Abstract

Several studies have identified a supramodal network critical to the reorienting of attention toward stimuli at novel locations and which involves the right temporoparietal junction and the inferior frontal areas. The present functional magnetic resonance imaging (fMRI)\magnetoencephalography (MEG) study investigates: 1) the cerebral circuit underlying attentional reorienting to spatially varying sound locations; 2) the circuit related to the regular change of sound location in the same hemifield, the change of sound location across hemifields, or sounds presented randomly at different locations on the azimuth plane; 3) functional temporal dynamics of the observed cortical areas exploiting the complementary characteristics of the fMRI and MEG paradigms. fMRI results suggest 3 distinct roles: the supratemporal plane appears modulated by variations of sound location; the inferior parietal lobule is modulated by the cross-meridian effect; and the inferior frontal cortex is engaged by the inhibition of a motor response. MEG data help to elucidate the temporal dynamics of this network by providing high-resolution time series with which to measure latency of neural activation manipulated by the reorienting of attention.

The neural correlates of spatial attention have long been studied in the visual domain. More recently, investigations are beginning to focus on spatial attention in the auditory modality. In a previous study, using a passive listening paradigm, we found that sound localization processing involves the supratemporal plane and supramarginal gyrus with different activation patterns for sounds from fixed locations on the frontal plane, and sounds presented randomly at different locations (Brunetti et al. 2005). The different activation in the 2 above conditions could be due to: 1) different pathways for orienting attention toward fixed versus moving sound locations; 2) distinct covert motor responses elicited by fixed and moving sounds; 3) different pathways depending on whether the sounds cross the vertical meridian plane. In regard to the first hypothesis, Corbetta and Shulman (2002), reviewing experimental evidences about the control of visual attention, proposed a 2-system model composed of: 1) a dorsal network involving temporoparietal and dorsal frontal regions for the intrinsic direction of attention toward behaviorally relevant events and 2) a ventral network involving the temporoparietal junction and ventral frontal cortex implicated in the extrinsic reorienting of attention by the environment. The latter circuit, recruited to detect unattended or low-frequency events, has been shown to be independent of sensory modality. In regard to the second hypothesis, Downar et al. (2000), using multisensory stimulation, found activation in the temporoparietal junction, in the inferior frontal gyrus and in the insula, lateralized to the right hemisphere. In particular, the authors stress that the activation in the frontal region, corresponding to Brodmann area (BA) 44 and normally involved in planning motor responses, was observed in subjects that were not performing a motor task during the experiment. They attributed this activation to the involuntary planning of motor responses to changing stimuli, even if these motor responses were not executed. Macaluso et al. (2002), in an functional magnetic resonance imaging (fMRI) study, demonstrated that the dorsal frontoparietal circuit for spatial attention, previously observed to be activated in the visual modality, was also observed in the tactile and auditory modality; furthermore, in the auditory modality, the activity was increased with increasing binaural coherence (Zimmer and Macaluso 2006). Finally, in relation to our third hypothesis, Rizzolatti et al. (1987) found that a large “cognitive” cost is paid when a stimulus appears at an unattended location in the hemifield opposite the attended one—that is, across the vertical or horizontal meridian plane (meridian effect). The authors postulate that the meridian effect is related to the way in which eye movements are programmed and suggest that overt and covert orienting of attention are controlled by common mechanisms. Moreover, recent studies have demonstrated the existence of an auditory vertical meridian (Ferlazzo et al. 2002) and suggested that the meridian effect could be a consequence of the interaction between visual and auditory modalities (Olivetti Belardinelli et al. 2005, 2007).

The present fMRI/magnetoencephalography (MEG) study aims to investigate the cerebral circuits that are engaged in the orienting of attention toward different sounds locations. In particular, we study: 1) the cerebral circuit activated by the orienting of attention toward spatially varying sound locations, providing a counterpart to earlier neuroimaging studies of attentional reorienting in the visual modality; 2) differences in the investigated circuit related to: b1 regular changes of sound location within the same hemifield or across hemifields and b2 irregular sound source change on the azimuth plane; 3) the functional temporal dynamics of these areas. With these aims, we combine fMRI and MEG data to examine the effect of reorienting attention on the waveform and latency of neural activation in the involved regions disclosing the sequence of activation in attention control areas.

Materials and Methods

Subjects

A group of 10 healthy volunteers (mean age 24 ± 2 years), all females, participated in the fMRI data acquisitions, after providing written informed consent. The experimental protocol was approved by the local institutional ethics committee. Out of these 10 subjects, 6 were studied with MEG as well. All subjects were right handed according to the Edinburgh handedness questionnaire (Oldfield 1971). The volunteers had no anamnestic and clinical auditory impairment; they had normal hearing thresholds at pure-tone audiometry, and they had no previous history of neurological or psychiatric illness. Before the experiment, the sound localization abilities of each subject were assessed by delivering the same stimuli used during the experiment and asking the subjects to report on the position of sounds aloud.

Stimuli

During both the fMRI and MEG sessions, stimuli were delivered via a nonmagnetic and MRI compatible sound system (Commander XG MRI Audio System) with a frequency range from 100 Hz to 25 kHz. The electric signals generated by the computer audio board were amplified and sent through the shielded room penetration panel to an electropneumatic transducer. The sounds reached the subject's headset via flexible plastic tubes.

The stimulus used was an audio recording of a knife tapping on an empty glass with a duration of 500 ms. The frequency band of the stimulus ranged from 1200 to 7200 Hz with principle components before and after the critical threshold of 1500 Hz. These values lie within the frequency band range of both the computer audio card and the nonmagnetic headset used in the experiment (for more details about the stimulus choice rationale, see Brunetti et al. 2005). The output of each channel was calculated from the primitive sound by convolution with the proper head-related transfer functions (HRTFs) in order to simulate the incoming direction of the sound. For each position of the sound source, the Matlab convolution function was used to convolve the source stimulus with the HRTF corresponding to that position. The HRTFs were downloaded from the Massachusetts Institute of Technology Web page (http://xenia.media.mit.edu/∼billg/). The calculations have been made for a standard head.

