyslexia At Risk Risk 12 12.6
12 11.4
8 13.4
11 13.2
28 11.1
12 11.2
30 6.5
15 6.3
Study 4 Intervention (Pseudoword Reading) Ch. w/ Dyslexia 8 11.4
Note. There were no significant differences between groups in Studies 1–3 with respect to age or gender ratio. Ch.w/ = children with; Ch. w/o = children without.
that the brain activity recorded corresponded to phonological decoding operations without contamination by myogenic artifacts. Aside from over 200 adult participants and patients tested thus far, who participated in the reliability and validity studies to be reviewed later, an evergrowing number of typically achieving children and children with dyslexia are also participating in a number of different studies. Some basic demographic information of these participants that have been tested thus far (39 normal readers, 40 children with dyslexia, and 30 younger children at risk for developing a reading disability) and the tasks that each child has performed are summarized in Table 1.
VALIDITY AND RELIABILITY OF AURAL AND WRITTEN WORD RECOGNITION MAPS In a series of recent studies involving more than 200 individuals, we established the spatiotemporal patterns of brain activation specific to simple somatosensory functions, aural language comprehension, and word reading, and we verified their stability or reproducibility over time (Papanicolaou et al., 1999). Moreover, in two investigations still in progress, we have established the validity and topographical specificity of these maps by comparing them with the results of direct cortical stimulation mapping and with the results of the Wada procedure in more than 60 patients thus far. Preliminary reports of these findings can be found in Breier, Simos, Zouridakis, Wheless, et al. (1999) and Simos et al. (1999). The aural word recognition task as well as the reading task that have resulted in the previouslymentioned valid and reliable maps are described later, because the very same tasks have also been used with children with dyslexia and typically achieving agematched readers.
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Participants (both adult normal controls and adult neurological patients) in these studies were tested using two verbal tasks, one involving printed words and the other spoken words. In both tasks the verbal stimuli were presented one at a time, and EFs to each were recorded by means of the neuromagnetometer previously described. In the Auditory Word Recognition task, participants hear 33 target words before the MEG recording session begins, and they are instructed to remember the words so that they can recognize them later, when the words will appear along with new, distractor words. Next, during MEG recordings, the participants hear, one word at a time, three blocks of 43 words each. Each block consists of all 33 target words as well as 10 sets of randomly mixed distractor words. The distractor words differ for each block. Participants are instructed to raise their index finger each time a target word appears, but to not respond each time a distractor word appears. The spoken word stimuli are produced by a native English-speaker with a flat intonation (with a duration of 300–750 ms; M = 450 ms). The recordings of these words are then digitized with a sampling rate of 22,000 Hz and 16-bit resolution and stored on a portable computer that is also used for stimulus presentation. The Visual Word Recognition task is identical to the auditory task, except that the same words are presented visually. Participants first view the same 33 target words and attempt to remember them for the upcoming MEG session. Next, they view three blocks of 43 words each, consisting of all 33 target words as well as 10 distractor words. Each word has a frequency of >20 per million in the corpus of second-grade-level reading materials, according to the norms provided by Zeno, Ivens, Millard, and Duvvuri (1995). The participants are again instructed to raise their index finger each time a target word appears, but to not respond each time a distractor word appears. Each word is presented for 1 sec. The interstimulus interval varies randomly between 3 and 4 sec. The brain activation maps that resulted from aural and written word recognition tasks and that have been validated in the context of the previously cited studies may be summarized as follows. Aural language comprehension and reading are subserved by mechanisms that share many components. Identifying both the similarities and the fine differences between these mechanisms is possible because the same linguistic stimuli can be presented within identical time frames either acoustically or visually to participants, who are instructed to process the stimuli in an identical manner in both cases. The initial component of the cerebral mechanism of both functions (reflected in the early EF components) consists of the engagement of the primary sensory cortex: the floor of the Sylvian fissure bilaterally (in the case of aurally presented words) and the occipital cortex (in the case of written words) within the first 100–150 ms of the presentation of each verbal stimulus. Next, within 150–250 ms, in the case of aural language, the posterior portion of the left superior temporal gyrus (STGp) is predominantly activated, whereas in the case of reading, the left fusiform and lingual gyri (basal temporal cortex) is predominantly activated. These activations are followed by predominant left STGp,
