Layer-specific attentional modulation in the human primary somatosensory cortex

Domain: neuroscience
Published: 2026-04-13
Editorial outcome: major_revision

Abstract
Selective attention enhances relevant sensory inputs while filtering out distractions, yet its layer-specific effects remain poorly understood. Here, we used microvascular-specific spin-echo BOLD fMRI at 7 T to investigate attentional modulation across cortical layers in the human primary somatosensory cortex (S1) during finger and wrist stimulation. During passive, unattended stimulation, the middle and deep layers exhibited stronger signals than the superficial layer. In the attended finger region, attention significantly increased activity in the superficial layer, consistent with top-down feedback, and decreased activity in the deep layer, while leaving the middle layer unchanged. In the wrist region processing tactile or pain distractors, signals were uniformly suppressed across layers, including the thalamic-input middle layer, consistent with the impaired sensory discrimination observed in behavioral studies. Our findings reveal that attention reshapes laminar activation in S1, selectively enhancing relevant signals while suppressing irrelevant input, consistent with an attentional gating mechanism.

Introduction
When navigating environments with a myriad of competing sensory inputs, selective attention allows individuals to focus on task-relevant stimuli while controlling distraction 1-9. In the brain, the sensory cortex maps tactile inputs from the external environment onto topographically organized receptive fields 10, and attention modulates their responses by increasing the neural representation of relevant stimuli while reducing responses representing distractors 11-20. Classic neurophysiological studies have demonstrated attentional modulation both in early sensory areas 4,21 and in higher-order regions involved in top-down control 22,23. However, despite extensive evidence that attention modulates neural responses across multiple brain regions, much less is known about how such modulation is expressed within the cortical microcircuit. In particular, whether attention differentially influences the responses of specific cortical layers—thereby providing insight into how sensory information is processed in a layer-specific manner—remains unclear.

Attentional modulation in the human somatosensory cortex can be examined using high-resolution fMRI, focusing on laminar organization. Primary sensory cortices (e.g., V1 and S1) process sensory information through a multilayered structure: layer 4 receives initial sensory input from the thalamus, layers 2/3 integrate feedforward and feedback inputs, and layers 5/6 transmit processed information to other cortical and subcortical regions, contributing to motor control and thalamic modulation 10,11,24-31. Previous studies have shown that attention enhances perception by differentially modulating neural responses across cortical layers, particularly by increasing responses in the superficial layer 32-34, reflecting the prioritization of sensory information relevant to ongoing tasks or environmental demands 35,36. However, while attention reliably increases superficial-layer responses, its influence on other layers remains inconclusive 33,34,37-41, and it is unknown whether representations of unattended distractors are modulated differently across layers. Therefore, we hypothesized that attention-related suppression would exhibit a laminar profile different from that of attentional enhancement, reflecting distinct layer-specific influences in attended versus unattended regions.

To test our hypothesis, we investigated layer-specific attentional modulation in the primary somatosensory cortex (S1) of 17 human participants using microvascular-specific spin-echo BOLD fMRI at 7 T. In our paradigm, attention was consistently directed to the fingers (target site), while the wrist (distractor site) was concurrently stimulated but unattended, enabling us to investigate somatotopically organized modulation of attended versus unattended representations within S1. Two sets of competing stimuli were presented concurrently at a target site (fingers) and a distractor site (wrist): (i) tactile stimulation to both sites, and (ii) tactile stimulation to the target site with painful thermal stimulation to the distractor site. In the attended condition, participants discriminated tactile frequencies at the target site while ignoring the distractor. In the passive condition, the same stimuli were presented, but participants simply experienced them without performing a task; here, the term “distractor” is used solely to denote the non-target site, irrespective of attentional demands.

We found that passive stimulation elicited greater BOLD signals in the middle (layers 4/5) and deep layers (layer 6) than in the superficial layer (layers 2/3) across both the finger and wrist representations in S1. When attention is directed to the fingers, however, superficial-layer activity increased while deep-layer activity decreased in the attended finger region. In contrast, the unattended wrist representation showed uniform suppression across all layers, consistent with the impaired sensory discrimination observed in a follow-up behavioral experiment. Together, these findings demonstrate that attention induces distinct, layer-specific modulation in human S1, highlighting that even early sensory processing is shaped by attentional influences across both spatial and laminar domains 3,7,8,34.

Results
Overall experimental design

To obtain laminar-dependent fMRI responses in S1 at 7 T, imaging slices were precisely positioned perpendicular to the central sulcus between the motor and sensory cortices 42-45 (Fig. 1a). We used spin-echo (SE) BOLD contrast because of its high sensitivity to microvascular signals, whereas conventional gradient-echo BOLD is more susceptible to macrovascular contributions that can bias responses across cortical layers 42,46,47. High-resolution SE-BOLD data were acquired at 0.8 mm isotropic resolution (Fig. 1b), and S1 was identified using anatomical MRI (Fig. 1b).

We employed two experimental designs: i) tactile stimuli delivered to the fingers with concurrent tactile stimuli to the wrist (Experiment 1), and ii) tactile stimuli to the fingers combined with thermal stimuli to the wrist (Experiment 2). In Experiment 1, tactile stimulation was applied to the left index and middle fingers (target site) and the left wrist (distractor site) (Fig. 1c). Four tactile stimulators were used—two on the fingers and two on the wrist—each delivering vibration frequencies of either 3 Hz or 8 Hz (Fig. 1d). Frequencies were randomly varied across trials. Eight participants (Subjects 1–8; Group 1) initially completed Experiment 1, and additional eight participants (Subjects 10–17; Group 2) were later recruited to replicate the findings. In Experiment 2, tactile stimulation was applied to the same fingers (two stimulators), while a single thermal stimulator delivered heat to the wrist (n = 9, including the eight Group 1 participants from Experiment 1 plus one additional participant; Fig. 1e). Finger stimulation was identical to that in Experiment 1, while the wrist thermal stimulus was set to 44 C to activate nociceptors 48,49, ensuring it was perceptibly salient and sufficiently distracting 50 (see Fig. 1f).

For both experiments, participants were instructed to either: i) remain awake and experience both stimulations (passive condition), or ii) concentrate on discriminating tactile frequency differences of stimulators on their fingers (attended condition) (Fig. 1d). To ensure the two conditions were matched in motor demands, no behavioral responses were collected. Instead, we verbally confirmed with participants between runs that they perceived both finger and wrist stimuli. In each fMRI run, 18 seconds of stimulation followed by 36 seconds of rest were repeated eight times. High-resolution spin-echo BOLD fMRI data were processed by averaging runs at the subject level, followed by laminar sampling procedures (see Methods for details).

Laminar boundaries in the finger and wrist regions defined by anatomy and functional activation

To assess fMRI signal changes between the passive and attended conditions, it was essential to compare responses in the attended finger region and the unattended wrist region. These regions were identified through two localization steps: (1) lateral boundaries were delineated using functional activation maps and anatomical landmarks, and (2) cortical-depth boundaries were defined from anatomical images.

Finger and wrist regions were identified using the traveling wave paradigm (Fig. 2a and Supplementary Figs. 1a–b). Fifteen of the 17 participants, including the 7 who participated in both experiments, completed this separate localizer session. In this paradigm, four sites on the left arm—the fingers, hand, wrist, and forearm—were sequentially stimulated every 10 seconds in either forward or reverse order, and neural responses were measured using conventional gradient-echo (GE) BOLD contrast 51 (see Supplementary Figs. 1a–b). Finger and wrist regions identified by the localizer were further refined using activation maps from both passive and attended conditions (Fig. 2b). In the passive condition, activation patterns were distributed around the hand knob area within S1. When attention was directed to the fingers, the number of activated voxels was markedly reduced (see also Supplementary Figs. 1c–d). The finger region of interest (ROI) was defined as the voxels activated in both passive and attended conditions, located lateral to the hand knob. Because significant activation was often absent medial to the hand knob during attended stimulation, the wrist ROI was further refined based on two criteria: (1) anatomical landmarks (hand knob), and (2) activation during the passive condition (Fig. 2b for multiple slices in one subject; Supplementary Fig. 2 for a representative slice in the other participants). For two participants without localizer data, finger and wrist ROIs were defined using anatomical landmarks and the aforementioned functional activation criteria. Consequently, medio–lateral (somatotopic) boundaries separating the finger and wrist ROIs were delineated along the cortical surface (white dashed lines in Fig. 2b and Supplementary Fig. 2).

Laminar boundaries were determined as follows. The cortical depth of area 3b (~2 mm thick) was defined using GE/SE BOLD ratio images (Fig. 2c), which allowed visualization of both the cerebrospinal fluid (CSF)–gray matter (GM) boundary and the GM–white matter (WM) boundary 46. This cortical ROI was divided into 8 equivolume depth bins. To identify the middle cortical layer (layer 4), quantitative depth-dependent T1 (qT1) values from T1-weighted anatomical images were analyzed 52 (Fig. 2d and Supplementary Figs 3b-d). Based on qT1 gradient analysis and previous literature 53,54, bins 1–2 were grouped as superficial (layers 2/3), bins 4–5 as middle (layers 4/5), and bins 7–8 as deep (layer 6). These laminar ROIs were then used to extract time courses for each subject.

Attentional modulation differently affects the targeted finger area and the non-targeted wrist area in S1

We first examined attentional modulation of the BOLD signal, averaged across cortical depth, along lateral-to-medial columnar strips within area 3b of S1 before investigating layer-dependent responses in the finger and wrist ROIs defined above (Fig. 3a for multiple slices in a representative subject and Supplementary Fig. 4a for a single slice across all sixteen participants in Experiment 1). The lateral-to-medial columnar strips were divided into five ROIs based on anatomical landmarks—particularly the hand knob—and somatotopic maps from the independent traveling-wave localizer (Fig. 3b). BOLD signal time courses (mean ± SEM, n = 16) were extracted from the five columnar ROIs during the passive and attended conditions in Experiment 1.

In the passive condition (Fig. 3b, left panel), responses were evident in Columns 2 and 3. When attention was directed to the fingers (right panel), the response in Column 2 increased, whereas that in Column 3 decreased markedly. This pattern was replicated in Experiment 2 (Supplementary Fig. 5a), indicating attentional enhancement in the finger-associated column ROI (Column 2) and suppression in the adjacent wrist-associated column ROI (Column 3). Our spatial activation profile matched predictions from the attention literature: in the passive condition, regions corresponding to both the stimulated fingers and wrist should show strong responses, whereas in the attended condition, the finger region should remain active but was suppressed in the wrist region and adjacent medial areas 1-9.

To quantify these effects, we computed the percent BOLD signal change within a window of 6–24 s after stimulus onset, chosen to capture the stimulation-evoked BOLD response while accounting for hemodynamic delay (Fig. 3c). A 2 (Condition: passive vs. attended) × 5 (Column: 1–5) repeated-measures ANOVA revealed a significant interaction (Experiment 1: F(4, 60) = 3.082, p = 0.022, partial η² = 0.170; Experiment 2: F(4, 32) = 8.034, p < 0.001, partial η² = 0.501), indicating that attention differentially modulated BOLD signals along the somatotopic axis, particularly between Columns 2 and 3 (Fig. 3c; see also Supplementary Figs. 4b–c for individual data points and caption Supplementary Fig. 5b for Experiment 2). These attentional effects across the somatotopic axis motivated us to test whether similar modulation occurs across cortical layers.