A passive listening paradigm was used in which subjects were asked to localize the position of the incoming stimuli in each of 4 conditions. Three conditions consisted of sounds regularly alternating between 2 locations in a 40-degree slice of space centered on the subject at a distance of 1 m (+90° and +50°; −90° and −50°; −20° and +20°; see Fig. 1). These conditions were termed RIGHT, LEFT, and CENTRAL depending on whether they were confined to one hemifield or crossed the meridian. The fourth condition, termed MIXED, consisted of a random sequence of sounds projected from 5 locations, the 4 locations used in the RIGHT and LEFT fixed conditions and a fifth location at the meridian (±90°, ±50°, and 0°). The stimuli were presented in blocks of each condition, each block consisting of 8 events with an interstimulus interval of 1.5 s. The 4 conditions were presented in pseudorandom order so that a total of 35 blocks of each type were presented to each subject.

Figure 1.

Stimuli are delivered from 5 different spatial locations: the vertical head-centered meridian (0°), the right angles to the meridian axis on both sides (left −90°, right +90°), and 40° to the vertical head-centered meridian (left −50°, right +50).

Figure 1.

Stimuli are delivered from 5 different spatial locations: the vertical head-centered meridian (0°), the right angles to the meridian axis on both sides (left −90°, right +90°), and 40° to the vertical head-centered meridian (left −50°, right +50).

This paradigm allowed us to verify the cerebral circuit activated by the orienting of attention toward regularly varying sound locations either in the same or in different hemifields and toward sounds presented randomly at different locations on the azimuth plane.

fMRI Data Acquisition and Analysis

fMRI was carried out with a SIEMENS MAGNETOM VISION scanner at 1.5 T. A standard head coil was used, and the subject's head was held in place with foam pads to reduce involuntary movements. Blood oxygen level–dependent (BOLD) contrast functional images were acquired by means of T*2-weighted echo planar imaging free induction decay sequences with the following parameters: time echo (TE) 60 ms, matrix size 64 × 64, field of view (FoV) 256 mm, in-plane voxel size 4 × 4 mm, flip angle 90°, slice thickness 4 mm, and no gap. To avoid the interference of the scanner intense bursts of noise, the “sparse” sampling technique proposed by Hall et al. (1999) was used. Following the procedure outlined by these authors, functional volumes at the end of the stimulation periods and of the baseline (silent) periods were acquired. Each stimulus sequence was preceded by a 2 s and followed by a 14-s silent period (REST). The number of silent periods was 140, so that a total of 280 functional volumes were acquired (35 × 4 total sequences + 140 silent periods). The interval between 2 consecutive acquisitions (time repitition [TR]) was set at 14 s to allow the hemodynamic response to return to baseline before the following image acquisition (see above in the Stimuli paragraph). Functional volumes consisted of 18 transaxial slices parallel to the anterior commissura-posterior comminssura line covering the cortical regions of interest (ROIs). A high-resolution structural volume was acquired at the end of the session via a 3-dimensional (3D) magnetization prepared rapid gradient echo (MP–RAGE) sequence with the following features: sagittal, matrix 256 × 256, FoV 256 mm, slice thickness 1 mm, no gap, in-plane voxel size 1 × 1 mm, flip angle 12°, TR = 9.7 ms, and TE = 4 ms.

Raw data were analyzed by means of the Brain Voyager software version 4.9 (Brain Innovation, The Netherlands). Preprocessing of functional scans included motion correction and the removal of linear trends from voxel time series. The preprocessed functional volumes of each subject were recorded in the same session as the corresponding structural data set from the same session. The coregistration transformation was determined using the slice position parameters of the functional images and the position parameters of the structural volume. After visual inspection, this transformation was slightly adjusted, when necessary, to account for subject movement between functional and anatomical scans. Structural and functional volumes were normalized to the Talairach space (Talairach et al. 1988) using a piecewise affine and continuous transformation. Statistical activation maps were generated by means of a t-test comparing voxel by voxel images of a given stimulation condition (LEFT, RIGHT, CENTRAL, or MIXED) to those of the REST condition (baseline condition). These statistical maps were thresholded at P < 0.0004 at the voxel level, and a cluster size of at least 4 voxels was required. These thresholds and an estimate of the spatial correlation of voxels (Forman et al. 1995; 3dFWHM routine of AFNI package, Cox 1996) were used as input in a Monte-Carlo simulation (AlphaSim routine of AFNI package, Cox 1996; Forman et al. 1995), in order to assess the overall significance level (which is the probability of a false detection of a cluster in the entire functional volume). A corrected P value of 0.05 was thus obtained. Thresholded statistical maps were then overlaid onto the subject structural scan to localize significantly activated areas. A statistical group analysis was also performed. The time series obtained from all subjects were z normalized and concatenated prior to the computation of the group statistical activation maps. The group activation map was then superimposed onto the Talairach transformed structural scan of one of the subjects.

For each subject, ROIs were determined on the basis of the individual activation maps. Specifically, for each subject, ROIs were determined by superimposing activation maps for each of the 4 conditions (considering the Boolean OR among the 4 conditions). Rather than defining ROIs on the basis of group activation, the above mentioned method was used in order to take into account interindividual anatomical variability, so that BOLD signals were not underestimated due to a mismatch between a mean ROI and individual activation. The procedure was consistent because the functional area was always clearly defined. A common ROI (based on group data) was defined only when individual activations were not observed in all subjects. Subject responses in each stimulation condition were characterized by evaluating the BOLD signal intensity variation in each ROI. The strength of the activation in a given experimental condition was expressed as the mean relative change with respect to the baseline of the BOLD signal of the voxels belonging to a given ROI. Heschl's gyrus was identified by reviewing the coronal aspect of the MP–RAGE passing through the temporal lobes and locating the prominent mid-superior temporal features of the gyrus. We then located the anterolateral and posteromedial boundaries of the gyrus for each individual. It has been reported that many superior temporal gyri may contain multiple Heschl formations. In accordance with the work of Galaburda and Sanides (1980), we identify only the most anterior transverse gyrus as Heschl's.

