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Leibniz Institute for Neurobiology, Magdeburg, Germany
Submitted 11 November 2005; accepted in final form 16 January 2006
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ABSTRACT |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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). Interpretation of lesion-based investigations, however, has to consider e.g., the possibility of compensation after a brain lesion or that one lesion can effect more than one neural network (Demonet et al. 2005).
In brain-imaging studies, specialization of a region is often concluded from stronger activation compared with the homologue region in the other hemisphere. However, activation of a region specifically involved in a task can decrease with improved task performance of subjects (Brechmann and Scheich 2005). Thus in some cases, e.g., when the task demand is low, activation may not be lateralized. Therefore it seems to be more appropriate to analyze activation within a region in response to parametrically varied stimulus conditions, by varying tasks, or by varying task difficulty. For this, different conditions are needed which differ only in one aspect of the stimulus or task intended to be investigated.
During dichotic listening experiments, different auditory stimuli are presented to the two ears. This technique concludes from ear advantages which hemisphere is mainly involved in the processing. However, it has been shown that attention can change results on ear advantage (Grimshaw et al. 2003; Hugdahl 2003; Loberg et al. 1999).
Using a combination of fMRI and dichotic listening, we recently suggested that presenting information-bearing stimuli to one ear and noise to the other ear may be a general strategy to determine hemispheric specialization in the AC (Behne et al. 2005). There we used the stimulus class of linear frequency modulations (FM) in combination with a directional categorization task known to be mainly processed in the right AC (Brechmann and Scheich 2005). It was shown that an additional presentation of white noise contralateral to the ear that was stimulated by the information-bearing FM enhanced activation exclusively in right but not left AC. This was explained by the auditory cortical representation of monaural stimuli. The pathways from the two ears project to both auditory cortices. However, the input from the contralateral ear causes a stronger cortical representation and is supposed to suppress information from the ipsilateral ear (Kimura 1967). Thus from a bottom-up view, response properties of cortical neurons in AC would predict that activation in each hemisphere is strongest for contralateral, intermediate for binaural, and weakest for ipsilateral stimulation (Clarey et al. 1992; Reser et al. 2000). However, activation of AC is not only determined by bottom-up mechanisms but also by top-down influences, e.g., selective attention or task-demands (e.g., Brechmann and Scheich 2005; Holcomb et al. 1998; Ohl and Scheich 2005; Sussman et al. 2002), which may lead to changes in activation specifically in the hemisphere specialized for a given task. With respect to processing demands, ipsilateral presentation of information-bearing stimuli represents a condition with low signal-to-noise-ratio because only the weak input via the ipsilateral pathway and the input from the contralateral hemisphere via the corpus callosum are available. By additional presentation of white noise to the contralateral ear, this ratio may be further decreased. To enable adequate task performance in this condition, functional neural compensation may be required leading to an upregulation of activity in the hemisphere specialized for the processing of the task (Behne et al. 2005).
The present study investigated the lateralization of auditory information processing using the paradigm described in the preceding text with natural words and pseudowords in combination with a lexical decision task that is known to involve mainly the left hemisphere (Hugdahl et al. 2003; Kotz et al. 2002; Poeppel et al. 2004; Specht et al. 2003). Subjects had to distinguish between words and pseudowords presented monaurally to the left or right ear with or without contralateral white noise to the other ear. Assuming that contralateral noise mainly effects the activation of the AC specialized for the task, we predicted a strong influence on the activation of left AC.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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Sixteen right-handed subjects (Edingburgh Handedness Inventory) with normal hearing participated in this study. All subjects were native German speakers. Subjects (9 females, 7 males, between 22 and 40 yr of age, mean age: 27 yr) gave written informed consent to the study, which was approved by the ethics committee of the University of Magdeburg.
Stimuli and task
A set of 250 semantically neutral German words (nouns) and 222 pseudowords from the "Magdeburger Prosodie-Korpus" served as stimuli (Wendt and Scheich 2002). All stimuli had two syllables and were spoken with neutral prosody. The pseudowords followed the rules of German phonology but were meaningless compositions of syllables. The stimuli were presented in 25 stimulation blocks of 24 s alternating with 26 silence blocks of 24 s. Each stimulation block contained 10 words and 10 pseudowords in randomized order. In each block, one half of the real words and pseudowords was spoken by a woman, the other half by a man. The interstimulus interval between the words within each block varied between 0.357 and 0.538 s depending on the duration of the words. The duration of the real words varied between 0.354 and 1.287 s (mean: 0.747 s). The duration of the pseudowords varied between 0.429 and 1.326 s (mean: 0.781 s). Five blocks of words were presented for each of the five modes of stimulation: binaural, monaural to the left ear (either with or without noise to the right ear), and monaural to the right ear (either with or without noise to the left ear). White noise had the same duration as the real words and pseudowords including a linear ramp of 50 ms at the beginning and end. The bursts of white noise exactly overlapped with each word/pseudoword.
