ORIGINAL PAPER

Source Analysis of Event-Related Potentials During PitchDiscrimination and Pitch Memory Tasks

Suvi Talja • Kimmo Alho • Teemu Rinne

Received: 30 April 2013 / Accepted: 10 August 2013

� Springer Science+Business Media New York 2013

Abstract Our previous studies using fMRI have demon-

strated that activations in human auditory cortex (AC) are

strongly dependent on the characteristics of the task. The

present study tested whether source estimation of scalp-

recorded event-related potentials (ERPs) can be used to

investigate task-dependent AC activations. Subjects were

presented with frequency-varying two-part tones during

pitch discrimination, pitch n-back memory, and visual

tasks identical to our previous fMRI study (Rinne et al.,

J Neurosci 29:13338–13343, 2009). ERPs and their mini-

mum-norm source estimates in AC were strongly modu-

lated by task at 200–700 ms from tone onset. As in the

fMRI study, the pitch discrimination and pitch memory

tasks were associated with distinct AC activation patterns.

In the pitch discrimination task, increased activity in the

anterior AC was detected relatively late at 300–700 ms

from tone onset. Therefore, this activity was probably not

associated with enhanced pitch processing but rather with

the actual discrimination process (comparison between the

two parts of tone). Increased activity in more posterior

areas associated with the pitch memory task, in turn,

occurred at 200–700 ms suggesting that this activity was

related to operations on pitch categories after pitch analysis

was completed. Finally, decreased activity associated with

the pitch memory task occurred at 150–300 ms consistent

with the notion that, in the demanding pitch memory task,

spectrotemporal analysis is actively halted as soon as cat-

egory information has been obtained. These results dem-

onstrate that ERP source analysis can be used to

complement fMRI to investigate task-dependent activa-

tions of human AC.

Keywords Event-related potentials �Auditory cortex � Human � Attention � Pitch

Introduction

In our previous fMRI study (Rinne et al. 2009), we

reported spatially distinct activation patterns in human

auditory cortex (AC) to similar sounds presented during

pitch discrimination and pitch memory tasks. This result

demonstrates that AC activations are not only determined

by physical features of the sounds but also depend strongly

on the characteristics of the listening task (see also Rinne

et al. 2012; Harinen and Rinne 2013; Hickok and Saberi

2012). Current theoretical models assume that auditory

information is processed hierarchically from primary to

higher-order auditory areas (feedforward hierarchy).

However, it is also possible that during active tasks acti-

vations in lower-level auditory areas depend on the output

of higher-level areas (feedback hierarchy, e.g., Ahissar

et al. 2009). Thus, temporal activation patterns could pro-

vide important information on the functional significance

of AC activations during active listening tasks. Despite

high spatial accuracy, the temporal resolution (hundreds of

This is one of several papers published together in Brain Topography

on the ‘‘Special Issue: Auditory Cortex 2012’’.

S. Talja (&) � K. Alho � T. Rinne

Institute of Behavioural Sciences, University of Helsinki,

PO Box 9, 00014 Helsinki, Finland

e-mail: suvi.m.talja@helsinki.fi

K. Alho � T. Rinne

Advanced Magnetic Imaging Centre, Aalto University School of

Science, Espoo, Finland

K. Alho

Helsinki Collegium for Advanced Studies, University of

Helsinki, Helsinki, Finland

123

Brain Topogr

DOI 10.1007/s10548-013-0307-9

milliseconds) of fMRI does not allow one to elucidate the

activation order of different AC areas. In the present study,

we investigated whether the activation patterns measured

with fMRI and associated with pitch discrimination and

pitch memory tasks may also be detected using source

analysis of scalp-recorded event-related potentials (ERPs).

Together with the spatially specific fMRI, source analysis

of ERPs could provide millisecond-scale information on

the spatiotemporal dynamics of activations in AC during

active listening tasks.

While EEG and fMRI measure different aspects of brain

activity (post-synaptic potentials and hemodynamics,

respectively), many studies have suggested that these

methods can be used to investigate the same functional

processes in the brain (Debener et al. 2006; Michel and

Murray 2012). For example, in studies using fMRI and

ERP source analysis, both methods have shown activations

within the retinotopic V1 consistent with the spatial

eccentricity of stimuli (Im et al. 2007; Plomp et al. 2010;

Sharon et al. 2007). The results of these studies suggest

that, given a reasonable signal-to-noise ratio, EEG source

localization accuracy can be expected to be relatively close

to the spatial accuracy of fMRI within 1–4 cm. Further,

previous studies have demonstrated that the magnitude of

ERP and fMRI signals associated with active tasks often

behave similarly. For example, Schubert et al. (2008)

studied the effect of tactile spatial-selective attention on

activations in the primary somatosensory cortex using

simultaneous ERP and fMRI measurements, and reported

that the effects of attentional manipulations on ERP and

fMRI signals were linearly related.