A regional comparison of activation was then performed by means of a repeated-measures analysis of variance (ANOVA). The dependent variable of the ANOVA analysis was the relative variation of the BOLD signal between the stimulation and silent condition, and the factor was the experimental condition (RIGHT, LEFT, CENTRAL, and MIXED).

MEG Data Acquisition and Analysis

MEG recordings were used to reveal high-resolution timing of the activation patterns observed for attention control in the fMRI sessions by localizing the neural components in time using Equivalent Current Dipole MEG source localization. Auditory evoked fields were recorded using the whole-head neuromagnetic system at the University of Chieti (Pizzella et al. 2001), which was developed in collaboration with Advanced Technologies Biomagnetics srl (Pescara, Italy).

In order to determine the position of the subject's head with respect to the sensors the magnetic field generated by 4 coils placed on the scalp was recorded before and after each measurement session. The positions of the coils on the subject head were digitized by means of a 3D digitizer (Polhemus, 3Space Fastrak), together with 4 anatomical landmarks (nasion, left/right ear, and vertex), to be used for the MRI-fMRI-MEG coregistration. To this end, spherical oil capsules were applied at the nasion and left/right ear landmarks for structural MRI acquisition. About 40 additional points were digitized on the scalp and subsequently used for fitting the spherical volume conductor to the subject head.

During MEG recordings, a similar experimental paradigm as in fMRI was used. The overall magnetic noise of the stimulation apparatus was below the noise level of the sensor. A total of 1120 stimuli were presented from the 4 conditions (RIGHT, LEFT, CENTRAL, and MIXED as described above) with a time lag of 3 s between sequences. The auditory evoked magnetic fields were sampled at 1 kHz and bandpass filtered between 0.16 and 250 Hz. After artifact rejection, trials were averaged for each condition from −100 ms to +700 ms relative to stimulus onset. For each channel, the baseline was calculated as the mean field value from 10 to 20 ms after stimulus onset. Source analysis was performed using BESA (MEGIS Software, Germany) multiple source analysis based on the Equivalent Current Dipole source model and a homogenously conducting spherical volume to model the subject's head.

Source localization was performed on the averaged data in the MIXED condition because the total signal power was the largest in this condition. These localizations were then used to estimate the strength and orientation of the sources for the other conditions. Inspection of the data time course showed components of activity in 5 distinct time intervals. According to the components observed in the time course, the data were fitted in the above time intervals using a source model consisting of 5 moving equivalent current dipoles (ECDs), 2 pairs of which were constrained to be symmetric.

In order to explain the residual field (i.e., the measured field minus the field generated by the localized ECDs) after the localization of the first 5 ECDs, 2 additional fixed dipoles were introduced at locations constrained by the fMRI activation (see table 1 for the source time intervals). The coordinates of these 2 ECDs were bounded to a 6-mm cube centered on the “center of mass” of the corresponding fMRI activations in the parietal and frontal areas (see Results) (concerning this method, see also Ahlfors et al. 1999). A complete 7-dipole configuration was accepted when the relative residual variance was less than 15%.

Table 1

Group results (P < 0.05 corrected): Talairach coordinates and Z scores of the peak activity in brain areas activated during the different experimental conditions

Experimental conditions Cerebral regions x y z Z score 
MIXED Right LHg 49 −19 11 8.13 
Left LHg −58 −25 19 8.31 
Right MHg 44 −29 11 7.79 
Left MHg −40 −35 19 9.06 
Right PSTg 59 −39 11 8.49 
Right IPL 34 −48 35 6.36 
Right PFC 40 26 28 4.70 
RIGHT Right LHg 56 −20 14 5.05 
Left LHg −58 −21 12 6.42 
Right MHg 39 −20 14 5.47 
Left MHg −40 −30 15 6.60 
Right PSTg 61 −40 12 4.86 
Right IPL 45 −40 40 3.22 
Right PFC 37 29 39 5.62 
LEFT Right LHg 50 −24 14 7.52 
Left LHg −60 −21 12 3.78 
Right MHg 36 −20 14 6.73 
Left MHg −44 −16 5.97 
Right PSTg 58 −32 14 5.61 
Right IPL 50 −41 31 2.57 
Right PFC 33 25 31 3.39 
CENTRAL Right LHg 49 −20 16 6.29 
Left LHg −49 −29 16 6.06 
Right MHg 50 −24 16 6.48 
Left MHg −37 −33 16 6.42 
Right PSTg 58 −27 21 5.49 
Right IPL −36 −52 34 3.89 
Right PFC 37 37 33 3.88 
Experimental conditions Cerebral regions x y z Z score 
MIXED Right LHg 49 −19 11 8.13 
Left LHg −58 −25 19 8.31 
Right MHg 44 −29 11 7.79 
Left MHg −40 −35 19 9.06 
Right PSTg 59 −39 11 8.49 
Right IPL 34 −48 35 6.36 
Right PFC 40 26 28 4.70 
RIGHT Right LHg 56 −20 14 5.05 
Left LHg −58 −21 12 6.42 
Right MHg 39 −20 14 5.47 
Left MHg −40 −30 15 6.60 
Right PSTg 61 −40 12 4.86 
Right IPL 45 −40 40 3.22 
Right PFC 37 29 39 5.62 
LEFT Right LHg 50 −24 14 7.52 
Left LHg −60 −21 12 3.78 
Right MHg 36 −20 14 6.73 
Left MHg −44 −16 5.97 
Right PSTg 58 −32 14 5.61 
Right IPL 50 −41 31 2.57 
Right PFC 33 25 31 3.39 
CENTRAL Right LHg 49 −20 16 6.29 
Left LHg −49 −29 16 6.06 
Right MHg 50 −24 16 6.48 
Left MHg −37 −33 16 6.42 
Right PSTg 58 −27 21 5.49 
Right IPL −36 −52 34 3.89 
Right PFC 37 37 33 3.88 