Attention directed to the fingers modulates activity in the superficial and deep layers of the finger area, while suppressing activity in the entire wrist area

Next, we examined how attention modulates layer-dependent BOLD signals in S1 in Experiment 1. Because thalamic inputs primarily target the middle cortical layer, the middle layer is expected to exhibit the strongest BOLD response during passive tactile stimulation—assuming that SE-BOLD fMRI primarily reflects microvascular signals. The time courses in both the finger and wrist ROIs during the passive condition (Figs. 4a–b, left panels) showed that middle layer responses were slightly higher than or comparable to those in the deep layer, and substantially greater than those in the superficial layer. Notably, prior GE-BOLD studies typically revealed greater middle-layer activation only after applying subtractive contrasts between conditions (e.g., attended minus unattended) to reduce bias from large pial and penetrating vessels 33,39,40,55.

Directing attention to the fingers led to a marked increase in superficial-layer BOLD signals within the finger ROI (t(15) = 4.76, p < 0.001, d = 1.19; 93.8% of participants) and a decrease in deep-layer BOLD signals (t(15) = –3.82, p = 0.002, d = –0.95; 75.0%) (Figs. 4c,e). In contrast, middle-layer signals did not change significantly, despite a small, non-significant reduction (t(15) = –1.43, p = 0.17, d = –0.36; 68.8%), suggesting that thalamic input was not modulated by attention (Figs. 4c,e). One might expect that attentional enhancement of superficial-layer responses down-regulates deep-layer activity; however, we found no relationship between attention-induced changes in the superficial and deep layers at the subject level (R² = 0.04, p = 0.458; Supplementary Fig. 7), likely reflecting substantial inter-subject variability.

Interestingly, attention produced a near-complete suppression—or even slightly negative signals—in the wrist ROI across all cortical layers in all participants. This suppression was greatest in the middle layer (t(15) = –13.17, p < 0.001, d = –3.29), followed by the deep layer (t(15) = –11.57, p < 0.001, d = –2.89) and the superficial layer (t(15) = –6.13, p < 0.001, d = –1.53) (Figs. 4d,f).

These layer-specific patterns were further supported by a two-way repeated-measures ANOVA with Condition (passive, attended) and Layer (superficial, middle, deep), which revealed a significant interaction in both the finger ROI (F(2,30) = 27.51, p < 0.001, partial η² = 0.647) and the wrist ROI (F(2,30) = 8.34, p = 0.001, partial η² = 0.357), confirming that attentional modulation varied systematically with cortical depth. Also, these laminar patterns were largely consistent when we divided the data into the original eight participants and the additional eight participants (in Fig. 4, Group 1 and Group 2 are denoted by distinct symbols; see also Supplementary Fig. 6 for the results presented separately for each group).

Wrist-region activation remains suppressed, even when distracting pain stimuli are applied directly to the wrist

We next examined whether the attention-modulated, layer-specific BOLD signals observed in Experiment 1 were also present in Experiment 2, which included distracting painful stimulation. The same analyses were conducted in nine subjects (Figs. 5a–d). Attention increased superficial-layer signals and decreased deep-layer signals in the attention-driven finger ROI (Fig. 5e), while middle-layer signals in the finger ROI remained unchanged (Fig. 5e) and signals in the distracted wrist ROI were uniformly suppressed across all layers (Fig. 5f). As in Experiment 1, the cross-participant correlation between superficial-layer enhancement and deep-layer suppression was not significant (R² = 0.07, p = 0.498; Supplementary Fig. 7). Despite the use of a more potent distractor, the overall pattern of attentional modulation closely mirrored that observed with the tactile distractor, indicating that these laminar effects are robust and consistently reproducible across different types of distractors.

Behavioral correlates of suppressed wrist-region activity during finger-directed attention

The absence of BOLD responses across all layers of the wrist region when attention was directed to the fingers prompted a separate psychophysical experiment outside the scanner to investigate its potential behavioral consequences. Twelve participants were instructed to identify the exact location of a tactile stimulus randomly applied to one of eight possible spots on the forearm (Fig. 6a). This experiment consisted of two tasks: in the first four blocks of trials, participants performed a single wrist tactile stimulation task, and in the subsequent four blocks, they completed a dual task involving wrist tactile stimulation alongside a finger attention task. In the dual-task condition, participants simultaneously performed a frequency judgment task on tactile stimuli applied to the fingers while completing the forearm localization task, thereby simulating the passive and attention conditions described in the fMRI experiments.

Figs. 6b and 6c show confusion matrices of the conditional probabilities of participants’ responses to specific tactile stimuli. In the single wrist tactile stimulation condition, participants localized stimuli accurately, as indicated by sharp diagonal peaks (mean accuracy: 0.556 ± 0.046, chance level: 0.125). The mean conditional probability for correct diagonal responses was significantly higher than for off-diagonal responses (0.5492 ± 0.0462 vs. 0.2286 ± 0.0224; t(11) = 5.159, p = 3.45×10⁻4, Cohen’s d = 1.489) (Fig. 6b).

In contrast, during the wrist tactile stimulation with the finger attention task, participants’ responses were more dispersed, showing a bias toward locating stimuli near the center of the forearm. Mean accuracy in this dual-task condition was significantly lower (0.1232 ± 0.0112) than the single wrist tactile stimulation condition (mean difference: 0.4324 ± 0.0419; t(11) = 10.21, p = 6.03×10⁻⁷, Cohen’s d = 2.95), with the chance level at 0.125. The mean values of conditional probability for diagonal versus off-diagonal responses were 0.1235 ± 0.0113 and 0.1477 ± 0.0028, respectively (t(11) = –1.853, p = 0.091, Cohen’s d = –0.535) (Fig. 6c). The similar probabilities between correct and incorrect perception suggest that attentional resources were almost entirely allocated to the finger task, leaving insufficient capacity to process task-irrelevant input.

These results suggest that diverting attention away from the forearm to the fingers impairs sensory discrimination, consistent with the absence of BOLD responses in the unattended wrist region when attention is directed to the fingers.

Methods
Participants and MRI System

Seventeen healthy participants (ten males and seven females), aged 25-49 years (mean age: 34 years, standard deviation: 8.01 years), participated across Experiments 1 (n = 16) and 2 (n = 9) of our fMRI study. Additionally, twelve participants (eight males and four females), aged 19-25 years (mean age: 23 years, standard deviation: 1.65 years), took part in the behavioral experiment. Sex was self-reported by participants. No sex-based analyses were performed because the study was not powered to detect sex differences. All experiments were approved by the Institutional Review Board of Sungkyunkwan University and conducted in accordance with the Declaration of Helsinki. All subjects were thoroughly informed about the procedures and provided written consent prior to participation.

Task Paradigms

A tactile discrimination task was employed to direct participants' attention to tactile stimuli on their fingers while additional tactile or thermal stimuli were simultaneously presented on their wrists as unattended (Fig. 1c–f). Each stimulus lasted 18 seconds (Fig. 1f), aiming to examine neural response differences during active task engagement compared to passive conditions. To ensure that the task and passive conditions were matched in motor demands, no behavioral responses were required during stimulus presentation.

Experiment 1 involved sixteen participants who received tactile stimuli on their left index and middle fingers and on their left wrist, as depicted in Fig. 1c. Four MR-compatible PTS Piezo Tactile Stimulator stimulators (Dancer design, UK) were used to deliver tactile stimuli at frequencies of either 3 Hz or 8 Hz. The frequencies were randomized across trials to ensure varied sensory input, as detailed in Fig. 1d. This setup allowed us to investigate how directed attention towards stimuli on the fingers could influence the processing of concurrent, unattended distractor stimuli on the wrist.

Experiment 2 introduced a thermal stimulus at the wrist as an additional unattended variable while continuing the tactile discrimination task on the fingers for nine participants, including eight from Experiment 1 and one new participant, as illustrated in Fig. 1e. The thermal stimulus, set at 44 degrees Celsius to activate nociceptors, was perceptibly noticeable and sufficiently distracting, as described in Fig. 1e. In this setup, an MR-compatible thermode (CHEPS, Pathway system, Medoc, Israel) was attached to the wrist and used to deliver thermal stimulation. The temperature ramped up from a baseline of 32°C to 44°C over 5.5 seconds, remained at a plateau of 44°C for 7 seconds, and then ramped back down to baseline over another 5.5 seconds (Fig.1f). Each stimulus presentation lasted 18 seconds, followed by a 36-second rest period, repeated eight times per run, alternating between task and passive conditions across eight total runs.

For the behavioral experiment, twelve additional participants engaged in eight blocks, each consisting of 32 trials. The first four blocks involved a single wrist tactile stimulation condition where participants identified the precise location of a tactile stimulus randomly presented at one of eight locations on the forearm (Fig. 6a). The subsequent four blocks were wrist tactile stimulation with an attentional finger tactile task, where participants first assessed whether the frequencies of tactile stimuli on their fingers were the same or different, followed by identifying the specific location of the stimulus on their forearm.

Layer-specific fMRI Data Acquisition

The measurements were conducted on a 7T scanner (MAGNETOM Terra, Siemens Healthineers, Erlangen, Germany) equipped with a single-channel transmitter and a 32-channel receive head coil (NOVA Medical, Wilmington, MA). To minimize subject movement, MR-compatible cushions securely padded the space inside the coil. Anatomical images were obtained using the MP2RAGE sequence 85 with the following imaging parameters: sagittal orientation, 0.7 mm isotropic resolution, FOV of 224 × 210 × 168 mm3, R in-plane = 3, inversion times (TIs) of 1.0 / 3.2s, TE of 2.29 ms, TR of 4500 ms, readout bandwidth of 200 Hz/Px, and flip angle of 4°.

To obtain layer-dependent fMRI responses, oblique slices were targeted to regions of the human primary sensory cortex (S1) adjacent to the central sulcus. We employed a multi-shot segmented spin and gradient echo (SAGE) EPI approach to achieve high spatial resolution fMRI and overcome the spatial encoding limitations of single-shot EPI 42,46. The multi-shot SAGE EPI imaging parameters included a 0.8 × 0.8 mm2 in-plane resolution, Rin-plane = 9 (for each shot; effective Rin-plane = 3 by 3 shots), field of view (FOV) of 144 × 144 mm2, 37 slices (slice thickness of 0.8 mm), a flip angle pair of 90–180°, partial Fourier of 6/8, echo spacing (ESP) of 1 ms (1282 Hz/Px), and a repetition time (TR) for each shot of 3000 ms. TE GE / TE SE were 14 / 56.84 ms. The EPI readout per shot was 12 ms, which is near the optimal values for a readout window of around 0.5 × T2* to minimize T2* contamination 42,46. For distortion correction of EPI images, a B0 field map was acquired using FLASH images with the same imaging parameters as the SAGE EPI, except for a bandwidth of 620 Hz/Px, TEs of 3.3, 6.3 ms, and a flip angle of 50°.

An 8-minute task paradigm involved alternating blocks of 18 seconds of tactile stimulation and 36 seconds of rest, starting with an initial 36-second rest period. Slices were precisely positioned perpendicular to the central sulcus between the motor and sensory cortices (M1 and S1) 42-45.