Parallel EEG and fMRI measurements have also been

used to analyze both the spatial and temporal aspects of AC

activations during passive and active conditions (Alain

et al. 2001; Liebenthal et al. 2010; Lin et al. 2006; Mulert

et al. 2004, 2005). Further, a number of previous studies

have used various ERP source analysis techniques to

investigate spatiotemporal activity patterns in AC and

adjacent areas (e.g., Alain et al. 2009; Bourquin et al. 2013;

Butler and Trainor 2012; Degerman et al. 2008; Kreitewolf

et al. 2011; Rinne et al. 2000). Therefore, we hypothesized

that ERP source analysis would be able to detect the strong

and distinct task-dependent modulations of AC activations

observed in our previous fMRI study.

The present experimental design was identical to that

used in our previous fMRI study (Rinne et al. 2009).

Subjects were presented with frequency-varying sounds

during pitch n-back memory, pitch discrimination, and

visual task blocks. In the 1-back, 2-back and 3-back

memory tasks, subjects were required to indicate when a

tone belonged to the same pitch category as the tone pre-

sented one, two or three trials before, respectively. In the

pitch discrimination task, most of the tones had a slight

pitch difference between the first and second part of the

tone and subjects responded to targets in which the parts

had the same pitch. In our previous fMRI study using these

conditions, we found activation enhancements in the

anterior superior temporal gyrus (STG) associated with the

pitch discrimination task, while activations in the posterior

STG and inferior parietal lobule (IPL) were enhanced

during the pitch memory task. In the pitch memory task,

activations in the IPL and insula increased with increasing

task difficulty, whereas task difficulty did not significantly

modulate activations in the pitch discrimination task. Fur-

ther, wide areas of the anterior STG and insula were

associated with decreased activations during the pitch

memory task. In these areas, activations also decreased

with increasing difficulty in the pitch memory tasks. In the

present study, we tested whether these task-dependent

activation patterns can be detected also using source ana-

lysis of scalp-recorded ERPs. We hypothesized that ERP

source analysis would show enhanced activity during

auditory tasks, distinct activity patterns during pitch dis-

crimination and pitch memory tasks, and that task difficulty

would modulate AC activity especially in the pitch mem-

ory task. In particular, we were interested in whether EEG

could provide information on the temporal dynamics of

these task-dependent activations.

Materials and Methods

Subjects

A total of 21 subjects participated in this study. All subjects

were right-handed, reported no history of hearing problems

and had normal or corrected-to-normal vision. None of the

subjects had participated in the previous fMRI study

(Rinne et al. 2009). Four subjects were excluded due to

excessive EEG artifacts or poor contrast in structural MRI.

Thus, 17 subjects (9 female; age range 20–41 years, mean

25.1 years) were included in the analyses. The study pro-

tocol was approved by the Ethics Committee of the

Department of Psychology, University of Helsinki, and a

written informed consent was obtained from all subjects.

Stimuli and Tasks

The experimental design was identical to that of our pre-

vious fMRI study (see Fig. 1 of Rinne et al. 2009). Subjects

were presented with tones of 200 ms in duration (onset-to-

onset interval 800–1,000 ms, 30 ms steps, rectangular

distribution). The tones consisted of two successive 100 ms

parts (each part included 5 ms linear onset and offset

ramps). The tones formed low (lowest frequency 200 Hz),

medium (561 Hz) and high (1573 Hz) pitch categories

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each including six equidistant pitch levels. During training

before EEG acquisition (1–2 h of training in two sessions),

the pitch range within each category was adjusted indi-

vidually for each subject depending on their pitch dis-

crimination ability (highest possible frequencies in the low,

medium and high category were 320, 898 and 2,517 Hz,

respectively). In the pitch discrimination task, the two tone

parts were either identical or the second part was one, two

or three pitch levels (depending on the difficulty level)

lower or higher in pitch than the first part. In the pitch

memory task, the two parts of a tone always had the same

pitch.

The tones were presented in 15 s blocks alternating with

8 s silent breaks. During the breaks, subjects were

instructed to fixate on a white cross presented on a gray

(R 190, G 190, B 190) background. After 2 s the cross was

replaced by nonverbal task instruction symbols. The task

instruction symbols were presented until the end of the

block.

In the pitch discrimination task, subjects were required

to indicate by pressing a button with their right hand when

the tone parts had the same pitch. In the 1-back, 2-back,

and 3-back pitch memory tasks, subjects pressed the button

when tone belonged to the same pitch category as the one

presented one, two or three trials before, respectively. In

the visual task, subjects were instructed to ignore the

sounds and to indicate when the flickering gray rectangle

(duration 200 ms; onset-to-onset interval 800–1,000 ms,

30 ms steps, rectangular distribution; R 186, G 186, B 186)

underlying the task instruction symbols was slightly

brighter (R 194, G 194, B 194). The sounds presented

during each visual task block were identical to the sounds

presented during one of the auditory tasks. There were 2–4

targets in each block.