Results

fMRI—Group Analysis

Group analysis showed activation in the bilateral supratemporal plane, in the right inferior parietal lobule (IPL) and in the right prefrontal cortex (PFC). Bilateral activation was larger in the right hemisphere. Statistical activation maps during the different experimental conditions are superimposed on the Talairach-transformed inflated cortex obtained from one of the subjects (Fig. 2, Table 1). Three clusters of activation were revealed in the supratemporal plane of the right hemisphere: the medial (BA 42) and lateral regions (BA 41) of Heschl'gyrus (MHg and LHg, respectively) and posterior superior temporal gyrus (PSTg, BA 22). The latter activation showed a larger posterior extension (up to y = −55 mm in Talairach coordinates) during the MIXED condition with respect to the other experimental conditions. In the left hemisphere, 2 peaks of activity were observed in the supratemporal plane: the MHg (BA 42) and LHg regions (BA 41).

Figure 2.

Results from the group analysis (P < 0.05, corrected) superimposed on the inflated cortex of a representative subject: activated areas during auditory stimulation in the 4 conditions: MIXED (a), RIGHT (b) LEFT (c), and CENTRAL (d). In the MIXED condition, activation in the bilateral Heschl's gyrus and in the right PSTg was more extended than in the other conditions. The PSTg activation extends dorsally (y = −55 in the right hemisphere). A right activation in the IPL is also observable. Activation in the PFC in the right hemisphere is present in the MIXED, RIGHT, and CENTRAL conditions (note that the group statistical maps shows activation in the right frontal cortex in these 3 conditions, whereas the individual subject analysis shows the same region activated also during the LEFT condition [see Fig. 3]).

Figure 2.

Results from the group analysis (P < 0.05, corrected) superimposed on the inflated cortex of a representative subject: activated areas during auditory stimulation in the 4 conditions: MIXED (a), RIGHT (b) LEFT (c), and CENTRAL (d). In the MIXED condition, activation in the bilateral Heschl's gyrus and in the right PSTg was more extended than in the other conditions. The PSTg activation extends dorsally (y = −55 in the right hemisphere). A right activation in the IPL is also observable. Activation in the PFC in the right hemisphere is present in the MIXED, RIGHT, and CENTRAL conditions (note that the group statistical maps shows activation in the right frontal cortex in these 3 conditions, whereas the individual subject analysis shows the same region activated also during the LEFT condition [see Fig. 3]).

The right IPL (BA 40) activation was larger during the MIXED condition as compared to the other conditions. The activation in the right PFC (BA 44, 9) was larger during the MIXED than during the RIGHT or the CENTRAL condition. It should be noted that due to intersubject variability, activation in the right hemisphere during the LEFT condition was below the statistical significance threshold. However, statistically significant activation was observed in every single subject. Activation was also observed in the premotor area (BA 6), suggesting some covert motor response; however, analysis did not reach statistical significance due to large variability across subjects and therefore was not considered for further analysis in this study. Talairach coordinates and peak Z scores of activated areas are shown in table 1.

fMRI—Individual Subject Analysis

The ROIs for the individual subject analysis were consistent with the 3 active regions of the supratemporal plane (the LHg and MHg, and the PSTg) and with the activation in the IPL and the PFC. The individual activation (relative variation of the BOLD signal between each experimental condition and the baseline condition) for each ROI was analyzed by a repeated-measures ANOVA in order to assess possible effects of the experimental conditions and of hemispheric asymmetry (Fig. 3). In the right hemisphere, the ANOVA on the LHg and MHg across experimental conditions revealed a stronger activation during the MIXED condition than during the other conditions (P < 0.05 and P < 0.01, respectively). The activation in the PSTg showed a significant difference across conditions (P < 0.01). A post hoc analysis (Duncan test) revealed a stronger activation during the MIXED condition than during the other conditions for these 3 temporal regions (see table 2). The contrast CENTRAL versus RIGHT + LEFT in the 3 temporal regions revealed a statistical difference only in MHg (P < 0.05). Finally, the contrast MIXED versus CENTRAL also revealed stronger activation during the MIXED condition in the 3 temporal regions.

Figure 3.

Activated areas in subject n°5 during MIXED condition. Activation map is superimposed on the segmented cortex (we decided to show the activation during the MIXED condition just for a representative purpose). In the box on the right side, activation map is superimposed on an axial section passing through supratemporal plane. View graphics: relative variation of the BOLD signal and standard error in the LHg and MHg, in the PSTg, in the supramarginal gyrus (IPL), and in the PFC across the 4 experimental conditions. The ANOVA analysis shows that the relative variation of the BOLD signal is higher in the MIXED condition than in the other conditions (see also table 2).

Figure 3.

Activated areas in subject n°5 during MIXED condition. Activation map is superimposed on the segmented cortex (we decided to show the activation during the MIXED condition just for a representative purpose). In the box on the right side, activation map is superimposed on an axial section passing through supratemporal plane. View graphics: relative variation of the BOLD signal and standard error in the LHg and MHg, in the PSTg, in the supramarginal gyrus (IPL), and in the PFC across the 4 experimental conditions. The ANOVA analysis shows that the relative variation of the BOLD signal is higher in the MIXED condition than in the other conditions (see also table 2).

