Clinical Neurophysiology 124 (2013) 1578–1585

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Clinical Neurophysiology

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Infants’ brain responses for speech sound changes in fast multifeatureMMN paradigm

1388-2457/$36.00 � 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland All rights reserved.http://dx.doi.org/10.1016/j.clinph.2013.02.014

⇑ Corresponding author at: Cognitive Brain Research Unit, P.O. Box 9 (Siltavuo-renpenger 1 B), 00014 University of Helsinki, Finland. Tel.: +358 40 5604141.

E-mail address: eino.partanen@helsinki.fi (E. Partanen).

Eino Partanen a,b,⇑, Satu Pakarinen a,c, Teija Kujala a,d, Minna Huotilainen a,b,c

a Cognitive Brain Research Unit, Cognitive Science, Institute of Behavioral Sciences, University of Helsinki, Finlandb Finnish Center of Excellence in Interdisciplinary Music Research, Dept. of Music, University of Jyväskylä, Finlandc Finnish Institute of Occupational Health, Helsinki, Finlandd Cicero Learning, University of Helsinki, Finland

a r t i c l e i n f o

Article history:Accepted 5 February 2013Available online 20 March 2013

Keywords:Mismatch negativity (MMN)LanguageEvent-related potentials (ERP)Multifeature paradigmInfantNewborn

h i g h l i g h t s

� Newborns’ neural speech sound discrimination can be studied using a fast multifeature paradigm.� The responses obtained with the multifeature paradigm do not differ from those obtained with the tra-ditional oddball paradigm.� The newborn speech-sound change-detection responses are predominantly positive but a small sub-group elicits negative responses.

a b s t r a c t

Objective: We investigated whether newborn speech-sound discrimination can be studied in 40 minusing fast multifeature mismatch negativity (MMN) paradigm and do the results differ from thoseobtained with the traditional oddball paradigm.Methods: Newborns’ MMN responses to five types of changes (consonant identity, F0, intensity, vowelduration and vowel identity) were recorded in the multifeature group (N = 15) and vowel duration andvowel identity changes in the oddball group (N = 13), after which the MMNs from both groups were com-pared with each others.Results: Statistically significant MMNs in the 190–600 ms time range from the stimulus onset were foundfor most change types in both paradigms. Newborn MMN responses were predominantly positive but asmall number of participants elicited negative MMNs instead. MMN amplitudes did not differ betweenthe multifeature and oddball groups.Conclusions: Newborn speech-sound discrimination can be assessed in a short recording time using thefast multifeature paradigm.Significance: The paradigm presented here can be used to record extensive auditory discrimination pro-files in newborns and assess development of speech-sound discrimination and its difficulties.

� 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland All rightsreserved.

1. Introduction

Mismatch negativity (MMN), a component of the event-re-lated potentials (ERPs), is an automatic change-detection re-sponse which is elicited when the participant perceives adiscriminable change in the auditory stream (for a review, seeNäätänen et al., 2007). The MMN is considered to reflect thecomparison of the auditory input with the neural representationof the repeating standard stimulus; should a difference be found,

then the MMN is elicited. However, the MMN is not only elicitedby acoustic changes but also by changes in abstract features ofthe auditory input, such as violations of sound regularities (Ter-vaniemi et al., 1994; Näätänen et al., 2001). Furthermore, theMMN reflects behavioral discrimination accuracy (e.g. Kujalaand Näätänen, 2010). The MMN can be recorded in the absenceof attention (Näätänen et al., 1978) and is even elicited in sleep-ing newborns (Cheour et al., 2002) or in fetuses (Huotilainenet al., 2005). Therefore, the MMN has been extensively used instudies of infant and newborn auditory discrimination (e.g., Che-our et al., 2000; Weber et al., 2004) and also in studies of at-riskgroups (e.g., Pihko et al., 1999; Leppänen et al., 1999; Lovio et al.,2010).