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inferior parietal (i.e., angular and supramarginal gyri), and, particularly during reading, inferior frontal cortex activation (Broca’s area; Breier, Simos, Zouridakis, & Papanicolaou, 1998, 1999). Finally, during both visual and auditory presentation, and in parallel with neocortical activation, there is activation of the hippocampus and of the middle temporal gyrus (MTGp), starting at approximately 250 ms after presentation of the stimulus (predominantly on the left) as shown in Figure 1. The role of STGp in reading has been investigated in a more direct fashion by monitoring the effects of transient interference with normal neurophysiological function in portions of STGp (Simos, Breier, Wheless, et al., 2000). In that study the impact of direct electrocortical stimulation on the ability to read aloud various types of print was examined. This procedure was employed in patients undergoing electrocortical stimulation mapping prior to epilepsy surgery. The results clearly indicated that a key component of the mechanism for reading aloud letter strings that do not possess lexical representations (pseudowords), thus requiring phonological decoding, is the engagement of a distinct portion of STGp. However, when the material to be read consists of pseudowords, activation is restricted to STGp, inferior parietal, and inferior frontal regions, again predominantly in the left hemisphere. It appears, therefore, that at least in (adult) experienced readers, the middle temporal gyrus and the hippocampus may not be a key component of the cerebral mechanism involved in pseudoword reading (Simos, Breier, et al., 2002). This finding is consistent with the view that MTGp and the hippocampus play a crucial role in word recognition (Damasio & Damasio, 1989; Kuperberg et al., 2000; Mummery, Patterson, Hodges, & Price, 1998).
FIGURE 1 Prototypical brain activation profiles, obtained with MSI, in the context of the auditory and visual word recognition tasks from neurologically intact volunteers.
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STUDY 1 Activation profiles have been obtained with MSI, using the auditory word recognition task described above, from 11 children that were normal readers and from 8 children with dyslexia. Profiles were also obtained using the visual word recognition task from 12 children that were normal readers and from 12 children with dyslexia (Simos, Breier, Fletcher, Bergman, et al., 2000). All children in the dyslexia group in this study (and also in Studies 2 and 4) showed severe impairment in phonological decoding skills: They scored under the 20th percentile on the Word Attack subtest of the Woodcock–Johnson Psychoeducational Test Battery (Woodcock & Johnson, 1999), as compared to scores above the 80th percentile for each of the normal readers. In addition, all participants in Studies 1, 2, and 4 had Full Scale IQ scores on the Wechsler Intelligence Scale for Children-III of 85 or above, were right-handed, had English as their primary language, and had no history of hearing deficits, neurological injury or disease, or visual impairments. The main features of these data can be summarized as follows. First, typically achieving readers as well as dyslexic children present indistinguishable activation profiles associated with aural word recognition. Second, the main features of these profiles are, with minor exceptions, basically identical to the corresponding adult profiles summarized in the previous section of this review. Also, reading of the same words results, for typically achieving children, in profiles that are generally similar to those obtained from adult readers (Simos et al., 2001). Subtle profile differences were also observed: As a group, children do not show the consistent hemispheric asymmetries in the degree of activation of basal temporal areas that are present in the adult readers, and may lack the clear temporal distinction in the engagement of basal temporal and temporoparietal areas. Third, in individual children already identified with dyslexia, the brain activation profile during reading deviates from that of typically achieving readers, in that predominant activation is observed in the right temporal and temporoparietal region (i.e., the posterior portion of the superior temporal gyrus, the supramarginal and the angular gyri) instead of the corresponding regions in the left hemisphere. This clear difference between the activation profiles of children who experience serious reading difficulties and those who do not has been observed in essentially every child tested thus far, and it is illustrated in Figures 2, 3, and 4.
STUDY 2 In view of the fact that the word recognition tasks associated with aberrant activation profiles among children with dyslexia involved meaningful word reading, the
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FIGURE 2 Brain activation profiles from 2 representative participants obtained in the context of the auditory (top) and the visual word recognition tasks (bottom).
aberrant feature of these profiles could be due to peculiarities in the ways semantic operations are mediated by the brains of children with dyslexia, rather than to peculiarities in how the brain mediates phonological decoding. Also, the aberrant feature could reflect the fact that the silent word-reading task involved a much greater level of difficulty and required much greater effort on the part of the children with dyslexia. To determine whether the aberrant activation pattern reflected either effort or meaningfulness rather than the process of converting letters to sounds (i.e., phonological decoding), the activation profiles of children with dyslexia (n = 28) and typically achieving readers (n = 12) were recorded during a task that was of
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FIGURE 3 Mean number of activity sources in temporoparietal (upper left) and mesial temporal (upper right) brain regions during the auditory word recognition task in Study 1 from groups of children with and without dyslexia. Lower graph: the relative incidence of brain activation profiles, for each group, featuring a greater amount of activity in the left STGp and left inferior parietal areas as compared to corresponding right hemisphere areas for both groups of children. W/O D = without dyslexia; WD = with dyslexia.