Somatotopic Mapping and ROI Localization

To identify somatotopic representations of fingers and wrist within primary somatosensory cortex (S1), we employed a phase-encoded tactile traveling wave (TW) paradigm (Supplementary Fig. 1a) 51. Four body sites—fingers, hand, wrist, and forearm—were stimulated sequentially every 10 seconds in forward (0° to 270°) or reverse (270° to 0°) order. Each participant underwent six runs.

Localizer scans were acquired in an independent scanning session using a gradient-echo EPI sequence (0.8 mm isotropic resolution, TR = 2 s, TE = 20 ms, 25 slices from 15 out of 17 participants, including all participants except one in Experiment 1 (Group 1: n = 7, Group 2: n = 8). In Experiment 2, no new localizer runs were conducted, as participants P1–P7 had already completed the localizer in Experiment 1. The only participant who took part exclusively in Experiment 2 did not undergo the localizer.

Phase values were computed using Fourier analysis, and circular means revealed location-specific preferences (Supplementary Fig. 1b). Voxels with an r > 0.06 were selected to visualize reliable tuning (Fig. 2a), revealing a somatotopic progression along the posterior bank of the central sulcus (area 3b). ROIs were defined from finger- and wrist-preferring voxels. For the two participants without localizer data, ROIs were identified from the main task activation maps using anatomical landmarks, such as the hand knob, and functional overlap between passive and task conditions (Fig 2b and Supplementary Fig. 2).

Layer-specific fMRI Data Preprocessing and Functional Analysis

K-space data were reconstructed using a sliding-window concept to maintain temporal resolution with specific shot repetition times 42, utilizing a custom MATLAB script (MathWorks, Natick, MA). For example, three shots—TRshot (2), TRshot (3), and TRshot (4)—were combined for image reconstruction, enhancing the clarity and quality of the images. Nyquist ghost correction and phase offset correction were performed independently for each shot. The combined data then underwent conventional Generalized Autocalibrating Partial Parallel Acquisition (GRAPPA).

The preprocessing pipeline was adopted from the previous studies 42,46. Functional runs were first concatenated and then underwent motion correction using SPM12 (Functional Imaging Laboratory, University College London, UK) with six motion parameters. To improve signal-to-noise ratio for laminar analysis, all repeated runs were motion-corrected and averaged without additional spatial alignment, preserving the native functional space for subsequent analyses. The fMRI data were then upsampled to a fourfold finer in-plane grid (0.2 × 0.2 mm²) using cubic interpolation to facilitate alignment with cortical depth estimates 42,46. Distortions in the EPI images were corrected using a B0 field map processed with PRELUDE and FUGUE from FSL package, ensuring alignment with scanner-specific echo spacing and unwarping parameters. Anatomical MP2RAGE images were co-registered to the motion- and distortion-corrected functional images using SPM12.

A mask of the 3b region of the primary sensory cortex (S1) was generated using FreeSurfer. Cerebrospinal fluid (CSF), gray matter, and white matter were visually identified from the anatomical images, aiding in the creation of precise layer masks for subsequent analysis. All data analyses were conducted using custom-written MATLAB scripts. For statistical analyses, spatial smoothing with a Gaussian kernel of 1.6 mm (twice the voxel size of 0.8 mm³) was applied using FSL FEAT 86 to facilitate the manual drawing of regions of interest (ROIs) from the activation maps. However, for layer-specific and columnar analyses, all steps were performed without spatial smoothing to preserve the native resolution of the data, ensuring precise measurements of layer-specific and columnar activity (see the section below, Region of Interest (ROI) Selection and Columnar Analysis, for details).

Functional Activation Mapping and Percent Signal Change

Functional activation maps were created by averaging BOLD signals across individual trials for each condition (task and passive), followed by a General Linear Model (GLM) analysis using a canonical hemodynamic response function (HRF) to produce z-statistic maps. A primary threshold of z > 1.5 was applied, and results were cluster-corrected at p < 0.05. Passive activation maps generally included both wrist and finger responses, while task maps primarily highlighted finger representations.

Percent signal change was computed by subtracting the mean BOLD signal during the 6 seconds prior to stimulus onset (baseline) from the signal during stimulation, dividing by the baseline, and multiplying by 100. The stimulation duration was 18 seconds (6 TRs; TR = 3 s), and BOLD responses were averaged over the full 18-second window, starting 2 TRs (6 s) after stimulus onset to account for the hemodynamic delay.

Columnar Analyses

To examine fine-scale spatial patterns, columnar ROIs were manually defined along the somatotopic axis of area 3b, covering transitions from wrist to finger representations (Fig. 3a and Supplementary Fig. 4a). These ROIs were divided into five columnar segments, each representing a contiguous band of cortex. For each condition, signal time courses were extracted across columns. This allowed for visualization of attentional modulation across somatotopic space. Average signal change during stimulation was compared across columns, and columns 1–5 were tested for condition × location interaction effects.

Laminar Profile and Layer Assignment

Finger and wrist ROIs were manually drawn on GE/SE BOLD ratio images, which provided high contrast between tissue types and enabled clear visualization of both the CSF–GM boundary and the GM–WM boundary (Fig 2c). ROIs were centered on finger- and wrist-preferring voxels identified from an independent somatotopic localizer (or task activation maps in the absence of a localizer; see Somatotopic Mapping and ROI Localization). These delineations allowed precise identification of the full cortical ribbon in area 3b of S1 for laminar analysis. Following this delineation, cortical depth bins were generated using the LAYNII software suite 87, which divides the ribbon into 8 equivolume bins, spanning the ~2 mm cortical thickness of S1 45 (Fig. 2c). To reduce slice-selection bias and improve statistical power, laminar profiles were averaged across slices within the manually defined ROIs. Percent signal changes were then calculated for each bin.

To validate the laminar structure, quantitative T1 (qT1) maps from MP2RAGE data were analyzed (Fig. 2d and Supplementary Fig. 3) 52. qT1 values decreased monotonically from the pial surface to the WM boundary. First and second derivatives revealed consistent transitions and inflection points across subjects (Supplementary Fig. 3b–d), supporting known laminar boundaries. Based on the qT1 gradient analysis and relative cortical depth, we grouped cortical depth bins into three laminar compartments: Bins 1–2 were designated as superficial layers, Bins 4–5 as middle layers, and Bins 7–8 as deep layers.