For stimulus presentation and recording of behavioral responses, the software Presentation (Neurobehavioral Systems) was used. Before the experiments, the sound pressure level was adjusted for each subject so that it was 
70 ± 5 (SD) dB SPL and equal at both ears. The peak amplitude of white noise was 5 dB lower than that of the words and pseudowords.
The subjects performed a lexical decision task in which they had to identify real words by pressing a response key.
Scanning procedure
Subjects were scanned in a BRUKER 30/60 3T head scanner equipped with a quadrupolar birdcage head coil. Three slices of 6-mm thickness oriented roughly parallel to the Sylvian fissure on both sides were collected covering the superior temporal plane in both hemispheres. In 20 min and 24 s, 255 functional volumes were acquired with a low-noise FLASH-based gradient echo sequence (TE: 32.2 ms; TR: 133.34 ms; flip angel: 15°; matrix size: 64 x 60; field of view: 18 cm, gradient rise time: 2,500 µs). A long gradient rise time (2,500 µs) reduced the scanner noise to 54 dB SPL at the subjects ear (Scheich et al. 1998).
A keyhole technique was used to increase data-acquisition rate (Gao et al. 1996; Jones et al. 1993; van Vaals et al. 1993). With the keyhole technique, only the central fraction of k-space data, that contributes primarily to signal-to-noise ratio and image contrast, is collected. The missing peripheral lines in k-space, which contribute primarily to edge definition, are supplied from a reference image. During each keyhole block, the middle of five acquisitions was chosen as reference image. For the rest of the images only the central "keyhole" of k-space data (keyhole-factor = 0.5) was used and the higher-order k-space terms were supplied from the reference image. High contrast T1-weighted imaging immediately followed the fMRI to obtain anatomical landmarks. The head of the subjects was fixed with a vacuum-cushion with attached ear muffs containing the MRI compatible headphones (Baumgart et al. 1998).
Data analysis
Each functional dataset was subjected to a quality check: subject's three-dimensional movement was monitored using the AIR package (Woods et al. 1998). Continuous movements exceeding one voxel in at least one direction were used as criterion for data exclusion. Furthermore, the mean gray value of the temporal lobe defined in two slices was computed for each volume. Images with percentage deviation of gray values from the mean gray value >2.5% were excluded from further analysis. This procedure was derived in former studies of our lab that showed that gray value deviations of >2.5% reliability extracts volumes in which the subjects made strong transient head movements as confirmed by visual inspection of each single brain volume. Images were corrected for two-dimensional movement using the AIR package.
The functional data were analyzed with the software-package KHORFu (Gaschler et al. 1996). A second-order trend correction was performed to remove slow drifts in signal intensity. The matrix size of 64 x 64 was increased to 128 x 128 by pixel replication followed by smoothing with a Gaussian filter [FWHM = 2 pixel (2.8 mm), Kernel = 5 pixel (7 mm)]. Each voxel series was temporally smoothed using a moving averaging filter with a kernel width of two time points. Functional activation was analyzed by correlation analysis to obtain statistical parametric maps. A simple trapezoid function served as correlation vector, roughly modeling the expected BOLD response. The correlation vector points corresponding to the first image of each stimulus and silence block were set to half-maximum values. The vector points corresponding to the remaining images acquired during the silence blocks were set to minimum values and the vector points corresponding to the remaining images acquired during the stimulus blocks were set to maximum values. Activated voxels (P < 0.001; minimum cluster size = 8) were assigned to one of the four territories TA, T1, T2, and T3, defined in each individual subject by anatomical landmarks (Brechmann et al. 2002). For each voxel, the average blood-oxygen-level-dependent (BOLD) signal intensity, i.e., the percentage change in image signal between stimulus and silence blocks, was determined. The intensity weighted volume (IWV) as the product of the number of activated voxels and their mean BOLD signal intensity change was computed. Contralaterality index of activation in each AC was determined as activation (IWV) by contralateral word/pseudoword stimulation minus activation by ipsilateral word/pseudoword stimulation divided by the sum of both conditions.
Statistical data analysis was performed using parametric ANOVAs and paired t-test. In the figures, significance levels of P < 0.05 are indicated by one asterisk and significance levels of P < 0.01 by two asterisks.