Table 2

Significant differences in activation in the ROIs as result by post hoc analysis (Duncan test)

Contrasts LHg MHg PSTg IPL PFC 
MIXED versus CENTRAL P < 0.01 P < 0.01 P < 0.01 P = 0.05 P = 0.06 
MIXED versus CENTRAL + RIGHT + LEFT P < 0.01 P < 0.01 P < 0.01 P < 0.05 P = 0.01 
CENTRAL versus RIGHT + LEFT — P < 0.05 — P < 0.01 — 
Contrasts LHg MHg PSTg IPL PFC 
MIXED versus CENTRAL P < 0.01 P < 0.01 P < 0.01 P = 0.05 P = 0.06 
MIXED versus CENTRAL + RIGHT + LEFT P < 0.01 P < 0.01 P < 0.01 P < 0.05 P = 0.01 
CENTRAL versus RIGHT + LEFT — P < 0.05 — P < 0.01 — 

A stronger activation in the MIXED condition than in the others was also observed in the IPL (P < 0.05). Specifically, post hoc analysis revealed a trend toward significance (P = 0.05) in the contrast MIXED versus CENTRAL in IPL and a statistical difference (P < 0.01) in the contrast CENTRAL versus RIGHT + LEFT (more details in table 2). The PFC activation tended to be significantly different across the experimental conditions with a stronger activation during the MIXED condition than during the 3 other condition. In the left hemisphere, activation in LHg and MHg was not significantly different across the experimental conditions. Furthermore, for these regions, a 2-way ANOVA with the experimental condition and the hemisphere as factors did not reveal any significant difference between hemispheres.

The MEG

In all subjects, the evoked magnetic field measured over the helmet showed 3 components with reproducible latencies of 40/60 (double peak), 100, and 180 ms. Additionally, 2 components with smaller amplitudes occurred at about 240 and 350 ms. At these latencies, a dipolar pattern over the right and left temporal region, the right IPL, and the right PFC was observed. Figure 4 shows the butterfly plot of the evoked signals (a) and the global field power (b) for a representative subject (n°5). The time intervals used for the dipole fit are marked on the butterfly plot (see further on). In Figure 5, field maps and isofield contours are shown for subject n°5. We identified 7 sources according to the following procedure: First, a middle-latency bilateral component, characterized by a W-shaped waveform with 2 similar positive peaks at approximately 40 and 60 ms (P40/60) and a mean peak amplitude of 9 and 11 nAm for the right and left hemisphere, respectively, was localized in MHg anterior to primary auditory cortex. Second, a distinct, long-latency bilateral source was identified in the primary auditory cortex (LHg) and peaking at about 100 ms after the stimulus presentation (N100) with a mean amplitude of 34 and 27 nAm for the right and left hemisphere, respectively. A late component was also observed peaking at about 180 ms after the stimulus onset (P180, peak amplitude 23 nAm) and was localized in the PSTg in the right hemisphere. A left hemisphere source was also localized for the 180-ms component in 2 subjects, but further statistical analysis was not performed on this source. The position of these 5 ECDs was consistent with the centroids of the fMRI activations found bilaterally in MHg, LHg, and in right PSTg. In Figure 6, the dipole positions localized in each subject are superimposed on the individual fMRI maps for the MIXED condition. For each of the 5 sources in the right hemisphere, the grand average across subjects of the ECD waveform is shown in Figure 7 (upper, left side). The amplitude of the N100 peak in the right hemisphere was larger than the amplitude of the corresponding peak in the left hemisphere (P = 0.05). During the MIXED condition, the amplitude of the P40/60 was significantly larger (P < 0.05) than in the other conditions. The amplitudes of the other 4 sources localized in the supratemporal plane were larger in the MIXED condition than in the other ones, even if this comparison was not statistically significant.

Figure 4.

Butterfly plot of the evoked signals (a) and the global field power (b) for a representative subject. Time intervals used for dipole fit are shown. See also table 3 for further details.

Figure 4.

Butterfly plot of the evoked signals (a) and the global field power (b) for a representative subject. Time intervals used for dipole fit are shown. See also table 3 for further details.

Figure 5.

Field maps and isofield contours for a representative subject.

Figure 5.

Field maps and isofield contours for a representative subject.

Figure 6.

Individual dipole positions superimposed on the individual fMRI maps for the MIXED condition are shown for each subject.

Figure 6.

Individual dipole positions superimposed on the individual fMRI maps for the MIXED condition are shown for each subject.

Figure 7.

Upper: The seven ECDs modeling the evoked field are superimposed on the individual structural MRI—left side: 3 sources in the supratemporal plane and the grand average of the waveform of the 3 sources in the right hemisphere; right side: 2 sources in the supramarginal gyrus and in the PFC and the grand average of the waveform of the 2 sources in the right hemisphere (the waveform color corresponds to the dipoles color). Lower: Mean latencies and standard error of the 5 sources in the right hemisphere: MHg and LHg, PSTg, supramarginal gyrus (in the IPL), and PFC. The ANOVA revealed a significant difference between the latencies of the 5 sources in the right hemisphere, with P < 0.01.

Figure 7.

Upper: The seven ECDs modeling the evoked field are superimposed on the individual structural MRI—left side: 3 sources in the supratemporal plane and the grand average of the waveform of the 3 sources in the right hemisphere; right side: 2 sources in the supramarginal gyrus and in the PFC and the grand average of the waveform of the 2 sources in the right hemisphere (the waveform color corresponds to the dipoles color). Lower: Mean latencies and standard error of the 5 sources in the right hemisphere: MHg and LHg, PSTg, supramarginal gyrus (in the IPL), and PFC. The ANOVA revealed a significant difference between the latencies of the 5 sources in the right hemisphere, with P < 0.01.