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In adults the MMN is seen as a negative deflection within 100–200 ms from change onset. However, both negative and positivechange-detection responses (mismatch response, MMR1) havebeen reported in infant studies (e.g., Alho et al., 1990; Kushnerenkoet al., 2002; Morr et al., 2002; Ruusuvirta et al., 2003; Novitski et al.,2007; Tew et al., 2009). While the mechanisms behind the responsesof the different polarities are not entirely clear, Leppänen et al.(2004) have shown that the polarity of the change-detection re-sponse in newborns is correlated both with the gestational age andcardiac measures related to vagal tone and maturation (e.g., Porgeset al., 1999). Furthermore, He et al. (2007) have shown that the slowpositive change-detection response is prevalent in 2-month-old in-fants, but slowly diminishes in amplitude and disappears by theage of 4 months. Thus, the polarity seems to be affected by matura-tion and it seems plausible that newborn change-detection re-sponses are primarily positive in polarity, but by the age of4 months they develop to resemble adult-like negative MMN (see,e.g., Kurtzberg, 1982; Kurtzberg et al., 1995; Choudhury and Benas-ich, 2011; Trainor, 2012; Näätänen et al., 2012, for a discussion onthe maturation of MMN and basic ERP-waveforms). In addition tothe maturation effects, also differences in experimental setups canhave an effect on change-detection responses in newborns. For in-stance, slow stimulus presentation rate diminishes the neural refrac-toriness, which results more likely in negative waveforms (He et al.,2009). However, in many studies some infants elicit MMRs of oppos-ing polarity in comparison to the majority of the group. Approachesto dealing with infants with responses of opposite polarity vary: insome studies they are removed from further analysis either on thebasis of prematurity (e.g., Carral et al., 2005; 1 infant out of 11) orabnormality of responses in comparison to the group mean (e.g.,Sambeth et al., 2009; 2 infants out of 13). Many papers also reportthe number of infants showing only positivities (e.g., Ceponieneet al., 2002, 19–21%; see Kurtzberg et al., 1995 for discussion).

Since the MMN the is an attractive tool for investigating audi-tory discrimination abilities across the lifespan and in various clin-ical groups (see Kujala and Näätänen, 2010, and Kujala et al., 2007for reviews), fast and efficient MMN paradigms have been devel-oped for recording extensive auditory discrimination profiles.Näätänen et al. (2004) developed the so-called multifeature para-digm (Optimum-1 in the original paper) in which every other stim-ulus is a standard and every other is one of five different deviants.The multifeature paradigm is based on the premise that memorytraces are formed for each feature of the sound (e.g., intensity) sep-arately. While one feature of the sound changes (e.g., frequency),the other features remain unchanged strengthen the memorytraces for the unchanged features while the MMN is elicited bythe change in one feature of the stimulus. In adults, very similarMMNs were obtained for harmonical tones (Näätänen et al.,2004) and speech sounds (Pakarinen et al., 2009) with multifeatureand oddball paradigms.

To our knowledge there is one study that has investigated new-borns’ MMRs with a multifeature paradigm (Sambeth et al., 2009).In this study, infant MMRs for changes of frequency, intensity, gap,and duration were recorded using magnetoencephalography(MEG). Changes of frequency, intensity and gap elicited a statisti-cally significant response in MEG while frequency and durationchanges elicited statistically significant responses in EEG. The cur-rent study investigated whether MMRs can be obtained from new-borns for speech stimuli with the multi-feature paradigm. Inadults, MMN to changes in speech sounds is thought to reflect boththe activation of long-term memory traces for native languagephonemes (Näätänen et al., 1997; Cheour et al., 1998) and short-

1 In the present paper we refer to the adult and child negative change-detectionresponse as MMN and the infant change detection response as MMR, regardless of theresponse polarity.

term memory traces of the regularities in the preceding auditorystimuli (Näätänen and Winkler, 1999; Näätänen et al., 2005). In in-fants the MMR is thought to primarily reflect the detection ofacoustical difference between the deviant and standard stimuli,but on the basis of infant preferences for the native language ofthe mother (e.g., Moon et al., 1993), the presence of early memorytraces for native language phonemes cannot be completely dis-counted. An MMN paradigm with speech sounds may be particu-larly relevant for investigating infants at risk for language-relateddisorders, dyslexia or specific language impairment.