Sounds were delivered diotically via headphones

(MDR-7509HD, Sony Corporation, Tokyo, Japan) at ca.

60 dB SPL above hearing threshold. The hearing threshold

was determined using the sounds of the experimental tasks

immediately before the EEG measurement. Visual

instructions and stimuli were presented on a computer

screen placed ca. 1.5 m in front of the subject. The

experiment was controlled with Presentation software

(Neurobehavioral Systems, Albany, CA, USA). For each of

the ten conditions (two auditory tasks with three difficulty

levels, visual task with sounds of the memory task, and

three visual task conditions with sounds of each discrimi-

nation task difficulty level) 16 blocks were presented.

EEG Acquisition

Continuous EEG (sampling rate 512 Hz, bandwidth

128 Hz) was recorded with a Biosemi ActiveTwo amplifier

system (Biosemi, Amsterdam, The Netherlands) from 136

electrodes. In addition to the 128 electrodes of a Biosemi

electrode cap (ABC montage), electrodes were attached to

the left and right outer canthi, anterior to the left and right

preauricular points, at the left and right mastoids, below the

left eye, and at the tip of the nose (Fig. 1, bottom).

Immediately after the experiment, the locations of all

electrodes were measured relative to the nasion and pre-

auricular points using a Fastrack 3D digitizer (Polhemus,

Colchester, VT, USA) and 3D Space software (Neuroscan

Labs, El Paso, TX, USA.

Analysis of the Behavioral Data

In all tasks, a button press within 200–1300 ms after target

onset (i.e., onset of the first or second part of the target tone

in the pitch memory and pitch discrimination task,

respectively, or from the onset of a visual target) was

accepted as a hit. Other responses were considered as false

alarms. Hit rates (HRs; the number of hits divided by the

number of targets), false alarm rates (FaRs; the number of

false alarms divided by the number of nontargets), and hit

reaction times (RTs) were calculated for each subject and

condition. HRs and FaRs were used to compute d0 values

[index of stimulus detectability, d0 = Z(HR) - Z(FaR)].

The effect of Task Difficulty (3 levels) on performance was

analyzed using one-way analyses of variance (ANOVAs)

for repeated measures. In ANOVAs, Greenhouse–Geisser

correction was used when appropriate (e \ 0.75).

EEG Preprocessing and Averaging

Noisy electrodes (1–10 on 11 subjects, mean 2 electrodes)

were rejected from further analyses after a visual inspec-

tion. For scalp-level analyses, the data of these electrodes

were replaced by interpolating the data of the surrounding

electrodes (distance \5 cm) using inverse distance

weighting. In addition to these noisy electrodes, the data

from the electrode on the tip of the nose were not used in

the source analysis.

Auditory ERPs were computed using the MNE software

(version 2.7, http://martinos.org/mne). Data were first re-

referenced to common average and passband-filtered

(0.5–40 Hz). Continuous EEG data were then divided into

900 ms epochs (-100 to 800 ms relative to tone onset).

Baseline for the waveforms was defined as the mean

voltage over the 100 ms period before tone onset. First two

epochs of each task block, epochs associated with a target

in the pitch discrimination task, epochs associated with a

button press (-300 to 1,100 ms from stimulus onset), and

epochs with extensive extracerebral artefacts ([120 lV

amplitude changes on any electrode) were excluded.

Finally, the epochs were averaged separately for each

condition (mean 170 epochs, range 92–228).

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Analysis of ERP Scalp Potential Distributions

Two different statistical comparisons were conducted to

analyze the scalp potential distributions during pitch

discrimination, pitch memory and visual tasks: (1) channel-

wise repeated-measures t tests or ANOVAs with fac-

tor Difficulty (3 levels), and (2) topographic ANOVA

(TANOVA, 5,000 permutations; Manly 1991) based on

global map dissimilarity. Global map dissimilarity is a

measure of topographic differences of scalp potential maps

(Lehmann and Skrandies 1980). The results were consid-

ered significant if a p value less than 0.05 was detected on

at least 11 consecutive time points (21.5 ms). In ANOVAs,

Greenhouse–Geisser correction was used when appropriate

(e\ 0.75).

Analysis of ERP Sources

Inner skull, outer skull and scalp surfaces were extracted

from T1-weighted MRI images (3.0 T, voxel matrix

256 9 256 9 256; slice thickness 1.0 mm, in-plane reso-

lution 1.0 9 1.0 mm2) using the BET tool of FSL (version

4.1, http://fsl.fmrib.ox.ac.uk) and decimated to 5,120 ver-

tices. These surfaces were used to construct individual

three-layer boundary-element models (BEM; conductivities

0.3, 0.006 and 0.3 S/m). White matter surface was extracted

with FreeSurfer (version 4.5; Fischl et al. 1999a) and dec-

imated to 5,000–7,000 vertices using ca. 5 mm spacing.