much greater difficulty than the silent word-reading task used before (Simos, Breier, Fletcher, Foorman, et al., 2000). The task involved silent reading of meaningless, yet pronounceable, letter strings (pseudowords). In this Visual Pseudoword Rhyme-Matching task, children viewed four blocks of 25 pairs of pseudowords (e.g., yoat and Wote) and attempted to determine whether the stimuli in each pair rhymed or not. Each pseudoword was shown for 1500 ms and was followed by a 1-sec interval separating the members of a pair. An interstimulus interval, ranging from 1500 to 2300 ms, separated each pair of pseudowords in a randomly determined order. Stimuli were 4 to 5 letters long and were always orthographically dissimilar, to discourage performing comparisons on the basis of orthographic information. The children were instructed to raise their index finger each time two pseudowords rhymed, but to not respond if they did not rhyme. The brain activation profiles obtained in the context of the visual pseudoword rhyme-matching task were very similar to those obtained during the visual word recognition task. In the case of typically achieving readers, they involved sequential activation of the primary and secondary visual areas of the brain
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FIGURE 4 Mean number of activity sources in temporoparietal (upper left), mesial temporal (upper right), and basal temporal brain regions (lower left) during the visual word recognition task in Study 1, from groups of children with and without dyslexia. Also displayed (lower right) for each group is the relative incidence of brain activation profiles featuring (a) greater amount of activity in the left STGp and left inferior parietal areas as compared to corresponding right hemisphere areas, (b) equal amount of activity in left and right hemisphere areas, and (c) greater right over left hemisphere activity found in STGp and inferior parietal areas, in the 2 groups of children. W/O D = without dyslexia; WD = with dyslexia.
(about 100–150 ms following presentation of the word or nonsense letter string to be read), followed by activation of the basal surface of the temporal lobes (but primarily the left), lasting from about 150 to 300 ms. Finally, activation was observed in the STGp, inferior parietal (supramarginal and angular gyri), and inferior frontal regions, predominantly in the left hemisphere. Activation profiles obtained from children with dyslexia were very similar to those from the visual word recognition task, but consistently different from those obtained from the age-matched controls. There was little or no activity in the left STGp and inferior parietal area, and strong activation of the homotopic regions in the right hemisphere (see Figures 5 and 6). Therefore, degree of difficulty does not appear to be responsible for the aberrant activation profile among dyslexic children, and neither does stimulus meaningfulness. The meaningfulness factor, however, appears to account for the activation of the middle temporal gyrus in both groups, as mentioned earlier.
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FIGURE 5 Brain activation profiles from 2 representative participants, obtained in the context of the visual pseudoword rhyme-matching task.
STUDY 3 The studies described thus far involved children who had already been identified as having dyslexia. Children cannot be reliably identified for reading disabilities until Grade 2 (Shaywitz, Escobar, Shaywitz, Fletcher, & Makuch, 1992). In fact, most children with reading problems are not identified until Grade 3 or later. Thus, the samples in Studies 1 and 2 consisted of children 8 years or older. However, little is known regarding the development of the aberrant brain activation profiles found in younger children who are eventually identified with dyslexia. Of particular interest for designing effective reading instruction programs that may be able to prevent the emergence of reading disabilities is to determine the developmental course that leads to the establishment of the aberrant activation profile in older children with severe reading disabilities. The primary goal of Study 3 was to determine whether this profile is already present during the early stages of reading acquisition and whether this profile can be consistently obtained in the context of tasks involving precursors of reading skills, such as the ability to associate sounds with single letters. Eventually, this ongoing longitudinal study should enhance our understanding of how brain activation profiles change as children learn to read. For this project, children were assessed with measures of pre-reading and early reading skills. Those who were identified as “at risk” for reading problems (n = 30) had not, at the end of kindergarten, mastered important concepts
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FIGURE 6 Mean number of activity sources in temporoparietal (upper left), mesial temporal (upper right), and basal temporal brain regions (lower left) during the visual pseudoword rhyme-matching task in Study 2, from groups of children with and without dyslexia. The proportion of children exhibiting left-sided, right-sided, or no hemispheric asymmetry in temporoparietal activation during each task is displayed in the graph at the lower right-hand portion of the figure. In contrast to the visual word recognition task, no participants evidenced bilaterally symmetric activity in this region. W/O D = children without dyslexia; WD = children with dyslexia.