The aim of the present study was to investigate whether a fastmultifeature MMN paradigm with speech sounds is feasible forinvestigating newborn infants. Furthermore, we determinedwhether similar MMRs are elicited in the multifeature and oddballparadigms.

2. Methods

2.1. Participants

The mothers or both parents gave an informed consent for a to-tal of 29 infants to participate in the experiment. The EEG of theparticipating infants was recorded in the Helsinki University Cen-tral Hospital by a trained nurse. Prior to the EEG recording thehearing of the infants was tested with Evoked Oto-Acoustic Emis-sions (EOAE, ILO88 Dpi, Otodynamics Ltd., Hatfield, UK) in order toensure the inner ear of the infants was functioning as normal. Nor-mal EOAE responses were elicited binaurally in all infants and allinfants were considered healthy by a neonatologist. 16 of the in-fants were in the multifeature experiment group and the remaining13 in the oddball experiment group. No infants participated in bothmultifeature and oddball groups. One participant from the multifea-ture group was removed from the analysis due to abnormally largeresponses and was shown to be an extreme case by using boxplots.The study was approved by the Ethical Committees of the Depart-ment of Psychology and the Helsinki University Central Hospital.

The infants were born between 37 + 5 and 42 + 2 (weeks + days)of gestational age (GA; mean 39 + 6; 39 + 5 in the multifeaturegroup and 39 + 6 in the oddball group). Birth weights ranged from3030 to 4215 g (mean 3640 g; 3710 in the multifeature group and3560 in the oddball group). Apgar scores measured immediatelyafter birth varied from 7 to 9 (mean 9 in both groups), with all in-fants receiving an Apgar score of at least 9 five minutes after birth.

During the recording infants were lying in a crib while theywere presented with the stimuli from two loudspeakers placedapproximately 1 m from the infant, on both sides of the head.The sound level was 60 dB SPL at the approximate location of theinfant’s head, measured with a sound level meter (Extech Instru-ments, Model HD600). The age of the infants at the time of themeasurement ranged from 0.5 to 4 days (mean 1.6 days; 1.3 forthe multifeature group and 1.9 for the oddball group).

2.2. Stimuli and procedure

Stimuli used in the experiment consisted of 170 ms long semi-synthetic syllables /te:/ and /pi:/, generated using the Semisyn-thetic Speech Generation method (SSG; Alku et al., 1999). Theexperiment consisted of four pseudorandomly predefined presen-tation blocks presented in a random order. In two of the blocks astandard stimulus /te:/, and in two blocks /pi:/ was used. The prob-ability of standard stimuli was 50% for the multifeature group(where standard and deviant stimuli were alternating) and 90%for the oddball group (where stimuli occurred pseudorandomly).In the oddball paradigm, 2430 standard stimuli and 135 deviantstimuli of each type were presented. In the multifeature paradigm,

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1500 standard stimuli and 300 deviant stimuli of each type werepresented. The deviants were presented less frequently in the odd-ball paradigm because only one deviant type was presented in eachof the presentation blocks. This was chosen in order to keep theoddball paradigm as simple as possible for the newborn auditorysystem and avoid any possible confound due to two deviant typesbeing presented in the same stimulus block.

A total of five different deviant categories were used: consonantidentity (/pe:/ for the /te:/ blocks and /ti:/ for the /pi:/ blocks), F0(syllable frequency; +8% for half of the stimuli, �8% the rest ofthe stimuli), intensity (+7 dB for half of the stimuli, �7 dB for therest of the stimuli), vowel duration (�70 ms) and vowel identity(/ti:/ for the /te:/ blocks and /pe:/ for the /pi:/ blocks). For details,see Pakarinen et al. (2009) and Lovio et al. (2009), using identicalstimuli. The probabilities of all deviant types were the same(10%); for the oddball group only the vowel duration deviant waspresented in two of the blocks and vowel identity in the othertwo, whereas all deviant types were present in all the blocks forthe multifeature group. Stimulus onset asynchrony (SOA) of650 ms was used in both experiments. During the recording, atrained nurse took notes on the behavioral indices and activity ofthe infant and for each block, made a preliminary classification ofthe sleep stage(s).