Statistical analysis

Unless otherwise specified, statistical analyses in the main text report uncorrected p-values. For multiple comparisons across ROIs or cortical layers, we applied the Benjamini-Hochberg false-discovery-rate (FDR) procedure (q < 0.05). Specifically, one-sample and paired t-tests across the five columnar ROIs and across the three cortical layers were corrected within each family of tests. Statistical significance in the figures is indicated using FDR-corrected thresholds.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "1. What are the noteworthy results?\n-> Human 7T FMRI provided evidences that attention selectively enhanced the responses of the superficial layer, associated with top-down signals, while leaving the middle layer, which receives sensory input from the thalamus, unaffected.\n2. Will the work be of significance to the field and related fields? How does it compare to the established literature? If the work is not original, please provide relevant references.\n-> Classic neurpsychology has offered enough evidences on the attentional modulation in animal experimental settings even not only limited to sensory motor. It seems an interesting work by the present findings to imaging the similar modulation in humans.\n3. Does the work support the conclusions and claims, or is additional evidence needed?\n-> The connection between claims and the conclusions is straightforward. One potential limitation is the sample size. Is there any possibility of getting a replication (e.g., performed based on another N=10 participants) to ensure the generalizability? Meanwhile, are the present results observable under normal 3T MRI imaging settings with its most advances?\n4. Are there any flaws in the data analysis, interpretation and conclusions? Do these prohibit publication or require revision?\n-> Beyond classic task-activation analysis, oscillation methods can add more information of the brain dynamics underlying the cognitive process and advance insights of enegy budget (see https://pubmed.ncbi.nlm.nih.gov/39933322 for recent progresses).\n5. Is the methodology sound? Does the work meet the expected standards in your field?\n-> All statistics should be reported with full details (confidence intervals, effect size, etc). According such a small sample size, better to present all the individual samples, not use bar/box plots as in the current figures.\n6. Is there enough detail provided in the methods for the work to be reproduced?\n-> I failed in finding the information about data sharing or any other claims on open science practice.", "reviewer_2": "The authors investigate n=9 participants using ultra-high field 7T fMRI during stimulation of the wrist and the index and middle fingers. In some trials, participants attend to the fingers, in others, they do not attend to any body part in particular. No behavioral data are recorded in the MRI. The authors take the results to argue that activation in the S1 finger area is enhanced during attention to the fingers but that activation in the S1 wrist area is suppressed during attention to the fingers. They take this to argue that the superficial layer mediates somatosensory attention.\nMajor concerns\n- Overall study aim. The overall aim as stated in the introduction is to investigate the INTERACTION between superficial layers, middle layers and deep layers during attentional modulation, where the effect of attentional modulation of the superficial layer has been reported previously. However, such an interaction, which could be investigated for example by layer-specific connectivity analyses or by testing how superficial layer activation predicts middle or deep layer activation, is not tested for. Instead, only the net activations are extracted, which do not test for the major aim of the study.\n- Localization. The localization approach is not accurate and leads to a number of downstream errors. In order to conduct layer-specific activations and to draw firm conclusions on the im-/precision or layer activation of a cluster, an accurate localization approach is of pivotal importance. Sampling just 1-2 voxels away from the correct location can result in totally different profiles. The authors state in the text that ROIs were \"anatomically defined based on previous studies\". However, this study used probabilistic mapping (https://www.sciencedirect.com/science/article/pii/S1053811920303669) and showed that the representations of D1 and D2 are overlapping in S1, and can hence not be defined purely based on anatomy. Even more critically, the wrist area cannot be located anatomically at all. Therefore, in the methods section, it is then suddenly stated (other than in the results section) “The wrist ROI was identified based on the passive condition map, and the finger ROI was located at the overlap between the passive and task condition maps.” This approach is even worse, as the authors here report to have chosen different approaches for localizing both body parts, and also apply an approach that includes double dipping. Statements and conclusions that are following such as \"diffusive BOLD responses were observed across multiple columns\" are therefore unsupported, because no good definition of what \"precise\" would be can be obtained. Also the later conclusion on \"surround suppression\" is unsupported without any clear localization of the individual fingers, and their surround. Similarly wrong is to later focus on the \"attended column\", because the columns are not defined precisely but just drawn manually onto the cortex with large chunks without explaining how this definition was obtained. The missing localizer unfortunately biases all reported analyses.\n- Study design. It is not clear if their Dancer design stimulation can reliably activate the wrist area, and if participants feel this stimulation clearly. I have tried to map the wrist myself in the 7T MRI scanner using stimulation intensities much stronger than the Dancer stimulator can apply, but I could not obtain reliable results. The first thing therefore should have been to run a topographic mapping paradigm, ideally stimulating all fingers and different parts of the wrist, and to show that a reliable map can be obtained in each participant. This would be the basis for modulating attention. In addition, the design lacks the reversed contrast (attend to wrist, disregard fingers) to see if the effect can be replicated with the reversed pattern. In the present case, the results of the study could just be biased by overall bad activation of the wrist area that is not localized clearly, and localized differently than the fingers.\n- Results. The statement \"However, when attention was directed to the fingers, activation became more focused on the finger region\" is unsupported. In the Supplementary Figure 1 that the authors refer to, data of n=1 participant is shown. In this participant, the opposite is true for experiment b, i.e., the passive b activation is stronger localized towards the area opposite the hand knob than the active b activation. In Supplementary Figure 3 that is cited later, many participants seem to show stronger activation for the passive compared to the active condition. I therefore do not agree with the conclusion that \"This initial analysis demonstrates that attention enhances responses to task-relevant stimuli\" given it does not summarize correctly the results of experiment b.\n- Layer definition. The authors write \"For quantitative analyses, layers were drawn in the 3b region of S1, where stimulation-driven responsive activation was observed\". To draw in layers where activation is seen is not an objective way of defining cortical layers, because it biases the definition towards areas more strongly activated in a given condition. Layer definition should be done based on independent anatomical data. A recent approach introduced a way to delineate superficial, middle and deep layers if area 3b based on 7T MRI MP2RAGE data (https://www.jneurosci.org/content/43/19/3456?utm_source=TrendMD&utm_medium=cpc&utm_campaign=JNeurosci_TrendMD_1). This or a similar approach should be chosen.\nMinor concerns\n- Supplementary Figure 1 should be changed in a way that the display on the upper left corner does not hide brain activation by the purple line indicating where the hand knob is. This display should be shown on a different display to not hide any brain data.", "reviewer_3": "Overview\nThis paper provides compelling evidence that attention modulates neural activity at the laminar level in the primary somatosensory cortex (S1). Using cutting-edge neuroimaging methods, the authors capture high-resolution, layer-specific BOLD activity associated with finger and wrist stimulation and demonstrate that this activity is strongly influenced by somatosensory attention. In my view, this paper represents a very significant contribution to the field due to its methodological rigor, large and consistent effect sizes, and well-written manuscript. I commend the authors for their impressive work and offer several suggestions, outlined below, to further strengthen what is already a high-quality paper worthy of publication.\nSummary\nThe authors set out to address how attention changes somatotopic responses in S1 and which cortical layers are modulated. They hypothesize that focusing attention on the finger region will increase response in that area while suppressing responses in the unattended wrist region. Moreover, they specifically ask whether superficial (layers II/III), middle (layer IV), or deep (layers V/VI) compartments are most affected by attention.\nMethodologically, the study employs 7T SE BOLD imaging at 0.8 mm isotropic resolution, which minimizes large-vessel contamination and highlights more localized microvascular signals. Participants either (i) passively experienced stimuli on both hands and wrist or (ii) performed a frequency discrimination task on the hands under the instruction to ignore wrist stimulation. In Experiment 2, the distractor stimulus at the wrist was a painful heat.\nThe key findings confirm that attention boosts activity in the finger ROI and suppresses the wrist ROI almost completely. Within the finger ROI, attention particularly enhances the superficial layer, whereas passive stimulation sees peak activation in the middle layer, consistent with feedforward thalamic inputs. Critically, in the unattended wrist region, activity is driven down to near zero, and follow-up behavioral data show that participants’ performance on a wrist-based discrimination task plummets if they are concurrently focusing on finger stimuli. These findings reinforce that attentional modulation in S1 is tightly tied to laminar microcircuitry, with top-down enhancement targeting superficial layers and robust suppression of irrelevant inputs.\nMajor Comments\n(1) The strong effect sizes reported—especially given the inherent challenges of laminar fMRI—are impressive. Similarly, the striking behavioral results give the imaging findings real-world significance, confirming that attentional focus on finger stimulation has tangible consequences for wrist-based tasks.\n(2) Figure 2A: The anatomy depiction in Figure 2A is somewhat difficult to parse due to multiple overlaid gradients (from lower to upper slices, different color schemes, and column numbering). It would help to clarify exactly how these gradients map onto each other or provide a more step-by-step explanation in the legend.\n(3) Figure 2B Passive Condition: In Figure 2B (passive condition), the BOLD response in column 2 (representing fingers) appears weaker than in other columns (including column 1, which may not even be a hand ROI). This prompts questions about which somatotopic regions each column represents. A clearer functional localizer or more precise labeling could help readers interpret these responses accurately and avoid confusion if anatomical definitions differ slightly across participants.\n(4) Laminar fMRI Analysis Concerns\n* It is somewhat problematic that the finger ROI is defined functionally, using the same response data you subsequently analyze for differences across conditions, while the wrist ROI is defined anatomically, meaning it is almost certainly less precise for each subject. Given the large effect sizes, this is unlikely to invalidate the results, but it is worth mentioning as a potential source of bias.\n* Although SE BOLD at 7 T helps curb macrovessel signals, laminar fMRI remains subject to partial-volume effects and the spread of the hemodynamic response. Claims of “complete suppression” or “exclusively superficial” activation should thus be interpreted carefully, with vascular confounds in mind.\n(5) The paper reports “complete suppression” to zero in certain wrist ROI plots (Figure 3), but Figure 2 sometimes shows negative BOLD in nearby wrist areas. Clarification on whether the signal dips below baseline or remains at baseline across the entire wrist region would be beneficial to reconcile these displays.\n(6) The drop in psychophysical performance on the 8-way wrist location discrimination task is dramatic, nearing chance level. This indeed underscores the potency of attentional gating. The authors might briefly discuss how a simpler task (e.g., a two-location discrimination) might reveal partial interference rather than near-complete impairment, highlighting the interplay between task difficulty and attentional resources.\n(7) Discussion of Theoretical Implications: The authors note that attention bypasses the thalamocortical (middle-layer) inputs and instead amplifies superficial layers. This has direct relevance for models of top-down attentional control, which often posit that feedback targets supragranular layers. Expanding the discussion to connect these layer-specific findings more explicitly to current theories of attention (e.g., gating vs. normalization) would strengthen the conceptual impact.\nMinor Comments\n(1) Presenting per-subject effect sizes or explicitly stating how many subjects individually replicate the key patterns would help confirm that the group-level findings are robust.