The enigma of dyslexic musicians

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The enigma of dyslexic musicians

Atalia H. Weiss a,d,n, Roni Y. Granot d, Merav Ahissar b,c

a Institute for Cognitive Science, Hebrew University, Mt. Scopus, Jerusalem 91905, Israelb Department of Psychology, Hebrew University, Mt. Scopus, Jerusalem 91905, Israelc Interdisciplinary Center for Neural Computation (ICNC), Hebrew University, Mt. Scopus, Jerusalem 91905, Israeld Department of Musicology, Hebrew University, Mt. Scopus, Jerusalem 91905, Israel

a r t i c l e i n f o

Article history:Received 7 July 2013Received in revised form14 November 2013Accepted 10 December 2013Available online 19 December 2013

Keywords:DyslexiaFrequency discriminationMusical trainingWorking memoryAnchoringAuditory perceptionPerceptual learning

a b s t r a c t

Musicians are known to have exceptional sensitivity to sounds, whereas poor phonological representa-tions (or access to these representations) are considered a main characteristic of dyslexic individuals.Though these two characteristics refer to different abilities that are related to non-verbal and verbal skillsrespectively, the recent literature suggests that they are tightly related. However, there are informalreports of dyslexic musicians. To better understand this enigma, two groups of musicians were recruited,with and without a history of reading difficulties. The pattern of reading difficulties found amongmusicians was similar to that reported for non-musician dyslexics, though its magnitude was less severe.In contrast to non-musician dyslexics, their performance in pitch and interval discrimination, synchro-nous tapping and speech perception tasks, did not differ from the performance of their musician peers,and was superior to that of the general population. However, the auditory working memory scores ofdyslexic musicians were consistently poor, including memory for rhythm, melody and speech sounds.Moreover, these abilities were inter-correlated, and highly correlated with their reading accuracy. Theseresults point to a discrepancy between their perceptual and working memory skills rather than betweensensitivity to speech and non-speech sounds. The results further suggest that in spite of intensivemusical training, auditory working memory remains a bottleneck to the reading accuracy of dyslexicmusicians.

& 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Developmental dyslexia is defined as a specific deficit in read-ing acquisition that cannot be accounted for by low IQ, pooreducational opportunities, or an obvious sensory or neurologicaldamage (World Health Organization, 2008). There is a wideconsensus that dyslexia is a neurological disorder with a geneticorigin. The most influential account for reading difficulties is thephonological hypothesis which suggests that dyslexia is character-ized by deficits related to phonological representations or access tothese representations. These deficits pose a bottleneck to efficientlearning of grapheme to phoneme correspondences, which are thebasis of alphabetical writing systems (Shaywitz, Mody, & Shaywitz,2006; Snowling, 2000; Wehner, Ahlfors, & Mody, 2007). Althoughthis hypothesis is influential (see Ramus, Marshall, Rosen, & Lely,2013, for a multidimensional account), other theories eitherchallenge it (e.g. “The anchoring deficit hypothesis” (Ahissar,Lubin, Putter-Katz, & Banai, 2006; Ahissar, 2007)), or assert that

it only addresses some aspects of a broader deficit, and perhapsnot the basic deficit. For example, several researchers claimed ageneral deficit in processing rapid sequences of stimuli, both in theauditory (Tallal, 1980) and in the visual modalities (“The magnocel-lular theory”, Stein, 2001). Others suggested a general deficit in theacquisition of automaticity (cerebellar or procedural deficit, Nicolson,Fawcett, & Dean, 1995, 2001; Nicolson, Fawcett, Brookes, & Needle,2010; Lum, Ullman, & Conti-Ramsden, 2013), or a sluggish attentioalsystem (Hari & Renvall, 2001; Lallier et al., 2009). Given that readingis a challenging visual task, other researchers focused on visualattentional skills (Lacroix et al., 2005; Valdois, Bosse, & Tainturier,2004; Vidyasagar & Pammer, 2010).

A key tenet of the phonological deficit hypothesis is that itassumes a domain specific impairment. It is specific even withrespect to the auditory modality, where it claims that dyslexics0

deficits relate only to speech components. However, a series ofstudies reported broader auditory deficits. In a pioneering study,Tallal and colleagues found that dyslexics have a deficit inidentifying fast, briefly presented auditory stimuli (Tallal &Piercy, 1974). A series of subsequent studies documented impair-ments in a range of simple perceptual tasks, including tasks thatdid not challenge the rate of dyslexics0 identification, but ratherthe accuracy of their auditory discrimination in spectral (Ahissar

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0028-3932/$ - see front matter & 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.neuropsychologia.2013.12.009

n Corresponding author at: Institute for Cognitive Science, Hebrew University,Mt. Scopus, Jerusalem 91905, Israel. Tel.: þ972 55 23418957.

E-mail address: [email protected] (A.H. Weiss).

Neuropsychologia 54 (2014) 28–40

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et al., 2006; Ahissar, Protopapas, Reid, & Merzenich, 2000; Amitay,Ahissar, & Nelken, 2002; Baldeweg, Richardson, Watkins, Foale, &Gruzelier, 1999; France et al., 2002; Oganian & Ahissar, 2012;Santos, Joly-Pottuz, Moreno, Habib, & Besson, 2007) and temporal(Corriveau, Pasquini, & Goswami, 2007; Goswami et al., 2002;Huss, Verney, Fosker, Mead, & Goswami, 2011; Vandermostenet al., 2010) dimensions. Other studies pointed to sensory-motordifficulties, particularly when temporal accuracy was required, asin the case of synchronized tapping (e.g. Thomson, Fryer, Maltby, &Goswami, 2006; Wolff, 2002). Importantly, the sensitivity ofdyslexics to non-speech sounds was found to be correlated withtheir reading proficiency as well as with their verbal memoryscores (Banai & Ahissar, 2004, 2009). Additional studies documen-ted impaired performance among dyslexics when hearing speechin noise (Chandrasekaran, Hornickel, Skoe, Nicol, & Kraus, 2009;Ziegler, Pech-Georgel, George, & Lorenzi, 2009). Taken together,these studies suggest that dyslexia is characterized by a broaderauditory deficit, and more specifically, dyslexics0 difficulties arerelated to mechanisms that are common to speech and non-speech stimuli. This conjecture has been further supported byrecent studies, which found that activity in auditory areas,including auditory brainstem (Hornickel & Kraus, 2013), auditorythalamus (Díaz, Hintz, Kiebel, & von Kriegstein, 2012), and theauditory cortex (Lehongre, Ramus, Villiermet, Schwartz, & Giraud,2011), is impaired in dyslexia.

Additional support for the idea that general auditory skills areassociated with linguistic skills comes from many studies amongchildren at various ages. Some studies show that cortical responsesto speech and non-speech stimuli already at birth are significantpredictors of later lingusitc and reading abilities (Choudhury &Benasich, 2011; Leppänen & Hämäläinen, 2010; Molfese, 2000).Other studies show that musical skills at pre-reading stagespredict subsequent phonological and reading skills (Anvari,Trainor, Woodside, & Levy, 2002; Bolduc & Montésinos-Gelet,2005; Degé & Schwarzer, 2011; Moritz, Yampolsky, Papadelis,Thomson, & Wolf, 2012). Indeed, among young readers (firstgrades of school), auditory and reading related skills are correlated(Forgeard, Schlaug, & Norton, 2008; Grube, Kumar, Cooper, Turton,& Griffiths, 2012; Loui, Kroog, Zuk, Winner, & Schlaug, 2011),particularly among those who had no musical training (Banai &Ahissar, 2013; Corrigall & Trainor, 2011; Forgeard, Winner, Norton,& Schlaug, 2008; Tsang & Conrad, 2011). In a complementarymanner, ‘tone deaf’ individuals who have difficulty in auditoryfrequency discrmination, have significant deficits in phonemicawareness (Jones, Lucker, Zalewski, Brewer, & Drayna, 2009).