2.3. EEG recording and data analysis

EEG was recorded from 11 channels using Ag/Cl electrodesplaced according to the international 10-20 system. F3, F4, C3,Cz, C4, P3, P4, T3 and T4 locations were used in addition to twochannels monitoring horizontal and vertical eye movements, oneplaced below and the other to the right of the outer corner of theright eye. The electrodes were referenced to the average of thetwo mastoid electrodes. The recordings were conducted using asampling rate of 500 Hz and a band-pass filter of 0.01 and 40 Hz,using NeuroScan recording system. The temporal electrodes wereremoved from further analysis due to small signals.

Offline, the continuous data were first divided into sleep stages.Sleep stage was determined using the EEG, EOG, and the notesfrom the nurse. The sleep was classified to be active (AS) whenthe EEG showed low-voltage high-frequency activity, quiet (QS)when it included either high-voltage low frequency activity ortrace alternants (high and low-voltage slow waves alternating)and awake when the EOG channels showed frequent and largeeye movements or large movement artefacts and on basis of theobservations of a trained nurse conducting the experiment (see,e.g., Mirmiran et al., 2003 for classification criteria). The EEG dataduring which the infant was awake (even for an occasional periodof time), or with large artifacts, were rejected during the visualanalysis of the sleep stages. The responses to the first five stimuliin the beginning of each block were rejected. For further analysisthe data from active and quiet sleep were combined.

The data were offline filtered (zero-phase) from 0.5 to 20 Hzwith 24 dB attenuation in the stop band. The data were then di-vided into epochs of 700 ms, starting 100 ms prior to stimulus on-set. The epochs were baseline corrected to the 100 ms silentinterval preceding each syllable. Any epochs in which the EEGamplitude exceeded ±200 lV in channels F3, F4, C3, Cz, C4 or inthe channels monitoring eye movements were rejected. Data foreach deviant type were separately averaged, and the correspond-ing deviants from /te:/ and /pi:/ blocks were averaged together.Furthermore, as stimuli of greater intensity tend to elicit largerobligatory responses (e.g. Hegerl and Juckel, 1993), we averagedthe increases and decreases of intensity together to form a com-mon intensity deviant, as in previous studies utilizing identicalstimuli (Pakarinen et al., 2009; Lovio et al., 2009). The same wasdone for the F0 deviants. For the multifeature group, the minimum

number of accepted epochs was 99 for the consonant identity(median 229, mean 213), 102 for the F0 (median 203, mean 215),100 for the intensity (median 233, mean 217), 101 for the vowelduration (median 231, mean 218) and 97 for the vowel identity(median 223, mean 211). For the oddball group, the minimumnumber of accepted epochs was 48 for the vowel duration deviant(median 93, mean 89) and 96 for the vowel identity deviant (med-ian 96, mean 98).

To locate the latencies of interest, temporal PCA (tPCA) wasused (see, e.g., Dien, 1998; Leppänen et al., 2010), separately forthe multifeature and oddball groups. PCA is a method where a smallnumber of orthogonal variables (the principal components) are ex-tracted from the data. The first principal component explains themaximum amount of the variance in the data and each subsequentPCA component is formed to explain the maximum amount of theremaining variance, after discounting the variance explained bythe previous components. For tPCA, mean amplitudes in successive10 ms windows between �100 ms and 600 ms were used as vari-ables (a total of 70) and the ERPs recorded from different elec-trodes, stimuli and participants were used as cases. This resultedin 450 cases for the multifeature group (5 electrodes, 6 stimuli, 15participants) and 195 cases for the oddball group. The principalcomponents were rotated using the Promax rotation (see, e.g., Dienet al., 2005). Further statistical analyses were conducted for theoriginal averaged ERPs using the mean amplitude values fromthe latencies of interest as indicated by the tPCA.