\n(2) Fig. 2C: why do you think column 5 is modulated almost as much as column 2 by attention? That seems unexpected.\n(3) Although dividing the cortex into eight equal depths is a common approach, the thickness of layer IV can vary slightly across S1 subregions. A more precise approach might incorporate the known laminar thickness ratios in S1 or individual cytoarchitecture data.\n(4) On line 250, “superficial” is spelled as “superfical.” A quick search for similar minor typos might be useful.\nOverall, these results are a strong contribution to our understanding of layer-specific attentional modulation in the somatosensory cortex."}, "author_response": "Ms. No.: NCOMMS-24-86161-T\nWe would like to thank the Nature Communications Editors and Reviewers for their thoughtful\ncomments and the opportunity to improve our manuscript. We are grateful for the constructive\nfeedback, which helped us refine both our experimental rationale and presentation of results.\nWe have substantially revised the manuscript in response to the comments received.\nTo summarize, the major changes and findings in the revised manuscript are as follows:\n1. Expanded Dataset\nWe conducted an additional fMRI experiment (Experiment 1) with eight new participants\n(total N = 16), as suggested by Reviewer #1. Laminar-specific attentional modulation\nobserved in our original dataset was replicated in Experiment 1 and further supported by\nfindings from Experiment 2 (pain stimulation, N = 9), enhancing the robustness and\ngeneralizability of our results.\n2. Improved ROI Definition\nAs suggested by Reviewer #2, we performed phase-encoded traveling wave localizer\nexperiments in both new and existing participants to objectively determine finger and wrist\nROIs in S1. To assign cortical layers, we incorporated qT mapping, as suggested by\n1\nlayer, specifically layer 4.\n3. Further analysis of Inter-Laminar Interactions\nWe examined the relationship between subject-wise attentional modulation (ΔS) in the\nsuperficial and deep layers, but found no significant relationship, likely due to large inter-\nsubject variability.\n4. Revised Text and Figures\nWe revised key sections of the manuscript and updated all major figures (Figs. 1-6 and\nSupplementary Figs. 1-7) to better illustrate experimental design, laminar analysis, and\nattentional effects. Given the scope of revisions, we highlight only the changes relevant to\neach reviewer’s comment.\nWe hope these substantial revisions address the reviewers’ concerns and sincerely appreciate\nthe opportunity to improve the manuscript.\nOur responses to the reviewer’s comments are shown in blue text. The corresponding excerpts\nfrom the revised manuscript (including figures, where relevant) are presented in red.\nReviewer #1\nR1-1. “1. What are the noteworthy results?\n-> Human 7T FMRI provided evidences that attention selectively enhanced the responses of the\nsuperficial layer, associated with top-down signals, while leaving the middle layer, which\nreceives sensory input from the thalamus, unaffected.”\nResponse: We thank the reviewer for highlighting this key result.\nR1-2. “2. Will the work be of significance to the field and related fields? How does it compare to\nthe established literature? If the work is not original, please provide relevant references.\n-> Classic neurpsychology has offered enough evidences on the attentional modulation in\nanimal experimental settings even not only limited to sensory motor. It seems an interesting\nwork by the present findings to imaging the similar modulation in humans.”\nResponse: We thank the reviewer for acknowledging the significance of our findings and for\nhighlighting the opportunity to better contextualize our work within the broader literature. We\nhave now added the relevant citations to strengthen the background. In the revised manuscript,\nwe state:\np.3 (introduction) “Classic neurophysiological studies have demonstrated attentional\nmodulation both in early sensory areas (Moran & Desimone, 1985; Reynolds &\nChelazzi, 2004) and in higher-order regions involved in top-down control (Buschman &\nMiller, 2007; Gregoriou et al., 2009).”\nR1-3. 3. Does the work support the conclusions and claims, or is additional evidence needed?\n-> The connection between claims and the conclusions is straightforward. One potential\nlimitation is the sample size. Is there any possibility of getting a replication (e.g., performed\nbased on another N=10 participants) to ensure the generalizability? Meanwhile, are the present\nresults observable under normal 3T MRI imaging settings with its most advances?\nResponse: We appreciate the reviewer’s thoughtful comments regarding the generalizability of\nour findings.\n1) To address this concern, we conducted additional fMRI experiments with 8 new subjects for\ntactile stimulation to the finger and wrist (Experiment 1). This brings the total sample size of\nExperiment 1 to N = 16. The results from this independent cohort replicate and reinforce the\nlaminar-specific attentional modulation observed in our original dataset (see two different\nsymbols in Fig. 4 and Supplementary Fig. 6). Furthermore, the findings from Experiment 1\nwere also replicated in Experiment 2 using pain stimulation. The inclusion of this additional\ndataset strengthens the robustness and reproducibility of our conclusions. This critical point\nwas addressed as follows:\np. 5. “Eight participants (Subjects 1–8; Group 1) initially completed Experiment 1, and\nadditional eight participants (Subjects 10–17; Group 2) were later recruited to replicate\nthe findings. In Experiment 2, tactile stimulation was applied to the same fingers (two\nstimulators), while a single thermal stimulator delivered heat to the wrist (n = 9,\nincluding the eight Group 1 participants from Experiment 1 plus one additional\nparticipant; Fig. 1e).”\np. 10. “Also, these laminar patterns were largely consistent when we divided the data\ninto the original eight participants and the additional eight participants (in Fig. 4, Group\n1 and Group 2 are denoted by distinct symbols; see also Supplementary Fig. 6 for the\nresults presented separately for each group).”\nFig 4. e–f Layer-specific BOLD modulation (passive vs attended) in the finger (e) and wrist (f)\nROIs. Each bar shows the mean percent signal change (± SEM) across participants. Paired\nmarkers reflect within-subject differences between passive and attended conditions. Circles\nrepresent data from Group 1, while triangles represent Group 2.\nSupplementary Fig. 6: Layer-specific BOLD modulation by attention in Group 1 and\nGroup 2 in Experiment 1. We first tested for attention-related differences across cortical layers\nusing a 2 (Condition: passive, attended) × 3 (Layer: superficial, middle, deep) repeated-\nmeasures ANOVA. In group 1, a significant Condition × Layer interaction was found in the finger\nROI (F(2,14) = 10.687, p = 0.002, η² = 0.604), with attention increasing activity in the superficial\nlayer (p = 0.015, d = 1.137, passive vs. attended paired t-test), marginally suppressing the deep\nlayer (p = 0.077, d = –0.733), and leaving the middle layer unchanged (p = 0.202, d = –0.498). In\nthe wrist ROI, a significant interaction was also observed (F(2,14) = 8.929, p = 0.003,\nη² = 0.561), and a main effect of condition was present (F(1,7) = 150.556, p < 0.001, η² = 0.956),\nwith all layers suppressed under attention (ps < 0.008). In group 2, a similar Condition × Layer\ninteraction was observed in the finger ROI (F(2,14) = 23.483, p < 0.001, η² = 0.770), driven by\ngreater activation in the superficial layer (p = 0.003, d = 1.597) and suppression in the deep\nlayer (p = 0.013, d = –1.178), while no significant modulation was found in the middle layer\n(p = 0.727, d = –0.128). In the wrist ROI, no significant interaction was observed\n(F(2,14) = 1.468, p = 0.264, η² = 0.173), though a strong main effect of condition was present\n(F(1,7) = 117.744, p < 0.001, η² = 0.944), with all layers suppressed under attention (ps < 0.003).\nLeft panels show the BOLD time courses during passive (a–b, e–f) and attended (c–d, g–h)\nconditions, separated by layer (superficial: orange, middle: green, deep: purple), with shaded\nerror bars indicating ±SEM. Right panels show mean BOLD responses during stimulation.\n2) Regarding the feasibility of replicating these results with 3T MRI, we note that\nmicrovascular-sensitive spin-echo BOLD fMRI inherently has low sensitivity. Therefore,\nenhancing sensitivity through the use of higher magnetic field strengths is critical. Under\nstandard 3T imaging conditions, the spatial resolution and specificity required for layer-\ndependent analysis are not practically achievable. We have clarified this point in the revised\nmanuscript as follows:\np. 16 (Discussion) “While laminar-resolution SE-BOLD fMRI offers greater specificity\nthan GE-BOLD fMRI, it has lower sensitivity. Achieving robust microvascular signals,\ntherefore, requires ultra-high magnetic field strengths (e.g., 7 T) and extensive signal\naveraging across many repeated trials.”\nR1-4. 4. Are there any flaws in the data analysis, interpretation and conclusions? Do these\nprohibit publication or require revision?\n-> Beyond classic task-activation analysis, oscillation methods can add more information of the\nbrain dynamics underlying the cognitive process and advance insights of enegy budget (see\nhttps://pubmed.ncbi.nlm.nih.gov/39933322 for recent progresses).\nResponse: We thank the reviewer for suggesting oscillation-based methods to explore the\ndynamics and energy efficiency of cognitive processes. We agree that these approaches could\npotentially offer insights, particularly at the network level, as illustrated by the cited work.\nHowever, our layer-specific spin-echo BOLD fMRI studies prioritize high spatial resolution,\nwhich necessarily limits temporal resolution. Therefore, our microvascular-sensitive BOLD\nimaging is not well-suited for dynamic oscillatory analyses. Implementing such methods would\nrequire a fundamentally different acquisition protocol, such as fast fMRI, which falls beyond the\nscope of the present study. Nonetheless, we have acknowledged this important consideration in\nour revised manuscript as follows:\np. 17 “Fifth, in our fMRI studies, we prioritized high spatial resolution and specificity at\nthe expense of temporal resolution. As a result, we were unable to examine the\ndynamics and interaction between layers that would be informative in inferring energy\nefficiency of cognitive processes, which have been studied at the network level (Gong\n& Zuo, 2025). In future studies, it would be valuable to adopt high temporal resolution\ntechniques—such as gradient-echo BOLD fMRI—to investigate the dynamics of fMRI\nsignals across brain regions and cortical layers.”\nR1-5. 5. Is the methodology sound? Does the work meet the expected standards in your field?\n-> All statistics should be reported with full details (confidence intervals, effect size, etc). According such a small sample\nsize, better to present all the individual samples, not use bar/box plots as in the current figures.\nResponse: We appreciate the reviewer’s feedback regarding statistical reporting and data\nvisualization. In the revised manuscript, we have incorporated both individual data points and\nmean values in the main and Supplementary figures, wherever appropriate. We have also\nadded detailed statistical information wherever necessary. Due to the widespread nature of\nthese revisions across figures and text, we have not described each change individually. We\nkindly ask the reviewer to review the main text and Supplementary Figures for the updated\ncontent.\nR1-6. 6. Is there enough detail provided in the methods for the work to be reproduced?\n-> I failed in finding the information about data sharing or any other claims on open science\npractice.\nResponse: We thank the reviewer for highlighting the importance of open science practices. In\nline with community standards, we will deposit the fMRI time series of individual subjects in\nNIfTI format on a public repository and make them openly available upon publication. We have\nnow added a Data and Code Availability section (p. 18) outlining the open science plan as\nfollows:\np. 18 “All data and analysis code supporting the findings of this study are available on\nthe Open Science Framework (OSF) at https://osf.io/2v6nb/.“.\nReviewer #2\n“The authors investigate n=9 participants using ultra-high field 7T fMRI during stimulation of the\nwrist and the index and middle fingers. In some trials, participants attend to the fingers, in\nothers, they do not attend to any body part in particular. No behavioral data are recorded in the\nMRI. The authors take the results to argue that activation in the S1 finger area is enhanced\nduring attention to the fingers but that activation in the S1 wrist area is suppressed during\nattention to the fingers. They take this to argue that the superficial layer mediates\nsomatosensory attention.”\nResponse: Thank you for summarizing our work and providing many constructive comments.\nWe believe that, thanks to your comments, the quality of our manuscript has improved\nsignificantly. Please find our point-by-point responses below.\nR2-1. “Major concerns\nOverall study aim. The overall aim as stated in the introduction is to investigate the\nINTERACTION between superficial layers, middle layers and deep layers during attentional\nmodulation, where the effect of attentional modulation of the superficial layer has been reported\npreviously. However, such an interaction, which could be investigated for example by layer-\nspecific connectivity analyses or by testing how superficial layer activation predicts middle or\ndeep layer activation, is not tested for. Instead, only the net activations are extracted, which do\nnot test for the major aim of the study.”