Abstract

Recent studies investigating the influence of spatial-selective attention on primary somatosensory processing have produced inconsistent results. The aim of this study was to explore the influence of tactile spatial-selective attention on spatiotemporal aspects of evoked neuronal activity in the primary somatosensory cortex (S1). We employed simultaneous electroencephalography (EEG)–functional magnetic resonance imaging (fMRI) in 14 right-handed subjects during bilateral index finger Braille stimulation to investigate the relationship between attentional effects on somatosensory evoked potential (SEP) components and the blood oxygenation level–dependent (BOLD) signal. The 1st reliable EEG response following left tactile stimulation (P50) was significantly enhanced by spatial-selective attention, which has not been reported before. FMRI analysis revealed increased activity in contralateral S1. Remarkably, the effect of attention on the P50 component as well as long-latency SEP components starting at 190 ms for left stimuli correlated with attentional effects on the BOLD signal in contralateral S1. The implications are 2-fold: First, the correlation between early and long-latency SEP components and the BOLD effect suggest that spatial-selective attention enhances processing in S1 at 2 time points: During an early passage of the signal and during a later passage, probably via re-entrant feedback from higher cortical areas. Second, attentional modulations of the fast electrophysiological signals and the slow hemodynamic response are linearly related in S1.

Introduction

Selective attention to a location in space improves the processing of stimuli expressed in decreased reaction times (RTs) or increased accuracy (Posner et al. 1978), and involves specific cortical networks. Functional imaging and electrophysiological studies found activation of a multimodal fronto-parietal network during spatial-selective attention (Eimer and Driver 2001; Corbetta and Shulman 2002; Macaluso et al. 2003). Research from the past 15 years has established the view that spatial attention to auditory or visual stimuli also enhances activity in primary sensory areas (Woldorff and Hillyard 1991; Woldorff et al. 1993; Roelfsema et al. 1998; Vidyasagar 1998; Alho et al. 1999; Brefczynski and DeYoe 1999; Gruber et al. 1999; Martinez et al. 1999; Somers et al. 1999; Hashimoto et al. 2000; Noesselt et al. 2002). For the somatosensory system, effects of attention on the primary somatosensory cortex (S1) were shown in monkeys using single unit recordings (Hyvarinen et al. 1980), in human somatosensory evoked potentials (SEPs) (Desmedt and Tomberg 1989; Garcia-Larrea et al. 1991; Eimer and Forster 2003; Zopf et al. 2004), positron emission tomography (PET) (Meyer et al. 1991), and functional magnetic resonance imaging (fMRI) (Johansen-Berg et al. 2000; Meador et al. 2002; Arthurs et al. 2004). Most imaging studies, however, investigated nonselective variants of attention, in which stimulation during attention (e.g., counting certain stimuli) was compared with stimulation during another task (e.g., reading or relaxing). Such a comparison may include unspecific effects, such as variations of alertness or the anticipation of the stimuli in the attended condition (Naatanen 1992). In order to investigate the pure effects of selective attention, it is important to control for the type of task while manipulating only the direction of attention.

Thus, less is known about the effects of tactile spatial-selective attention in S1, that is, of varying the spatial focus of attention during constant stimulation. In a PET study, Roland (1981) compared activations for the anticipation of hand versus foot stimulation. He found an increased blood flow in the contralateral hand or foot representation area within S1 for expected compared with unexpected stimulation. In an fMRI study Meador et al. (2002) found increased activity in contralateral S1 when subjects were instructed to discriminate numbers written on the palm of a specified hand while ignoring the numbers written on the other hand. Also, in a recent electroencephalography (EEG) study, the effects of tactile spatial selective attention to vibrotactile stimuli in the steady-state somatosensory evoked responses from 500 to 3000 ms after stimulation onset could clearly be assigned to S1 (Giabbiconi et al. 2007). A comparable effect was also shown in a magnetoencephalographic (MEG) study during a task of tactile spatial-selective attention, where S1 assigned gamma-band activity significantly increased following attended stimuli (Bauer et al. 2006).

These studies suggest that spatial-selective attention enhances activity in contralateral S1. However, it remains unresolved if this enhancement results from 1) a modulation of the signal at an early passage in the primary cortical area or 2) reentrant feedback modulation from secondary somatosensory cortex (S2) or higher cortical areas projecting to S1. Due to the sluggishness of the hemodynamic response, fMRI studies alone cannot clarify the precise temporal sequence of the attentional modulation of activity in S1. One approach to solve this problem is combining fMRI with simultaneous recording of high temporal resolution EEG. Two combined EEG–fMRI studies investigating visual spatial attention found an increased blood oxygenation level–dependent (BOLD) signal in the primary visual cortex (V1) for attended visual objects (Martinez et al. 1999; Noesselt et al. 2002). However, in the EEG, the initial sensory input to the striate cortex at 50–55 ms (C1-component) was unaffected by attention. According to the authors, this discrepancy may result either 1) from a delayed reentrant feedback into V1 from higher cortical areas (Super et al. 2001) or 2) top-down processes producing a sustained increase in neural activity (Luck et al. 1997; Kastner et al. 1999), without modulating the initial evoked response. To investigate spatial-selective attention in the somatosensory system we transferred this approach by simultaneously recording EEG and fMRI.

In general, mechanical stimulation elicits 2 reliably measurable early SEP components, most probably generated in contralateral S1 (P50, N80) and a mid-latency component (P100), most probably generated in bilateral S2 (Hari et al. 1984; Hamalainen et al. 1988; Allison et al. 1989, 1991, 1992; Mima et al. 1998). In a recent MEG study using tactile stimulation (Zhu et al. 2007), the peak for the early contralateral source was found at 45 ms in the posterior wall of the central sulcus, whereas the maximum for the late response was found at 100 ms in the upper bank of the Sylvian fissure. Following early and mid-latency components, long-latency components (N140, P190) are generated beyond somatosensory regions such as bilateral frontal lobes including the orbito-frontal, lateral, and medial cortex (Desmedt and Robertson 1977; Allison et al. 1989, 1992). Previous results about the effects of spatial-selective attention on SEPs are rather inconsistent: In some studies the N80 was found to be enhanced by attention and this effect was localized in S1 (Desmedt and Robertson 1977; Michie et al. 1987; Eimer and Forster 2003), whereas other studies did not find a modulation of SEP components generated in S1 (Michie 1984; Eimer and Driver 2000; Zopf et al. 2004). Different stimulation modalities (electrical vs. mechanical), stimulus intensities and tasks might be responsible for these variable findings. Eimer and Forster (2003) and Zopf et al. (2004) conducted similar experiments using bilateral mechanical stimulation and attention directed to one hand in order to detect deviant among standard stimuli. Although the former found an effect of attention on the N80, the earliest attentional modulation found by the latter was of the N140. Furthermore, in both studies subjects reached a detection rate of almost 100%. We assume that easily discernable deviants and standards may require less attentional resources to one hand. Initial studies investigating effects of selective attention on auditory potentials reported 1st effects after 100 ms being modulated by attention (Picton and Hillyard 1974). However, increasing target detection difficulty also lead to effects in auditory evoked components after 20–50 ms, which has been ascribed to the increased attentional engagement (Woldorff et al. 1987; Woldorff et al. 1993). This idea may be generalized to attentional effects in early SEPs by sharpening the difference between the neural response to the attended and unattended finger sensations. Therefore, we applied a demanding pattern discrimination task requiring high attentional engagement.

The relation between effects of tactile spatial-selective attention on early SEP components and attentional BOLD signal increases in S1 is unknown. In sequential somatosensory EEG and fMRI recordings the electrically evoked N20–P25 to different stimulus intensities was found to increase linearly with increasing BOLD signal in S1 (Arthurs et al. 2000, 2004). However, although a cognitive distraction task during electrical stimulation did not modulate the N20–P25, the same distraction task significantly reduced the BOLD signal in S1 (Arthurs et al. 2004). Thus, no relationship between the early SEP component and the BOLD signal in an attentional task could be established. In line with the combined visual EEG–fMRI studies, the authors suggest that the BOLD response in S1 should rather be sensitive to metabolic changes accompanying long-latency SEPs (140–230 ms) known to be sensitive to attention. Alternatively, they propose that EEG and fMRI either reflect activity in functionally distinct regions within S1 or show sensitivity to different types of neuronal responses (as slow bursts, oscillations or changes in synchronicity) being differentially modulated by attention.

Although effects of tactile spatial-selective attention have been found on early SEPs (Eimer and Forster 2003) and on BOLD signal in S1 (Meador et al. 2002), the relationship between the effects in both measures has not been clarified as yet. Therefore confirming the finding of an effect of tactile spatial-selective attention on early SEPs and the BOLD signal in S1 constitute necessary prerequisites for investigating their relationship.