This surface defined the source space.

ERP sources were computed in the MNE software using

cortically distributed minimum-norm estimation (MNE;

Hamalainen and Ilmoniemi 1984) with depth weighting

(weighting parameter 2.0) and a loose orientation con-

straint (weighting parameter 0.2; Dale and Sereno 1993).

Noise covariance was estimated based on the EEG mea-

sured during the 8 s silent periods between the task blocks.

The noise covariance matrix was diagonalized and scaled

by the number of samples in each condition.

In order to compare ERP source estimates across sub-

jects, the individual cortical surfaces were anatomically

normalized on the basis of the cortical gyral and sulcal

patterns (FreeSurfer; Fischl et al. 1999b). To compensate

for anatomical differences between subjects, individual

MNEs were spatially smoothed. For seven successive

iterations, each vertex (of the white matter surface defining

the source space) was assigned the average value of that

vertex and adjacent vertices. To reduce ghost sources and

bias related to the varying amount of epochs in different

task conditions, mean MNE during the 100 ms pre-stimu-

lus period was set as baseline (Wendel et al. 2009).

Auditory taskVisual task (same sounds)Difference (auditory task - visual task)

A

P

RL

-1 V

1 V800 ms

Pitch discrimination vs. visual task Pitch memory vs. visual task

P2 P2

N1 N1

C

Fig. 1 The left panel shows grand average (N = 17) ERPs to

identical tones presented during the pitch discrimination and visual

tasks, and their difference. The right panel shows the comparison for

the pitch memory and visual tasks. ERPs are shown at nine electrodes.

A schematic illustration of the electrode layout (136 electrodes) and

scalp locations of the nine selected electrodes are shown at the

bottom. A anterior, C central, P posterior, L left, R right

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Statistical analyses were carried out as follows: First, we

studied the mean MNEs during auditory and visual tasks

over the interval 100–700 ms from tone onset that showed

significant task-dependent effects in the scalp-level analy-

ses. The mean MNEs during the pitch discrimination and

pitch memory tasks were compared with the mean MNEs

during the visual task with identical sounds using repeated-

measures t tests. Second, the temporal dynamics of source

activity during the auditory tasks were investigated using

repeated-measures t tests to compare MNEs at each time

point during the pitch discrimination and pitch memory

tasks with MNEs during the visual task with identical

sounds. Third, task-dependent effects were similarly

investigated by comparing MNEs during the pitch dis-

crimination and pitch memory task with each other. Fourth,

the effect of task difficulty on MNEs at each time point was

examined using repeated-measures ANOVAs with factor

Task Difficulty (3 levels; Trujillo-Ortiz 2004, 2006). In

ANOVAs, Greenhouse–Geisser correction was used when

appropriate (e \ 0.75). In all tests, the result was consid-

ered significant if the p-value at the source point was less

than 0.05 during at least 11 consecutive time points

(21.5 ms). For illustration, the results of these statistical

tests were first collapsed into 50 ms bins so that each

source point in a bin was assigned the most significant

value during that bin, and, finally, the results were trans-

formed to flattened 2D cortical surfaces showing the areas

of AC and adjacent IPL (see Fig. 5, top).

Results

Performance

Subjects performed the demanding auditory tasks as

instructed (for each subject, average d0 in auditory tasks

[1.9). Mean HRs in the pitch discrimination, pitch mem-

ory, and visual tasks were 73, 64 and 85 %, respectively.

Mean FaRs were 0.93, 1.96 and 0.23 %, mean d0 values

2.79, 2.60 and 3.62, and mean RTs 536, 561 and 519 ms,

respectively. In both pitch discrimination and pitch mem-

ory tasks, HRs and d0 values decreased and RTs increased

linearly (F2,32 [ 8.9, p \ 0.001, and linear contrast

F1,16 [ 16.4, p \ 0.001, for each test) with increasing task

difficulty.

ERPs

Grand average ERPs to sounds presented during different

conditions are shown in Fig. 1. Sounds elicited N1 and P2

responses peaking at 100 and 180 ms, respectively, in all

conditions. Scalp potential distributions of ERPs to sounds

presented during the pitch discrimination, pitch memory

and visual tasks, and scalp potential difference maps

(auditory task–visual task with the same sounds) are plot-

ted in Fig. 2. The scalp distributions suggest that auditory

tasks modulated ERPs to sounds and that these modulations

were different during pitch discrimination and pitch

memory tasks. This was confirmed by the results of sta-

tistical analyses shown in Fig. 3. Channel-wise t tests and

TANOVAs revealed significant differences between ERP

scalp distributions to sounds presented during pitch dis-

crimination and visual tasks at 60–120 and 160–700 ms

from tone onset (top left). Correspondingly, scalp distri-

butions during pitch memory and visual tasks differed at

200–700 ms (top right). In a direct comparison, the ERP

distributions during pitch discrimination and pitch memory

tasks were significantly different at 180–700 ms (bottom

left). Comparison of responses to sounds used in pitch

discrimination and pitch memory tasks presented during

the visual task showed a significant difference only at

180–220 ms (not shown).