\nResponse 1: We thank the reviewer for highlighting the importance of examining inter-laminar\ninteractions, particularly in the context of attentional modulation. In our original manuscript, we\nunintentionally referred to interaction effects between layers; accordingly, we have removed\nsuch statements from the Introduction to avoid confusion.\nNonetheless, we did assess inter-laminar interactions by correlating attention-induced changes\nbetween superficial and deep layers at the subject level. These analyses are now described in\nthe Results section and illustrated in Supplementary Fig. 7.\np. 11 (Results) “One might expect that attentional enhancement of superficial-layer\nresponses down-regulates deep-layer activity; however, we found no relationship\nbetween attention-induced changes in the superficial and deep layers at the subject\nlevel (R² = 0.03, p = 0.505; Supplementary Fig. 7), likely reflecting substantial inter-\nsubject variability.”\np. 12 (Results) “As in Experiment 1, the cross-participant correlation between\nsuperficial-layer enhancement and deep-layer suppression was not significant (R² =\n0.07, p = 0.458; Supplementary Fig. 7).”\nSupplementary Fig. 7: Relationship between superficial- and deep-layer attentional\nmodulation in the attended finger ROI. Scatter plots show individual participants’ attention-\ninduced changes (ΔS) in superficial and deep layers for a, Experiment 1 and b, Experiment 2.\nSymbols indicate participant groups (Group 1, open circles; Group 2, open triangles in\nExperiment 1). Shaded areas represent 95% confidence intervals for the regression line. In\nboth experiments, superficial- and deep-layer modulations were not significantly correlated\n(Experiment 1: R² = 0.02, p = 0.584; Experiment 2: R² = 0.07, p = 0.458), ruling out a simple\ndirect inhibition account within cortical columns.\nR2-2. “Localization. The localization approach is not accurate and leads to a number of\ndownstream errors. In order to conduct layer-specific activations and to draw firm conclusions\non the im-/precision or layer activation of a cluster, an accurate localization approach is of\npivotal importance. Sampling just 1-2 voxels away from the correct location can result in totally\ndifferent profiles. The authors state in the text that ROIs were \"anatomically defined based on\nprevious studies\". However, this study used probabilistic mapping\n(https://www.sciencedirect.com/science/article/pii/S1053811920303669) and showed that the\nrepresentations of D1 and D2 are overlapping in S1, and can hence not be defined purely based\non anatomy. Even more critically, the wrist area cannot be located anatomically at all. Therefore,\nin the methods section, it is then suddenly stated (other than in the results section)\n“The wrist ROI was identified based on the passive condition map, and the finger ROI was\nlocated at the overlap between the passive and task condition maps.” This approach is even\nworse, as the authors here report to have chosen different approaches for localizing both body\nparts, and also apply an approach that includes double dipping. Statements and conclusions\nthat are following such as \"diffusive BOLD responses were observed across multiple columns\"\nare therefore unsupported, because no good definition of what \"precise\" would be can be\nobtained. Also the later conclusion on \"surround suppression\" is unsupported without any clear\nlocalization of the individual fingers, and their surround. Similarly wrong is to later focus on the\n\"attended column\", because the columns are not defined precisely but just drawn manually onto\nthe cortex with large chunks without explaining how this definition was obtained. The missing\nlocalizer unfortunately biases all reported analyses.”\nResponse: We thank the reviewer for the detailed and constructive feedback regarding our ROI\nlocalization procedure. We fully agree that accurate localization is essential for laminar fMRI\nstudies, and we have revised the manuscript to clarify and strengthen this aspect of our\nmethodology.\n1) To define the finger and wrist ROIs more accurately, we conducted additional experiments\nusing a traveling wave tactile stimulation paradigm in all scanned subjects except two. The\nscheme for the tactile traveling wave paradigm is shown in Supplementary Fig. 1a.\nThis functional localizer allowed us to initially delineate the finger and wrist ROIs (see Fig.\n2a and Supplementary Fig. 2). Then, finger and wrist ROIs were refined by functional activity\nmaps (Fig. 2b and Supplementary Fig. 2). The new definition of ROIs reduces the circularity\nas noted by the Reviewer.\nFig. 2a-b: Laminar boundaries in finger and wrist regions defined by anatomical and\nfunctional activity.\na Phase-encoded somatotopic maps across selected slices from a representative subject,\ncentered on the hand knob. Colors denote peak locations for fingers (blue), hand (pink),\nwrist (green), and forearm (yellow). Slices are arranged from inferior to superior cortex.\nb Activation patterns during passive (top row) and attended (middle row) tactile stimulation in the same\nsubject. Functional ROIs (bottom row) were defined based on activity patterns and anatomical\nlandmarks: the finger ROI (yellow) includes voxels activated in both conditions lateral to the\nhand knob, while the wrist ROI (green) includes voxels activated only during passive\nstimulation, medial to the hand knob.\nSupplementary Fig. 2: Activation Maps in Area 3b of the Primary Somatosensory Cortex\n(S1) During Passive and Attended Conditions. This figure displays individual-level activation\nmaps in area 3b of the primary somatosensory cortex (S1), comparing neural responses during\npassive and attended conditions across two experiments.\nTo enhance clarity of ROI definitions, we have added Fig. 2 to more clearly illustrate the ROI\ndefinition procedure. Please refer to the revised figure (Fig. 2).\n2) For the columnar analyses along the medial-to-lateral axis, we defined isodistance columns\nbased on the anatomical landmark known as the hand knob. As noted by the reviewer,\nthese anatomically defined ROIs cannot be unambiguously assigned to specific body parts.\nAccordingly, we reported the columnar results from 16 subjects in Experiment 1 (8 original\nand 8 newly acquired datasets; see Fig. 3 and Supplementary Fig. 4) and from 9 subjects in\nExperiment 2 (see Supplementary Fig. 5). Based on the additional data and refined analysis,\nwe found that only Column 2 consistently remained active during attention and have\nremoved speculative language such as “surround suppression.”\nFig. 3: Attention-Modulated BOLD Signal Changes Across Columnar ROIs in S1\nSupplementary Fig. 4b-c: b BOLD percent signal change during passive tactile-tactile\nstimulation for each individual column ROI (1–5). Each marker represents a subject from\nExperiment 1; cyan circles and golden triangles denote subjects from Group 1 and Group 2,\nrespectively. Black lines show the group mean ± SEM. c, Same as in b, but for the attended\ncondition.\nSupplementary Fig. 5: Attention-Modulated BOLD Signal Changes Across Columnar\nROIs in S1 in Experiment 2.\n3) Using the newly defined finger and wrist ROIs, we were able to replicate all major findings,\nfurther supporting the robustness of our conclusions. However, since these ROIs were\ndefined using a phase-sensitive traveling-wave paradigm and further refined with task-based\nfMRI data, they are not entirely independent from the data used in the main analyses. This\nraises the possibility of circularity in the ROI definition. Nevertheless, we believe this\nconcern is limited, as similar results were obtained using anatomically defined ROIs (Fig. 3),\nproviding converging evidence for our conclusions.\nThis issue is now noted as a potential limitation in the manuscript as follows:\np. 17 (Discussion) “Third, the finger and wrist ROIs were defined using phase-sensitive\ntraveling-wave tactile stimulation and further refined based on actual task data.\nTherefore, the ROIs are not entirely independent, raising the possibility of circular\nreasoning due to activity-dependent ROI definition. However, we believe this concern\nis minimal, as analyses based on anatomically defined ROIs (Fig. 3) yielded results\nsimilar to those obtained with functionally defined ROIs (Figs. 4–5).”\nR2-3. - Study design. It is not clear if their Dancer design stimulation can reliably activate the\nwrist area, and if participants feel this stimulation clearly. I have tried to map the wrist myself in\nthe 7T MRI scanner using stimulation intensities much stronger than the Dancer stimulator can\napply, but I could not obtain reliable results. The first thing therefore should have been to run a\ntopographic mapping paradigm, ideally stimulating all fingers and different parts of the wrist, and\nto show that a reliable map can be obtained in each participant. This would be the basis for\nmodulating attention. In addition, the design lacks the reversed contrast (attend to wrist, disregard fingers) to see if the effect can be replicated with the reversed pattern. In the present case, the results of the study could just be biased by overall bad activation of the wrist area that is not localized clearly, and localized differently than the fingers.\nResponse: We thank the reviewer for their critical comments regarding the efficacy of wrist\nstimulation and the importance of functional localization.\n1) To define the wrist ROI, we employed a phase-encoded traveling wave (TW) localizer, as\nsuggested by the reviewer. This localizer was applied not only to newly recruited participants\nbut also to most individuals from the earlier experiments, enabling us to confirm the\nconsistency of somatotopic representations across subjects (see Supplementary Fig. 2 in\nR2-2 or Supplementary Information). In our 7T studies, participants consistently reported\ndistinct perceptual sensations during wrist stimulation, which is now described in the revised\nmanuscript. We also observed reliable activation maps in response to passive wrist\nstimulation (see Supplementary Fig. 2 also see response in R2-2), supporting the\neffectiveness of our Dancer stimulation paradigm. The discrepancy between our findings\nand the reviewer’s observations remains unclear; however, it may be attributed to\ndifferences in stimulation intensity and frequency.\n2) Regarding the study design, we agree that including a reversed contrast—attending to the\nwrist while ignoring the fingers—could provide complementary insights. However, our\nprimary objective was to examine how selective attention modulates laminar responses\nwhen directed toward a task-relevant somatotopic region (fingers) and how input from an\nirrelevant region (wrist) is suppressed. Incorporating a reversed condition would have\nsubstantially increased the experimental complexity and introduced potential confounds\nrelated to differences in task difficulty between finger- and wrist-based discrimination.\nFurthermore, our layer-specific SE-BOLD fMRI approach requires extensive averaging\nacross repeated trials over a 2-hour session to achieve sufficient sensitivity, making the\ninclusion of an additional condition unfeasible within practical constraints.\nWe also acknowledge that discriminative sensitivity on the wrist is substantially lower than\non the fingers, particularly for tactile tasks requiring fine spatial or temporal resolution. This\ninherent limitation could make it more difficult to detect attentional modulation in wrist\nrepresentations. Nonetheless, we believe that investigating attentional effects in lower-\nsensitivity regions such as the wrist remains a valuable direction for future research,\nparticularly for testing whether attention operates uniformly across somatotopically\norganized areas with differing sensory acuity.\nWe now explicitly acknowledge this limitation in the revised Discussion section as follows:\np. 17 (Discussion) “First, although both stimulus conditions produced similar results in\nthe finger and wrist regions, attention was directed only to the fingers, not to the wrist.\nTo determine whether our findings generalize to other attended regions, it is essential\nto conduct experiments involving attention directed to the wrist.”.\nR2-4. - Results. The statement \"However, when attention was directed to the fingers, activation\nbecame more focused on the finger region\" is unsupported. In the Supplementary Figure 1 that\nthe authors refer to, data of n=1 participant is shown. In this participant, the opposite is true for\nexperiment b, i.e., the passive b activation is stronger localized towards the area opposite the\nhand knob than the active b activation. In Supplementary Figure 3 that is cited later, many\nparticipants seem to show stronger activation for the passive compared to the active condition.\nI therefore do not agree with the conclusion that \"This initial analysis demonstrates that attention\nenhances responses to task-relevant stimuli\" given it does not summarize correctly the results\nof experiment b.\nResponse: We thank the reviewer for their careful reading and insightful critique. We now\nrecognize that our original phrasing—specifically the statement “activation became more\nfocused on the finger region”—may have led to misinterpretation. In the revised manuscript, we\nhave removed such speculative language and instead report the observed reduction of activity\nin Column 3 (presumed wrist region) during attention to the fingers, where significant activation\nwas present during passive tactile stimulation.\nTo clarify this point, we have revised the relevant sentence in the manuscript to avoid\noverstatement. The updated main text now reads:\np. 6. “Finger and wrist regions identified by the localizer were further refined using\nactivation maps from both passive and attended conditions (Fig. 2b). In the passive\ncondition, activation patterns were distributed around the hand knob area within S1.\nWhen attention was directed to the fingers, the number of activated voxels was\nmarkedly reduced (see also Supplementary Figs. 1c-d).”