Definition of territories
We used an empirical landmark-oriented approach to systematize across individuals the separate clusters of activated voxels in the AC that are regularly seen with imaging parallel to the Sylvian fissure. This scheme has proven useful for regional comparison, since a functional parcellation of human AC is not yet available (for discussion, see Brechmann et al. 2002).
Clusters of activation were scrutinized in a three-dimensional analysis of both hemispheres of individual brains (Brain Voyager 2000) in relation to the prominent anatomical landmarks insular sulcus, first transverse sulcus, Heschl's sulcus, and superior temporal sulcus. First, clusters of activation centered on and following the course of Heschl's sulcus were attributed to T2. Clusters on Heschl's gyrus anterior to T2 and posterior to first transverse sulcus were attributed to T1. Clusters on planum polare anterior to first transverse sulcus were attributed to TA. Clusters posterior to T2 on planum temporale including the anterior gray matter of the supramarginal gyrus were defined as T3.
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RESULTS |
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The hit rate was 85.3 ± 1.6% for words presented to the left ear, 91.4 ± 1.5% when presented binaurally, 89.4 ± 1.9% when presented to the right ear, 91.1 ± 1.8% when presented to the left and noise to the right ear, and 86.3 ± 1.7% when presented to the right and noise to the left ear. The differences in hit rate between the conditions were due to a few words that half or more of the subjects did not recognize as a real word. After correction of this effect by excluding these words from the calculation, the hit rate was 93.3 ± 1.7% for words presented to the left ear, 93.1 ± 1.5% when presented binaurally, 91.4 ± 2% when presented to the right ear, 93 ± 1.8% when presented to the left and noise to the right ear, and 91.2 ± 1.5% when presented to the right and noise to the left ear. After the correction no significant differences between the conditions remained.
fMRI activation
In the control conditions, i.e., words/pseudowords were presented without noise, activation in right and left AC was strongest by contralateral monaural stimulation (contraWP), intermediate by binaural stimulation (binWP), and weakest by ipsilateral monaural stimulation (ipsiWP) (Fig. 1A).
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To test whether these effects are significant for the entire AC and in individual territories, we subjected the activation in terms of IWV to ANOVAs with the factors side of word presentation (contralateral vs. ipsilateral), noise-condition (with or without contralateral noise), and hemisphere. We found the following interrelated effects. 1) A main effect of side of word presentation in whole AC (P < 0.01), in TA (P < 0.01), T1 (P < 0.01), T2 (P < 0.01), and T3 (P < 0.05) with stronger activation on contralateral than on ipsilateral word presentation. 2) We also found an interaction between side of word presentation and noise-condition in whole AC (P < 0.01), T1 (P < 0.01), T2 (P < 0.01), and T3 (P < 0.05). 3) The noise-condition had a main effect on activation in whole AC (P < 0.05) and in T2 (P < 0.05) and as a trend in T3 (P = 0.059), with stronger activation in the conditions with noise than without noise. 4) The factor hemisphere in interaction with side of word presentation and noise-condition was significant in whole AC (P < 0.05) and showed a trend in each auditory territory (P < 0.1). These effects are consistent with the qualitative findings described in the preceding text that contralateral white noise effects the activation difference between ipsiWP and contraWP in left AC (Fig. 1B).
To further characterize the interaction effects, we used paired t-test comparing the activation of each territory between each of the conditions separately.
In the control conditions, the activation was significantly stronger by contraWP compared with ipsiWP in left and right AC (P < 0.01; Fig. 1A) as well as in all individual auditory territories on both sides (P < 0.01, right T3: P < 0.05) except right TA (Fig. 2A).
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A comparison between the control and the test conditions revealed significant differences exclusively in the left AC and only for ipsiWP (Figs. 1 and 2). Thus activation in left AC (P < 0.01) as well as in the individual territories T1 (P < 0.05), T2 (P < 0.01), and T3 (P < 0.05) were significantly stronger by ipsiWP with contralateral noise compared with ipsiWP without noise. In the right AC, this comparison was not significant, either in whole AC (P > 0.05) or in any territory (P > 0.1).
The binaural condition was not included in the ANOVA analysis because it does not contain a noise condition. In general, this condition caused no lateralized activation neither in global AC nor in any territory. Compared with contraWP the binaural condition led to weaker activation in left and right AC and in left T1, left T2, and left T3 (P < 0.05) and compared with ipsiWP it led to stronger activation in left T1, left T2, and right T1 (P < 0.05). Compared with contraWP with ipsilateral noise the binaural condition led to weaker global activation in right AC and right T2 (P < 0.05) and compared with ipsiWP with contralateral noise it led to stronger activation in right T1 (P < 0.05).