The effects of discrimination and memory task difficulty

on ERPs were less pronounced than the differences

between the tasks. In the pitch discrimination task, no

systematic task difficulty effects were detected (not

shown). In the pitch memory task, task difficulty modu-

lated ERP scalp distributions but the results of the channel-

wise ANOVAs and TANOVAs were not fully consistent

(Fig. 3, bottom right).

ERP Sources

MNEs indicated widespread neural activity in the supra-

temporal cortex to sounds presented during all tasks. To

demonstrate the auditory-specific nature of this activity,

Fig. 4 illustrates MNEs for the auditory N1 (100–120 ms

from tone onset) to sounds presented during the visual task

(left), for the visual ERP (200–220 ms from picture onset)

to pictures presented during the visual task (middle), and

for the motor ERP (0–20 ms from button press onset)

elicited by button presses measured during the visual task

(right) on inflated cortical surfaces.

Figure 5 shows a comparison of the mean MNEs

(100–700 ms) during the pitch discrimination and pitch

memory tasks on flattened 2D cortical surfaces. Both tasks

were associated with enhanced AC activity relative to the

visual task (identical sounds; t test, N = 17, uncorrected

p \ 0.05). In the pitch discrimination task, enhanced

activity was detected in the insula, anterior STG, and

posterior STG (red and yellow). In the pitch memory task,

enhanced activity occurred in the posterior STG and IPL

(blue and yellow). In general, these activation patterns are

quite similar to those seen in our previous fMRI study

using identical pitch tasks (Fig. 5, bottom; Rinne et al.

2009).

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The time course of MNEs associated with the pitch dis-

crimination and pitch memory tasks is illustrated in Fig. 6. In

the pitch discrimination task (left), some scattered activity

increases were detected during 0–200 ms. More systematic

activity increases started in the time window 200–250 ms

(first significant difference in this time window at 210 ms),

Pitch discrimination DifferenceVisual (same sounds)

Pitch memory Visual (same sounds) Difference

easy medium hard Discreasy

Discrmedium

Discrhard

1-back 2-back 3-back n-back

100 ms

200 ms

260 ms

300 ms

400 ms

600 ms

100 ms

200 ms

260 ms

300 ms

400 ms

600 ms-1 V

1 V

Fig. 2 Grand average (N = 17) ERP scalp potential distributions in

the pitch discrimination, pitch memory and visual tasks at six time

points. Top left Scalp potential distributions for the easy, medium and

hard pitch discrimination tasks. Top middle Scalp potential distribu-

tions for the same sounds presented during the visual task. Top right

Difference between the pitch discrimination and visual tasks. Bottom

Scalp potential distributions in the pitch memory task, visual task

(same sounds), and their difference. Each map shows a 20 ms average

beginning at the indicated latency

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and continued until about 400 ms, in the bilateral posterior

STG and left IPL. Further, enhanced activity was detected in

the left anterior STG and insula (350–700 ms), in the right

anterior STG (300–450 ms), and in the right posterior STG

and IPL (450–700 ms). The pitch memory task was associ-

ated with a different activity pattern (right). First, activity

decreased relative to the visual task in the left anterior STG

and HG at 200–300 ms (first significant difference in this

time window at 230 ms). Then, activity increased in the left

IPL at 500–650 ms and in the right IPL at 250–700 ms.

Direct comparisons of MNEs to sounds presented during

the pitch discrimination and pitch memory tasks are shown

in Fig. 7 (left). During pitch discrimination, source activity

was stronger in the left anterior STG, posterior STG and

IPL at 200–400 ms (first significant difference in this time

window at 210 ms), whereas the pitch memory task was

associated with enhanced activity in the bilateral IPL at

500–700 ms. Comparison of MNEs to sounds of the pitch

discrimination and memory tasks presented during the

visual task (not shown) revealed enhanced activity to

sounds of the discrimination task in the left IPL at

400–600 ms and in the right IPL at 300–450 ms, and

decreased activity in the left HG and PT at 200–300 ms

(first significant difference in this time window at 240 ms).

As the visual task was identical in both cases, these activity

differences have to be due to the small differences in the

sound sequences of the pitch discrimination and pitch

memory tasks (no within-tone pitch changes in the pitch

memory task). Nevertheless, these stimulus-dependent

effects cannot account for the much stronger task-depen-

dent differences.

