Behavioural Brain Research 209 (2010) 179–182
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Behavioural Brain Research
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Short communication
Brain plasticity in developmental dyslexia after phonological treatment:
A beta EEG band study
Barbara Penolazzi a,b,1 , Chiara Spironelli b,2 , Claudio Vio c , Alessandro Angrilli b,d,∗
a
Department of Biomedical Sciences, University “G. d’Annunzio” of Chieti, Blocco A - Via Dei Vestini I-66013 Chieti, Italy
Department of General Psychology, University of Padova, Via Venezia 8, 35131 Padova, Italy
c
Children’s Neuropsychiatric Medical Facility of San Donà di Piave, Venice, Italy
d
CNR Institute of Neuroscience, Padova, Italy
b
a r t i c l e
i n f o
Article history:
Received 15 December 2009
Received in revised form 18 January 2010
Accepted 20 January 2010
Available online 28 January 2010
Keywords:
Dyslexia
Training
Beta band
EEG
Phonology
Semantics
Lateralization
Cortical reorganization
a b s t r a c t
Linguistic EEG hemispheric reorganization was investigated in 14 dyslexic children after a 6-month
phonological training (10 min/day through PC software). Error rates from three linguistic tasks significantly decreased and reading speed improved after the training. A significant positive correlation
(r12 = 0.536) was found at posterior sites for the phonological task only, showing that those children who
had the greatest reading speed enhancement showed the largest left posterior EEG beta power increase.
© 2010 Elsevier B.V. All rights reserved.
Developmental Dyslexia (DD) is a phenotypically heterogeneous clinic syndrome consisting in a pronounced and persistent
difficulty in reading acquisition, despite normal intelligence,
sensory acuity, motivation, and educational opportunities [21].
Although experimental evidence confirmed its genetic aetiology
[3], individuals suffering from this disorder differ in their individual
profiles for many characteristics [4,22] also depending on environmental factors. Among these, the intrinsic structure of the language
to which the individual is exposed is decisive for the risk of developing the disorder and for the extent of the disability. Indeed, DD
occurrence is much higher in deep orthographies (i.e., English) than
in shallow ones (i.e., Italian), as the former involve more irregular
grapheme–phoneme correspondences which make word decoding mechanism rather difficult [8]. DD is marked by incorrect and
non-fluent written language decoding. In irregular orthographies,
reading accuracy remains the greatest problem. Conversely, in regular orthographies, it can improve until it reaches a ceiling level
∗ Corresponding author at: Department of General Psychology, Via Venezia 8,
35131 Padova, Italy. Tel.: +39 049 8276692; fax: +39 049 8276600.
E-mail address: alessandro.angrilli@unipd.it (A. Angrilli).
1
Tel.: +39 0871 3554206; fax: +39 0871 3554163/049 8276600.
2
Tel.: +39 049 8276635/6914; fax: +39 049 8276600.
0166-4328/$ – see front matter © 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.bbr.2010.01.029
[19], whereas reading speed in dyslexics follows a linear trend
across years with an incremental speed approximately half-sized
with respect to normal condition (i.e., in 7–13 year-old Italian children the mean increase per year is 0.3 vs. 0.5 syllable/s for impairedvs. normal-readers [19]). Since DD is often characterized by multiple interacting altered mechanisms, many theories on its nature
still coexist, nevertheless, the strongest evidence converges in identifying the phonological deficit (i.e., a deficit in the representation
and/or manipulation of the smallest speech sounds, the phonemes)
as the core dysfunction of reading disabilities [9–11,13,14]. A number of functional brain imaging studies has localized this altered
phonological processing in a large cortical network distributed
mainly in the left hemisphere, and including the perisylvian and
temporo-parieto-occipital areas [13]. In particular, past studies
on DD pointed to an impairment of left posterior brain systems
involved in the cross-modal integration of auditory and visual information which include the connections between occipitotemporal
and parietotempotal circuits [13]. When performing phonological
tasks, these posterior systems often exhibit reduced or absent activation in impaired compared with normal-readers. Similarly, also
dyslexics’ left frontal system often revealed an altered languagerelated activity, likely secondary to the disruption of posterior
linguistic networks which are selectively activated in the early
phases of word reading [9,10,13,14]. An increasing body of data sug-
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gested that the severity of reading difficulties can be diminished by
different intensive trainings, aimed at improving reading speed and
accuracy by stimulating cortical plastic reorganization [13,17,18].