An example of the activation in AC in one slice of an individual subject is given in Fig. 3.
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The strong influence of white noise on the activity in left AC became quantitatively even more evident when the contralaterality index of the conditions with and without noise was compared (Fig. 4). The contralaterality indices were subjected to an ANOVA with noise-condition (with or without contralateral noise), hemisphere, and territory as factors. We did not include TA because several subjects showed only weak or no activation in this area. Therefore the contralaterality index could not be properly determined. We found a significant main effect of noise-condition (P < 0.01) with higher contralaterality indices in the conditions without noise than with noise. Furthermore, we found a significant main effect of territory (P < 0.05). Additionally, the following interactions were significant: noise-condition x hemisphere (P < 0.05), noise-condition x territory (P < 0.05), and hemisphere x territory (P < 0.05). Due to the multiple interactions comprising all three factors of the ANOVA, we separately compared the contralaterality index of each territory in each hemisphere between the conditions without and with noise.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSREFERENCES |
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The results of the present study support our initial hypothesis that additional presentation of contralateral white noise has a strong influence on left AC but only minimal effect on right AC activation produced by ipsilateral stimulation with words and pseudowords during the lexical decision task. Thus these findings mirror the results in right AC obtained during a directional categorization task with FM sweeps (Behne et al. 2005).
Assuming a special involvement of the left hemisphere in the lexical decision task, presentation of words and pseudowords to the left ear and white noise to the right ear represents a condition with strongly reduced signal-to-noise ratio for the task-relevant stimuli. Words and pseudowords presented to the left ear mainly arrive in right AC via the excitatory pathway, but in left AC only via the weaker ipsilateral pathway or via the corpus callosum from the right AC. Therefore the processing of words and pseudowords in the left AC has to compete with direct input from the noise from the right ear. In other words, the left AC has to differentiate the word/pseudoword input from the noise input. According to a hypothesis by Kimura (1967), the contralateral noise additionally suppresses the ipsilateral information. Thus this condition may require neuronal compensations to secure proper task processing. This may have led to the enhanced activation in left AC compared with the condition without noise. This influence of contralateral noise was present mainly in the left AC and in all functional territories of this hemisphere as demonstrated by the reduction in contralaterality index. In contrast, contralateral white noise had no significant effect on activation of AC in the right hemisphere. Thus the contralaterality index in the right AC was not significantly reduced in the conditions with noise compared with the conditions without noise. This suggests that right AC was not significantly involved in the discrimination aspect of stimulus processing in the lexical decision task.
In conclusion, the present results support our hypothesis that activation by ipsilateral information-bearing stimuli is upregulated in the hemisphere specialized for a given task in the presence of noise at the contralateral ear (Behne et al. 2005). This hypothesis, however, assumes that the bottom-up activation produced by noise alone is equal in left and right AC. This is supported by studies that show that passive, binaural presentation of noise did not lead to asymmetric activation in AC (Binder et al. 2000; Caird et al. 1991; see also discussion in Behne et al. 2005). Furthermore, we assume that noise per se leads to weaker activation than words/pseudowords because noise was merely a distractor stimulus for the subjects, who had to focus their attention on the words and pseudowords to solve the task. The strongest support that the bottom-up contribution of noise per se cannot explain the present result comes from our former study (Behne et al. 2005). There we show that activation of right AC is upregulated in the presence of contralateral noise in a task that has been shown to be mainly processed in right AC.
There are two previous studies using dichotic stimulus presentation with information-bearing stimuli presented to one ear and white noise to the other ear (Brancucci and San Martini 2003; Hertrich et al. 2004). Brancucci and San Martini (2003) used this approach in a psychoacoustic study because they assumed that this mode of presentation allows a reliable detection of laterality effects. They found a left-ear advantage in a matching-to-sample task in which the subjects had to compare tones with respect to their amplitude envelope. Unfortunately, they did not test the control conditions without contralateral white noise to reveal a difference of ear advantage. Nevertheless, results of this study are consistent with our hypothesis that such a dichotic approach is a valuable tool to determine hemispheric specialization of the AC.