Overall, these findings suggest that an individual is either sensitiveto both verbal sounds and non-verbal sounds, or is insensitive to both.Pitch and duration form the basic auditory dimensions that underliethe melodic and rhythmic patterns of musical tunes. Not surprisingly,musicians have exceptionally high sensitivity to pitch (Kishon-Rabin &Amir, 2001; Micheyl, Delhommeau, Perrot, & Oxenham, 2006;Schellenberg & Moreno, 2009) and duration of non-verbal stimuli(Banai, Fisher, & Ganot, 2012; Montagni & Peru, 2012; Rammsayer,Buttkus, & Altenmueller, 2012; Rammsayer & Altenmuller, 2006).However, both pitch and duration are also linguistically relevant, bothfor phonological identifications and for extracting prosodic informa-tion (e.g. Astésano, Besson, & Alter, 2004; Böcker, Bastiaansen,Vroomen, Brunia, & Gelder, 1999; Eckstein & Friederici, 2005).Musicians are expert in pitch processing in linguistic contexts, e.g.when differentiating between syllables (Chobert, Marie, François,Schön, & Besson, 2011; Kühnis, Elmer, Meyer, & Jäncke, 2013; Ott,Langer, Oechslin, Meyer, & Jäncke, 2011; Sadakata & Sekiyama, 2011)or words (Besson, Schön, Moreno, Santos, & Magne, 2007; Bidelman,Hutka, & Moreno, 2013; Deguchi et al., 2012; Wong, Skoe, Russo, Dees,& Kraus, 2007). Musicians are also expert in duration processingin linguistic contexts, e.g. identifying metrically congruous or

incongruous syllables or words (Chobert, Clément, Jean-Luc, &Mireille, 2012; Marie, Magne, & Besson, 2011). In addition, musiciansare more sensitive to emotions conveyed by speech prosody(Thompson, Schellenberg, & Husain, 2004).

In line with the reported behavioral findings, musicians0 brainsshow differences compared to non-musicians0, both structurally (e.g.Herdener et al., 2010; Imfeld, Oechslin, Meyer, Loenneker, & Jancke,2009; Oechslin, Imfeld, Loenneker, Meyer, & Jäncke, 2009; Schneider,Scherg, & Dosch, 2002; Steele, Bailey, Zatorre, & Penhune, 2013), andfunctionally, at the cortical level (e.g. Fujioka, Trainor, Ross, Kakigi, &Pantev, 2005; Kuchenbuch, Paraskevopoulos, Herholz, & Pantev, 2012;Seppänen, Hämäläinen, Pesonen, & Tervaniemi, 2012; Trainor, Shahin,& Roberts, 2009), and at sub-cortical levels (e.g. Bidelman, Krishnan, &Gandour, 2011; Musacchia, Sams, Skoe, & Kraus, 2007; Parbery-Clark,Strait, & Kraus, 2011; Strait, Kraus, Parbery-Clark, & Ashley, 2010).These changes probably reflect the combined contribution of aninitially elevated sensitivity and prolonged musical training (Baeck,2002; Hyde et al., 2009; Schlaug et al., 2009).

Taken together, the pattern of musicians0 auditory skills andtheir elevated brain responses to auditory stimuli look like theopposite of that reported for dyslexic individuals. Thus, one wouldnot expect to find individuals who are both musicians anddyslexics. Yet some musicians including very famous ones (e.g.John Lennon and Nigel Kennedy, http://www.dyslexia.com/famous.htm), have claimed that they were dyslexic.

One possible solution to this seeming inconsistency is that thesensitivity of dyslexic musicians to both speech and non-speechsounds is indeed enhanced, as expected for musicians, and theirreading difficulty stems from a non-auditory or phonologicaldeficit (e.g. visual attention; Franceschini, Gori, Ruffino, Pedrolli,& Facoetti, 2012; Gabrieli & Norton, 2012; Zorzi et al., 2012).Alternatively, dyslexic musicians may have excellent sensitivity tonon-speech sounds, but poor sensitivity to speech sounds. Such aprofile would challenge the claim that there are common mechan-isms for processing speech and non-speech sounds (Kraus &Chandrasekaran, 2010; Salamé & Baddeley, 1989; Schendel &Palmer, 2007; Williamson, Baddeley, & Hitch, 2010). The thirdalternative is that dyslexic musicians exhibit the typical dyslexicprofile but do not manifest the typical musicians0 profile. Namely,their difficulties may include non-verbal sounds, either at theperceptual or at the working memory processing stage, or both.

The current study was aimed to resolve this enigma, by assessingthe reading, memory and auditory skills of self-reported musiciandyslexics. We recruited professional musicians from the MusicAcademy of the Hebrew University of Jerusalem who reporteddifficulties in reading (including, but not specific to, reading musicalnotes) throughout their school years, and still have reading difficul-ties, as measured in the lab. We composed their control group fromtheir musician peers with no reading difficulties, who were matchedfor age, musical education (years and self-reported amounts ofpractice) and reasoning skills. In order to further assess the severityof their reading and phonological deficits, we compared theirperformance to that of their non-musician peers matched for age,general education and reasoning abilities (who participated in anearlier study; Oganian & Ahissar, 2012).

We found that most of the musicians who reported havingreading difficulties were indeed slow and/or inaccurate readerswith poor phonological skills compared with their musician peers.Their decoding and phonological skills were well below thoseof non-musician controls, though, in average, they were lessimpaired than those of non-musician dyslexics.

We systematically characterized musicians0 psychoacoustic skillswith simple tones and with verbal stimuli. We found that psychoa-coustic thresholds and sensory-motor accuracy of dyslexic musicianswere similar to those of their non-dyslexic musician peers. Namely,they were superior to those of the general population.

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We further assessed working memory skills, since several studiessuggested that poor working memory is a core deficit in dyslexia(Baddeley, 2003; Gathercole, Alloway, Willis, & Adams, 2006; Kibby,2009), whereas studies of musicians reported enhanced verbalworking memory skills (e.g. Chan, Ho, & Cheung, 1998; Ho,Cheung, & Chan, 2003; Jakobson, Lewycky, Kilgour, & Stoesz, 2011).Importantly, we studied both verbal and non-verbal working mem-ory. Though verbal working memory was more intensively studied,studies that assessed non-verbal working memory documentedsubstantial difficulties, whose extent was correlated with the extentof their reading inaccuracy (e.g. Ahissar et al., 2006; Ahissar, 2007;Banai & Ahissar, 2006). We found that verbal, melodic and rhythmicworking memory skills of dyslexic musicians were all significantlypoorer than those of their musician peers.