Difference signals for each stimulus type were obtained by sub-tracting the response to the standard stimulus from that to thedeviant stimulus. As expected, the difference signals in a largemajority of the infants had a positive polarity (called positiveresponders from now on). However, a minority of infants in bothoddball and multifeature groups had large negative deflections(called negative responders from now on) to all deviant types in-stead. In order to assess whether it was statistically justifiable todivide the participants into two groups and that the difference be-tween the responder types was not merely due to researcher bias, acluster analysis was conducted. In the k-means cluster analysis theMMR amplitudes for different deviant types on 7 electrodes (F3, F4,C3, Cz, C4, P3, P4) were used as variables (MMRs to vowel durationand vowel identity for the oddball group, and MMR amplitudes toconsonant identity, F0, intensity, vowel duration and vowel iden-tity for the multifeature group). No other factors were included inthe cluster analysis.

The cluster analysis divided the participants of oddball and mul-tifeature groups into two separate responder types; one having pre-dominantly positive MMRs (positive responders, N = 11 for themultifeature group and N = 10 for the oddball group) and the otherhaving predominantly negative MMRs (negative responders). Thedata for the positive responders was analyzed further; no statisti-cal analyses were conducted for the negative responders due tosmall group size (4 out of 15 in multifeature and 3 out of 13 in odd-ball group).

To see if the MMRs were statistically significant, the MMRamplitudes were tested by comparing the mean amplitudes inthe latencies of interest to zero using two-tailed t-tests, separatelyfor both multifeature and oddball groups. To study the differencesbetween the oddball and multifeature groups, mixed model ANO-VA with Group (multifeature, oddball) as the between-group andStimulus (vowel duration, vowel identity) and Electrode (F3, F4,C3, Cz, C4) as the within-subject factors was used. P-electrodeswere removed from further analysis due to poor signal quality. Dif-ferences in frontality and laterality between the groups were stud-ied using a mixed model ANOVA with Group (multifeature,oddball) as the between-group and Stimulus (vowel duration, vo-wel identity), Frontality (frontal, central), and Laterality (left, right)as the within-subject factors, separately for each latency of inter-

Table 1Latency ranges for principal components 1, 2 and 3, and the amount of total varianceexplained by the temporal principal components for both multifeature and oddballgroups.

Component (ms) Multifeature group Oddball group

Latencyrange (ms)

Varianceexplained (%)

Latencyrange (ms)

Varianceexplained (%)

PC1 (350–600) 360–600 51.3 320–600 56.7PC2 (50–200) 50–190 19.2 70–230 20.1PC3 (200–400) 220–400 9.1 190–400 6.4

E. Partanen et al. / Clinical Neurophysiology 124 (2013) 1578–1585 1581

est. For the deviant types not presented in the oddball paradigm,frontality and laterality was assessed with an ANOVA with Stimu-lus (consonant identity, F0, intensity), Frontality (frontal, central),

Vowel identity

Vowel duration

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PC3 PC1

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EOG

EOG

Fig. 1. MMR waveforms as an average of F3, F4, C3, Cz, and C4 electrodes for vowel duramultifeature and oddball groups (left column). In the EOG panel, the solid line denotes vertlatencies of interest, reflected by principal components (PC) 3 and 1, are marked in gray inon the right. Statistically significant MMRs (p < 0.05) are marked with an asterisk.

and Laterality (left, right) as the within-subject factors, separatelyfor each latency of interest. Differences between MMRs to differentdeviant types were analyzed using a mixed model ANOVA withStimulus, Latency of interest and Electrode as within-subject fac-tors, separately for both groups.

Greenhouse-Geisser correction was used in all ANOVAs (onlycorrected values are reported). In post hoc tests Bonferroni correc-tion was used to correct for multiple comparisons (only correctedvalues are reported). The Bonferroni-corrected values for post hoctests are reported in format p � n < a, where n is the correctioncoefficient. We also tested whether the infants in oddball and mul-tifeature groups and positive and negative responders were differ-ent from each other with regard to background variables (GA,sleep stages, birth weight, APGAR-score, age which infant partici-pated in the EEG experiment) using two-tailed t-tests, corrected

−3

−1.5

0

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3PC3 (220-400 ms) PC1 (360-600 ms)