Hertrich et al. (2004) analyzed evoked magnetic fields in response to rippled noise presented to one ear and white noise to the contralateral ear. The subjects had to detect the pitch of the rippled noise stimuli. In the right hemisphere, the rippled noise evoked a larger amplitude of a late M100 component (M136) when presented to the left ear compared with the right ear. This contralaterality of the M136 amplitude in the right hemisphere was observed despite the presentation of white noise to the respective contralateral ear. In contrast, no such contralaterality was observed in the left hemisphere in which the amplitude of the M136 was equally large independent of the rippled noise stimulus presented to the left or right ear. From several control experiments involving stimuli other than rippled noise, the authors concluded that pitch-related information of the rippled noise is mainly processed in the right hemisphere. However, in the light of our results, this interpretation is not mandatory. The contralaterality of the M136 amplitude in the right hemisphere would also be expected if no white noise was presented to the respective contralateral ear. In contrast, the reduced contralaterality in the left hemisphere can be explained assuming a strong influence of contralateral white noise on the M136 amplitude in the left hemisphere. Along the argumentation of our study, we would therefore conclude that the task of pitch detection in rippled noise is processed in the left hemisphere. In support of this interpretation, the M136 component in the study of Hertrich et al. (2004) showed enhanced negative values over left as compared with right hemisphere and, furthermore, a target-specific effect on the left side. To decide which of the two opposing interpretations is correct, a control condition with monaurally presented rippled noise without contralateral white noise would have been necessary. However, the findings may also be the result of an interaction of white and rippled noise because the subjects failed to reliably detect the ear on which the rippled noise and thus the pitch information was presented.
AC activation on bin- and monaural stimulus presentation without contralateral noise
In the present study and in several other imaging studies that use speech or speech-like stimuli, stronger activation was shown by contralateral than by ipsilateral stimuli, although the subjects had to solve a task (Greenberg et al. 1981; Hirano et al. 1997; Jäncke et al. 2002; Kushner et al. 1987; Maehara et al. 1999; Suzuki et al. 2002). Thus despite the task demand, contralaterality was not significantly modulated by top-down effects in all of these monaural studies. However, such modulations on monaural stimulation may occur in areas specialized for the task, possibly leading to activation that is invariant of the stimulated ear as shown in the former FM study for right T3 (Behne et al. 2005). It has been suggested that areas processing specific aspects of a stimulus might be largely invariant for the processing of nonspecific aspects of the same stimulus (Brechmann et al. 2002; Frackowiak 1994; Suga 1994). Thus assuming that the left AC is specifically involved in the lexical decision task, an activation independent of stimulated ear may be expected in territories of the left AC and especially in left T3 as part of Wernicke's area. This was not the case in our study, possibly because the difficulty of the lexical decision task was much lower than the directional categorization of FM tones. Nevertheless, the reduction of the contralaterality index caused by contralateral noise was equally significant for right T3 in the FM directional categorization task as well as for left T3 in the lexical decision task. Thus despite possible modulation of activity by top-down processes, our approach leads to a reliable reduction of the contralaterality index in the hemisphere specialized for a given task. In the present study, this effect confirms the specialization of the left hemisphere in lexical decision tasks.
In the binaural condition, we did not find a left lateralized activation in AC, either in whole AC or any single territory, in contrast to several other imaging studies using a similar auditory lexical decision task with real words and pseudowords (Hugdahl et al. 2003; Kotz et al. 2002; Poeppel et al. 2004; Specht et al. 2003). One reason for this discrepancy might be that activation was influenced by the different modes of presentation. In our study, the speech stimuli were serially presented in five different modes (1 binaural, 2 monaural, and 2 dichotic) in the same session, whereas in all of the studies mentioned above the stimuli were always presented binaurally. This could have induced different strategies of listening and processing. Methodological differences in the experimental design may also explain this discrepancy, e.g., overall number, duration, or presentation rate of the stimuli, phonological properties of the pseudowords or different control-stimuli serving as contrasting condition. Furthermore, in a study using randomly presented real words, pseudowords, and nonwords in the first and second language of the subjects, the distribution of event-related potentials (ERPs) altered between left and right hemisphere dominance (Sinai and Pratt 2003). The ERPs in response to pseudowords of the first language revealed more right sided activation than to real words. This was explained by a familiarity dependence of hemispheric dominance with more right sided activation caused by unfamiliar stimuli. In the present fMRI study, the activation per block includes the combined response to real words and pseudowords. This might have contributed to the balanced activation of left and right AC. Nevertheless, even without a left lateralized activation, our dichotic paradigm of presenting information-bearing stimuli to one ear and white noise to the other ear confirmed the left hemispheric specialization for the lexical decision task. Thus in future studies, this experimental design seems to be a useful tool to determine yet unknown hemispheric specialization of the human AC with fMRI.
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FOOTNOTES |
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Address for reprint requests and other correspondence: N. Behne, Leibniz Institute for Neurobiology, Brenneckestr. 6, 39118 Magdeburg, Germany (E-mail: nbehne{at}ifn-magdeburg.de)
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REFERENCES |
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