By simultaneously recording EEG and fMRI during a task of tactile spatial-selective attention, we posed the following questions:

  • 1) When does tactile spatial-selective attention 1st modify the SEP signal to a Braille pattern stimulus? Does attention affect S1 during an early signal passage having an effect on early (P50, N80) SEP components or do 1st attentional modulations occur only in higher cortical areas, having an effect on mid- and long-latency components of the SEP as reported previously?

  • 2) Will the simultaneously recorded BOLD signal in S1 contralateral to the focus of attention be increased for attended as compared with unattended Braille patterns?

  • 3) If attention exhibits an effect on early SEP components and the BOLD signal in contralateral S1, is there a correlation between both measures of neural activity?

Materials and Methods

Subjects

Fourteen healthy volunteers (6 women) between 21 and 29 years (mean age = 26.1, standard deviation [SD] = 2.2) participated in the study. All were right-handed according to the Edinburgh Handedness Inventory (Oldfield 1971) (EHI = 79.1; standard error of the mean [SEM] = 5.9) and had no history of neurological or psychiatric illness. All subjects gave informed written consent and were paid for their participation. The study was approved by the ethics committee of the Charité, University Medicine Berlin.

Tactile Stimuli

Tactile stimuli were applied to the distal phalanx of left and right index fingers using 2 MR-compatible piezoelectric Braille stimulators (Metec GmbH, Stuttgart, Germany). Each stimulator had 8 individually controllable plastic pins, grouped in a 2 × 4 array (Fig. 1A). Using a custom built electrical drive, pins could be elevated from the resting position by 0.7 mm with a rise-time of 1 ms [tactile force = 1.7 × 10-1 N (±1 × 10-2 N)]. In the present experiment we presented a standard and a deviant pin pattern: For the standard pattern, 4 pins of the 2 outer rows and for the deviant pattern 4 pins of the 2 middle rows were elevated (Fig. 1B).

Figure 1.

(A) Braille stimulator used for tactile stimulation of the index finger. White dots on the black rectangle in the middle depict the 8 plastic pins, which could be individually elevated. (B) Schematic figure of the standard and deviant patterns applied to the 1st segment of the index fingers used for the oddball-paradigm. (C) The oddball task used to investigate spatial-selective attention. An example sequence of Braille patterns applied to the 1st segment of the left and right index finger preceded by the auditory cue. Rectangles represent the piezoelectrical drive. White circles represent pins at rest position, gray pins denote elevated pins. The timing refers to the beginning of a task block following the 30 s baseline block.

Figure 1.

(A) Braille stimulator used for tactile stimulation of the index finger. White dots on the black rectangle in the middle depict the 8 plastic pins, which could be individually elevated. (B) Schematic figure of the standard and deviant patterns applied to the 1st segment of the index fingers used for the oddball-paradigm. (C) The oddball task used to investigate spatial-selective attention. An example sequence of Braille patterns applied to the 1st segment of the left and right index finger preceded by the auditory cue. Rectangles represent the piezoelectrical drive. White circles represent pins at rest position, gray pins denote elevated pins. The timing refers to the beginning of a task block following the 30 s baseline block.

One task block consisted of 40 stimuli, that is, 20 stimuli for each finger, including 2 deviant patterns and 18 standard patterns, adding up to 32 deviants and 288 standards in total for each finger. Each stimulus lasted 200 ms; the interstimulus interval at a given finger was 500–700 ms and only one finger was stimulated at a time, resulting in a total block time of 32 s (Fig. 1C).

Experimental Protocol

A short practice session of 5-min duration was performed after attaching the EEG electrodes and before placing the subjects into the MR scanner. After the practice session, subjects were brought into the scanner bed with a Braille stimulator to the left and right side of their body and their index fingers were placed on the corresponding stimulators.

All runs (4 in total, including 8 alternating baseline and task blocks each; duration of each run was 8.5 min) started with a baseline period of 30 s without stimulation. The beginning of the stimulation of each run was triggered by the fMRI scanner pulses so that stimulation started after a specific interval after starting the scanner. During the baseline condition subjects were not stimulated and instructed to relax. At the beginning of each task block, 2 s before stimulation onset, a binaurally sine wave tone of 250 or 500 Hz frequency was presented for 500 ms. The tone was transmitted via the standard pneumatic headphones of the SIEMENS MR-system. When a high tone was presented, subjects were instructed to direct their attention to the stimulation of the left index finger and to ignore stimulation at the right index finger and vice versa following a low tone. High and low tones were given in random order and with equal probability across each run. During the 32 s of a given the task block, both index fingers were stimulated in a pseudorandom order with at most 3 consecutive stimulations to the same finger. Using a classical oddball-paradigm, subjects were asked to detect rare deviant stimulus patterns among frequent standard stimulus patterns at the attended finger by pressing a pedal with their right foot. The pedal was attached to the end of the bed. Between runs subjects could take a rest for about 3 min. Experimental stimulation and response registration was controlled by a computer running Presentation (V0.7.1., Neurobehavioral Systems, Albany, CA) on an MS Windows 98 platform.

During the entire experiment, subjects kept their eyes closed following the familiar practice of closing the eyes when concentrating on a demanding nonvisual task (Kawashima et al. 1995). Closing eyes has been shown to influence occipital alpha rhythms but does not seem to affect early SEPs (Emerson et al. 1988; Gobbele et al. 2000). Subjects were also instructed to avoid movements of the body, in particular of eyes and fingers.

Recordings and Image Acquisition

We recorded the electroencephalogram (BrainAmp MR+, BrainProducts, Inc., Munich, Germany) from 24 sintered Ag/AgCl ring electrodes using a 10/20 standard system electrode cap (Brain Cap, Falk Minow Services, Germany) referenced against FCz. The horizontal electrooculo gram (EOG) was recorded bipolarly from the outer canthi of both eyes. The vertical EOG was recorded above and below the left eye. Impedance was kept below 5 kΩ and the sampling rate was 5 kHz.

Simultaneously to the recording of the EEG, we acquired functional images with a 1.5-Tesla MRI scanner (SONATA, Siemens, Erlangen, Germany) using the standard circular polarized head coil. BOLD contrasted images were obtained using a T2* weighted 2D gradient echo EPI (echo planar imaging) pulse sequence. During the experiment, we acquired 704 EPI images comprising 26 slices covering the whole brain parallel to the anterior–posterior commissural plane (TR [repetition time] = 3 s, time of acquisition = 2.5 s, TE [echo time] = 40 ms, flip angle = 90°, matrix = 64 × 64, voxel size = 4 mm × 4 mm × 4 mm). In addition we recorded a high resolution structural T1-weighted 3D-magnetization prepared rapid acquisition gradient echo sequence of every subject (TR = 12.24 ms, TE = 3.56 ms, flip angle = 23°, voxel size = 1 mm × 1 mm × 1 mm) (Deichmann et al. 2004). To reduce movement artifacts, subjects’ heads were immobilized with a vacuum pad.

EEG Data Analysis

Because MR gradients during MR image acquisition contaminate the physiological EEG signal and occur as high-amplitude and multifrequency artifacts, we corrected the EEG for MR gradient artifacts by means of an algorithm provided by the Vision-Analyzer software (V0.1.03, Brain Products, Inc., Munich, Germany). This correction algorithm subtracts an artifact template, based on a sliding average of the 10 previous artifacts from the current artifact interval (Allen et al. 2000). For further analysis, the EEG data were recalculated to average reference, filtered with a bandpass of 0.1–80 Hz, and down-sampled to 200 Hz. We removed trials with horizontal eye movements or other artifacts identified by visual inspection at any electrode location manually.

For the SEP analysis we segmented the data offline from 200 ms before to 700 ms after the stimulus onset and averaged them for each stimulation condition. Because the focus of our study was on the effect of spatial-selective attention, deviant stimuli were excluded from further analysis and only attended and unattended standards were averaged for each hand separately.