PC3 (190-400 ms) PC1 (320-600 ms)

C3 (220-400 ms) PC1 (360-600 ms)

C3 (190-400 ms) PC1 (320-600 ms)

tion and vowel identity deviants from the infants eliciting positive MMRs from theical EOG channel and the dotted line the horizontal EOG channel. The time ranges of

the MMR waveform. MMR distributions in the latency ranges of interest are shown

1582 E. Partanen et al. / Clinical Neurophysiology 124 (2013) 1578–1585

for inequality of variances. The effects of sleep stages on the ERPswere analyzed using Pearson correlation where the amount of timethe infants spent in active sleep was correlated with MMR ampli-tudes, separately for both groups. The effects of background factors(gestational age, APGAR score, birth weight) on MMR amplitudeswas also analyzed in similar manner. Due to large number of cor-relation tests conducted (latencies of interest � number of stim-uli � number of electrodes), a p-value of 0.01 was consideredsignificant.

3. Results

The PCA resulted in 7 components, out of which 3 componentsshowed factor loadings of 0.8 or greater (after rotation) and wereselected for further analysis. These 3 components accounted for79.6% of the variance in the multifeature and 83.2% in the oddballgroup. See Table 1. As principal components were very similar be-tween the groups both in terms of latency range and explained var-iance, the data from the latencies of interest indicated by the PCAswere assumed to reflect similar underlying neural processes. Assuch, the data from the latency range of PC1 in the multifeaturegroup was compared to the data from the latency range of PC1 inthe oddball group, and similar approach was adopted for the other

Consonant identity

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*

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EOG

Fig. 2. MMR waveforms as an average of F3, F4, C3, Cz, and C4 electrodes for consonantfrom the multifeature group (left column). In the EOG panel, the solid line denotes verticlatencies of interest, reflected by principal components (PC) 3 and 1, are marked in gray inon the right. Statistically significant MMRs (p < 0.05) are marked with an asterisk.

latencies of interest as well. See Figs. 1 and 2 for the MMRs andscalp distribution of the multifeature and oddball groups. Similarfigures for the negative responders are provided as SupplementaryFigs. S1 and S2.

Statistically significant MMRs were found for consonant iden-tity, intensity, vowel duration and vowel identity deviants in themultifeature group and for both vowel identity and vowel durationdeviants in the oddball group. F0 deviant did not elicit statisticallysignificant MMRs (see Table 2 for the summary of the results). Acomparison of MMR amplitudes between the multifeature and odd-ball groups yielded a group x frontality interaction (F1,19 = 6.059,p < 0.026). Post hoc tests showed that the infants in the oddballgroup had larger responses at frontal electrodes than the oddballgroup in the 200–400 ms time range as reflected by the PC3 com-ponent (1.500 vs 0.697, F1,19 = 4.630, p < 0.044). The analysis on theeffects of sleep stages on MMR amplitudes showed that the infantsin the oddball group had larger MMRs for the duration deviant inthe 70–240 ms latency range the more time they spent in activesleep (electrode F4; r = 0.813, p < 0.005). No effects of backgroundfactors (gestational age, APGAR score, birth weight) on MMRamplitudes were found.

The multifeature and oddball groups did not differ from eachother with respects to GA, Apgar score, birth weight or age at mea-

−3

−1.5

0

1.5

3PC3 (220-400 ms) PC1 (360-600 ms)

PC3 (220-400 ms) PC1 (360-600 ms)

PC3 (220-400 ms) PC1 (360-600 ms)

identity, frequency and intensity deviants from the infants eliciting positive MMRsal EOG channel and the dotted line the horizontal EOG channel. The time ranges of

the MMR waveform. MMR distributions in the latency ranges of interest are shown

Table 2Statistically significant MMRs for the positive responders in multifeature and oddball groups. Consonant identity, F0, and intensity deviants were not used in the oddballexperiment. Amplitudes and standard errors of the mean (S.E.M.) are reported in brackets.