Specifically, during developmental age, training-induced reading
enhancement has been associated with increased activation of both
left temporo-parietal and inferior frontal areas—usually involved
in the phonological processing—and of several right hemisphere
areas, which, after the achievement of automatic normal reading,
are no more necessary for graphemic decoding [17]. However, most
of research focussed on English orthographies and therefore on
reading accuracy, whereas the development and improvement of
fluent reading and its underlying neural systems still need to be
clarified [13]. In the present study we aimed at investigating the
improvement of reading fluency after a 6-month linguistic intervention based on phonological awareness, by using beta power
band as a neurophysiological marker of cortical cognitive activation [15]. Evidence of dysfunctional beta band alterations in DD
has been recently demonstrated in several studies [5,7], and, using
the same well-validated linguistic paradigm of the present study
a sample of impaired-readers showed, differently from controls, a
dysfunctional anterior right lateralization in all linguistic tasks, and
left posterior lateralization during both phonological and orthographic tasks [14]. The altered recruitment of left posterior regions,
specialized in the encoding and integration of the phonological
components of words, was interpreted as due to dysfunctional
mechanisms of DD. However, without data on training-induced
plastic changes, we could not resolve if dyslexics’ beta activity patterns reflected a primary impairment or a cortical reorganization
aimed at compensating their deficit. With the present research we
specifically addressed this issue. In addition, to prove the efficacy
of phonological intervention, we expected to find, together with
reading speed improvement, a hemispheric reorganization of beta
activity in posterior sites and selectively to the phonological task.
Specifically, according to Bakker’s theory on dyslexia as depending
on an imbalance in the contribution of hemispheres to reading [1],
we expected the EEG beta activity reorganization in the left hemisphere to be associated with greater reading speed enhancement.
After parents’ informed consent signature according to the Declaration of Helsinki, 14 native Italian-speaking children (11 boys;
mean age: 118.6 months ± 21.6) participated in the study. Children were recruited from the Children’s Neuropsychiatric Medical
Facility of San Dona’ di Piave: they all had a diagnosis of phonological dyslexia, assessed by means of the standard tests for reading
evaluation [2]. Additional inclusion criteria were normal IQ [20]
and no attention deficit disorder comorbidity. They had an average
handedness of 92.9%, and normal or corrected-to normal vision.
Dyslexics participated in the experimental session before and after
a 6-months phonological training, occurring at home, 5 times a
week, for 10 min/day. The training was carried out by means of
a standardized rehabilitative software, the WinABC program (5.0
version) based on the improvement of phonological awareness
through timed passage reading (additional information is available on-line at: http://www.impararegiocando.it/WinABC50.htm).
In each experimental session carried out before and after the training phase, children were asked to judge (by providing a response
with the left hand) visually presented word pairs on the basis
of different linguistic criteria (each corresponding to an experimental task): the type similarity in the control orthographic task,
the rhyme relationship in the phonological task and the semantic
classification in the semantic task. The same set of 80 words was
used as first stimulus of each pair throughout the tasks, to exclude
interfering effects related to word uncontrolled features. Stimulus
pairs were presented word by word, the first word (W1) lasting
1500 ms, the second (W2) until the response (but no longer than
5000 ms), with a 2000 ms interstimulus interval (ISI), and a 3000 ms
intertrial interval. In both pre- and post-training sessions, passage
reading speed (measured in syllable/s) was assessed and correct
response times (RTs), error rates (ERs) and EEG data were collected during task execution. One-tailed t-test comparisons were
used to contrast the pre- and post-training reading speed measures, whereas for both RTs and ERs an analysis of variance (ANOVA)
was performed, with Session (pre-training vs. post-training) and
Task (orthographic vs. phonological vs. semantic) as within group
factors. Newman-Keuls post hoc tests further specified significant
effects and when necessary the Greenhouse–Geisser correction was
applied (and corrected probabilities were reported). EEG was continuously recorded in DC mode from 38 sites: 31 placed according
to the International 10–20 system, and the remaining positioned
around each eye (Io1, Io2, F9, F10), on the mastoids (M1, M2) and
on the nasion. Impedance was kept below 5 k and EEG was amplified with a SynAmp system (NeuroScan Labs, Sterling, USA), using
DC-100 Hz bandpass filter, and sampling rate of 500 Hz. Analyses,
performed through Brain Vision Analyzer (Brain Products GmbH,
Germany), started with eye movement and blink corrections, by
applying the Independent Component Analysis correction method.