Mean SEP amplitudes were computed within the following time windows relative to stimulus onset: P50 (40–70 ms), N80 (70–100 ms), and P100 (100–130 ms). Individual peak values were derived from the local amplitude maximum/minimum within each time window and were analyzed with the following repeated measures analyses of variance (ANOVAs): 1) For lateral electrodes, the factors were attention (attended vs. unattended standard pattern), side of stimulation (left vs. right index finger) hemisphere (contralateral vs. ipsilateral to the stimulated hand) and electrodes (FP1/2, F3/4, FC5/6 C3/4, CP1/2, CP5/6, P3/4, O1/2). 2) For left and right index finger stimulation at lateral electrodes, the factors were attention, hemisphere (left vs. right) and electrodes. At the central midline (Fz, Cz, and Pz) separate ANOVAs were conducted for the factors attention and electrodes. Greenhouse–Geisser corrected degrees of freedom were used in cases of sphericity violation. For the ANOVA for left and right index finger stimulation, we report only statistically significant effects that include the factor attention. Significant effects unrelated to the factor attention can be derived from the statistic table in the Supplementary Material (Supplement Table 1). To investigate long-latency effects of attention (140–600 ms), EEG data underwent a topographic ANOVA (LORETA, Strik et al. 1998). In a 1-way replicated design, topographic average-maps of attended and unattended standard stimuli were compared for every sampling point from 140 to 600 ms.

fMRI Data Analysis

Preprocessing

We analyzed the data with SPM2 (http://www.fil.ion.ucl.ac.uk). MR images were corrected for temporal differences in slice acquisition within 1 repetition time and for head motion by realigning all images to the 1st image. To allow for intersubject analysis, the images were normalized to the Montreal Neurological Institute (MNI) standard brain, retaining the original voxel size of 4 mm × 4 mm × 4 mm. Then the normalized functional images were spatially smoothed using a Gaussian kernel with 8-mm full width at half maximum. Finally, to remove low-frequency signal drifts or aliasing effects caused by physiological artifacts, the voxel time series were high pass filtered (cut off frequency = 1/256 Hz) and, to remove high-frequency noise, intrinsic autocorrelations were modeled.

Statistics

Statistics were performed based on the general linear model approach implemented in SPM2. For each subject we estimated a model containing the following explanatory variables (regressors): 1) 4 regressors of interest for left and right attended and unattended standard stimuli; 2) in order to eliminate variance components of no interest we introduced a regressor for the deviant stimuli and the 6 realignment parameters (1 parameter for each translation- and rotation-axis, respectively) calculated during the preprocessing procedure. Regressors for the standard and deviant stimuli had been generated by convolving the stimulus stick-functions with the standard canonical hemodynamic response function as implemented in SPM2.

After fitting the described model into the experimental data, voxel-wise linear contrasts were computed by means of the estimated model weights for the regressors regarding the standard stimuli. Thus, for each subject contrast images for the 2 main effects of interest, respectively (1: attend left, i.e., left stimulus attended and right stimulus unattended minus baseline, 2: attend right, i.e., right stimulus attended and left stimulus unattended minus baseline) and for the 2 differential effects, respectively (attend left minus attend right and vice versa) were generated.

Group statistics for the main effects were performed by calculating a between subjects ANOVA (PFDR (false discovery rate) - corrected < 0.005, df = 13, minimal cluster size [k] = 15 voxels). In order to describe the brain regions that showed a positive rather than a negative difference, we used the main effect of attend left minus baseline with a less conservative threshold of Puncorrected < 0.01, as a mask for the differential contrast attend left minus attend right and vice versa for attend right minus attend left (Puncorrected < 0.03, df = 13, k = 3 voxels). The differential contrasts will show the mere effect of spatial-selective attention because unspecific effects will be canceled out by the subtraction method.

Because of a strong anatomical a priori hypothesis about the effect in a very small and specific anatomical area, namely the hand area of S1 in the hemisphere contralateral to the focus of attention, the relatively liberal significance threshold seems reasonable. To further diminish the probability of unspecific findings and to verify the anatomical location of the results, we created an fMRI-literature based anatomical reference for the hand area in S1. We only included studies with tactile or electrical stimulation of the fingers (digit 2–digit 5) or median nerve. Thus, 10 recent papers containing data from 69 subjects were selected (Backes et al. 2000; Francis et al. 2000; Deuchert et al. 2002; McGlone et al. 2002; Blankenburg et al. 2003; Stoeckel et al. 2003, 2004; Thees et al. 2003; Hlushchuk and Hari 2006; Arthurs et al. 2007). The coordinates of all stimulation related activations in S1 reported by the authors were pooled and—if necessary—transformed to the MNI space. This was done by applying the affine algorithm proposed by Brett (Brett et al. 2001). Based on this data set the probability that a given activation focus actually lay within the hand area of S1 can be estimated by calculating a 3D normal (Gaussian) distribution G(x, y, z) as follows (Turkeltaub et al. 2002): 

graphic
where C is the covariance matrix for all coordinate triples x, y, z from the underlying literature and mx, my, mz are the mean values of the x, y, and z coordinates, respectively (Nielsen and Hansen 2002). The outer limits of the finally used anatomical reference were defined by thresholds of ±1, 2, and 3 SD of the resulting 3D distribution (Fig. 2). Thus, we were able to verify if an inference statistical effect was located in the expected hand area of S1.

Figure 2.

Probability maps of the hand area in S1 derived from the meta analysis superimposed on the single-subject T1-MNI-template. The grid illustrates the MNI space and the x, y, z coordinates indicate the center of the map. Circles in the upper and lower panels depict the outer limits of 1 (black), 2 (white), and 3 (black) standard deviations (SDs) of anatomical reference probability map. LH = left hemisphere, RH = right hemisphere.

Figure 2.

Probability maps of the hand area in S1 derived from the meta analysis superimposed on the single-subject T1-MNI-template. The grid illustrates the MNI space and the x, y, z coordinates indicate the center of the map. Circles in the upper and lower panels depict the outer limits of 1 (black), 2 (white), and 3 (black) standard deviations (SDs) of anatomical reference probability map. LH = left hemisphere, RH = right hemisphere.

Correlation Analysis

The relationship between the attentional effects on fast electrophysiological signals and the slow hemodynamic signal changes in the somatosensory cortex was addressed by calculating a time course correlation analysis across subjects. We correlated the individually averaged difference time course of the EEG data (attend left minus attend right for left standard stimuli and vice versa for right stimuli from −120 to 600 ms relative to stimulus onset) with the parameter estimates of the individual fMRI contrast (attend left minus attend right and vice versa for right stimuli). To focus on our research questions concerning the somatosensory cortex and to generate a more detailed picture of the relationship, we calculated the correlation with the signal in 4 anatomical regions of interest (ROIs) of contralateral S1 and S2, respectively. To do this, we defined the ROIs by generating Most Probability Maps for S1 and S2 using the probabilistic cytoarchitectonic anatomy toolbox by Eickhoff et al. (2005) implemented in SPM2. Using MarSBaR (http://marsbar.sourceforge.net/), we then extracted the parameter estimates for each subject for the respective differential contrast from the time series by applying spherical masks with a diameter of 8 mm centered at the peak voxels. For the EEG signal, we selected the centro-lateral electrodes (FC5/6, C3/4, CP5/6, P3/4), which exhibited the largest stimulation effects. Then, an across subject correlation analysis was conducted for every sample time point between the EEG difference amplitude and the parameter estimates.

Results

Behavioral Data

Subjects detected 66.3% (SEM = 3.2%) of the left- and 64.6% (SEM = 3.7%) of the right-finger deviants. The mean deviant detection rate was 65.5% (SEM = 2.8%). Subjects responded falsely positive in 0.2% of the trials for left- and right-finger standards resulting in a mean signal detection criterion for perceptual sensitivity (d′) of 3.28 (min. = 1.64, max. = 3.92). Mean RT was 800 ms (SEM = 20 ms) for left- and 798 ms (SEM = 26 ms) for right-finger deviants. Detection rate and RT did not differ significantly for left and right deviant stimuli (see Supplement Fig. 1 for a detailed presentation of the individual behavioral data).

EEG Data

As can be seen in Figure 3, left and right tactile stimulation evoked the 3 expected SEP components (P50, N80, and P100).

Figure 3.

Grand-averaged waveforms for the tactile Braille standard stimuli applied to the left (A) and right (B) index finger at electrodes FC5/6, C3/4, and CP5/6, located above the contralateral (3 upper rows) and ipsilateral (3 lower rows) hemisphere for left and right attended and unattended standard stimuli (attended = solid line; unattended = dashed line). Waveforms are depicted from −120 to 600 ms in relation to the onset (0 ms) of the stimulus.

Figure 3.

Grand-averaged waveforms for the tactile Braille standard stimuli applied to the left (A) and right (B) index finger at electrodes FC5/6, C3/4, and CP5/6, located above the contralateral (3 upper rows) and ipsilateral (3 lower rows) hemisphere for left and right attended and unattended standard stimuli (attended = solid line; unattended = dashed line). Waveforms are depicted from −120 to 600 ms in relation to the onset (0 ms) of the stimulus.