We conclude that rather than showing a discrepancy betweenenhanced sensitivity to non-speech sounds and reduced sensitiv-ity to speech sounds, dyslexic musicians show a discrepancybetween perceptual skills and working memory skills. Theirreduced working memory abilities were correlated with theirreading accuracy, suggesting that working memory poses a bottle-neck to their performance.

2. Methods

2.1. Cognitive and phonological tests

1. General cognitive abilities were assessed by 2 subtests from the Hebrew versionof the Wechsler Adult Intelligence Scale (WAIS-III): Block Design and Digit Span(Wechsler, 1997). The Block Design task measures spatial reasoning abilities.The Digit span test measures verbal working memory and made up of twoparts: Digit forward – a series of orally presented digits that must be repeatedin their order of presentation, and Digit Backward – a series of orally presenteddigits that must be repeated in reverse order. In both conditions the length ofthe sequence of digits is gradually increased.

2. Phonological awareness was assessed by a Spoonerism task, in which pairs ofwords (20 pairs in total) are presented and the participants are asked to swap theinitial phonemes of the two words (Ben-Yehudah & Ahissar, 2004; Ben-Yehudah,Sackett, Malchi-Ginzberg, & Ahissar, 2001). Both accuracy and rate were scored.

3. Phonological decoding was assessed by reading single real words and pseudo-words, presented with diacritics, in separate lists of 24 words each. We shouldnote the diacritics make Hebrew orthography transparent, but are typicallyused only during the initial stages of reading acquisition. The lists of real wordsand pseudo-words were standard lists (Deutsch & Bentin, 1996). Both accuracyand rate were scored for each of the tests.

4. Reading in context was assessed by oral reading of a 4-paragraph academic leveltext in Hebrew (Ben-Yehudah et al., 2001). In order to prime text comprehen-sion, participants were told in advance that they would be asked a simplecontent question at the end. Most participants made no mistakes; thereforeonly rate scores are reported.

5. Visual word recognition was assessed by choosing the correctly spelled word ina pair of words composed of a real word and a pseudo-homophone. The listcontained 24 word pairs (Ben-Yehudah et al., 2001). Most participants made nomistakes; therefore only rate scores are reported.

2.2. Perceptual and sensory-motor tasks

2.2.1. Auditory frequency discriminationPerceptual thresholds for auditory 2-tone frequency discrimination were measured

with a pure tone of 1000 Hz as the first tone in each pair (the second tone was eitherhigher or lower) to minimize working memory load (“Reference 1st” protocol (Nahum,Daikhin, Lubin, Cohen, & Ahissar, 2010)). In each trial, two 50ms tones were presentedwith an inter-stimulus interval of 950 ms. After hearing both tones, participants had todecide which tone had a higher pitch (frequency). A visual feedback was given followingeach trial. Thresholds were assessed in blocks of 80 trials, using an adaptive 3-down1-up staircase procedure, converging to 79.9% correct (Levitt, 1971). The initial frequencydifference was 20%. The step sizewas decreased every four reversals from 4.5 to 2 to 1 to0.5 to 0.1%. Discrimination thresholds (Just Noticeable Difference, JND) were calculatedas the mean frequency difference in the last five reversals.

2.2.2. Temporal-interval discriminationPerceptual thresholds for auditory 2 temporal-interval discrimination were

measured using the “reference 1st” protocol (Nahum et al., 2010) with a reference

interval of 100 ms. In each trial, the onset and offset of the two intervals weremarked by pairs of 50 ms 1000 Hz tones, including 5 ms linear rise time, and 5 mslinear fall time. After hearing both intervals, participants had to decide whichinterval was longer. A visual feedback was given following each trial. Thresholdswere assessed in blocks of 80 trials, using an adaptive 3-down 1-up staircaseprocedure, converging to 79.9% correct (Levitt, 1971). Step sizes (in interval ratios)of 2 to 1.4 to 1.1 to 1.05 were used. Discrimination thresholds (Just NoticeableDifference, JND) were calculated as the mean interval difference in the last sixreversals.

2.2.3. Auditory discrimination of speech sounds embedded in noisePerceptual thresholds for auditory discrimination of two phonologically similar

pseudo-words (/barul/�/parul/) embedded in noise were measured. A dioticbinaural configuration was used (same stimuli presented to both ears). Themasking noise was speech noise played at a constant level of 66 dB SPL (seedetails in Nahum, Nelken, & Ahissar, 2008). On each trial, one of the two possiblewords was presented over headphones, masked by noise, and the listener had topress the left/right button on the computer screen whose label matched the playedword. Visual feedback was given after every button press. Thresholds for correctidentification were measured using a 3-down 1-up adaptive staircase procedure,converging at 79.4% correct (Levitt, 1971). Five different step sizes were used forchanging the level of the word, beginning at 3 mV and switching to smaller stepsafter every 3 reversals (3, 2, 1, 0.5, and 0.2 mV). Diotic thresholds were calculated asthe arithmetic mean of the signal amplitude in the last five reversals, and weretransformed into a difference (in dB) between the measured thresholds and themasking noise.

2.2.4. Synchronous tappingSensory-motor threshold was assessed with a synchronous finger tapping task.

Participants were asked to tap with a finger on the wooden box, and to synchronizetheir responses with the pacing of metronome beats. The metronome beats wereshort percussive sounds with an implied baseline inter-onset interval (IOI) of500 ms. Each block contained 100 beats, which alternated between two tempi.Blocks varied in the magnitude of the deviations from the baseline IOI, rangingfrom 72, 76, 710, 714, to 718%. For example, a block with a baselineIOI¼500 ms and 710% deviations alternated between actual IOIs of 450 and550 ms. Each block started with the faster tempo. Each new step change occurredrandomly within 8–12 metronome beats after the previous change. Blocks wereseparated by short pauses. Each participant completed two series of assessments offive blocks each (5 deviation magnitudes). The blocks were organized in 4 possiblerandom orders. Prior to the test procedure, all participants completed a practiceblock containing 100 metronome beats. The mean absolute asynchronies (i.e., theabsolute time difference between each metronome beat and the correspondingfinger tap) and the standard deviation (signed within block) of asynchronies wereused to characterize performance.

The pre-recorded stimuli were played through a computer on a Focusritesoundcard. The output of the soundcard was presented to participants throughheadphones and was simultaneously redirected to one of the inputs of thesoundcard. Participants tapped on a wooden box, and their tapping was recordedby a microphone installed inside the box that was connected to another input ofthe soundcard. The two channels of the soundcard were recorded together usingthe Audacity software. This procedure ensures that the audio signal of theheadphones is synchronized with a sub-millisecond accuracy to the microphone0srecording. The audio signals were low-pass filtered, and a designated peakdetection MATLAB script was then applied to locate the onsets of the taps.

2.3. Working memory tasks

2.3.1. Verbal working memoryVerbal working memory was assessed with a syllable span test. This paradigm

was designed on the basis of the procedure for assessing forward Digit span in thisWAIS sub-test (Wechsler, 1997). Participants were presented with sequences ofrecorded syllables of increasing length and were requested to repeat the syllablesin the presented order. Participants were presented with two sequences for eachlength, starting with two syllables; the task continued until the participant eitherfailed on two sequences of the same length or reached the maximal sequencelength of 8 syllables. We used two list types, with and without cross-trial repetition(as detailed in Oganian & Ahissar, 2012). The order of list assessment wascounterbalanced across participants. The total number of successfully reproducedseries across the two subtests is reported.