Due to the fact that the 5 ECDs located in the supratemporal plane accounted for an average of 82% of the total variance for latencies larger than 220 ms, we decided to use fMRI results to seed additional sources in an attempt to more fully represent the data. Activation in fMRI suggested the addition of 2 sources in the right hemisphere. We therefore seeded 2 ECDs in the IPL and the PFC of the right hemisphere at locations corresponding to the fMRI activation in these regions. The ECD located in the IPL (sixth source) showed a component peaking at about 240 ms (P240): After adding the IPL dipole, the explained variance increased to 91.4% at this latency. The ECD located in the PFC (seventh source) exhibited a component peaking at about 350 ms after the stimulus onset (P350). After adding the PFC dipole, the explained variance increased to 89.7% at this latency. (See table 3 for a summary of ECDs definition and related fit interval). In general, the explained variance increased on average by 9.9% due to the IPL dipole and by 7.4% after adding the PFC dipole. The mean amplitude of these latter components was 11.12 and 13.82 nAm, respectively. The P350 amplitude differed across the experimental conditions. Specifically, it was stronger during the MIXED condition with respect to the other conditions (P < 0.05). The grand average across subjects of the waveform of these 2 sources is shown in Figure 7 (upper, right side). A one-way ANOVA for repeated measurements was then performed on the latency of each component of the right hemisphere for the CENTRAL versus RIGHT + LEFT contrast. For the components in the temporal and the parietal regions, a delay was observed during the CENTRAL condition, but the comparison was not significant.

Table 3

Definition of ECDs and related fit interval

Fitted ECDs Seeded from fMRI Fit interval (ms) 
1\2 Symmetric (P40/60No 40–60 
3\4 Symmetric (N100No 80–120 
5 Right hemisphere (P180No 120–210 
6 Right hemisphere (P240Yes 220–280 
7 Right hemisphere (P350Yes 330–360 
Fitted ECDs Seeded from fMRI Fit interval (ms) 
1\2 Symmetric (P40/60No 40–60 
3\4 Symmetric (N100No 80–120 
5 Right hemisphere (P180No 120–210 
6 Right hemisphere (P240Yes 220–280 
7 Right hemisphere (P350Yes 330–360 

Furthermore, one-way ANOVA for repeated measure was performed to verify statistically significant differences among the mean peak latencies of the 5 dipoles located in the right hemisphere (in MHg, LHg, PSTg, IPL, and PFC). The analysis revealed a statistical difference in peak latency (P < 0.01), with further post hoc analysis confirming that each component latency was significantly different from the others (P < 0.01). Figure 7 (lower) shows the mean latencies of the 5 sources together with the statistical significance levels.

Discussion

In the literature, the neurophysiological correlates of orienting attention in space have been extensively studied, mainly with regard to visual attention. Both universal and modality-specific systems have been hypothesized for attention processes (Bushara et al. 1999). Further, a 2-system attentional model for distinct stimulus characteristics: a posterior system monitoring stimulus position and an anterior system attending to the selection of stimulus features (Posner and Petersen 1990) has been described.

In a previous paper (Brunetti et al. 2005), we found that the reorienting of attention to auditory stimuli at unpredictable locations takes place in a circuit involving the supratemporal plane. More specifically, the posterior portion of the superior temporal gyrus and the supramarginal gyrus. Moreover, we found that the activation related to regularly moving stimuli were different from those produced by stimuli randomly presented at different locations. Starting from these considerations, we developed a novel paradigm to compare, under passive conditions, reorienting responses to spatially varying auditory targets. We took care to ensure that the reorienting response did not contain the execution of any motor response. The main advantage of our paradigm is that it allows us to manipulate the meridian effect by means of a contrast between the CENTRAL condition and the RIGHT and LEFT conditions. Using a completely passive paradigm, in which it was possible to control the place of sound appearance, we investigated the involvement of the temporoparietal junction and the ventral frontal areas (BA 44) in the reorienting of covert attention in the auditory modality. Particularly, we tried to answer 3 questions concerning the ventral frontoparietal network. We wanted to know if the network exhibited: a spatial variation effect, distinct covert motor responses for still and moving sounds, and an effect for whether or not attention had to cross the vertical meridian plane.

Activation of Superior Temporal Regions

fMRI results indicated 3 clusters of activation (BA 41, 42, 22) in the supratemporal plane during passive listening to sounds from different locations in the same hemifield and in different hemifields. Activation in MHg and LHg (BA 41, 42), comprising the primary auditory cortex, was observed bilaterally, in accordance with previous results (Rao et al. 1997; Nakai et al. 2005). An additional region in the PSTg was also activated. Analysis of MEG data revealed different sources in the supratemporal plane: 2 sources with 2 identical positive peaks at 40 and 60 ms (P40/60), 2 additional bilateral components peaking at 93 ms (N100), and a fifth source peaking at 182 ms (P180). The sources were localized in the primary auditory cortex (bilateral LHg and MHg) and in the right PSTg. Previous studies (Itoh et al. 2000; Yvert et al. 2001) found a middle-latency magnetic component in the supratemporal plane at a different latency and with constrasting results to hemispheric dominance. Some difference was found in the amplitude of the sources localized in the temporal region suggesting a response to predictability; however, this result was statistically significant only for the sources localized in LHg. The lack of statistical significance for the contrast in the other regions could be due to the limited number of subjects. MEG analysis also indicated a statistical trend for the response latency of left MHg, which was larger during the MIXED condition than during the other conditions. Essentially, there is some evidence that left hemisphere response is slower during the MIXED condition than during more regular conditions. This result suggests that the left hemisphere response in MHg could be affected by a spatial variation effect with a larger cognitive cost demanded when it is necessary to reorient attention to stimulus positions that randomly change in space, rather than toward regularly changing stimulus position. The involvement of the PSTg was in agreement with previous studies, further demonstrating the role of this area in the sound localization process (Rauschecker et al. 2000; Brunetti et al. 2005). These results suggest that the temporal regions (MHg, LHg, and PSTg) could be responsive to auditory location change detection, in accordance with previous studies that stress the role of the temporoparietal junction in the detection of stimulus salience over the processing of primary stimulus features (Corbetta and Shulmann 2002; Shulman et al. 2003).