Latency of interest

50–200 ms (PC2) 200–400 ms (PC3) 350–600 ms (PC1)

Consonant identity Multifeature group C3: t(10) = 2.28*

(1.41 ± 0.62 lV)F3: t(10) = 2.62*

(1.86 ± 0.71 lV)

C3: t(10) = 3.09*

(1.73 ± 0.56 lV)

Cz: t(10) = 3.59**

(1.85 ± 0.53 lV)F0 Multifeature groupIntensity Multifeature group F3: t(10) = 2.30*

(2.61 ± 0.79 lV)F3: t(10) = 2.52*

(1.53 ± 0.61 lV)

C3: t(10) = 2.27*

(1.42 ± 0.63 lV)C3: t(10) = 2.52*

(1.45 ± 0.57 lV)Vowel duration Multifeature group C3: t(10) = 3.08*

(1.88 ± 0.61 lV)F3: t(10) = 3.85**

(2.18 ± 0.57 lV)

C4: t(10) = 2.55*

(1.74 ± 0.68 lV)F4: t(10) = 2.41*

(1.81 ± 0.75 lV)

C3: t(10) = 4.03**

(2.93 ± 0.73 lV)

Cz: t(10) = 3.90**

(2.77 ± 0.71 lV)Oddball group Cz: t(9) = 2.67, p = 0.026

(1.82 ± 0.68 lV)Cz: t(9) = 2.46*

(2.05 ± 0.84 lV)Vowel identity Multifeature group C3: t(10) = 3.13*

(2.10 ± 0.67 lV)Oddball group F3: t(9) = 2.75*

(1.76 ± 0.64 lV)

F4: t(9) = 2.63*

(1.70 ± 0.65 lV)

* p < 0.05.** p < 0.01.

E. Partanen et al. / Clinical Neurophysiology 124 (2013) 1578–1585 1583

surement (p > 0.5 for all tests). However, the positive responders inthe oddball group spent more time in active sleep than positiveresponders in the multifeature group (19.6% versus 7.4%;t18 = 2.304, p < 0.045). No further differences were found in sleepstages. No other differences were found in the background vari-ables, except for the negative responders having a tendency for asmaller birth weights than the positive responders, t27 = 1.895,p < 0.076.

4. Discussion

The present study investigated whether the multifeature MMNparadigm involving 5 different types of deviants is feasible forinvestigating speech-sound discrimination in newborns. We foundthat the infants eliciting positive MMRs in the multifeature grouphad statistically significant responses for consonant identity, inten-sity, vowel duration, and vowel deviants whereas no statisticallysignificant MMRs were found for the F0 deviant. The infants elicit-ing positive MMRs in the oddball group had statistically significantresponses for both vowel duration and vowel identity deviants in-cluded in that condition. While some previous studies reportMMRs for pitch changes of a similar magnitude (e.g., He et al.,2009), not all studies found statistically significant MMRs for smallpitch changes (e.g., Novitski et al., 2007). In our study, the non-sig-nificant MMR for pitch changes may be partly due to the multifea-ture paradigm with several deviant types which may be morechallenging for the auditory system than the oddball paradigm(Kujala et al., 2006). Also the fast stimulus presentation rate couldhave affected the results (600 ms SOA). However, the results on thepossible effects of SOA on the MMRs are conflicting, with He et al.(2009), showing no effect of SOA on MMNs for pitch changeswhereas, e.g., Leppänen et al. (1999) and Pihko et al. (1999) report-ing possible effects due to fast SOA on MMNs for duration changes.

Similar tPCA components were elicited by multifeature andoddball paradigms, suggesting that, regardless of the paradigmused, similar speech-sound discrimination processes were en-gaged. However, the responses were in general later in the multi-feature than oddball paradigm. Specifically, the MMRs for vowelduration and vowel identity changes in the oddball paradigm weresignificant in the 190–400 ms latency window whereas those inthe multifeature paradigm were statistically significant in the later360–600 ms latency range. In addition, statistically significantMMRs were found to the duration deviant in the 50–190 ms timerange, but only in the oddball group. The discrepancy may partly re-sult from the higher proportion of active sleep in infants in theoddball group. Namely, sleep stages were shown to affect MMRpolarity and amplitude (e.g., Pihko et al., 2004; Sambeth et al.,2008; Friederici et al., 2002), although not all studies found suchan effect (Martynova et al., 2003). However, differences in sleepstages may not sufficiently explain the differences in MMR laten-cies between the paradigms.