P50

The repeated measures ANOVA for the P50 revealed a strong trend for the main effect of attention (F1,14 = 4.34; P = 0.054) and an interaction between attention, hemisphere and electrode positions (F2.3,29.8 = 3.86; P < 0.05; ϵ = 0.33). For left-side stimulation, amplitudes were more positive at contralateral parietal and more negative at ipsilateral frontal electrode positions (Figs. 3A and 4A). The ANOVA of the P50 following left-side stimulation revealed a main effect of attention (F1,13 = 5.16; P < 0.05), an interaction between attention, hemisphere, and electrode position (F2.3,29.5 = 3.61; P < 0.05; ϵ = 0.32) and a trend for an interaction between attention and hemisphere (F1,13 = 4.30; P = 0.059) for the lateral electrode positions. The interactions were due to the fact that over the contralateral right hemisphere, amplitudes were more positive and more extended for attended compared with unattended stimuli whereas over the ipsilateral left hemisphere they were more negative for attended compared with unattended stimuli (Figs 3A and 4A). For right-side stimulation, differences between attended and unattended stimuli were smaller than for left-side stimulation. Moreover, in this stimulation condition amplitudes were positive at contralateral parietal and negative at contralateral frontal electrode positions (Figs 3B and 4A). For right index finger stimulation, the analysis of the P50 revealed no main effect or interaction for the factor attention.

Figure 4.

Group analysis of the effects of attention on the topographic voltage distribution and the BOLD signal. (A) Grand-averaged topographic voltage distributions for the 3 SEP components of interest (P50, N80, and P100) for the left and right attended and unattended standard stimuli and their respective difference voltage distributions for attended minus unattended stimuli. Maps are derived from the peak amplitudes within the respective time windows (P50 = 40–70 ms, N80 = 70–100 ms, P100 = 100–130 ms). Asterisks mark the SEP components that had revealed a significant main effect of attention or interaction including the factor attention in the ANOVA (n.s. = not significant). (B) fMRI group analysis of the effects of attention on the BOLD signal superimposed on the single-subject T1-MNI-template. Circles in the upper and lower panels depict the outer limits of 1 (black), 2 (white), and 3 (black) SD of anatomical reference probability map of the hand area in S1 derived from the meta-analysis. LH = left hemisphere, RH = right hemisphere. BOLD contrast images for attention to the right (yellow) and to the left (green) index finger minus the baseline condition and the overlapping effects for both conditions (red) (PFDR-corrected < 0.005). (C) Differential BOLD contrast image for the effects of spatial-selective attention for attend right versus attend left (Puncorrected < 0.03). (D) Differential BOLD contrast image for the effects of spatial-selective attention for attend left versus attend right (Puncorrected < 0.03).

Figure 4.

Group analysis of the effects of attention on the topographic voltage distribution and the BOLD signal. (A) Grand-averaged topographic voltage distributions for the 3 SEP components of interest (P50, N80, and P100) for the left and right attended and unattended standard stimuli and their respective difference voltage distributions for attended minus unattended stimuli. Maps are derived from the peak amplitudes within the respective time windows (P50 = 40–70 ms, N80 = 70–100 ms, P100 = 100–130 ms). Asterisks mark the SEP components that had revealed a significant main effect of attention or interaction including the factor attention in the ANOVA (n.s. = not significant). (B) fMRI group analysis of the effects of attention on the BOLD signal superimposed on the single-subject T1-MNI-template. Circles in the upper and lower panels depict the outer limits of 1 (black), 2 (white), and 3 (black) SD of anatomical reference probability map of the hand area in S1 derived from the meta-analysis. LH = left hemisphere, RH = right hemisphere. BOLD contrast images for attention to the right (yellow) and to the left (green) index finger minus the baseline condition and the overlapping effects for both conditions (red) (PFDR-corrected < 0.005). (C) Differential BOLD contrast image for the effects of spatial-selective attention for attend right versus attend left (Puncorrected < 0.03). (D) Differential BOLD contrast image for the effects of spatial-selective attention for attend left versus attend right (Puncorrected < 0.03).

N80

The next peak following the P50 was a contralateral negative component at 80 ms (Figs 3A,B and 4A). For left and right stimuli, the peaks for attended stimuli were more negative than for unattended stimuli. The analysis of the N80 revealed a trend for the main effect of attention (F1,13 = 3.67; P = 0.078) and resulted in an interaction between attention and electrode positions (F2.3,29.3 = 4.68; P < 0.05; ϵ = 0.32). For left-side stimulation, the analysis of the N80 did not result in any significant effect including the factor of attention. For right-side stimulation, the ANOVA of the N80 resulted in an interaction between attention and electrode positions (F2.7,35.8 = 5.38; P < 0.01; ϵ = 0.39) for lateral as well as for central electrode positions (F2,26 = 4.14; P < 0.05). The signal was larger for attended stimuli at frontal positions (Fig. 3B). The ANOVA at central electrode positions also revealed a main effect of attention (F1,13 = 7.9; P < 0.05).

P100

A 3rd peak with a positive parietal deflection can be seen at 100 ms (P100) (Figs 3A,B and 4A). The ANOVA for left and right stimuli revealed an interaction between attention and electrode position (F1.9,25.1 = 4.11; P < 0.05; ϵ = 0.28) and an interaction between side of stimulation, attention and electrode position (F2.3,89.2 = 6.98; P < 0.005; ϵ = 0.32). For left-side stimulation, the ANOVA of the P100 resulted in an interaction between attention and electrode position (F2.3,29.8 = 10.7; P < 0.001; ϵ = 0.33). This was due to the fact that amplitudes from frontal electrodes were more negative and amplitudes from parietal electrodes were positive for attended compared with unattended stimuli. The same effect was found for central electrode positions (F2,26 = 6.0; P < 0.01) (Fig. 3A). For right-side stimulation, the analysis of the P100 revealed no significant main effect or interaction including the factor attention (Figs 3B and 4A).

Long-Latency EEG Components (140–600 ms)

For left standard stimuli, significant differences between attended and unattended standard stimuli (P < 0.05) were found at 230–575 ms (Fig. 3A). For right standard stimuli, the difference was significant at 175–190 ms, 230–240 ms, 295–360 ms, 380–440 ms, 460–485 ms, and at 500 ms (Fig. 3B).

fMRI Data

Main Effects of Attention versus Baseline

For the baseline contrasts, representing activation following left- and right-finger stimulation under both directions of attention, we found increased hemodynamic responses in several overlapping brain regions (Table 1 and Fig. 4B). Both contrasts led to an increase of the BOLD signal in bilateral postcentral gyri (PoCG), including S1 (Brodmann area [BA] 1 and 2) and the parietal operculum (OP, i.e., S2) (OP1, OP4, and BA 40). These large activation clusters extended to the inferior parietal lobe (IPL). For both contrasts, the hemodynamic response in right OP had the highest stimulus related signal change. Also in the left inferior frontal gyrus (IFG), the left precentral gyrus (PrCG) and bilateral in the medial frontal gyrus (MdFG, i.e., supplementary motor area, SMA) overlapping hemodynamic responses were found. Attention to the left but not to the right side resulted in activity in right PrCG extending to the middle frontal gyrus (MFG).

Table 1

fMRI BOLD areas of activation modulated by Braille stimulation and attention

Brain region Hem Comparison attend left versus baseline
 
Comparison attend right versus baseline
 
  k x y z BA T value k x y z BA T value 
Parietal lobe 
    PoCG R 94 56 −20 24 OP4 (S2), 3 (S1) 13.71* 45 56 −20 24 OP4 (S2), 3 (S1) 13.32* 
   60 −28 24 OP1 (S2) 10.43  64 −24 20 OP1 (S2) 10.74 
    IPL   52 −48 44 40 9.41  52 −28 24 40 10.37 
    PoCG L 27 −44 −28 32 2 (S1) 9.56* 78 −44 −28 32 2 (S1) 12.82* 
    IPL   −56 −32 24 40, OP1 (S2) 8.00       
   −56 −24 28 40, OP1 (S2) 7.62       
    PoCG L 19 −52 −32 52 1, 2, 40 (S1) 9.07*  −60 −28 44 1 (S1) 11.92 
   −60 −28 44 1, 2 (S1) 8.86  −52 −28 52 S (S1) 10.83 
        15 −52 −4 8 OP4 (S2) 8.11* 
    IPL   −52 −44 52 40 6.82       
    IPL R       18 44 −36 48 40 8.62* 
         56 −44 40 40 8.38 
         40 −36 40 40 7.90 
Frontal lobe 
    IFG L 34 −60 8 32 9 9.18* 45 −60 8 32 9 10.41* 
    PrCG   −48 −4 48 8.12  −40 −4 60 10.08 
   −52 0 36 8.00  −56 0 40 9.54 
    MdFG L 20 −8 0 64 6 8.80*       
  4 0 68 8.47 17 4 0 68 6 9.96* 
  −4 −4 72 7.06  −4 0 64 7.84 
    PrCG 18 36 −8 52 6 8.73*       
    MFG   48 −4 52 6.65       
Brain region Hem Comparison attend left versus baseline
 