necessary to support early reading acquisition (i.e., knowledge of letter sounds). These children were compared to those who had mastered these concepts and were not at risk for developing reading difficulties (n = 15). Brain activation profiles were constructed from these children, after their kindergarten year, during a Letter–Sound Pronunciation task. During this task, letter stimuli were presented visually to the children. They attempted to pronounce the letter’s sound after it disappeared from the screen. Brain activity was recorded as the visual letter stimuli were presented, rather than as children enunciated the letter sounds, to ensure that the brain activity recorded corresponded to phonological decoding operations and not to the additional cognitive operations that enunciation would entail. As the children are presently in the middle of Grade 1, only baseline MSI data have been collected and summarized (Simos, Fletcher, Foorman, et al., 2002). They will be reevaluated in the summer after Grade 1. The performance of children in the at-risk group on the letter–sound task was sufficiently high to ensure that they were indeed engaging in the task, albeit
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significantly lower than the performance of the not-at-risk group (M percent correct = .69; SD = .24 for the at-risk group, and M percent correct = .91; SD = .06 for the not-at-risk group; p < .0008). We predicted, based on our previous studies of children with reading problems, that children at risk for reading problems would exhibit reduced activity in STGp and inferior parietal areas of the left hemisphere, but increased activity in corresponding areas of the right hemisphere. The results corroborated this prediction by showing that children in the not-at-risk group displayed significantly greater left than right STGp activity, whereas children in the at-risk group displayed significantly greater right than left STGp activity. The groups did not evidence different amounts of brain activity in any other area studied. Figure 7 summarizes the results of these analyses. Finally, we conducted a binomial logistic regression analysis predicting group membership (at-risk, not-at-risk) from the number of intracranial sources in the left and right STGp. These variables correctly classified 77.8% of the participants, χ2(4) = 16.87, p < .001, although only the number of sources in the left STGp was a significant predictor of group membership (p < .01). The number of sources in the right STGp did not significantly predict group membership. MSI-derived brain activation profiles from two representative cases, a child from the at-risk group and a child from the not-at-risk group, are shown in Figure 8. These results indicate that children at risk for reading problems exhibit noticeably different activation profiles than children not at risk for developing reading problems. To our knowledge, this is the first report of such a finding in children who are just beginning the reading acquisition process. Learning letter–sound correspondences is an important component of early reading development. Our data
FIGURE 7 Mean number of activity sources in the left and right superior temporal gyrus (posterior portion) as a function of group. STG = Superior temporal gyrus.
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FIGURE 8 MSI activation profiles from a typical at-risk child (left) and from a child in the not-at-risk group (right) during the letter–sound task. The images are composites of an axial MRI section traversing through the posterior part of the superior temporal gyrus and the inferior frontal gyrus and a coronal MRI section that slices through basal and mesial temporal cortices. Note the abundance of activity in the left STGp in the former case, and the scarcity of such activity in the latter case. Children in the 2 groups are indistinguishable with respect to activity in any other brain area.
clearly demonstrate that children who are able to readily master this skill, which is a predictor of phonological decoding, are significantly more likely to show activation profiles featuring the predominantly left STGp activity that characterizes proficient readers. In contrast, children who experience difficulty in mastering this skill display activation profiles very similar to those of older children who have been identified with dyslexia. As we have found with older children already identified with dyslexia, these at-risk children appear to exhibit more activity in the right STGp during phonological decoding tasks. These results are in perfect agreement with our previous finding that the left STGp is an indispensable component of the brain circuit that is responsible for the function of phonological decoding (Simos, Breier, Wheless, et al., 2000).