Alternatively, the multifeature and oddball paradigms may gen-uinely elicit differing MMRs in infants, as some studies have shownsuch effects in adults. For example, Huotilainen et al. (1993)showed an attenuation of the MMN response in paradigms includ-ing several change types simultaneously, possibly due to the differ-ent amount of attenuation of the ERP response to the repeatedstandard stimulus (p = 0.9 for the oddball paradigm, 2700 repeti-tions; p = 0.5 for the multifeature paradigm, 1500 repetitions)due to, e.g., habituation, stimulus specific adaptation, or refractori-ness. For instance, in adults it has been shown that increased rep-etition rate diminishes obligatory responses, such as the N1amplitude (e.g., Näätänen and Picton, 1987; Sable et al., 2004).However, the majority of the studies find no such effect (e.g.,Näätänen et al., 2004; Lovio et al., 2009; Pakarinen et al., 2009;Pakarinen et al., 2010). Yet, such a possibility must be taken into

1584 E. Partanen et al. / Clinical Neurophysiology 124 (2013) 1578–1585

account in studies on infants, as whose MMRs have not been pre-viously compared between the oddball and multifeatureparadigms.

In addition to the positive responders, a minority of participantshad MMRs that were negative in polarity. It was shown that infantswith negative responses have shorter RR-period related to less ma-ture vagal tone (Leppänen et al., 2004). The background variablesof the negative and positive responders were otherwise compara-ble, except for the birth weights that tended to be smaller in thenewborns with negative MMRs. Even though no differences inthe gestational ages were found, it is possible that the lower birthweight could be related to some degree of immaturity, which wasshown to affect both basic obligatory responses (e.g., Kurtzberg,1982; Kurtzberg et al., 1995) and the infant change-detection re-sponses (Fellman et al., 2004). In several studies the infants withnegative responses are merely rejected as abnormal (e.g., Carralet al., 2005; Sambeth et al., 2008), and further research is neededto determine why some infants elicit responses with oppositepolarity in comparison to the majority of the group and whetherthe sources for these responses differ.

Our results show that the multifeature paradigm is feasible forstudies evaluating auditory discrimination profiles of newborns toa variety of sound features (consonant identity, syllable frequency(F0), intensity, vowel duration and vowel identity) in a shortrecording time. The two paradigms yielded otherwise consistentresults, except for differences in MMR latencies Therefore, infantstudies focusing on timing related effects should be very cautiousin comparing or equating results from the multifeature and oddballparadigms. The applicability of the multifeature paradigm for in-fant studies is important, since different deficits of auditory pro-cessing may underlie developmental disorders (for a review, seeKujala et al., 2007). For example, dyslexic individuals have smallerthan normal MMNs for pitch changes (Baldeweg et al., 1999; Kuj-ala et al., 2006) and duration changes (e.g., Huttunen-Scott et al.,2008) than their controls. However, a quite different pattern hasbeen found in autism, with enhanced MMNs for pitch changes(Lepisto et al., 2008) and diminished MMNs for duration changes(Lepisto et al., 2005). Furthermore, our results showing thatspeech-sound elicited MMRs can be obtained from infants withthe multifeature paradigm are important since this approach en-ables the effective evaluation of, for instance, the development ofthe language-related long-term memory traces (Näätänen et al.,1997; Cheour et al., 1998; Shestakova et al., 2002). With this par-adigm, both the normal and deviant pattern of discriminationaccuracy of different speech features can be followed up.

Acknowledgements

This study was financially supported by the Academy of Finland(grants 128840, 1135304, and 1135161), ERANET-NEURON projectPANS, the University of Helsinki graduate school grant and theFinnish Cultural Foundation. Special thanks to Ms. Jenni Uimonen,M.Psych, for support and cups.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.clinph.2013.02.014.

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