Comparison attend right versus baseline
 
  k x y z BA T value k x y z BA T value 
Parietal lobe 
    PoCG R 94 56 −20 24 OP4 (S2), 3 (S1) 13.71* 45 56 −20 24 OP4 (S2), 3 (S1) 13.32* 
   60 −28 24 OP1 (S2) 10.43  64 −24 20 OP1 (S2) 10.74 
    IPL   52 −48 44 40 9.41  52 −28 24 40 10.37 
    PoCG L 27 −44 −28 32 2 (S1) 9.56* 78 −44 −28 32 2 (S1) 12.82* 
    IPL   −56 −32 24 40, OP1 (S2) 8.00       
   −56 −24 28 40, OP1 (S2) 7.62       
    PoCG L 19 −52 −32 52 1, 2, 40 (S1) 9.07*  −60 −28 44 1 (S1) 11.92 
   −60 −28 44 1, 2 (S1) 8.86  −52 −28 52 S (S1) 10.83 
        15 −52 −4 8 OP4 (S2) 8.11* 
    IPL   −52 −44 52 40 6.82       
    IPL R       18 44 −36 48 40 8.62* 
         56 −44 40 40 8.38 
         40 −36 40 40 7.90 
Frontal lobe 
    IFG L 34 −60 8 32 9 9.18* 45 −60 8 32 9 10.41* 
    PrCG   −48 −4 48 8.12  −40 −4 60 10.08 
   −52 0 36 8.00  −56 0 40 9.54 
    MdFG L 20 −8 0 64 6 8.80*       
  4 0 68 8.47 17 4 0 68 6 9.96* 
  −4 −4 72 7.06  −4 0 64 7.84 
    PrCG 18 36 −8 52 6 8.73*       
    MFG   48 −4 52 6.65       

Note: Coordinates (in italics) are given in MNI space. For each maximum within 1 cluster, the hemisphere (= Hem; right Hem = R, left Hem = L), the number of voxels (k), the coordinates and the corresponding Brodmann areas (BA) are given in bold letters. Results are shown at a significance threshold of PFDR-corrected < 0.005 at set level. Asterisks behind the T values denote the significance threshold at voxel level (* = P < 0.001). G = gyrus, STG = superior temporal G, S1 = primary somatosensory cortex, S2 = secondary somatosensory cortex.

Differential Effects of Attention

These contrasts were important to test whether activation of S1 contralateral to the direction of attention is enhanced during stimulation of the left and right index finger. The resulting contrast image should exclusively represent the effects of spatial attention because the effects of stimulation are canceled out.

Attention to the Right versus Attention to the Left Index Finger

This contrast resulted in a significant hemodynamic effect in the contralateral left PoCG (x = −48, y = −28, z = 52, BA 1, 2, and 3b, i.e., S1) and the left OP (OP1, BA 40, i.e., S2), the former extending from 1 to 2 SD of the probabilistic hand area of left S1 (Fig. 4C). No significant hemodynamic effect was found in the right S1 ipsilateral to the attentional focus. Differential effects in nonsomatosensory brain regions were found in the ipsilateral right superior temporal gyrus (STG) and medial temporal gyrus (MTG), the contralateral left IFG, left PrCG, left MFG, insula, the MdFG (i.e., SMA), the ipsilateral right anterior cingulate, the contralateral left corpus callosum, and left basal ganglia (Table 2 and Fig. 4C).

Table 2

fMRI BOLD areas of activation modulated by spatial-selective attention

  Comparison attend left versus attend right
 
Comparison attend right versus attend left
 
Brain region Hem k x y z BA T value k x y z BA T value 
Parietal lobe 
    IPL C 8 44 −36 24 40, OP1 (S2) 4.03*** 15 −44 −32 28 40, OP1 (S2), 2, (S1) 3.52*** 
  6 52 −48 40 40 2.84**       
    PoCG C 3 44 −36 60 1, 2 (S1) 2.17* 4 −48 −28 52 1, 2, 3b (S1) 2.56** 
Temporal lobe 
    STG I 4 −48 −48 12 22 2.42** 5 40 −32 0 22 3.93*** 
  3 −64 −44 12 22 2.27*       
    MTG I       3 60 −32 −4 21 2.84** 
Frontal lobe 
    IFG I 14 −36 32 12 46 4.51***       
 C 4 36 8 24 3.53*** 5 −36 28 −12 47 3.96*** 
        8 −44 44 −4 45, 47 3.32 
    PrCG C 14 36 −8 52 3.63*** 5 −40 −20 60 6, 4a 3.37 
  3 36 −20 36 2.64*** 8 −24 −28 52 3.06** 
    MdFG C 11 4 24 56 3.48*** 5 0 12 68 3.47 
    MFG C 7 32 20 48 3.03** 6 −24 40 0 11 4.56*** 
        5 −36 0 64 3.91*** 
    Insula C 3 32 24 12 13 2.74** 3 −32 24 20 13 3.10*** 
    Ant. Cing. I       5 12 40 16 32 2.71** 
Subcortical 
    Thalamus C 8 28 −28 4  3.43***       
    CC C       14 −4 −8 24  3.51*** 
    Basal ganglia C       8 −32 0 8  3.30 
  Comparison attend left versus attend right
 
Comparison attend right versus attend left
 
Brain region Hem k x y z BA T value k x y z BA T value 
Parietal lobe 
    IPL C 8 44 −36 24 40, OP1 (S2) 4.03*** 15 −44 −32 28 40, OP1 (S2), 2, (S1) 3.52*** 
  6 52 −48 40 40 2.84**       
    PoCG C 3 44 −36 60 1, 2 (S1) 2.17* 4 −48 −28 52 1, 2, 3b (S1) 2.56** 
Temporal lobe 
    STG I 4 −48 −48 12 22 2.42** 5 40 −32 0 22 3.93*** 
  3 −64 −44 12 22 2.27*       
    MTG I       3 60 −32 −4 21 2.84** 
Frontal lobe 
    IFG I 14 −36 32 12 46 4.51***       
 C 4 36 8 24 3.53*** 5 −36 28 −12 47 3.96*** 
        8 −44 44 −4 45, 47 3.32 
    PrCG C 14 36 −8 52 3.63*** 5 −40 −20 60 6, 4a 3.37 
  3 36 −20 36 2.64*** 8 −24 −28 52 3.06** 
    MdFG C 11 4 24 56 3.48*** 5 0 12 68 3.47 
    MFG C 7 32 20 48 3.03** 6 −24 40 0 11 4.56*** 
        5 −36 0 64 3.91*** 
    Insula C 3 32 24 12 13 2.74** 3 −32 24 20 13 3.10*** 
    Ant. Cing. I       5 12 40 16 32 2.71** 
Subcortical 
    Thalamus C 8 28 −28 4  3.43***       
    CC C       14 −4 −8 24  3.51*** 
    Basal ganglia C       8 −32 0 8  3.30 

Note: Coordinates (in italics) are given in MNI space. For each cluster, the hemisphere (= Hem; contralateral Hem = C, ipsilateral Hem = I) and the number of voxels (k) are given in bold letters. Results are shown at a significance threshold of Puncorrected < 0.005 at set level. Asterisks behind the T values denote the significance threshold at voxel level (*** = p < .005; ** = p < .01; * = p < .05). BA = Brodmann area, G = Gyrus, Ant. Cing. = Anterior Cingulate, CC = Corpus Callosum, IFG = Inferior Frontal G, IPL= Inferior Parietal Lobule, MFG = Middle Frontal G, Nuc. Caud. = Nucleus Caudatus, OP = Parietal Operculum, PoCG = Postcentral G, PrCG = Precentral G, STG = Superior Temporal G, S1 = Primary Somatosensory Cortex, S2 = Secondary Somatosensory Cortex.

Attention to the Left versus Attention to the Right Index Finger

This contrast led to a significant hemodynamic effect in the contralateral right PoCG (x = 44, y = −36, z = 60, BA 1 and 2, i.e., S1) extending from 2 to 3 SD of the probabilistic hand area of right S1 and right IPL extending to the right OP (BA 40, OP1, i.e., S2) (Table 2 and Fig. 4D). No significant difference in BOLD was found in the left somatosensory cortex ipsilateral to the attentional focus. Differential effects in nonsomatosensory brain regions were found in the ipsilateral left STG, bilateral in the IFG, contralateral right PrCG, MFG, insula, thalamus, and MdFG (i.e., SMA).