\nThis revision better reflects our intention and more accurately describes the observed effects.\nWe appreciate the reviewer’s feedback, which prompted us to refine both our interpretation and\nthe wording of our conclusions.\nR2-5. - Layer definition. The authors write \"For quantitative analyses, layers were drawn in the\n3b region of S1, where stimulation-driven responsive activation was observed\". To draw in\nlayers where activation is seen is not an objective way of defining cortical layers, because it\nbiases the definition towards areas more strongly activated in a given condition. Layer definition\nshould be done based on independent anatomical data. A recent approach introduced a way to\ndelineate superficial, middle and deep layers if area 3b based on 7T MRI MP2RAGE data\n(https://www.jneurosci.org/content/43/19/3456?utm_source=TrendMD&utm_medium=cpc&utm_\ncampaign=JNeurosci_TrendMD_1). This or a similar approach should be chosen.\nResponse: We thank the reviewer for highlighting this important issue regarding cortical layer\ndefinition. We acknowledge that the previous version of the manuscript did not clearly describe\nhow ROIs and laminar bins were defined. In the revised manuscript, we have redefined the\nlaminar ROIs (see Fig. 2) using anatomical CSF/GM and GM/WM boundaries, as well as qT1-\nbased laminar segmentation, as suggested by the reviewer (see Fig. 2c-d and Supplementary\nFig. 3).\nFig. 2c-d: c Functional ROIs were segmented along the cortical depth axis into 8 equidistant\nbins using anatomical boundaries derived from GE/SE BOLD contrast. d Second derivatives of\nquantitative T (qT ) profiles across cortical depth were used to assign laminar groups:\n1 1\nsuperficial (Bins 1–2), middle (Bins 4–5), and deep (Bins 7–8), corresponding to classical\ncortical layers (see Supplementary Fig. 3). The peak of the qT second derivative profile\n1\nindicates the location of layer 4 (Doehler et al., 2023). In our layer definition, layer 1 was not\nseparately specified due to its low neuronal density and was included in the superficial layer.\nSupplementary Fig. 3: Quantitative T Profile and Normalized Derivatives Across Cortical\nGroup-averaged qT1 profile across 8 equivolume cortical depth bins in area 3b of S1. Bin 1\ncorresponds to the pial surface (near CSF), and Bin 8 to the white matter boundary. Shaded\nregions represent the standard error of the mean (SEM) across subjects. b Normalized first\nderivative of the qT1 profile, reflecting the rate of change across depth. A peak around Bin 3–4\nindicates the steepest transition in qT1 values. c Normalized second derivative of the qT1\nprofile, capturing curvature (i.e., concavity). The peak indicates the most pronounced inflection\npoint. Derivative values were scaled to a maximum absolute value of 1 to enable shape-based\ncomparison independent of physical units.d Statistical evaluation of individual second-derivative\npeak locations relative to each bin depth. For each subject, the cortical depth of the maximal\nsecond derivative was identified and compared to the fixed bin depths (ranging from 0.9375\nnear CSF to 0.0625 near WM) using one-sample t-tests. These depth values correspond to the\ncenter of each equivolume bin. Resulting p-values are plotted on a logarithmic scale across\nbins. The dashed blue line indicates the significance threshold (p = 0.05); the dashed green line\nmarks the depth of Bin 4 (0.5625), which did not significantly differ from the individual peaks.\nThis supports Bin 4 as a valid group-level reference for the point of maximal qT1 curvature.\nNote that bin numbers increase from superficial (Bin 1) to deep (Bin 8), while depth values\nrepresent the normalized center of each bin in cortical depth space. e Axial slice from a\nrepresentative subject showing qT1 anatomical contrast with 8 equivolume cortical depth bins\noverlaid using an HSV colormap. The left hemisphere shows raw qT1; the right hemisphere\ndisplays bin contours. Colors progress from violet (Bin 1, near CSF) to cyan (Bin 8, near WM),\nrepresenting increasing cortical depth.\nWe recognized that the previous version of the manuscript did not clearly describe how regions\nof interest (ROIs) and laminar bins were defined. We re-determined layer ROI definitions (see\nFig. 2) by utilizing anatomical CSF/GM and GM/WM boundaries, and qT1-based laminar\nsegmentation suggested by the reviewer. Given the importance of accurate ROI definitions, we\nadded a new Results section entitled “Laminar Boundaries in Finger and Wrist Regions Defined\nby Anatomy and Functional Activity,” accompanied by a schematic figure (Fig. 2 in R2-2 and\nalso quoted in the revised Results section below).\np. 6 “ Laminar boundaries were determined as follows. The cortical depth of area 3b\n(~2 mm thick) was defined using GE-BOLD/SE-BOLD ratio images (Fig. 2c), which\nallowed visualization of both the cerebrospinal fluid (CSF)–gray matter (GM) boundary\nand the GM–white matter (WM) boundary (Han et al., 2022). This cortical ROI was\ndivided into 8 equidistant depth bins. To identify the middle cortical layer (layer 4),\nquantitative depth-dependent T (qT ) values from T -weighted anatomical images\n1 1 1\nwere analyzed (Doehler et al., 2023) (Fig. 2d and Supplementary Figs 3b-d). Based\non qT gradient analysis and previous literature (Dinse et al., 2015; Kuehn et al., 2017),\n1\nbins 1–2 were grouped as superficial (layers 2/3), bins 4–5 as middle (layers 4/5), and\nbins 7–8 as deep (layer 6). These laminar ROIs were then used to extract time courses\nfor each subject.”\nMinor concerns\nR2-6. - Supplementary Figure 1 should be changed in a way that the display on the upper left\ncorner does not hide brain activation by the purple line indicating where the hand knob is. This\ndisplay should be shown on a different display to not hide any brain data.\nResponse: Thank you for bringing this to our attention. We have revised Supplementary Figure\n1 (new Supplementary Fig. 1c) by relocating the purple hand knob marker and reducing its\nthickness to ensure that it no longer obscures any brain activation data.\nReviewer #3\nOverview\nThis paper provides compelling evidence that attention modulates neural activity at the laminar\nlevel in the primary somatosensory cortex (S1). Using cutting-edge neuroimaging methods, the\nauthors capture high-resolution, layer-specific BOLD activity associated with finger and wrist\nstimulation and demonstrate that this activity is strongly influenced by somatosensory attention.\nIn my view, this paper represents a very significant contribution to the field due to its\nmethodological rigor, large and consistent effect sizes, and well-written manuscript. I commend\nthe authors for their impressive work and offer several suggestions, outlined below, to further\nstrengthen what is already a high-quality paper worthy of publication.\nSummary\nThe authors set out to address how attention changes somatotopic responses in S1 and which\ncortical layers are modulated. They hypothesize that focusing attention on the finger region will\nincrease response in that area while suppressing responses in the unattended wrist region.\nMoreover, they specifically ask whether superficial (layers II/III), middle (layer IV), or deep\n(layers V/VI) compartments are most affected by attention.\nMethodologically, the study employs 7T SE BOLD imaging at 0.8 mm isotropic resolution, which\nminimizes large-vessel contamination and highlights more localized microvascular signals.\nParticipants either (i) passively experienced stimuli on both hands and wrist or (ii) performed a\nfrequency discrimination task on the hands under the instruction to ignore wrist stimulation. In\nExperiment 2, the distractor stimulus at the wrist was a painful heat.\nThe key findings confirm that attention boosts activity in the finger ROI and suppresses the wrist\nROI almost completely. Within the finger ROI, attention particularly enhances the superficial\nlayer, whereas passive stimulation sees peak activation in the middle layer, consistent with\nfeedforward thalamic inputs. Critically, in the unattended wrist region, activity is driven down to\nnear zero, and follow-up behavioral data show that participants’ performance on a wrist-based\ndiscrimination task plummets if they are concurrently focusing on finger stimuli. These findings\nreinforce that attentional modulation in S1 is tightly tied to laminar microcircuitry, with top-down\nenhancement targeting superficial layers and robust suppression of irrelevant inputs.\nResponse: Thank you for your support of our studies.\nMajor Comments\nR3-1. (1) The strong effect sizes reported—especially given the inherent challenges of laminar\nfMRI—are impressive. Similarly, the striking behavioral results give the imaging findings real-\nworld significance, confirming that attentional focus on finger stimulation has tangible\nconsequences for wrist-based tasks.\nResponse: Thank you for your positive feedback. We appreciate your recognition of the strong\neffect sizes and the significance of our behavioral findings in linking attentional modulation to\nreal-world consequences.\nR3-2. (2) Figure 2A: The anatomy depiction in Figure 2A is somewhat difficult to parse due to\nmultiple overlaid gradients (from lower to upper slices, different color schemes, and column\nnumbering). It would help to clarify exactly how these gradients map onto each other or provide\na more step-by-step explanation in the legend.\nResponse: We thank the reviewer for this constructive suggestion. In response, we have\nrevised Figure 2a (Fig. 3a in the revised manuscript) to improve clarity and readability.\nSpecifically, we added numerical labels (1–5) to indicate ROI columns across all slices, enabling\na more intuitive understanding of the somatotopic layout. We also clarified the anatomical\ngradient by marking the progression from lower (lateral) to upper (medial) slices with directional\nannotations. To further assist interpretation, we incorporated schematic drawings that map each\nROI column to specific body parts (e.g., fingers, wrist, arm), based on somatotopic information\nfrom an independent traveling wave (TW) localizer.\nWe also rewrote the figure caption to provide a step-by-step explanation of how columnar ROIs\nwere first defined based on anatomical landmarks (e.g., hand knob) and subsequently\nconfirmed using the TW localizer. This ensures consistency across participants while preserving\nindividual somatotopic precision (see Fig. 3 below).\nThese improvements clarify the spatial organization of the cortical gradient, ROI structure, and\nfunctional regions. We believe the revised figure and caption now convey our methodological\nrationale more transparently, and we have updated the manuscript accordingly in response to\nthe reviewer’s helpful feedback as follows:\nFig. 3: Attention-Modulated BOLD Signal Changes Across Columnar ROIs in S1. a\nColumnar ROIs were defined along the cortical ribbon of S1 using anatomical landmarks—\nparticularly the hand knob—and refined with somatotopic maps from an independent traveling\nwave (TW) localizer that delivered cyclic tactile stimulation to the fingers and wrist. This ensured\nconsistent yet individualized ROI placement. The top row displays SE-BOLD slices. Five\ncolumnar ROIs (Cols 1–5, colored yellow to green) trace a somatotopic gradient from distal\nfingers (Col 2) to proximal wrist (Col 3), with adjacent ROIs (Cols 1, 4, and 5) covering\nneighboring sensory areas. Note that the outermost ROIs taper in superior slices due to cortical\nnarrowing. Schematic illustrations depict the approximate body region represented by each\nROI, informed by the TW localizer. Orientation labels “A” (anterior) and “L” (lateral) indicate\nanatomical directions.\nR3-3. (3) Figure 2B Passive Condition: In Figure 2B (passive condition), the BOLD response in\ncolumn 2 (representing fingers) appears weaker than in other columns (including column 1,\nwhich may not even be a hand ROI). This prompts questions about which somatotopic regions\neach column represents. A clearer functional localizer or more precise labeling could help\nreaders interpret these responses accurately and avoid confusion if anatomical definitions differ\nslightly across participants.\nResponse: We thank the reviewer for raising this important point. To ensure accurate\nsomatotopic localization, we first anatomically defined columnar ROIs along the S1 cortical\nribbon using landmarks such as the hand knob and then confirmed these ROIs using an\nindependent traveling wave (TW) localizer. The TW localizer employed a phase-encoded tactile\nstimulation paradigm that cyclically targeted the fingers and wrist, producing continuous\nsomatotopic maps across participants. This allowed us to verify the functional identity of each\nROI column independent of the main experimental conditions.\nThe figures below illustrate the tactile traveling wave stimulation protocol used to map\nsomatotopy across four body sites—fingers, hand, wrist, and forearm—with each site stimulated\nfor 10 seconds per cycle (see Supplementary Fig. 1a).\nSupplementary Fig. 1a-b: Somatotopic mapping and activation patterns across\nconditions in Experiments 1 and 2. a Tactile traveling wave stimulation protocol used to map\nsomatotopy across four body sites (fingers, hand, wrist, forearm), each stimulated for 10\nseconds per cycle. Stimulation proceeded in either forward (0°–270°) or reverse (270°–0°)\norder across 10 cycles per run, repeated across 6 runs. b Circular mean of voxelwise phase\nresponses for each body location, color-coded by stimulus site. Arrows indicate the average\ndirection on the unit circle, accounting for the circular nature of phase data.\nThe next figure presents phase-encoded somatotopic maps from a representative subject (Fig.\n2a), centered on the hand knob. Colors indicate the peak activation locations for fingers (blue),\nhand (pink), wrist (green), and forearm (yellow). Slices are arranged from inferior to superior\ncortex.