2.3.2. Auditory non-verbal working memory tasksDiscrimination between two tonal patterns was assessed with a same-different

paradigm. In every trial participants listened to two sequences of tones and wereasked to decide whether these two patterns were the same or different. Visualfeedback followed each trial. Accuracy of performance (transformed to d0) wasassessed in a block of 60 trials (18 “same” trials and 42 “different” trials). The orderof same and different trials was randomly chosen for each participant. Stimuli were

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created using Finale 2007 software and converted into digital sound files. Thisgeneral scheme was used to assess memory for melodic and for rhythmic patterns.These two tests, designed by the first author, were intended to be challenging (butnot impossible) for musicians.

2.3.2.1. Melodic patterns. This protocol was composed of pairs of melodic isochroouspatterns; each pattern was composed of a sequence of nine 500 ms tones, using asampled piano timbre. The time interval between the two patterns was 1500 ms.The fundamental frequencies of each sequence were chosen from the range of 246.-94 Hz (B3) to 587.33 Hz (D5), based on the chromatic scale of Western music.The melodic patterns were randomly generated with some constraints (followingAkiva-Kabiri, Vecchi, Granot, Basso, & Schön, 2009). “Different” trials were created bychanging the order of two consecutive tones that resulted in a local contour change(in addition to the order change). Changes of order between consecutive tones in outerpositions (2nd-3rd, 3rd-4th, and 6th-7th, 7th-8th), which were found to be easier todetect, appeared in 9 trials each. Changes of consecutive tones in middle positions(4th-5th, 5th-6th), which were more difficult to detect, appeared only in 3 trials each.

2.3.2.2. Rhythmic patterns. This protocol included pairs of rhythmic monophonicsequences; each consisted of 8 beats, paced at a tempo of 120 beats per minute(500 ms for each beat). Trials were constructed of rhythms containing a constantstructure of six beats followed by two beats of silence that marked the transition tothe second sequence. All sequences were played at a pitch of G4 using a sampledharpsichord timbre, and were based on a constant underlying rhythmic structure oflong (L¼quarter-note) and short (S¼eighth note) notes (L-S-S-L-S-S-S-S-L). Rhyth-mic units included longer units (quarter notes), their subdivisions (eighth notes,sixteenth notes), and combinations of the various units. Out of the 42 “different”trails, 21 included changes that occurred on the second beat and 21 includedchanges that occurred on the fourth beat.

All auditory stimuli were presented binaurally through Sennheiser HD-265 linearheadphones at a comfortable volume.

2.3.3. Order of assessmentParticipants were invited to two sessions, administered a few days to several

months apart. The first session covered the cognitive, phonological, verbal memoryand the frequency discrimination and speech perception in noise tasks. The secondsession covered the non-verbal working memory tasks, the temporal intervaldiscrimination task and the tapping task.

2.4. Participants

2.4.1. MusiciansThe groups of musicians were comprised of students at the Music Academy of

the Hebrew University of Jerusalem or professional musicians with an academicdegree in music (hence all were very experienced in reading music). They all filled

out a questionnaire regarding their musical background, their reading and learningbackground and their medical condition. None of the participants had hearing orneurological problems and all had received all of their education in Hebrew.Preliminary assignment to groups was based on their self report of either havingadequate reading abilities or persistent reading difficulties.

This initial procedure yielded control group of 49 participants (23.772.5 years,15 males) and a dyslexic group of 34 participants (23.672.8 years, 22 males).All participants signed a written consent form describing the aims and thebehavioral tasks of the study. Participants were reimbursed for their time accordingto standard student rates.

2.4.1.1. Inclusion criteria

2.4.1.1.1. Phonological scores. Two phonological scores were calculated based onthe average of performance scores for pseudo-word reading and the Spoonerismtasks, one for accuracy and one for rate. Scores were converted into z-scores basedon the performance of the initial control group.

Participants in the control group were included in the analysis only if both theirphonological accuracy and phonological rate scores were no more than 1.5 SDbelow their group average. Dyslexic participants were included if either theirphonological accuracy or their phonological rate scores were at least 1.5 SD belowthe average of the control group. On this basis the data for 9 musicians wereexcluded from the control group and 2 participants were excluded from thedyslexic group.

2.4.1.1.2. Completing all tasks. The experiment was conducted in two sessions.The data for 2 control participants and 8 dyslexic participants who attended onlythe first session, were excluded since their data were only partial.

2.4.1.1.3. General cognitive scores. All participants0 general cognitive scores, asassessed by the Block Design subset of the WAIS-III (Wechsler, 1997), were withinor above the normal range of the general population (scaled score of 7 or above; i.e.no less than 2 SD below the general population average). However, consistent withthe literature (Schellenberg, 2006), the average score of the control musicians(14.1072.62, range¼9–19, n¼38 after excluding nine participants on the basis ofthe phonological exclusion criteria and two participants who did not complete allsessions) was well above the normal range of the general population andsignificantly above that of the dyslexic musicians (12.2072.62, range¼7–17,n¼24 after excluding two participants on the basis of phonological exclusioncriteria and 8 participants who did not complete all sessions), as revealed in a t-test(t(61)¼2.76, p¼0.007). In order to match general reasoning abilities, we excluded10 control participants whose scaled scores were higher than 15 (only 3 dyslexicparticipants scored above 15).

Following this exclusion procedure, the final groups consisted of 24 dyslexicmusicians and 28 control musicians that substantially differed in phonological-decoding skills in spite of being matched for age, education and general reasoningskills. The majority (17/24, 70.8%), though not all our dyslexic participants, wereformally diagnosed by clinicians. Those who were not formally diagnosed hadsimilar self reports of reading difficulties throughout school years (in spite of

Table 1Means and STDs of cognitive and reading related measures for the four groups of participants.

Musicians Non-musicians Scheffé post-hoc comparison

Controls Dyslexics t Controls Dyslexics t Control groups Dyslexic groups

n¼28 n¼24 n¼23s n¼24

19F 9F 12F 18F

Age (years) 23.5 (2.1) 23.7 (2.7) �0.3 24.8 (3.7) 25.6 (2.5) 1.2 p¼ .487 p¼ .998Cognitive tests (scaled WAIS scores)Block design 12.9 (2.0) 12.2 (2.6) 1.2 12.2 (2.8) 11.1 (2.5) 1.4 p¼ .798 p¼ .519Digit span 11.6 (2.9) 9.7 (2.1) 2.6n 11.7 (2.4) 8.0 (1.8) 5.9nnn p¼ .999 p¼ .101Reading accuracy (% correct)Words 98.9 (1.8) 94.1 (6.0) 4.1nnn 99.3 (1.6) 92.0 (6.5) 5.2nnn p¼ .996 p¼ .478Pseudo words 97.3 (2.3) 79.8 (17.3) 5.3nnn 96.4 (4.0) 69.4 (11.9) 10.1nnn p¼ .992 p¼ .012n

Reading rate (words/min)Paragraph 130.8 (13.4) 109.3 (25.3) 3.9nn – – – – –

Words 122.2 (21.2) 88.8 (28.5) 4.8nnn 114.3 (34.7) 69.4 (20.9) 5.5nnn p¼ .772 p¼ .096Pseudo-words 76.6 (12.4) 44.1 (11.7) 9.6nnn 65.9 (15.2) 33.1 (8.8) 9.0nnn P¼ .025n P¼ .026n

Visual word recognition (words/min)70.1 (11.7) 53.4 (12.6) 4.8nnn – – – – –

Phonological awareness (spoonerism)Accuracy (% correct) 95.1 (5.0) 81.6 (17.4) 3.9nnn 95.4 (5.6) 72.7 (21.7) 4.9nnn p¼1.0 p¼ .152Rate (items/min) 12.3 (3.7) 9.1 (3.8) 2.9nn 12.7 (3.8) 7.5 (3.2) 5.0nnn p¼ .983 p¼ .505

n po0.05, compared to control group.nn po0.01, compared to control group.nnn po0.001, compared to control group.