Data were segmented with respect to W1 onset, then artifact rejection was performed (maximum increment voltage step: 150 V;
minimum/maximum amplitude: ±75 V), leading to a percentage of rejected trials (34.75%) not statistically different between
sessions. Each segment was divided into four 1024-ms time intervals representing different processing phases required by the task:
1024 ms before W1 onset (baseline interval); 1024 ms after W1
onset (W1 interval); 1500 ms to 2524 ms after W1 onset (initial
ISI: iISI); and 2476 ms to 3500 ms after W1 onset (terminal ISI:
tISI). Whereas W1 interval was clearly related to word reading,
iISI mainly referred to stimulus encoding in the verbal working
memory, and tISI concerned the late processing of W1 features
to be compared with those of W2 [12]. The FFT was performed
using a Hamming window and including 512 samples (0.98 Hz
resolution). Epochs were averaged within each task for both pretraining and post-training sessions. Beta band power (∼13–20 Hz)
was normalized for all locations by computing its percentage in
the 0–100 Hz spectral range, in order to measure its relative contribution with respect to the whole spectrum. Electrodes were
clustered into 4 regions of interest: anterior left (Fp1, F7, F3, He1,
Ve1), anterior right (Fp2, F8, F4, He2, Ve2), posterior left (T7, P3, P7,
O1, M1), and posterior right (T8, P4, P8, O2, M2). In order to test
whether there was a hemispheric asymmetry depending on the
training, we performed a preliminary ANOVA with Session (prevs. post-training), Task (orthographic vs. phonological vs. semantic), Caudality (anterior vs. posterior electrodes) and Lateralization
(left vs. right electrodes) as within group factors. Then, to evaluate the relative contribution of one hemisphere with respect to
the other, at both anterior and posterior clusters, we computed
the hemispheric lateralization index as ratio between the difference of left and right clusters and the sum of left and right clusters
(i.e., left − right/left + right). This universally accepted index offers
the possibility of normalizing a cluster with respect to the activity of both left and right sites, and its value ranges from +1 to −1,
corresponding to 100% left or right lateralization, respectively. In
order to test our hypothesis, for each task and interval, Pearson’s
correlation analyses were performed by including the differences
between the post- and the pre-training values for the two correlated variables: the reading speed measure and the beta laterality
index (computed separately for anterior and posterior locations).
Thus, a positive correlation indicates that those children who had
greater reading skills improvement, had also an increase of left beta
activity in the post-training session. In correlational analyses it is
advised that outliers (one in our sample, detected because the corresponding value was more than 2.5 standard deviations below the
mean reading improvement of the sample) are excluded to avoid
the influence of extreme values, but in small samples this is rarely
B. Penolazzi et al. / Behavioural Brain Research 209 (2010) 179–182
181
Fig. 1. Positive Pearson’s correlations between reading speed improvement and beta band laterality index in posterior sites during the Phonological task for (A) iISI and (B)
tISI time windows. Confidence intervals and regression lines are computed by including the outlier (black circles).
accomplished, for this reason we decided to present correlations
with and without the outlier [16].
Analysis revealed that linguistic training was effective, since
t-test comparisons showed a significant improvement of reading speed (t(13) = −5.48, p < 0.001), with a mean increase of 0.37
syllable/s (pre-training:1.18 ± 0.56 SD; post-training: 1.55 ± 0.59
SD). Concerning RTs, ANOVA revealed a significant effect of Task
(F(2,26) = 25.68, p < 0.001), RTs being slower for the semantic with
respect to both phonological (p < 0.01) and orthographic tasks
(p < 0.001), and for the phonological compared with the orthographic one (p < 0.001). Analysis of Error Rates (ERs) revealed a
similar significant main effect of Task (F(2,26) = 7.57, p < 0.01), with
the semantic task inducing higher percentages of errors (24.87%)
compared with phonological (16.61%, p < 0.01) and orthographic
(15.27%, p < 0.01) tasks. Interestingly, the factor Session was also
significant (F(1,13) = 5.12, p < 0.05), ERs decreased in post- (17.2%)
compared with pre-training session (20.63%).
As regard to EEG data, ANOVA revealed a significant interaction
between the factors Training, Caudality and Laterality (F1,13 = 8.2,
p < 0.05). Post hoc tests showed in the pre-training session dyslexic
children having bilateral distribution of beta band activity over
anterior regions, whereas over posterior areas they had a higher
level of beta in the right than in the left sites (p < 0.05). Instead, in
the post-training session, beta level increased in the right anterior sites with respect to the left ones (p < 0.05), whereas, over
posterior areas, beta percentage increased significantly over left
hemisphere with respect to the pre-training session (p < 0.01).