As expected, AC activity during the pitch memory task

was modulated by task difficulty. The main effect of Task

Difficulty was significant in the left anterior STG and HG

at 150–250 ms (first significant difference in this time

window at 155 ms) and 400–650 ms and in the bilateral

IPL at 500–650 ms (not shown). Source activity was

weaker in the bilateral anterior STG and insula (150–250

and 550–700 ms) and stronger in the IPL (e.g., at

550–650 ms) during 3-back than 1-back tasks (Fig. 7,

right).

Discussion

In the present EEG study, we used the experimental design

of our previous fMRI study to investigate whether source

analysis allows us to detect the same task-dependent acti-

vation patterns in human AC using both fMRI and EEG. If

feasible, EEG measurements could be used to test func-

tional hypotheses on the temporal behavior of these acti-

vations. We found that the pitch discrimination and pitch

memory tasks elicited significant task-dependent effects on

the scalp-measured ERPs. Importantly, these task-depen-

dent ERP effects were associated with distinct activation

patterns in AC quite similar to those in our previous fMRI

results. First, like in the previous fMRI study, in the present

pitch discrimination task, activation enhancements were

detected in the insula, anterior STG and posterior STG,

whereas in the pitch memory task activation enhancements

occurred mainly in more posterior areas of STG and IPL

(Figs. 5, 6, 7). In general, this pattern of activations (i.e.,

0 200 400 600 800 ms

R

L

C

A

PChannel-wiset-test

Discrimination vs. memory Pitch memory difficulty(same sounds)

Channel-wiseANOVA

TANOVA

TANOVA

Pitch discrimination vs. visual(same sounds)

Pitch memory vs. visual(same sounds)

TANOVA

TANOVA

Channel-wiset-test

Channel-wiset-test

Fig. 3 Statistical analysis

(N = 17) of scalp-level effects.

Each panel shows the results of

channel-wise repeated-measures

t tests or repeated-measures

one-way ANOVAs (factor

Difficulty, 3 levels; for channel

grouping see Fig. 1) and

TANOVAs. The results of these

tests were considered significant

if a p value less than 0.05 was

detected on at least 11

consecutive time points

(21.5 ms). Red and blue encode

the right and left tails of the

t test, respectively (e.g., time

points in which pitch

discrimination [ visual are

shown in red) (Color figure

online)

Brain Topogr

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anterior activations during pitch discrimination and pos-

terior activations during pitch memory) is consistent with

the results of our previous fMRI study. Second, activity in

wide areas extending from insula to anterior and posterior

STG decreased during the pitch memory tasks (Fig. 6,

right). Consistently, in our previous fMRI study, similar

areas showed decreased activations during the n-back

memory task. Third, in the pitch memory task, activity in

the insula, anterior/middle STG and IPL were modulated

by task difficulty (Fig. 7, right). Although increasing dif-

ficulty decreased performance in both tasks, task difficulty

did not significantly modulate activity in the pitch dis-

crimination task. These task difficulty effects are in line

with the results of our previous fMRI study. Together these

results strongly suggest that EEG source analysis is able to

detect the same task-dependent activations in the AC as

fMRI.

Scalp-Level Differences Between Pitch Discrimination

and Pitch Memory Tasks

The present ERPs were strongly dependent on whether the

subjects performed the pitch discrimination or the pitch

memory task. For example, at 260 ms the scalp maps were

strikingly different during the two tasks (Figs. 2, 3). This

difference cannot be explained by a general attention effect

or by feature-specific attention as both tasks required

focused auditory attention and processing of pitch infor-

mation. Instead, these modulations are due to differences in

the processing required to perform the pitch discrimination

S1

S2

S3

S4

S5

S6

Auditory ERP (100–120 ms) Visual ERP (200–220 ms) Motor ERP (0–20 ms)Left Right

70 100%

Left Right Left Right

30 70 100%Mean (N = 17)

Fig. 4 Source activity of auditory, visual and motor ERPs. Top six

rows MNEs (individual inflated cortical surface; highest 70 %) of six

subjects to sounds (100–120 ms from tone onset), visual stimuli

(200–220 ms from picture onset), and motor responses (0–20 ms

from button press) measured during the visual task. Bottom Mean

(N = 17, highest 30 %) MNEs in each condition (FreeSurfer standard

brain surface)

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(e.g., enhanced spectrotemporal processing) and the cate-

gorical pitch n-back memory tasks (e.g., categorical pro-

cessing and memory load). Typically, previous ERP studies

have used simple tasks to control for (i.e., to subtract out)

vigilance and attention effects, or to direct selective

attention (e.g., attend to pitch or location) and, to our

knowledge, only a few studies have compared ERPs during

two or more distinct auditory tasks performed on the same

sound feature in order to investigate the task-dependency

of auditory activations (Bonte et al. 2009; Conley et al.