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adequate education), and showed a similar discrepancy between poor reading andphonological scores compared with adequate reasoning abilities. Thus, all ourparticipants conformed to the criteria of Dyslexia as defined by the World HealthOrganization (2008).

2.4.1.2. Musical background. The two groups of musicians had a similar number ofyears of formal musical training (Controls: 11.973.7 years, Dyslexics: 11.174.4 years;t(50)¼0.7, p¼0.500, n.s.) and did not differ in terms of age starting to take musiclessons (Controls: 8.473.2 years, Dyslexics: 9.473.5 years; t(50)¼�1.1, p¼0.276,n.s.). Of the 28 musicians in the control group, 10 had studied piano or another mel-odic percussion instrument, 4 strings, 1 voice and 13 had studied wind instruments. Ofthe 24 musicians in the dyslexic group, 5 studied piano or another melodic percussioninstrument, 9 strings, 5 voice and 5 wind instruments. All our participants stated thatthey practice 2–3 h a day every day. There was no siginificant difference between theamount of self-reported daily training among the two groups of musicians (Controls:2.571.2 h, Dyslexics: 2.470.9 h; t(50)¼0.1, p¼0.877, n.s).

2.4.2. Non-musiciansTwo goups of non-musicians, controls and dyslexics, who participated in a

previous study (Oganian & Ahissar, 2012) were included in this study. Theseparticipants were all students at the Hebrew University of Jerusalem and their readingscores were similar to those student norms accumulated over the last 10 years(detailed in http://elsc.huji.ac.il/ahissar/links/choose Hebrew Reading Norms). Addi-tionally, we had information regarding their musical background. Moreover, thebattery of tests administered to these participants included many of the same tasks,though not all of them, since some (e.g. non-verbal working memory tasks) weredeveloped for the current study. In order to compare the groups of musicians and non-musicians on the phonological scores reported above, the groups of non-musiciansonly included participants who were administered both the pseudo-word reading andthe Spoonerism tasks, resulting in groups of 23 control non-musicians and 24 dyslexicnon-musicians. Their general reading and cognitive characteristics are detailed inTable 1. None of these participants had a musical background of more than three yearsof playing an instrument. 14 control participants (60.8%) and 16 dyslexic participants(66.6%) had no musical background at all.

3. Results

3.1. Cognitive and reading profiles of musicians

We compared musicians with persisting difficulties in readingthroughout their school years, adequate reasoning skills and poorcurrent reading skills with matched peers, i.e. musicians with noreading difficulties. Our exclusion criteria ensured that the twogroups of musician participants did not differ in general reasoningskills (measured by the standard Block Design task, WAIS-III) or interms of years of formal musical education, while significantlydiffering in their phonological decoding skills (Table 1, three leftcolumns). The resulting two groups of musicians also significantly

differed in their spelling skills (measured by the Visual wordrecognition task), and in their verbal working memory scores(measured by the standard Digit span task-WAIS-III). We shouldnote, however, that though their Digit Span scores were signifi-cantly lower than their peers0, they were still within the normalrange, and marginally better than those of non-musicians (seeTable 1).

3.2. The severity of musicians0 dyslexia

We characterized the dyslexic musicians with respect to theirmusician peers. Though closest peers are the best match fordetecting specific reading difficulties, the severity of readingdifficulties can be evaluated with respect to the broader popula-tion of peers; i.e. non-musician students with an otherwise similareducational background. To evaluate the severity of their readingdifficulties we compared the performance of the musician parti-cipants – both controls and dyslexics – to that of non-musicianstudents matched for age and general reasoning abilities, whoparticipated in a previous study (Oganian & Ahissar, 2012). Thegeneral cognitive and reading scores of the two groups of non-musicians are shown in the two middle columns of Table 1.Although the two groups of dyslexics differed in all reading andphonological measures from their matched peers, the decodingskills (pseudo-word reading accuracy and rate) of the dyslexicmusicians were somewhat better (right column of Table 1), thoughsome musician dyslexics were very poor readers, as describedbelow. Still, both accuracy and rate of musician dyslexics0 pseudo-word reading were well below those of non-musician controls.

To compare the decoding skills of the control and dyslexicmusicians and non-musicians at the level of individual partici-pants, we plotted pseudo-word reading scores (accuracy versusrate) and phonological awareness scores (accuracy versus rate inthe Spoonerism task) of each participant, as shown in Fig. 1. As canbe seen in the plot of pseudo-word reading (left panel), musicians0

decoding rate was faster than that of non-musicians (see alsoTable 1). The distribution of musicians0 rate is shifted with respectto non-musicians; namely, the slowest readers were non-musi-cians, and fastest were musicians. Interestingly, this was not thecase for phonological awareness, as assessed by the Spoonerismtask, where neither rate nor accuracy of controls differed betweenmusicians and non-musicians (Fig. 1, right plot; see also Table 1).

Fig. 1. Scatter plots of accuracy scores as a function of rate. Each symbol denotes the scores of one participant. Dyslexic participants are denoted in red and controls in blue.Musicians are denoted in filled symbols and non-musicians in empty symbols. (A) Pseudo-word reading, (B) phonological awareness, measured with the Spoonerism task. Inboth tasks dyslexic participants are both less accurate (lower part of the plots) and tend to be slower (on the left part of the plots). The poorest readers (lower lefts sections ofA and B) are composed of both musicians (filled symbols) and non-musician (empty symbols) dyslexics, though musician dyslexics tend to be to the right (faster) than non-musicians.

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3.3. Sensory and sensory-motor abilities

In order to assess perceptual abilities we used a protocol thatcontained a reference tone in a fixed temporal position (the firsttone in 2-tone trials) and does not heavily load working memoryprocesses (at least not explicit processes; see discussion in (Ahissaret al., 2006; Ahissar, 2007; Nahum et al., 2010)). The thresholds ofdyslexic musicians did not significantly differ from those of theirpeer musicians. Neither frequency discrimination (t(50)¼�1.5,p¼0.143, n.s.), nor interval discrimination (t(50)¼�0.7, p¼0.470,n.s.) were impaired (Fig. 2A), in contrast to findings in non-musician dyslexics.

We tested speech perception in noise with a simple task ofdiscrimination between two phonologically similar pseudo-wordspresented in noise (Nahum et al., 2008). This protocol does notimpact working memory since participants were only asked todetermine which of two words was presented. The threshold(signal to noise ratio) of dyslexic musicians for discriminatingbetween the phonologically similar words (Fig. 2B) was similar tothat of control musicians (t(50)¼�1.4, p¼0.157, n.s).