Correlation of the Effects of Attention on the SEPs with the Differential BOLD Response

In line with the results from the EEG data, the correlation between the EEG difference waveforms (attended minus unattended) and the BOLD effect in contralateral S1 and S2 is stronger for left than for right standard stimuli (Fig. 5, compare A and C). Comparing the correlation matrices for S1 and S2 for left standard stimuli (Fig. 5A,B), it can be seen that the correlations show a strict separation between early positive and negative effects with electrodes over the contra- and ipsilateral hemisphere, respectively for S1 but not for S2. The results show that within the 1st 20–70 ms the BOLD effect in contralateral S1 positively correlates with early SEP effects from electrodes over the contralateral hemisphere (CP6, C4, FC6) and negatively correlates with effects over the ipsilateral hemisphere (CP5, C3, FC5). From 70 to 100 ms, also the contralateral SEP effects showed a negative correlation (Fig. 5A). Only the interval of 20–70 ms was found to be significant for positive and negative correlations (Fig. 5B). Not until 190 ms is there a 2nd volley of significantly positive correlations, starting on C4, followed by CP6 at 300 ms lasting until 500 ms after stimulation. For this long-latency interval, there are also 2 significantly negative correlations with the signal from the ipsilateral hemisphere: From 300 to 500 ms at FC5 and from 530 to 580 at CP5. The correlations with the effects in S2 are different: There are 2 early and significantly negative correlations wit contralateral CP6 from 0 to 10 ms and from 30 to 40 ms after stimulus onset. As with S1, there seems contribution from long-latency potentials expressed in a significantly positive correlation around 250 ms with the effect at electrode C4.

Figure 5.

Correlation between the EEG time course (subject-wise averaged difference waveforms for attended minus unattended standard stimuli from −120 to 600 ms in relation to the onset (0 ms) of the stimulus at electrodes FC5/6, C3/4, and CP5/6, located over the contralateral and ipsilateral hemisphere) and the parameter estimates of the BOLD signal across subjects (of the contrast attend left minus attend right [A and B] and attend right minus attend left [C and D]) from S1 (upper panel) and S2 (lower panel). (A) Correlation between the EEG time course for left standard stimuli and the BOLD signal from right S1 and S2 and (B) its respective significant intervals (P < 0.05). (C) Correlation between the EEG time course for right standard stimuli and the BOLD signal from left S1 and S2 (ROI analysis) and (D) its respective significant intervals (P < 0.05). The colors in (A) and (C) code the strength of the correlation between 1 (red) and −1 (blue) and the strength of the significance threshold in (B) and (D). The black rectangle depicts the time window of the early (P50 and N80) SEP components.

Figure 5.

Correlation between the EEG time course (subject-wise averaged difference waveforms for attended minus unattended standard stimuli from −120 to 600 ms in relation to the onset (0 ms) of the stimulus at electrodes FC5/6, C3/4, and CP5/6, located over the contralateral and ipsilateral hemisphere) and the parameter estimates of the BOLD signal across subjects (of the contrast attend left minus attend right [A and B] and attend right minus attend left [C and D]) from S1 (upper panel) and S2 (lower panel). (A) Correlation between the EEG time course for left standard stimuli and the BOLD signal from right S1 and S2 and (B) its respective significant intervals (P < 0.05). (C) Correlation between the EEG time course for right standard stimuli and the BOLD signal from left S1 and S2 (ROI analysis) and (D) its respective significant intervals (P < 0.05). The colors in (A) and (C) code the strength of the correlation between 1 (red) and −1 (blue) and the strength of the significance threshold in (B) and (D). The black rectangle depicts the time window of the early (P50 and N80) SEP components.

For right standard stimuli, there was a significantly negative correlation between the BOLD effect in S1 and the SEP effect in the ipsilateral hemisphere (CP6) from 120 to 400 ms, which was found significant between 120 and 160 ms and between 340 and 360 ms (Fig. 5C,D). As a mirror image of the mid- and long-latency effect for left stimuli, we found a positive correlation with the effect from the contralateral electrode C4 between 120 and 400 ms, which was significant only at 340–350 ms. For right stimuli, no significant correlation between the early SEP effects and BOLD in contralateral S1 was found. Again, the correlation for the effects with S2 shows a different picture: There are significantly negative correlations with early SEP effects over the contralateral hemisphere (at CP5 from 20 to 50 ms and at FC5 from 30 to 70 ms). There were 2 additional significantly negative correlations with the signal from FC5: from 150 to 170 ms and from 390 to 440 ms. For these 2 intervals, significantly positive correlations were found with the effects at ipsilateral CP6.

Discussion

Tactile spatial-selective attention enhanced early SEP components suggesting an attentional modulation of neural activity in the somatosensory cortex at an early passage of the signal. Accordingly, in the simultaneously recorded fMRI, we found an increased BOLD signal in S1 as well as S2 contralateral to the focus of attention. These fast electrophysiological effects correlated with BOLD signal changes in contralateral S1.

Behavioral Results

The relatively low deviant detection rate of 66% suggests that the task was either difficult for the subjects or they did not comply with the task. The latter concern is very unlikely because of the low false positive responses and because the RTs were within an acceptable range for foot responses. Furthermore, in every subject and for each hand, d′ values were larger than 1, suggesting that the detection of the deviants was above chance. The detection rate differs from the results by Eimer and Forster (2003) and Zopf et al. (2004). Importantly, a difficult detection task within the focus of attention requires the subjects to attend closely to all stimuli at the attended finger and may sharpen the difference between the attended and unattended stimulation. The implications of these findings on the SEP results will be discussed below.

Somatosensory Evoked Potentials

We found significant effects of spatial-selective attention for the P50 and P100 for left and for the N80 for right tactile stimuli. To date, the N80 has been the earliest somatosensory component found to be modulated by selective attention, using electrical (Desmedt and Robertson 1977; Michie et al. 1987) or tactile stimuli (Eimer and Forster 2003). Other studies reported even later components, such as the P100 or N140, the earliest components to be attentionally modulated (Michie 1984; Desmedt and Tomberg 1989; Eimer and Driver 2000; Zopf et al. 2004). Zopf and colleagues and Desmedt and Tomberg also reported effects of attention on earlier SEP components such as the P30 or P45/P50. However, in the study by Zopf and colleagues, an early effect was found for transient versus sustained attention but not for the comparison of attended versus unattended stimuli. The earliest effect of spatial-selective attention was found on the N140 component. Desmedt and Tomberg compared electrical stimulation during attention (counting the stimuli) with stimulation during another task (reading a novel) and thus it is hard to compare their findings with our task of spatial-selective attention. We were able to show an effect of tactile spatial-selective attention starting only 50 ms after tactile stimulation to the left index finger. Extending the findings by Eimer and Forster (2003) to an even earlier effect of tactile spatial-selective attention, our result correspondingly argues for an early modulation of S1 by tactile spatial-selective attention. To verify the location of the early effect, we conducted a dipole source localization analysis (BESA, MEGIS Software) showing that the dipoles for the P50 amplitudes for attended and unattended standard stimuli are located within 2 SD of the S1 hand area for both conditions (see Supplement Fig. 2).

The discrepancies between our findings and the results by Eimer and Forster (2003) and Zopf et al. (2004) cannot be ascribed to different stimulation modalities because all 3 studies applied tactile stimuli. One reason might be the different stimulus characteristics—spatial Braille patterns in our study compared with a single versus dual pulses from a single metal rod in the 2 other studies—being related to lower deviant detection rates of 66% in our study as compared with nearly 100% in the other studies. We assume that an increased difficulty to discern between deviants and standards may allocate more attentional resources to one hand. Another reason for the different findings might be that we analyzed responses to left- and right-finger stimulation separately and we found a significant effect on the P50 only for left hand focused attention. The above mentioned studies did not run separate analysis for left and right hand stimuli, which might have blurred any early effects in the SEP, possibly confined to left hand focused attention.