By moving onto correlational analyses, positive correlations were
found between reading speed and beta laterality index (computed
as post- minus pre-training changes) in posterior areas, exclusively
for the phonological task. In detail, including the outlier (n = 14),
positive correlations were found at posterior sites in both iISI
(r12 = 0.615, p < 0.05, Fig. 1A) and tISI (r12 = 0.536, p < 0.05, Fig. 1B).
By discarding the outlier (n = 13), the correlation in iISI did not reach
the significance (r11 = 0.273, p = n.s.), but that in posterior areas
during tISI remained significant (r11 = 0.584, p < 0.05). Hence, even
without the outlier, correlations revealed that reading improvement following the linguistic training was significantly associated
with greater left beta increments in posterior sites only in the last
interval of the phonological task. The correlations for the semantic
and orthographic tasks were all low and not significant (r12 ≤ 0.329
and r12 ≤ 0.383, respectively).1
1
In order to avoid the problem of biased p values, due to the fact that the actual
underlying distribution of our small sample might depart from normality, we also
performed the not-parametrical Spearman’s rank correlational analyses. Results of
An important result of the present research was the proven
efficacy of the linguistic training aimed at improving the phonological awareness. Indeed, in addition to a post-training overall
decrease of ERs during task execution, the passage reading speed
of our sample showed a 6-months mean increase of 0.37 syllable/s, corresponding to an yearly improvement of 0.74 syllable/s,
which, compared with normative data from Italian children [19], is
higher than normal-readers’ mean annual spontaneous improvement (i.e., 0.5 syllable/s) and more than twice with respect to
impaired-readers’ mean annual improvement (i.e., 0.3 syllable/s).
This demonstrates that reading amelioration cannot be merely
ascribed to maturational factors. In particular, unlike other functional studies which correlated the neural reorganization with
variables indirectly associated to reading speed (like oral language
skills [17]), we found a positive correlation which directly links
the training-induced hemispheric reorganization and the reading
performance. This result was mainly due to a significant increase
of beta percentage of left posterior sites after the training rather
than to a right posterior contribution (or a combination of left
and right sites contribution) as further specified by ANOVA. Since
the phonological training was directly associated to the fluency
improvement, and, at the same time, beta plastic changes were
related to this reading enhancement only for the phonological task
(i.e., improvements did not correlate with beta lateralization in all
tasks, but only in the phonological one, during the last interval
tISI which required the typical phonemic manipulation needed for
rhyming judgement), the present experiment provides further support to the key role of the phonological awareness in determining
a fluent reading. Results point on the effectiveness of phonological interventions in DD, but also on the validity of the phonological
deficit theory in accounting this learning disability [11]. In addition,
unlike a past electrophysiological study on DD treatment which
did not investigate the reorganized linguistic regions [6], we succeeded in finding beta plastic reorganization specifically in left
posterior areas. The present results further proved that traininginduced reading automaticity involves neural systems close to
those recruited in normal-readers, and therefore, pointed out normalizing, rather than compensatory, effects of remediation [13]. At
the same time, we can now re-interpret past results, achieved with
the same paradigm on a different sample of dyslexic children, which
Spearman’s rank correlations nearly replicated Pearson’s results. Indeed, positive
correlations between reading improvement and beta laterality index were found, in
posterior sites, exclusively for the phonological task, in both W1 (r12 = 0.55, p < 0.05,
Fig. 1A) and tISI (r12 = 0.63, p < 0.05). Therefore, this further analysis confirmed the
strong relationship between reading improvement and post-training increase of
beta band over posterior left areas during phonological processing.
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B. Penolazzi et al. / Behavioural Brain Research 209 (2010) 179–182
showed an EEG beta left posterior lateralization during word decoding [14]. In fact, with the present experiment we demonstrated
that this EEG effect is functionally correlated with faster reading
speed, therefore, it marks behavioural ameliorations, rather than a
fundamental deficit of DD.
In conclusion, beta EEG band proved to represent a valid
tool for measuring language lateralization and its reorganization in children affected by reading impairment. Left posterior
regions, considered important for the early stages of word reading
(especially for grapheme–phoneme conversion) were functionally
activated with respect to right homologous sites in children who
underwent an effective phonological treatment, which was followed by a substantial reading speed improvement. The adopted
training is especially suited for the treatment of dyslexic children
as it requires only 10 min per day and can be administered at home
through a PC, without a continuous and engaging intervention of
a speech therapist. Such a daily short-lasting training is especially
advised as, following their frustrating reading difficulties, dyslexic
children often refuse intensive logopedic trainings.
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
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