In order to assess the temporal accuracy of sensory-motorskills, we used a simple synchronous tapping task. We chose aprotocol that contained no explicit memory (i.e. no reproduction)component. Participants were only asked to synchronize their tapsto an external metronome. Sensory-motor accuracy (mean asyn-chrony, i.e. average interval between tapping time and metronome

beat time) and consistency (mean STD of this asynchrony) wereused as measures (Repp, 2010). Again, in both measures, theperformance of dyslexic musicians was similar to that of theiradequately reading peer musicians (mean asynchrony, t(48)¼0.2,p¼0.817, n.s., mean STD of asynchrony, t(48)¼�0.7, p¼0.499, n.s.;Fig. 3). The performance of the dyslexic musicians was better thanthat reported for non-musician (adult) dyslexics, both in theirmean asynchrony (Wolff, 2002) and in their consistency (Thomsonet al., 2006).

3.4. Measures of working memory and their inter-correlations

We assessed auditory working memory for phonology, melodyand rhythm separately. As shown in Fig. 4, auditory working-memory skills of dyslexic musicians were substantially and con-sistently lower than those of their peer musicians for syllables(Fig. 4A; t(50)¼3.9, po0.001), for melodic patterns (Fig. 4B; leftplot; t(50)¼3.1, p¼0.004) and for rhythmic patterns (Fig. 4B; rightplot; t(50)¼3.3, p¼0.002).

Given that all aspects of auditory working memory were foundto be impaired among dyslexic musicians, we tested whetherthese measures were inter-correlated. As shown in Table 2A,among dyslexic musicians, rhythmic and verbal working memoryscores were correlated. In contrast, among control musicians,measures of verbal working memory (digit and syllable span)were correlated, as were measures of non-verbal memory

Fig. 2. Average psychoacoustic thresholds of the control (blue) and dyslexic (red) groups. (A) JNDs for 2-tone Frequency discrimination. Average thresholds are similar anddo not significantly differ between groups. (B) JNDs for Temporal-interval discrimination. Average thresholds do not differ between groups. (C) JNDs (signal to noise ratio)needed to attain 80% correct discrimination for Speech perception in noise. Group thresholds are very similar. Error bars denote 1 SEM. (For interpretation of the referencesto color in this figure legend, the reader is referred to the web version of this article.)

Fig. 3. Average performance in synchronous tapping of the Control (blue) and dyslexic (red) groups. (A) Accuracy—measured as the average interval that tapping precededthe metronome. (B) Consistency—measured as the average standard deviation in the timing of tapping (i.e. the smaller the better) around the mean response (i.e. accuracy).Dyslexics0 performance did not differ from Controls. Error bars denote 1 SEM. (For interpretation of the references to color in this figure legend, the reader is referred to theweb version of this article.)

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(melodic and rhythmic). However, measures of verbal and non-verbal memory were not correlated, suggesting specialization ofworking memory that did not occur among dyslexic musicians.

3.5. Working memory and reading accuracy

Since working memory of dyslexic musicians was poorer thantheir peers0, we tested whether their degree of impairment wascorrelated with their reading difficulty. Reading rate was notcorrelated with any of the auditory working memory measures.However, among dyslexic musicians, measures of both verbal andrhythmic working memory were highly correlated with accuracyof reading words and pseudo-words (Table 2B, and scatter plot ofFig. 5). This was not the case for the control musicians, for whomnone of the auditory working memory measures was a significantpredictor of reading accuracy, perhaps because their readingaccuracy was near ceiling (see Table 1 and Fig. 5). Hence thenon-significant correlation among controls may result from theirhigh reading accuracy.

3.6. Comparison between the subgroups of inaccurate dyslexicreaders—musicians versus non-musicians

Because reading accuracy rather than reading rate was relatedto working memory among dyslexic musicians, we tested whetherthe subgroups of inaccurate dyslexics (pseudo-word readingaccuracy below dyslexic musicians0 average; i.e. o80%) showeda similar pattern of perceptual and working memory skills among

musicians and non-musicians. This group included 9 dyslexicmusicians and 20 non-musician dyslexics (see Fig. 1, left plot),reflecting the higher prevalence of inaccurate readers among non-musicians. These two groups were similar in accuracy of pseudo-word reading (Fig. 6A; t(27)¼�0.9, p¼0.331,) and in theirphonological awareness skills (Fig. 6B; accuracy t(27)¼�0.4,p¼0.707; rate t(27)¼�0.8, p¼0.392). In addition, they hadsimilar verbal working memory scores, both in digit span(Fig. 6D, t(27)¼0.4, p¼0.692,) and in syllable span (Fig. 6D;t(27)¼�0.2, p¼0.849). On the other hand, in line with musicians0

overall enhanced auditory dissscrimination skills, their frequencydiscrimination thresholds were significantly lower (Fig. 6C;t(27)¼�3.7, p¼0.001). Importantly, the musician group was fasterin phonological decoding (i.e. rate of pseudo-word reading;Fig. 6A; t(27)¼2.2, p¼0.035).

Thus, the specific comparison with non-musician dyslexics,matched for decoding accuracy, yielded the same pattern as foundfor the larger groups of dyslexics. Musician dyslexics0 perceptualaccuracy and rate of pseudo-word reading was enhanced but theirworking memory was comparable to that of non-musicians.

3.7. Years of training and working memory

We tested whether musicians0 working memory skills werecorrelated with the duration of their formal musical education.Among the control musicians, musical training (total years ofplaying) was correlated with their phonological span (measuredby syllable span, spearman correlation: r¼0.42, p¼0.042; Pearson

Fig. 4. Average scores of Control (blue) and dyslexic (red) musicians on working memory tasks. (A) Verbal working memory—the total number of correctly reproduced seriesof syllables (using series of gradually increasing length). (B) Calculated d0s for Melodic (left) and rhythmic (right) working memory tests. Dyslexics0 scores were poorer thanControls0 in all auditory working memory tasks. Error bars denote 1 SEM. npo0.05, nnpo0.01. (For interpretation of the references to color in this figure legend, the reader isreferred to the web version of this article.)

Table 2Pearson correlations for the various working memory scores.

Control musicians Dyslexic musicians

(1) Digitspan—total

(2) Syllablespan—total

(3) Melodicpatterns—d0

(4) Rhythmicpatterns—d0

(1) Digitspan—total

(2) Syllablespan—total

(3) Melodicpatterns—d0

(4) Rhythmicpatterns—d0

A (1) Digit Span—total 0.72nnn 0.36 �0.06 0.46n 0.28 0.63nn

(2) Syllable span—total 0.21 �0.07 0.39 0.49n

(3) Melodic patterns—d0 0.49nn 0.29B (4) Words (accuracy) 0.20 0.15 0.16 0.05 0.54nn 0.38 0.55nn 0.49n

(5) Pseudo words(accuracy)

-0.07 0.08 0.10 0.05 0.73nnn 0.51n 0.35 0.72nnn

n po0.05.nn po0.01.nnn po0.001.