1999; Flinker et al. 2011; Muller-Gass and Schroger 2007;

Sussman et al. 2002). For example, Muller-Gass and

Schroger (2007) investigated the effect of task-irrelevant

auditory changes (distraction) on auditory attention. While

their study focused on ERPs to auditory deviants, they also

reported ERPs to identical standard sounds presented dur-

ing duration discrimination and 1-back duration memory

tasks. Consistent with the present results, they found that

the duration discrimination task was associated with fron-

to-central negativity at 200–460 ms, whereas the 1-back

duration task was associated with positivity at parietal sites

at 360–460 ms.

Source-Level Effects

In the present study, we used cortically constrained MNEs

to analyze the brain sources of scalp-recorded auditory

ERPs. We also estimated the sources of visual and motor

ERPs recorded during the visual task. As expected, the

visual and motor ERPs were associated with activity in the

visual cortex and in the motor areas in and around the

central sulcus, respectively (Fig. 4). These results demon-

strate that we were able to estimate the brain sources of

scalp-recorded auditory ERPs with a reasonable accuracy.

MNEs indicated that activity elicited by auditory stimuli

in AC was, in general, enhanced during auditory tasks as

compared with the visual task. This is consistent with the

results of previous EEG, electrocorticography (ECoG),

magnetoencephalography (MEG) and fMRI experiments

showing stronger AC activations to attended than unattended

Pitch discrimination > Visual (same sounds)

Pitch memory > Visual (same sounds)

Pitch discrimination > VisualPitch memory > Visual

EEG (mean MNE at 100–700 ms)

fMRI (Rinne et al. 2009)

Both

Both

Inflated Spherical Flattened

Insula

HG IPL

IPLIPL In

sula HG

STG

IPL

IPLIPL

Anatomical transformation

RightLeft

10 cmDistance along the STG

anterior posterior

STG

Fig. 5 Top The cortical

surfaces of each subject were

inflated to a sphere, aligned in

spherical space, and flattened to

2D. Data analysis focused on a

cortical patch including AC and

adjacent areas (white rectangle).

Second row Anatomical

landmarks in the left and right

hemisphere AC patches. STG

superior temporal gyrus, HG

Heschl’s gyrus, IPL inferior

parietal lobule (angular gyrus

and supramarginal gyrus).

Bottom two rows Task-

dependent AC activations in the

present EEG (N = 17, mean

MNE at 100–700 ms,

uncorrected p \ 0.05) and in

our previous fMRI study using

the same stimuli and paradigm

(N = 17, Z [ 2.3, cluster-

corrected p \ 0.05; Rinne et al.

2009) (Color figure online)

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Left Right Left Right

Pitch discrimination vs. visual(same sounds)

Pitch memory vs. visual(same sounds)

0

100

200

300

400

500

600

700

Discr > Vis (discr)

Vis (discr) > DiscrMemory > Vis (memory)

Vis (memory) > Memory

Tim

e fr

om s

ound

ons

et (

ms)

p < 0.01

p < 0.01

p < 0.05

p < 0.05

p < 0.01

p < 0.01

p < 0.05

p < 0.05

Fig. 6 Time course of task-dependent activity. Left panel Compar-

ison of MNEs to the same tones presented during the pitch

discrimination and visual task. For each 50 ms time window, the

time point with the most significant p-value is shown (N = 17,

p \ 0.05 for at least 21.5 ms). Right panel The same comparison for

the pitch memory task

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123

Left Right Left Right

ksat yromem hctip tsedrah .sv tseisaEyromem .sv noitanimircsiD(same sounds)

0

100

200

300

400

500

600

700

Discr - Vis > Memory - Vis

Memory - Vis > Discr - Vis

3-back > 1-back

1-back > 3-back

Tim

e fr

om s

ound

ons

et (

ms)

p < 0.01

p < 0.01

p < 0.05

p < 0.05

p < 0.01

p < 0.01

p < 0.05

p < 0.05

Fig. 7 Comparison of MNEs to tones presented during the pitch

discrimination (pitch discrimination vs. visual) and the pitch memory

(pitch memory vs. visual) tasks (left), and the comparison between

1-back and 3-back pitch memory tasks (right). For each 50 ms time

window, the time point with the most significant p-value is shown

(N = 17, p \ 0.05 for at least 21.5 ms)

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123

sounds (Alho et al. 2012; Bidet-Caulet et al. 2007; Da Costa

et al. 2013; Degerman et al. 2008; Halgren et al. 2011; Jemel

et al. 2003; Linden 2005; Neelon et al. 2011; Petkov et al.

2004; Rif et al. 1991; Ross et al. 2010; Soltani and Knight

2000). However, in the present study, we also found that the

ERP source patterns were different during two pitch tasks

performed on similar frequency-varying tones (Figs. 5, 6, 7).

During the pitch discrimination task, increased activity

occurred in more anterior temporal and insular areas,

whereas during the pitch memory task activity enhancements

were detected in more posterior areas of the STG and IPL.

The pitch memory task was also associated with decreased

activity in the anterior STG, where activity also decreased

with increasing n-back difficulty, and with increased activity

in the IPL. In general, these results match quite well with

those of our previous fMRI study (Rinne et al. 2009). Thus,

the present results strongly suggest that it is possible to study

the same task-dependent activations with EEG and fMRI.