Activation of IPL

Activation in the right inferior parietal lobule (Ba 40) was observed with some response to the reorienting of attention in space and across the vertical meridian plane. The involvment of the right parietal cortex in the attentional orientation process was observed in several clinical and neuroimaging studies (Karnath et al. 2001; Brunetti et al. 2005). The activation in this area (which together with the supratemporal plane forms the temporoparietal junction) is consistent with the ventral frontoparietal network described by Corbetta and Shulmann (2002). Furthermore, our MEG results suggest a trend in the latency of P240, the component localized in the IPL, which may be interpreted as the influence of the meridian crossing effect on IPL activity. This result, together with fMRI data, indicates that the right IPL is a region responsive to the auditory meridian crossing effect.

Activation of Frontal regions

The fMRI activation that we found in the frontal areas, specifically in the PFC (BA 44), define a circuit that precisely overlaps with the ventral frontoparietal network implicated in detecting unattended or low-frequency events. Nonetheless, the activation in PFC is quite different compared with that observed in the parietal region: PFC appears only marginally involved in the meridian crossing effect or the spatial variation effect. A possible interpretation of this dual association is that our paradigm does not completely eliminate the possibility of head movement or oculomotor response. Although our protocol explicitly requests movement suppression in the subjects, we do not completely bar movement through restraint, and this could affect the activation in prefrontal region. In fact, activation in the right PFC, together with activation in IPL, was observed in a number of studies using a no-go task, suggesting that inferior/ventral right prefrontal regions are involved in response inhibition or no-go behavior (Garavan et al. 2002). More recently, Heinen et al. (2006) found ventral prefrontal activation in an oculomotor no-go task.

The observed pattern of activation is different from the one shown in our previous study, in which frontal activation was not observed in a similar paradigm based on fixed sounds (Brunetti et al. 2005). Results from the present study demonstrate the response of temporal regions to the detection of sounds that change location in space, more intensive when the sounds change location randomly. Furthermore, the difference in activation intensity of the temporo parietal junction during listening to sounds that cross or do not cross the vertical meridian plane allows us to consider the hypothesis of a specific cognitive cost for this situation and suggest the involvement of the IPL in this process. Finally, the weak responses in PFC to both spatial variation and meridian crossing could be explained as response inhibition more than the covert motor response hypothesized above.

In terms of lateralization, the literature contains evidence suggesting that this cortical circuit seems to be strongly lateralized to the right hemisphere (Knight et al. 1998; Arrington et al. 2000; Daffner et al. 2000). Our results partially confirm this data because the parietal and frontal activations were observed in the right hemisphere only. However, the bilateral activation of the supratemporal plane was not significantly stronger in the right hemisphere than in the left.

All together, these data suggest that the auditory attentional-reorienting response starts bilaterally in the auditory cortex before moving to the right PSTg and later projecting to the right inferior frontal regions through the right inferior parietal cortex.

In summary, our multimodal study reveals activation in the IPL and in the PFC, together with activation in the supratemporal plane. These activations were similar when the sound position changed in the same hemifield at regularly varying locations but were significantly stronger when the sound position changed between the 2 hemifields. These results allow us to describe a network, with different involvement of the component regions, for the reorientation of attention toward changing auditory stimuli locations. Additionally, our MEG results demonstrate the temporal dynamics of the regional activations within the described network: The activation of Heschl's gyrus was observed 95 ms after stimulus, the peak latency of the PSTg occurred at 182 ms, the IPL peaked at 245 ms, and the frontal region peaked at 343 ms. This sequence of neural activation, integrated with the fMRI results, highlights a bottom-up progression from the temporal to the frontal cortex and shows the way in which neural activity propagates through the attentional reorienting network.

The authors would like to thank Professor Maurizio Corbetta, Washington University School of Medicine, for his invaluable suggestions, and Chris Lewis, Institute of Advanced Biomedical Technologies, University “G. D'Annunzio of Chieti, for a careful editing of the manuscript. The authors would also like to thank the anonymous reviewers for helpful comments on the manuscript. Conflict of Interest: None declared.

References

Ahlfors
SP
Simpson
GV
Dale
AM
Belliveau
JW
Liu
AK
Korvenoja
A
Virtanen
J
Huotilainen
M
Tootell
RB
Aronen
HJ
, et al.  . 
Spatiotemporal activity of a cortical network for processing visual motion revealed by MEG and fMRI
J Neurophysiol.
 , 
1999
, vol. 
82
 
5
(pg. 
2545
-
2555
)
Arrington
CM
Carr
TH
Mayer
AR
Rao
SM
Neural mechanisms of visual attention: object-based selection of a region space
J Cogn Neurosci.
 , 
2000
, vol. 
12
 (pg. 
106
-
117
)
Brunetti
M
Belardinelli
P
Caulo
M
Del Gratta
C
Della Penna
S
Ferretti
A
Lucci
G
Moretti
A
Pizzella
V
Tartaro
A
, et al.  . 
Human brain activation during passive listening to sounds from different locations: a combined fMRI/MEG pilot study
Hum Brain Mapp.
 , 
2005
, vol. 
26
 
4
(pg. 
251
-
261
)
Bushara
KO
Weeks
RA
Ishii
K
Catalan
MJ
Tian
B
Rauschecker
JP
Hallett
M
Modality-specific frontal and parietal areas for auditory and visual spatial localization in humans
Nat Neurosci.
 , 
1999
, vol. 
2
 
8
(pg. 
759
-
766
)
Corbetta
M
Shulman
G
Control of goal-directed and stimulus-driven attention in the brain
Neuroscience
 , 
2002
, vol. 
3
 
3
(pg. 
201
-
215
)
Cox
RW
AFNI: software for analysis and visualization of functional magnetic resonance neuroimages
Comput Biomed Res.
 , 
1996
, vol. 
29
 (pg. 
162
-
173
)
Daffner
KR
Mesulam
MM
Scinto
LF
Acar
D
Calvo
V
Faust
R
Chabrerie
A
Kennedy
B
Holcomb
P
The central role of the prefrontal cortex in directing attention to novel events
Brain
 , 
2000
, vol. 
123
 (pg. 
927
-
939
)
Downar
J
Crawley
AP
Mikulis
JD
Davis
KD
A multimodal cortical network for the detection of changes in the sensory environment
Nat Neurosci.
 , 
2000
, vol. 
3
 