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correlation: r¼0.36, p¼0.057), and the age they started to playwas marginally correlated (spearman correlation: r¼�0.36,p¼0.063, Pearson correlation: r¼� .0.20 p¼0.308). However,among dyslexic musicians, neither age of starting music lessons,nor the total number of years of musical training were significantlycorrelated with verbal spans (spearman correlation: r¼�0.04,p¼0.852, n.s.; r¼0.17, p¼0.420, n.s., respectively; Pearson correla-tion: r¼�0.06, p¼0.777, n.s.; r¼0.14, p¼0.490, n.s., respectively).Thus, in contrast to the control group, among the dyslexicparticipants, length of formal musical training was not correlatedwith working memory skills.

4. Discussion

The phenomenon of dyslexic musicians challenges two aspectsof findings and theories that link linguistic and non-linguisticauditory processing skills. First, it suggests that this linkage maybe violated in this group. Second, it questions the impact of longand intensive musical training on phonological skills.

Surprisingly, we found that in spite of their musical training,accompanied by successful perceptual performance, the auditorydeficit among dyslexic musicians was not expressed solely in theverbal domain. Their non-verbal auditory working memory skills(both for melodic and rhythmic patterns) were also poorer thantheir peers0. Moreover, among dyslexic musicians, accuracy ofreading was correlated with auditory working memory skills,suggesting that this deficit indeed limits their reading ability (fornon-musician dyslexics, see Banai & Ahissar, 2004, 2009). Thus,the discrepancy in their skills was between psychoacoustic andworking memory skills rather than between processing of verbalversus non-verbal stimuli.

The decoding skills of control musicians were better than thoseof non-musician controls. Furthermore, the severity of dyslexiaamong musicians was milder than among non-musicians. Thisdifference may reflect a selection bias for musicians, or the effectof prolonged musical training, or both. Still, some dyslexic musi-cians were very poor decoders, indicating the limits of musicaltraining. Characterization of their perceptual and memory skillssuggested that the bottleneck to their musical-training inducedimprovement was in their auditory working memory.

4.1. Working memory as a core deficit in dyslexia

A series of previous studies, found that (non-musician) dys-lexics perform poorly on various auditory psychoacoustic taskscompared with matched (non-musician) controls (e.g. Ahissaret al., 2000, 2006; Corriveau et al., 2007; France et al., 2002;Goswami et al., 2002; Huss et al., 2011; Oganian & Ahissar, 2012).We now found that unlike non-musician dyslexics, musiciandyslexics did not differ from their peer musicians in their perfor-mance on psychoacoustic tasks. Yet, since non-musicians are naïveto psychoacoustic tasks, their poorer performance may stem frompoorer working memory skills. Working memory networks areactivated by the novice in difficult tasks (e.g. Duncan, 2010), evenwhen these tasks are perceptual. Since studies which assessperceptual skills assess performance on difficult perceptual tasks(i.e. stimuli are around threshold) it may be difficult to dissociateworking memory limitations from a genuine sensory impairmentin individuals with no experience on these tasks (e.g. Banai &Ahissar, 2006, see discussion in Ramus & Ahissar, 2012).

The population of dyslexic musicians is unique since they arenot novice in auditory discriminations and therefore, workingmemory limitations are not expected to pose a bottleneck to theirpsychoacoustic performance. Their performance did not differfrom their peers on any of the tested psychoacoustic tasks.However, they showed working memory impairments on alltested tasks. Moreover, the difficult phonological awareness task,which they performed poorly (Spoonerism, in which participantsare asked to switch the first phoneme of the first word and thefirst phoneme of the second word in an orally presented wordpair) is also demanding with respect to working memory.

Generally poor auditory working memory may thus limit thereading skills of both non-musician and musician dyslexics.Indeed, studies that tested non-musician dyslexics found thatpoor reading accuracy mainly characterizes individuals with poorauditory working memory (Banai & Ahissar, 2004). Moreover,increasing working memory load increases dyslexics0 relativedifficulties whereas increasing the perceptual load of tasks doesnot (Banai & Ahissar, 2006). Similar findings were reported forphonological tasks (Ramus & Szenkovits, 2008), suggesting thatboth types of stimuli show the same pattern. The specific under-lying deficit may reside between basic sensory and explicit work-ing memory processes, i.e. in implicit (perhaps automatic) workingmemory. This interpretation is in line with ERP studies thatreported a poor mismatch response (an automatic auditoryresponse to an oddball stimulus) in dyslexia (e.g. Baldeweg et al.,1999; Kujala, Lovio, Lepistö, Laasonen, & Näätänen, 2006). Thisinterpretation is also consistent with “The anchoring deficithypothesis” proposed by our group (Ahissar et al., 2006; Ahissar,2007), which attributes dyslexics0 difficulties to their lack ofimplicit ability to track auditory regularities in the stream ofincoming stimuli. The anchoring hypothesis attributes dyslexics0

poor working memory span to their impaired ability to implicitlychunk the series of incoming stimuli rather than to the executiveaspect of working memory. Since dyslexics0 difficulties wereobserved on series that exceed four items (i.e. more than fourdigits, more than four syllables and more than four tones in a

Fig. 5. Correlations between accuracy of pseudo-word reading and scores (d0) inrhythmic working memory test. The two sets of scores were significantly correlatedin the dyslexic group of musicians (red dots; R Pearson¼0.72, po0.001). However,these scores were not correlated in the Control group of musicians (blue dots, RPearson¼0.05, n.s.). Controls; accuracy was nearly at ceiling, which may accountfor their non-significant correlation. The dotted blue line denotes the averageaccuracy of Control musicians (97% correct, as shown in Table 1). (For interpretationof the references to color in this figure legend, the reader is referred to the webversion of this article.)

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melodic or a rhythmic pattern), successful performance was con-tingent upon successful chunking (Cowan, Blume, & Saults, 2012).Since successful chunking is based on implicit regularity detection(Mathy & Feldman, 2012), the difficulty of dyslexic musicians in theworking memory tasks that we administered may have beencaused by an inadequate implicit regularity detection mechanism.Namely, dyslexic musicians were perhaps less efficient in using thefamiliar syllables and common musical components (we used thefrequency and time intervals of Western music) to enhance theireffective working memory span.

Nevertheless, the average memory span of the musician dyslexics,though significantly poorer than their peers, was not much worsethan that of the general population, raising the question whether it isindeed the bottleneck to their reading and phonological perfor-mance. One potential account of that mild working memory deficitis that musicians are trained on this type of listening tasks, and henceperhaps developed compensatory strategies. This line of reasoningunderlies the choice of control groups for dyslexics to have similareducational background. For example, dyslexic participants in adyslexia study conducted at University College London (Ramuset al., 2003) were not worse than the general population in theirphonological decoding or in their standard memory scores. However,they were significantly poorer than their university peers, andshowed a clear discrepancy between their about-average readingand verbal memory scores versus their well-above-average generalreasoning abilities. Perhaps because they are more driven, had betteropportunities or general cognitive skills, they achieve overall higherscores than would be expected based on their specific difficulties.Still, even among the musician dyslexics, the particularly inaccurate

decoders had poor working memory scores, whose severity wassimilar to that of non-musicians.

Interestingly, although both melodic and rhythmic workingmemory scores were poor among dyslexic musicians, they werecorrelated with different reading tests. The rhythmic score wascorrelated with reading accuracy of both words and pseudo-words,perhaps due to the serial nature of this task. Dyslexics0 readinglargely relies on serial phonological decoding, similar to that of the‘early reading stage’ in children (Grainger & Ziegler, 2011). Themelodic score was only correlated with reading accuracy of realwords, perhaps due to its more global nature, since it was based oncontour change detection (Foxton et al., 2003, Ziegler, Pech-Georgel,George, & Foxton, 2012). Real word reading may also gain fromholistic processes even among dyslexics.