Our finding is in line with studies investigating effects of spatial-selective attention on the auditory system (e.g., Woldorff and Hillyard 1991; Woldorff et al. 1993). They found components at 20–50 ms after stimulus application to be enhanced by attention. An early attentional modulation of the somatosensory cortex supports the notion of a sensory gain control or amplification at the initial stages of cortical processing (Naatanen 1992; Hillyard et al. 1998). Early modulation is not in line with the findings from 2 combined EEG–fMRI studies investigating visual spatial attention, however (Martinez et al. 1999; Noesselt et al. 2002). It seems that spatial-selective attention does not operate identically in the different sensory modalities. Possible reasons might be the different encoding of spatial representations for the somatosensory and visual stimuli (body-centered in somatosensation and retinotopic in vision) or different physiological and anatomical characteristics of the 2 systems.

Corresponding to other studies using tactile stimulation, the P50 was the 1st component observed in the EEG (Hamalainen et al. 1990; Taylor-Clarke et al. 2002; Zopf et al. 2004). EEG studies applying electrical stimuli have frequently observed SEP components earlier than 50 ms (e.g., the N20) (Arthurs et al. 2004, 2007). This discrepancy is probably due to the relatively lower stimulus intensity (Hamalainen et al. 1990). Using electrical stimuli the high sensitivity of the N20 amplitude to stimulus intensity has recently been demonstrated (Arthurs et al. 2004, 2007). Other reasons for the absence of earlier potentials to mechanical stimulation might be its gradual onset as compared with the precise and steep onset of electrical stimulation and the stimulation of mechanoreceptors (as compared with nerve bundles in electrical stimulation), which implies different timing of receptor adaptation and conduction velocity.

An effect on the P50 suggests that spatial-selective attention modulates the signal during an early passage in S1. Following the N20, the P50 is not the 1st but the 2nd evoked potential in S1. Furthermore, one study using intracortical recordings (Barba et al. 2002) and one MEG study (Karhu and Tesche 1999) reported activation of S2 20–40 ms after stimulus onset. Thus, the present result cannot be unequivocally ascribed to a 1st pass effect in S1. It might be hypothesized that the effect on the P50 emerges from an attentionally enhanced feedback from S2 toward S1. On the other hand, an activation of S2 earlier than 60 ms has not been found in other studies applying intracortical recordings (Allison et al. 1989, 1991, 1992; Frot and Mauguiere 1999), MEG (Hari et al. 1993; Mauguiere et al. 1997; Forss et al. 1999; Zhu et al. 2007), and EEG (Hamalainen et al. 1990; Waberski et al. 2002). Furthermore, 1 of the 2 studies indicating an early activation of S2 did not observe attentional modulation from MEG S2 recordings for early responses in the range of 20–60 ms (Karhu and Tesche 1999). The signal in S2 was considerably enhanced by attention only for the late responses at 100 ms. The other group, reporting early S2 activation did not investigate effects of attention (Barba et al. 2002). Together, these findings make a feedback modulation of the P50 by attentional effects in S2 very unlikely. Thus, one explanation for our finding could be an attentional modulation during the initial passage of the signal in S1.

Effects of attention on long-latency components, as found here, are in line with findings of previous SEP studies (Desmedt and Robertson 1977; Josiassen et al. 1982; Desmedt and Tomberg 1989; Zopf et al. 2004).

Interestingly, we found asymmetric effects of spatial-selective attention for left- and right-finger stimuli for early, mid- and long-latency components. Although not the main focus of our study, this asymmetry will be briefly discussed. For left stimuli, attention enhanced the P50 and P100; for right stimuli, an effect of attention was only found on the N80. Unexpectedly, the effect on the N80 for right stimuli was significant only for electrodes of the central midline. Also, scalp topographies for the P50 and P100 components for left and right stimulations were not mirror images of each other. The P100 for left stimuli shows a posterior positive–anterior negative polarity distribution suggesting a bilateral parietal generator (in line with the assumed generators bilateral in S2). In contrast, for right stimuli, the P100 shows a contralateral negative–ipsilateral positive polarity, comparable to the N80 voltage distribution. We suggest 3 tentative explanations that may account for the asymmetric SEP findings: First, the effect could be due to a difference in stimulus processing between left and right index fingers. There may be a left hand/right hemispheric predominance for the processing of tactile stimuli. If this is the case, any asymmetries in left and right hand stimulus processing would be systematic in our participant sample, which was all right-handed. Indeed, a previous study has shown higher sensitivity for left compared with the right hand stimuli (Meador et al. 1998) and faster and more accurate left hand Braille reading in blind subjects (Hermelin and O'Connor 1971). Second, the asymmetric hemispheric activations may be explained by Mesulam's modality-unspecific model of spatial attention (Mesulam 1999). This model suggests that higher-order areas in the left hemisphere control attention for events only on the right side, whereas the right hemisphere controls attention for both, left and right side. Both theories may explain the asymmetric attentional effects on the SEPs, leading to earlier (P50) and more pronounced (P100 only for left not for right stimuli) attentional modulation for left stimuli. Third, the asymmetric activation may be related to the preparation of the right foot's behavioral response. Decreased blood flow has been measured in a PET study for stimulus anticipation in somatosensory areas ipsilateral to the side of the stimulus (Drevets et al. 1995). It might be assumed, that constantly attending to the right foot has an asymmetric inhibitory effect on left as compared with right somatosensory finger stimulation processing areas. Although it is difficult to conceive how a tonic preparatory state should modulate the brain response to a standard stimulus.

Functional MRI

Cortical Networks Related to Tactile Stimulation under Spatial Attention

When comparing the attentional conditions during bilateral stimulation with the baseline condition (no stimulation, no spatial-selective attention), the resulting activations may largely be attributed to 2 interacting processes: Tactile stimulation and spatial attention. For both attentional conditions, we found overlapping BOLD signal increases in bilateral S1 and S2, bilateral in the IPL, the left and right PrCG, the left IFG, and the left MdFG (i.e., SMA). The crucial involvement of the IPL in spatial attention has been shown in patients suffering from spatial neglect (Vallar 2001; Mort et al. 2003), in healthy subjects (Corbetta and Shulman 2002) and trained monkeys (Bisley and Goldberg 2003). The preparation and anticipation of the button press with the right foot may be responsible for the overlapping activity in the left PrCG. Activation of the IFG has been revealed in a PET study in a task of tactile attention, probably due to its projections from the somatosensory cortex (Hagen et al. 2002). Activity in the SMA was found in a previous fMRI study of tactile spatial-selective attention (Meador et al. 2002) and found to be relevant for response selection (Tanji and Mushiake 1996; Geyer et al. 2000).

Spatial-Selective Attention Modulates Activity in the Somatosensory Cortex

Contrasting attention to the left and right hand canceling out the effects of constant bilateral tactile stimulation, revealed enhanced activity in the hand area of S1 contralateral to the focus of attention. Thus, S1, which has long been assumed to be sensitive only to the physical attributes of somatosensory stimuli, such as frequency or intensity, also contributes to the highly cognitive process of spatial attention. This finding is in line with results from previous imaging studies investigating tactile spatial-selective attention (Meador et al. 2002; Roland 1981). It also agrees with results from studies investigating effects of spatial-selective attention on the visual or auditory modality (Woldorff and Hillyard 1991; Woldorff et al. 1993; Roelfsema et al. 1998; Vidyasagar 1998; Alho et al. 1999; Brefczynski and DeYoe 1999; Martinez et al. 1999; Somers et al. 1999; Hashimoto et al. 2000; Noesselt et al. 2002).

In addition to the effect of an increased activity in S1 contralateral to the focus of attention, we found attention to increase the BOLD signal even more in contralateral S2. This result is in line with findings of studies investigating cross-modal (Johansen-Berg et al. 2000; Fujiwara et al. 2002) and nonselective attention with usually only one stimulation site (Backes et al. 2000; Hamalainen et al. 2002) which found S2 BOLD signal amplitude to be more amplified by attention than S1. This finding underlines its role for the integration of somatosensory processes and cognitive functions, for example, attention, tactile learning and memory (Burton and Sinclair 2000; Johansen-Berg and Lloyd 2000).

Activations in nonsomatosensory brain areas revealed by the differential contrasts will not be discussed here because they were not the main focus of this study.