3
(pg. 
277
-
283
)
Ferlazzo
F
Padovani
T
Couyoumdjian
A
Olivetti Belardinelli
M
Head-centered meridian effect on auditory spatial attention orienting
Q J Exp Psychol.
 , 
2002
, vol. 
55
 
3
(pg. 
937
-
963
)
Forman
SD
Cohen
JD
Fitzgerald
M
Eddy
WF
Mintun
MA
Noll
DC
Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold
Magn Reson Med.
 , 
1995
, vol. 
33
 (pg. 
636
-
647
)
Galaburda
A
Sanides
F
Cytoarchitectonic organization of the human auditory cortex
J Comp Neurol.
 , 
1980
, vol. 
190
 (pg. 
597
-
610
)
Garavan
H
Ross
TJ
Murphy
K
Roche
RAP
Stein
EA
Dissociable executive functions in the dynamic control of behaviour: inhibition, error detection and correction
Neuroimage
 , 
2002
, vol. 
17
 
4
(pg. 
1820
-
1829
)
Hall
DA
Haggard
MP
Akeroyd
MA
Palmer
AR
Summerfield
AQ
Elliot
MR
Gurney
EM
Bowtell
RW
Sparse temporal sampling in auditory fMRI
Hum Brain Mapp.
 , 
1999
, vol. 
7
 (pg. 
213
-
223
)
Heinen
SJ
Rowland
J
Lee
BT
Wade
AR
An oculomotor decision process revealed by functional magnetic resonance imaging
J Neurosci.
 , 
2006
, vol. 
26
 
52
(pg. 
13515
-
13522
)
Itoh
K
Yumoto
M
Uno
A
Kurauchi
T
Kaga
K
Temporal stream of cortical representation for auditory spatial localization in human hemispheres
Neurosci Lett.
 , 
2000
, vol. 
292
 (pg. 
215
-
219
)
Karnath
HO
Faber
S
Himmelbach
M
Spatial awareness is a function of the temporal not the posterior parietal lobe
Nature
 , 
2001
, vol. 
411
 (pg. 
950
-
953
)
Knight
RT
Scabini
D
Anatomic bases of event-related potentials and their relationship to novelty detection in humans
J Clin Neurophysiol.
 , 
1998
, vol. 
15
 (pg. 
3
-
13
)
Macaluso
E
Frith
CD
Driver
J
Supramodal effects of covert spatial orienting triggered by visual or tactile events
J Cogn Neurosci.
 , 
2002
, vol. 
14
 
3
(pg. 
389
-
401
)
Nakai
T
Matsuo
K
Ohgami
Y
Oishi
K
Kato
C
An fMRI study of temporal sequencing of motor regulation guided by an auditory cue: a comparison with visual guidance
Cogn Process
 , 
2005
, vol. 
6
 (pg. 
128
-
135
)
Oldfield
RC
The assessment and analysis of handedness: the Edinburgh Inventory
Neuropsychologia
 , 
1971
, vol. 
9
 (pg. 
97
-
113
)
Olivetti Belardinelli
M
Santangelo
V
The head-centred meridian effect: auditory attention orienting in conditions of impaired visuo-spatial information
Disabil Rehabil.
 , 
2005
, vol. 
27
 
13
(pg. 
761
-
768
)
Olivetti Belardinelli
M
Santangelo
V
Botta
F
Are vertical meridian effects due to audio-visual interference? A new confirmation with deaf subjects
Disabil Rehabil.
 , 
2007
, vol. 
29
 
10
(pg. 
797
-
804
)
Pizzella
V
Della Penna
S
Del Gratta
C
Romani
GL
SQUID systems for biomagnetic imaging
Supercond Sci Technol.
 , 
2001
, vol. 
14
 (pg. 
79
-
114
)
Posner
MI
Petersen
SE
The attention system of the human brain
Annu Rev Neurosci.
 , 
1990
, vol. 
13
 (pg. 
25
-
42
)
Rao
SM
Harrington
DL
Haaland
KY
Bobholz
JA
Cox
RW
Binder
JR
Distributed neural systems underlying the timing of movements
J Neurosci.
 , 
1997
, vol. 
17
 (pg. 
5528
-
5535
)
Rauschecker
JP
Tian
B
Mechanisms and streams for processing of “what” and “where” in auditory cortex
Proc Natl Acad Sci USA
 , 
2000
, vol. 
97
 
22
(pg. 
11800
-
11806
)
Rizzolatti
G
Riggio
L
Dascola
I
Umiltà
C
Reorienting attention across the horizontal and vertical meridians: evidence in favor of a premotor theory of attention
Neuropsychologia
 , 
1987
, vol. 
25
 (pg. 
31
-
40
)
Shulman
GL
McAvoy
MP
Cowan
MC
Astafiev
SV
Tansy
AP
d'Avossa
G
Corbetta
M
Quantitative analysis of attention and detection signals during visual search
J Neurophysiol.
 , 
2003
, vol. 
90
 
5
(pg. 
3384
-
3397
)
Talairach
J
Tournoux
P
Co-planar stereotaxic atlas of the human brain
 , 
1988
New York
Thieme
Yvert
B
Crouzeix
A
Bertrand
O
Seither-Preisler
A
Pantev
C
Multiple supratemporal sources of magnetic and electric auditory evoked middle latency components in humans
Cereb Cortex
 , 
2001
, vol. 
11
 (pg. 
411
-
423
)
Zimmer
U
Macaluso
E
Processing of the binaural sound coherence in the human brain
Cogn Process
 , 
2006
, vol. 
7
 
Suppl 1
(pg. 
109
-
110
)