4.2. Implications for brain plasticity

Two findings characterized control musicians0 working mem-ory scores:

1. Verbal memory scores were correlated with the overall dura-tion (number of years) of musicians0 formal musical education,in line with the literature that suggests a possible transfer oftraining between music and speech (Besson, Chobert, & Marie,2011, Herholz & Zatorre, 2012)

2. Verbal memory scores, measured with digit and syllable spanwere correlated, and non-verbal scores, measured with melodicand rhythmic tunes were correlated. However, there was nocorrelation between verbal and non-verbal scores.

Fig. 6. A comparison of the average performance of the inaccurate dyslexic readers, musicians (filled bars) versus non-musicians (empty bars). (A) Accuracy and rate in thepseudo- word reading task. (B) Accuracy and rate in the Spoonerism task. (C) Thresholds in frequency discrimination. (D) Scores on verbal working memory tasks: Digit spanand syllable span. Inaccurate dyslexic musicians differed from their non-musician peers only in their frequency discrimination thresholds and in the rate of reading pseudo-words. Importantly, working memory scores were similarly poor in these two subgroups. Error bars denote 1 SEM. npo0.05, nnpo0.01.

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Taken together, these results might suggest that intensivemusical training enhances musicians0 working memory skills andleads to the developing of modular representation for verbal andnon-verbal stimuli, respectively. These results are congruent withprevious findings of some separation between phonological andtone related memory among musicians (Berti, Münzer, Schröger, &Pechmann, 2006; Pechmann & Mohr, 1992; Satoh, Takeda, Nagata,Hatazawa, & Kuzuhara, 2003; Schulze & Koelsch, 2012; Schulze,Zysset, Mueller, Friederici, & Koelsch, 2011).

None of these characteristics were observed in dyslexic musi-cians. Their working memory scores were not correlated withyears of playing and were overall lower than their peers.In addition, their verbal and non-verbal rhythmic stimuli werecorrelated. This pattern suggests that they retained non-expertforms of working memory. Indeed, non-musicians seem to havecommon working memory mechanisms for verbal and non-verbalauditory stimuli (Brandt, Gebrian, & Slevc, 2012; Hausen, Torppa,Salmela, Vainio, & Särkämö, 2013; Saito, 2001; Shahin, 2011).

The hypothesis that musicians develop modular representationsis in line with theories of learning that propose increased specificitywith increased practice (e.g. Reverse Hierarchy Theory, Ahissar &Hochstein, 1997, 2004; Ahissar, Nahum, Nelken, & Hochstein,2009). It is also consistent with the observation that in other skills,the acquisition of behavioral expertise is associated with the acquisi-tion of modular brain representation. A very related case is that of theVisual Word Form Area (Dehaene, Cohen, Sigman, & Vinckier, 2005;McCandliss, Cohen, & Dehaene, 2003), which develops with readingacquisition and is specialized for visual representation of words.Interestingly, functionally it is nearly absent in dyslexics (Dehaene &Cohen, 2011; Van der Mark et al., 2009). However, the hypothesis ofacquired modularity seems at odds with the suggestion that musicaltraining enhances general verbal skills in expert musicians (Chanet al., 1998; Ho et al., 2003; Jakobson et al., 2011). Whethermusicians0 verbal working memory superiority results from a selec-tion bias, where individuals with better auditory memory are morelikely to becomemusicians, or an actual consequence of their musicaleducation is still debated (Schellenberg, 2009, 2011). Our own data isnot conclusive, particularly since musicians0 advantage in melodicand rhythmic working memory was substantial whereas theiradvantage in verbal working memory was mild (unpublished data).

The question of the impact of musical training on verbal workingmemory is yet open. Whether working memory can be enhanced inother ways is also an open question. Several studies attempted toelevate working memory skills by training on demanding workingmemory tasks, with mixed results (reviewed by Jacoby & Ahissar,2013). In a related study (non-musicians) dyslexic students wereadministered a working memory training procedure, which includeda mixture of visual, auditory and cross-modality tasks (six weekswith four sessions per week, approximately 20 min each). Theauthors (Horowitz-Kraus & Breznitz, 2009) report that followingtraining, the dyslexic group had a significant increase in digit spanand a significant elevation in reading rate.

4.3. The difficulties of dyslexic musicians

The milder form of dyslexia among musicians may reflect theimpact of musical education. However, based on the current studywhich was not designed as a training study, we cannot excludetwo possibilities; that only individuals with milder workingmemory difficulties become musicians, or that individuals whobecome musicians are more likely to have had additional correc-tive teaching or supportive environment.

The advantage of dyslexic musicians in comparison to non-musician dyslexics was most apparent in reading rate, and to alesser extent in reading accuracy. We can only speculate about themechanism that boosts reading rate with music practice. One

option is that it has to do with reading musical notes undertemporal constraints. This type of practice may enhance readingrate, as suggested by the positive outcomes of training programs inwhich serially presented tones were matched with visual patterns(Kujala et al., 2001; Törmänen & Takala, 2009). Such a relationshipbetween performance on a nonverbal task requiring auditory–visual matching and reading tasks, suggests that dyslexics maybenefit from cross-modal training, as suggested by the cross-modal training program introduced in the study of Horowitz-Kraus & Breznitz (2009). Another option is that musicians learn tosynchronize to an internal tempo, and can hence shift their rate-accuracy tradeoff to faster reading rates, though compensatingaccuracy. Among adult non-musician dyslexics (particularly stu-dent), it is difficult to find a tradeoff that “prefers” faster readingrates to accuracy. This presumed shift in the time-accuracy trade-off may be particularly beneficial in reading systems that useshallow orthographies, and do not pose challenges to phonologicaldecoding (e.g. German, Spanish). Therefore, the main challengein reading these orthographies is rate rather than accuracy(Brunswick, McDougall, & Davies, 2010; Ellis et al. 2004; Landerl,Wimmer, & Frith, 1997).

The generally poorer working memory skills of dyslexic musi-cians compared with their musician peers are expected to pose abottleneck to some aspects of their musical skills. Though this wasnot our initial question, given our findings we asked our partici-pants to describe their difficulties in this domain. A commonreport is a difficulty in reading musical notes. Though we have nottested that systematically, this difficulty may be at least partiallyattributed to poor working memory, just as in alphabetical reading(Meinz & Hambrick, 2010). Some also reported that they have aharder time learning new pieces, but we have not quantified that.We did not attempt to estimate whether dyslexic musicians areless successful musicians.

4.4. Summary

A systematic characterization of the performance of dyslexicmusicians at various levels of processing including perceptual,sensory-motor, working memory and reading batteries showedthat contrary to the intuitive interpretation given their musicalexpertise, the difficulties of these individuals span both verbal andnon-verbal skills. Whereas intensive musical training has probablyenhanced their auditory perception, their auditory working mem-ory still seems to pose a bottleneck to their reading accuracy.

Acknowledgments

We thank the Israel Science Foundation for a grant supportingthis study. We thank Sagi Dex-Jaffe, Eitan Globerson, Nori Jacobyand Ofri Raviv for programming the psychophysical and workingmemory tasks.

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