Correlation between Attentional Effects on the P50 and the BOLD Signal

The correlation between the electrophysiological effects of attention for left stimuli and the BOLD effects in the somatosensory cortex suggests an early contribution of attentional effects to the hemodynamic signal in S1. Nevertheless, a 2nd contribution from long-latency attentional effects to this signal is also evident. This may represent a re-entrant feedback modulation from higher cortical areas where these long-latency components are probably generated (Allison et al. 1992). A contribution of long-latency potentials to BOLD effects in primary sensory areas is also in line with studies of visual attention (Martinez et al. 1999; Noesselt et al. 2002). We further investigated, whether these early and late SEP effects independently contributed to the BOLD effect in S1 or whether they had simply been caused by the fact that these SEP effects were interrelated. We ran an additional correlation analysis, where we correlated the difference value across subjects (attended minus unattended) of each of the 6 electrodes of interest (C3/4, FC5/6, CP5/6) averaged over the respective significant time windows (Fig. 5B) with each other. The 1st time window (early SEP, 45–60 ms) did not result in any significant correlation with the 2nd time window (late SEP 1, values derived only from electrode C4, 190–260 ms) nor with the 3rd time window (late SEP 2, 300–420 ms) (see Supplement Table 3 for detailed r and P values). We only found significant correlations between the 2nd and the 3rd time window at electrode C4 (r = 0.92; P = 0.00001), FC5 (r = −0.60; P = 0.03) and CP6 (r = 0.79; P = 0.001). The absence of any correlation between the early and later SEP effects suggests that early and late effects independently contribute to the BOLD effect in contralateral S1.

The asymmetric effects of attention with smaller amplitude differences for right stimuli are also reflected in the correlation analyses. The weak correlation coefficients are most likely due to the fact that the difference values (attended minus unattended) for right stimuli used in the correlation with the BOLD signal were smaller than for left stimuli. Thus, it is hard to draw conclusions about the correlations for attention to right stimuli. Nevertheless, although the significant effect of attention on the P50 for left stimuli significantly correlated with the BOLD signal difference in S1, the significant effect of attention on the N80 for right stimuli may be reflected in the significant correlation with S2.

To further investigate the relationship between the attentional effects on the P50 component for left standard stimuli and the BOLD signal, we calculated an additional combined EEG–fMRI analysis. Here, we used the absolute P50 amplitude value of each stimulation block as a regressor of the estimated hemodynamic response function (for details of the method and discussion see supplemental material “blockwise EEG–fMRI analysis,” Supplement Fig. 3 and Supplement Table 2). The results show that the P50 amplitude significantly covaries with the hemodynamic effects S1 in 4 subjects. A trend of the same effect was also found for the remaining subjects; also it did not survive the significance threshold of P < 0.05.

In previous studies relating early SEP amplitudes (N20–P25) with the fMRI BOLD signal in S1, a linear correlation was found between intensity-induced amplitude increases in the SEP and BOLD signal (Arthurs et al. 2000, 2007; Arthurs and Boniface 2003). In these studies the strength of the relationship varied between r = 0.66 and r = 0.71, comparable to the correlation found in our study ranging from r = 0.66 to r = 0.74. A direct comparison of these findings with our results has to be done carefully. Beside the fact that in these studies, effects of intensity were investigated and not attention, correlations were calculated between the absolute signal values and not signal differences. This involves the neural response to intensity changes additional to stimulation. We used difference values between attended and unattended stimuli for the SEP and the contrast images of attended left minus attended right for the BOLD signal. As the effects of stimulation are subtracted for both measures, we correlated only the effect of attention without the effect of stimulation.

Investigating the effect of attention, Arthurs et al. (2004) found an effect of attention on the BOLD signal in S1, but not in the N20–P25 SEP component. The authors’ suggestion of the BOLD response in S1 being sensitive only to metabolic changes accompanying long-latency SEPs (140–230 ms) is not in line with our findings. We suggest that a modulation of the neuronal response at 50 ms after stimulation also influences the BOLD signal as well. At the same time we do not dispute an additional and probably larger impact of the long-latency SEPs on the hemodynamic response. However, the hypotheses that early SEPs and the fMRI read functionally distinct regions or are sensitive to different types of neuronal responses being differentially modulated by attention is not supported by our findings. It might be suggested that components earlier than 50 ms are unaffected by attention and the P50 constitutes the 1st component sensitive to attention. But due to several differences in the experimental setting, one has to be cautious when comparing the above findings with our study: First, Arthurs and colleagues used electrical as opposed to tactile stimulation in our study. These are known to elicit different SEP components (N20 versus P50), which might represent different functional neuronal responses being distinctly modulated by attention. Second, there were task differences, a nonselective task used by Arthurs and colleagues as compared with the present spatial-selective task of attention. Third, in the study by Arthurs and colleagues, the signals were not acquired from simultaneous recordings and different stimulation frequencies for EEG and fMRI recording were applied. Fourth, Arthurs and colleagues stimulated only the right hand, whereas we found an effect on the early P50 component restricted to left-sided focused attention.

Another issue arises from the implications of the different temporal resolutions of EEG and fMRI: In our study, using a task of sustained attention over a block of rapid consecutive stimulation (ISI = 800 ms), the evoked potential represents an instantaneous effect of attention to a single event. In contrast, because of its low temporal resolution, the BOLD signal may display more slowly and sustained effects of attention on a series of stimuli. Our results suggest that these different attentional components revealed by the 2 methods are closely related.

The negative correlation between SEP effects of attention for left-sided stimuli over the ipsilateral hemisphere means that increased attentional activity in contralateral S1 are accompanied by decreased effects in ipsilateral S1. A negative correlation between an early contralateral SEP amplitude and the ipsilateral somatosensory cortex was also found in the previous sequential EEG–fMRI study (Arthurs et al. 2007). The authors suggested a mechanism of neuronal mediated cortico-cortical inhibition with ipsilateral cortical activity to be inhibited in proportion to increases in contralateral cortical activity. In EEG studies investigating the effect of visual spatial attention on neuronal rhythmic activity, synchronization in the alpha band in the hemisphere ipsilateral to the focus of attention was found (Worden et al. 2000; Kelly et al. 2006). These findings were interpreted as inhibitory mechanisms related to suppression of distracter stimulation. Here, we also presented distracter stimuli to the unattended hand and a decreased activity in the hemisphere contralateral to the distracter stimuli may represent cortical inhibition to suppress processing of the unattended stimulation. A decrease in cerebral blood flow ipsilateral to somatosensory stimulation was also reported in a PET study by Drevets et al. (1995) during anticipation of nocuous and innocuous stimuli. These findings had been interpreted as a suppression of the ipsilateral response in order to amplify “focusing” or “attention” to the contralateral stimuli. Although attention may have been involved in both tasks, the authors did not explicitly manipulate spatial attention. In our study, the ipsilateral negative correlation with the effect of attention corroborates this “suppression–amplification” theory.

In recent years, several studies have suggested that neuronal oscillatory activity is related to BOLD signal changes. Such a relation was found in invasive animal studies (Logothetis 2002) as well as noninvasive studies using MEG (Brookes et al. 2005) and EEG (Foucher et al. 2003; Moosmann et al. 2003; Feige et al. 2005; Laufs et al. 2006; de Munck et al. 2007). A recent simultaneous intracranial EEG–fMRI study detected a close overlap between the location of gamma frequency changes in a semantic decision task and the location of the BOLD signal changes (Lachaux et al. 2007). This supports the idea that local gamma-band changes require synchronized activity of inhibitory interneurons, whose activity substantially contributes to the local oxygen consumption (Niessing et al. 2005). Investigating changes in the sensorimotor alpha (mu), beta and gamma rhythms and their relation to effects on the SEPs and the hemodynamic response may give complementary information about mechanisms of attention. Although this question was not within the focus of the current study investigating short-latency effects, rhythm-related aspects in the context of attention and somatosensory processing would be of substantial interest for future study.

Conclusions

How may spatial-selective attention influence tactile processing before the signal has reached higher cortical regions? Imaging studies, investigating the effect of spatial attention during and before tactile stimulation, found enhanced activity in contralateral S1 in anticipation of a stimulus (Roland 1981; Macaluso et al. 2003). We assume that our task of sustained spatial-selective attention creates anticipation of stimulation at a specific location. This selectively changes the background activity shown to relate to enhanced evoked potentials at an early stage of signal processing and to have a modulating effect on the BOLD signal (Chawla et al. 1999).

Spatial-selective attention to the index finger of the left hand during bilateral tactile stimulation enhances early SEP components generated in contralateral S1, which had not been detected in previous studies. This finding suggests that attention enhances the sensory signal during its early passage in S1. Furthermore, we found an increase of the BOLD signal in S1 contralateral to the focus of attention. The effects of attention on early as well as long-latency SEPs were correlated with the slow hemodynamic changes in S1, describing an early as well as delayed re-entrant attentional enhancement, which can be described by a linear relationship.

Supplementary Material

Supplementary material can be found at: http://www.cercor.oxfordjournals.org/

Funding

Graduiertenkolleg 238 “Damage cascades in neurological disorders—studies with imaging techniques”; and the “Bundesministerium für Bildung und Forschung” in the Berlin NeuroImaging Center.

We thank Markus Bauer for the idea to use Braille stimulators.

Conflict of Interest: None declared.

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