In our previous fMRI study using the same experimental

design (Rinne et al. 2009), we observed stronger activa-

tions in the anterior STG during pitch discrimination than

during pitch memory and visual tasks. This activation

enhancement associated with the discrimination task could

be because the comparison of two similar sounds is likely

to require more detailed and thorough processing of spec-

trotemporal information than the pitch n-back memory

task. In the present EEG study, enhanced activity in the

anterior STG during pitch discrimination started at ca.

300 ms from tone onset (Fig. 6, left). Based on literature, it

can be estimated that an accurate pitch is obtained within

the first 200–300 ms (e.g., Butler and Trainor 2012; Chait

et al. 2006; Massaro et al. 1976; Murray and Spierer 2009;

Naatanen and Winkler 1999). Thus, the temporal pattern of

the present MNEs suggests that the pitch discrimination

task enhances AC activations after the pitch of the first part

of a tone has already been obtained. Given the fact that the

tones constantly varied in pitch, it seems unlikely that the

pitch discrimination task would enhance the analysis of the

second but not the first part of a tone. Therefore, the present

results suggest that these activation modulations are not

due to enhanced pitch processing as such but rather due to

comparison of the first and second part of the tone.

In our previous fMRI study (Rinne et al. 2009), we

unexpectedly found that activations in the anterior STG

and insula decreased with increasing task difficulty in the

pitch memory task. In that study, we suggested that this

activation decrement is because default sound processing is

actively halted as soon as the pitch category is resolved in

order to save resources and time for the actual n-back

memory task. The present EEG results suggest that this

effect emerges at 150–200 ms from tone onset (Figs. 6, 7).

Because the ERP is time-locked to the onset of the tone, the

present results support the notion that the activation

decrement is related to processing of stimulus information

and that it is not a general effect associated with the pitch

n-back memory task blocks. Further, the onset of the

activation decrement before the end of the tone is in line

with the idea that processing is actively halted after the

pitch category has been obtained and with the results of

previous studies suggesting that auditory categories are

formed by ca. 200–250 ms after sound onset (Alain et al.

2009; Liebenthal et al. 2010; Murray et al. 2006).

We also found that MNEs were stronger in the IPL

during the pitch memory than during the pitch discrimi-

nation and visual tasks. The enhanced IPL activity emerged

at about 200 ms and continued until 700 ms from tone

onset (Fig. 6). Previous fMRI studies have suggested that

activations in the posterior STG and IPL observed during

auditory n-back memory tasks are due to categorical pro-

cessing and memory required in these tasks (Alain et al.

2010; Brechmann et al. 2007; Harinen and Rinne 2013;

Leung and Alain 2011; Martinkauppi et al. 2000; McAll-

ister et al. 1999; Seidman et al. 1998). In current auditory

models, it is generally assumed that auditory processing is

hierarchically organized so that information processing

proceeds from primary AC to surrounding higher-order

areas (e.g., Hickok and Saberi 2012; Moerel et al. 2012;

Nodal et al. 2012; Rauschecker and Scott 2009; van der

Zwaag et al. 2011; Woods et al. 2010). Thus, these models

predict that higher-order processing in the IPL should

occur only after initial sound analysis in the supratemporal

auditory areas is completed and information for category

formation and categorical operations becomes available,

which is consistent with the present results.

Interestingly, while the pitch discrimination task was

associated with enhanced activity in the anterior STG

(300–700 ms), the enhanced activity actually started with a

more posterior pattern (200–400 ms, Fig. 6). This suggests

that, during the initial phase of the task, also the discrim-

ination task relies on resources in the posterior STG and

IPL. This activity could be related to the storage of infor-

mation for the comparison of the pitch of the first and

second part of the tone.

Conclusions

The present study demonstrates that EEG can be used to

complement fMRI to investigate task-dependent activa-

tions of human AC with high spatiotemporal resolution.

The present results extend our previous fMRI results by

revealing the temporal dynamics of task-dependent acti-

vations: (1) The anterior pattern associated with the pitch

discrimination task begins relatively late and is probably

associated with processing of the second tone part or, more

likely, with the actual comparison process. (2) Onset of the

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posterior activation pattern associated with the pitch n-back

memory task starts at a time point when the pitch analysis

is already likely to be completed (200 ms) and continues

until 700 ms. This is consistent with notion that these

activations are related to operations on pitch categories in

the pitch memory task. (3) The anterior activation decre-

ment associated with the pitch memory task occurs con-

sistently with the notion that spectrotemporal analysis of

the tones is actively halted as soon as category information

is obtained.

Acknowledgments This study was supported by the Academy of

Finland (grants #210587 and #1135900). We thank Mr. Patrik Wik-

man for assistance in data collection.

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