STUDY 4 All of the findings described previously simply show a correlation between performance in phonological decoding tasks and an aberrant pattern of activation in
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dyslexic children. To demonstrate that this correlation is not circumstantial and trivial, a further study is currently underway. Eight dyslexic children have thus far been tested using the Visual Pseudoword Rhyme-Matching task before and after a successful reading intervention (Simos, Fletcher, Bergman, Breier, et al., 2002). Intervention was conducted using intensive reading intervention programs that focus on the development of phonological decoding skills and consist of 80 hr of one-to-one instruction. Before enrolling in the intervention program, all six children showed the typical “dyslexia-specific” profile, which features little or no activity in the left STGp and inferior parietal areas and strong activity in the homologous regions in the right hemisphere. In all cases, completion of the program resulted in marked improvement in phonological decoding abilities: Word Attack scores (from the Woodcock–Johnson-III battery; Woodcock & Johnson, 1999) improved from below the 20th percentile into average range. Successful completion of the program was associated with a dramatic increase in left STGp and inferior parietal activation in all cases, ranging in degree from +115% to +2100% (M = +643%). In contrast, the amount of activity in the corresponding regions in the right hemisphere showed a moderate decline ranging in degree from –100% to –40% in 6 children, and a relatively small increase (+50–78%) in the other 2 children (M = –34%). A representative case is displayed in Figure 9. In agreement with the results reported in the previous section, it appears that an increase in left STGp and inferior parietal activity, rather than a reduction in right hemisphere activity, underlies the improvement in basic reading skills induced by reading intervention in children with dyslexia.
DISCUSSION The results of these four studies can be summarized as follows. First, the vast majority of children with serious reading problems show, during engagement in reading tasks, a distinct brain activation profile that is uncommon among children who have never experienced reading difficulties. It remains to be seen if this profile is independent of other conditions, such as attention deficit hyperactivity disorder, that show a high degree of comorbidity with dyslexia. Second, this profile is observed in a variety of tasks that involve phonological decoding, regardless of whether the task involves reading real words or pseudowords. Third, the main features of this profile do not appear to be dependent upon task difficulty, at least within the range of tasks we have examined thus far. Fourth, it appears that neurophysiological activity in left temporoparietal regions as revealed by MSI reflects the engagement of brain operations that are indispensable components of the brain mechanism for reading. If these operations are not engaged properly, as in the case of dyslexia, reading performance and the capacity to acquire reading skills is severely compromised. There are strong indications that these operations
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FIGURE 9 Activation maps from a 9-year-old child in Study 4, who was diagnosed as dyslexic, before and after instruction using the Phonographix program. As part of that study, 2 children received intervention using the Lindamood Phonemic Sequencing program. The Phonographix program was used with 6 children. Activation maps were obtained in the context of the pseudoword rhyme-matching task. All 8 children showed dramatic improvement in their phonological decoding skills after 8 weeks of enrollment in each program. Also, in every case, a dramatic increase in the activation of left temporoparietal regions (predominantly the left STGp) was observed.
are predominantly involved in the phonological processing of print. The extent to which they are also involved in the phonological processing of spoken language is still under investigation, although preliminary evidence suggests that they may indeed be involved (Simos, Breier, Wheless, et al., 2000). Systematic reading intervention that promotes the development of phonological awareness and decoding skills can drastically alter the aberrant activation profile found in children with dyslexia. It remains to be determined if there is an optimal time to effect such changes through proper instruction. We are in the process of addressing this issue in the context of two ongoing studies, which involve intervention with children at different grades (ranging from kindergarten to high school). These children are
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tested with MSI before and after completion of the instruction program. The results have important implications for views of neural plasticity as well as views of how environmental factors impact the brain. For example, it is becoming increasingly apparent that the brain becomes specialized for reading through specific environmental experiences (e.g., instruction). Although it is common to describe the children and adults who are poor readers as “disabled,” the preliminary data suggesting that the brain activation profiles associated with poor reading are malleable and change with instruction may indicate that instruction plays a significant role in the development of neural systems that are specialized for reading. Such a view is entirely consistent with current theories of reading development, which indicate that reading proficiency is scaffolded upon oral language proficiency as a secondary consequence of the development of oral language capacity in the human species (Liberman, 1996). It is also consistent with views of reading as a trait that is normally and quantitatively distributed in the population (Shaywitz et al., 1992). Thus, reading difficulties most likely represent variations in normal development, as opposed to a specific pathological condition. Moreover, reading difficulties in many individuals can be overcome by intervention that is sufficiently intense. Our preliminary evidence suggests that when successful intervention occurs, neural systems are altered, and that these neural systems are much more plastic than was believed in the past. These studies highlight the value of noninvasive functional imaging, especially MSI, as well as the importance of linking neuroscience and education. The integration of different domains of inquiry in areas like reading offers great promise for expanding researchers’ understanding of how children can learn to read or why they struggle to acquire this complex skill.
ACKNOWLEDGMENTS This work was partly supported by National Science Foundation Grant REC-9979968 and Grant HD 38346 to Andrew C. Papanicolaou.
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