\nBased on this TW localizer, we confirmed that column 2 corresponds to the fingers, column 3 to\nthe wrist, and columns 1, 4, and 5 to adjacent or transitional areas. This dual-criterion\napproach—anchoring columns to anatomical landmarks and validating them functionally—\nensured consistency and robustness across subjects.\nTo visualize responses across the five columnar ROIs, we plotted raw BOLD time courses with\nstandard errors of the mean across 16 subjects for Experiment 1 (new Fig. 3b; see also Fig. 3 in\nR3-2) and 9 subjects for Experiment 2 (new Supplementary Fig. 5; see below). With the\ninclusion of additional subjects, passive stimulation in Experiment 1 elicited significant activation\nspecifically in Columns 2 and 3 (see closed circles in Fig. 3c and Supplementary Fig. 5b). We\nhope these updated figures clarify our findings and adequately address the reviewer’s concern.\nSupplementary Fig. 5: Attention-Modulated BOLD Signal Changes Across Columnar\nROIs in S1 in Experiment 2.\nR3-4. (4) Laminar fMRI Analysis Concerns\n* It is somewhat problematic that the finger ROI is defined functionally, using the same response\ndata you subsequently analyze for differences across conditions, while the wrist ROI is defined\nanatomically, meaning it is almost certainly less precise for each subject. Given the large effect\nsizes, this is unlikely to invalidate the results, but it is worth mentioning as a potential source of\nbias.\n* Although SE BOLD at 7 T helps curb macrovessel signals, laminar fMRI remains subject to partial-volume effects and the spread of the hemodynamic response. Claims of “complete\nsuppression” or “exclusively superficial” activation should thus be interpreted carefully, with\nvascular confounds in mind.\nResponse:\n1) We appreciate the reviewer’s concern and agree that the ROI definition must be handled\nwith care to avoid circularity and localization bias. To clarify, both the finger and wrist ROIs\nwere defined based on an independent functional localizer using a traveling wave (TW)\nparadigm, which involved cyclic tactile stimulation of the fingers and wrist to generate high-\nresolution somatotopic maps. This localizer was acquired independently of the main\nexperiment and was used to delineate body-part–specific representations without relying on\nthe task conditions being analyzed.\nFor Experiments 1 and 2, participants underwent the TW localizer, ensuring that ROI\ndefinitions were independent of the main experimental BOLD data and thereby minimizing\nconcerns about circularity. However, we acknowledge that some degree of circularity may\nstill exist in the ROI definition, and we have addressed this point as a potential limitation in\nthe manuscript.\np. 17 (Discussion) “Third, the finger and wrist ROIs were defined using phase-sensitive\ntraveling-wave tactile stimulation and further refined based on actual task data.\nTherefore, the ROIs are not entirely independent, raising the possibility of circular\nreasoning due to activity-dependent ROI definition. However, we believe this concern\nis minimal, as analyses based on anatomically defined ROIs (Fig. 3) yielded results\nsimilar to those obtained with functionally defined ROIs (Figs. 4–5). ”\n2) Regarding the second point, we fully agree with the reviewer that even with spin-echo (SE)\nBOLD at 7 T—which reduces sensitivity to large draining veins—laminar fMRI remains\nsusceptible to residual vascular contributions, hemodynamic spread, and partial-volume\neffects. These factors, particularly prominent near the pial surface, necessitate caution in\ninterpreting layer-specific effects.\nAccordingly, we have revised the manuscript to avoid overstatements such as “complete\nsuppression” or “exclusively superficial” activation. Instead, we now describe our results\nusing more nuanced language (e.g., “predominantly superficial” or “broadly suppressed\nacross layers”) and explicitly acknowledge the methodological limitations of laminar fMRI in\nboth the Discussion and Limitations sections.\np. 17 (Discussion) “Second, our spatial resolution imposes inherent limitations. We\nused a 0.8 mm isotropic voxel size—typical for layer-specific fMRI (Han et al., 2021,\n2022; Kok et al., 2016; Lawrence, Norris, et al., 2019)—but insufficient to cleanly\nseparate signals from the three cortical layers, given the ~2 mm thickness of human\nS1. As shown in Fig. 2g, our middle-layer ROI spans both layer 4 (true middle) and\nlayer 5. Because layer 4 is thinner than a single 0.8 mm voxel, partial volume effects\nlikely introduced layer 5 contributions into the “middle”-layer signals. Moreover, the\npoint spread function (PSF) further blurs signals across layers (Fukuda et al., 2021;\nKim & Ogawa, 2012; Logothetis, 2008; Logothetis et al., 2001; Logothetis & Wandell,\n2004; Poplawsky et al., 2019), and variability in neurovascular coupling adds additional\ncomplexity (Buxton et al., 2004; Heeger & Ress, 2002; Kim & Ogawa, 2012;\nLogothetis, 2008). Achieving higher spatial resolution with advanced imaging\ntechnologies will be critical for more precise layer-specific mapping in humans.”\nR3-5. (5) The paper reports “complete suppression” to zero in certain wrist ROI plots (Figure 3),\nbut Figure 2 sometimes shows negative BOLD in nearby wrist areas. Clarification on whether\nthe signal dips below baseline or remains at baseline across the entire wrist region would be\nbeneficial to reconcile these displays.\nResponse: We appreciate the reviewer’s careful observation.\nAs noted by the reviewer, a negative change was observed in Column 3 during attention\nstimulation (new Fig. 3c and Supplementary Fig. 4c). To further examine the variability of\nattention-induced responses in the wrist ROI, we now present individual subject data points in\nthe new Fig. 3f and Fig. 4f, allowing for visualization of inter-subject differences. Although the\nobserved variability may partly reflect the low sensitivity inherent to spin-echo BOLD fMRI,\nit does not exclude the possibility of genuine negative responses (see averaged time course, Fig.\n4d). The slight discrepancy between the two analyses arises from differences in the ROI\ndefinition methods used in each figure. This point is now mentioned in potential limitations as\np. 17 (Discussion) “Fourth, attention induced a negative change in Column 3 (Fig. 3c\nand Supplementary Fig. 4c), whereas the wrist ROI showed near-zero but not\nnegative BOLD responses in Figs. 4 and 5. This discrepancy likely stems from\ndifferences in the methods used to define the ROIs. Future studies are warranted to\nelucidate the origin of these negative BOLD responses.”.\nR3-6. (6) The drop in psychophysical performance on the 8-way wrist location discrimination\ntask is dramatic, nearing chance level. This indeed underscores the potency of attentional\ngating. The authors might briefly discuss how a simpler task (e.g., a two-location discrimination)\nmight reveal partial interference rather than near-complete impairment, highlighting the interplay\nbetween task difficulty and attentional resources.\nResponse: We appreciate the reviewer’s insightful comment regarding the dramatic drop in\npsychophysical performance on the 8-way wrist location discrimination task and its implications\nfor attentional gating. Indeed, the near-chance performance highlights the strong effect of\nattentional modulation, suggesting that attentional resources are heavily allocated to the finger\ntask at the expense of wrist-based discrimination.\nWe briefly discussed this point in the revised manuscript (p. 14 and p. 17).\np. 14 (Results) “The similar probabilities between correct and incorrect perception\nsuggest that attentional resources were almost entirely allocated to the finger task,\nleaving insufficient capacity to process task-irrelevant input.”\np. 17 (Discussion) “Sixth, in our behavioral attention studies focused on the fingers,\naccuracy in discriminating among eight wrist locations was near chance, likely due to\nthe task’s high difficulty. Simpler distractor paradigms—such as a two-location wrist\ntask—may help disentangle attention effects from task difficulty.”\nR3-7. (7) Discussion of Theoretical Implications: The authors note that attention bypasses the\nthalamocortical (middle-layer) inputs and instead amplifies superficial layers. This has direct\nrelevance for models of top-down attentional control, which often posit that feedback targets\nsupragranular layers. Expanding the discussion to connect these layer-specific findings more\nexplicitly to current theories of attention (e.g., gating vs. normalization) would strengthen the\nconceptual impact.\nResponse: We appreciate the reviewer’s suggestion to expand our discussion on the\ntheoretical implications of our layer-specific findings in relation to current models of attentional\ncontrol. Indeed, our results demonstrate that attention bypasses thalamocortical (middle-layer)\ninputs and instead amplifies activity in superficial layers, aligning with theoretical frameworks\nsuggesting that top-down feedback primarily targets supragranular layers.\nWe agree that this observation is highly relevant to attentional gating theories, which propose\nthat attention selectively enhances relevant inputs while suppressing irrelevant ones, thereby\ncontrolling the flow of information across cortical circuits. Such gating models emphasize the\nrole of supragranular layers in mediating top-down influences, consistent with our finding of\nenhanced superficial-layer activity. In contrast, normalization models of attention (e.g., Reynolds\n& Heeger, 2009) frame attentional modulation as divisive gain control within neural populations.\nOur data—showing amplification in superficial layers without corresponding modulation in\nthalamic-recipient middle layers—favor a cortical gating mechanism over a purely normalization-\nbased account, while still leaving open the possibility that both processes contribute under\ndifferent conditions.\np. 16 “With this methodological advantage, our results reveal how attention modulates\nneural responses in the sensory cortex. Elevated superficial-layer activity during\nattention likely reflects enhanced encoding of behaviorally relevant input, consistent\nwith prior laminar fMRI findings (Lawrence, Formisano, et al., 2019; Liu et al., 2021;\nMuckli et al., 2015). In contrast, suppression in the deep layer was observed. In\nnonhuman primates, attention reduces alpha-band modulation in deep layers (Buffalo\net al., 2011). Although direct comparison between BOLD responses and\nneurophysiological alpha-band modulation is challenging, both measures reflect local\nneuronal activity, providing converging evidence for layer-specific attentional effects.”\nThis pattern—superficial amplification with deep suppression—aligns with attentional gating\nframeworks, consistent with the reviewer’s suggestion.\nMinor Comments\nR3-8. (1) Presenting per-subject effect sizes or explicitly stating how many subjects individually\nreplicate the key patterns would help confirm that the group-level findings are robust.\nResponse: We thank the reviewer for this important suggestion. To address this point, we\nquantified the number of individual participants who exhibited effects in the expected direction\nwithin the finger ROI, where tactile attention was directed. These per-subject consistency results\nhave been added to the revised Results section (p. 10) for Experiment 1 and to the Fig. 5\ncaption for Experiment 2, thereby strengthening the robustness of our laminar findings.\nExperiment 1 (Results, p. 10) “Directing attention to the fingers led to a marked\nincrease in superficial-layer BOLD signals within the finger ROI (t(15) = 4.76, p <\n0.001, d = 1.19; 93.8% of participants) and a decrease in deep-layer BOLD signals\n(t(15) = –3.82, p = 0.002, d = –0.95; 75.0%) (Figs. 4c,e). In contrast, middle-layer\nsignals did not change significantly, despite a small, non-significant reduction (t(15) = –\n1.43, p = 0.17, d = –0.36; 68.8%), suggesting that thalamic input was not modulated by\nattention (Figs. 4c,e).”\nExperiment 2 (Fig. 5 caption p. 13) “Paired t-tests in the finger ROI revealed increased\nsignals in the superficial layer (t(8) = 3.710, p = 0.006, d = 1.237; 88.9% of\nparticipants), no significant change in the middle layer (p = 0.906; 55.6%), and\nsuppression in the deep layer (t(8) = –2.793, p = 0.023, d = –0.931; 77.8%). In the\nwrist ROI, all layers were significantly suppressed (all p < 0.015; all participants).”\nR3-9. (2) Fig. 2C: why do you think column 5 is modulated almost as much as column 2 by\nattention? That seems unexpected.\nResponse: Thank you for pointing this out. We observed that when the pain stimulus was\napplied to the wrist while attention was directed toward finger tactile stimulation, activation in the\nwrist region shifted further into the proximal area. This suggests a complex interaction between\nattentional focus and nociceptive processing. Further studies will be needed to investigate this\neffect in greater detail and determine whether similar shifts occur under different stimulus\nintensities or attentional conditions. This point is now noted in the caption of Supplementary\nFigure 5, which includes the following statement:\n“It should be noted that attention induced significant responses in Column 5, which was\nunexpected. This finding suggests a more complex interaction between attentional\nfocus and nociceptive processing than previously assumed.”\nR3-10. (3) Although dividing the cortex into eight equal depths is a common approach, the\nthickness of layer IV can vary slightly across S1 subregions. A more precise approach might\nincorporate the known laminar thickness ratios in S1 or individual cytoarchitecture data.\nResponse: We appreciate the reviewer’s suggestion regarding laminar thickness ratios in S1.\nWhile we acknowledge that layer IV thickness can vary across S1 subregions, our approach—\ndividing the cortex into eight equidistant depth bins within the cortical thickness—is a widely\naccepted and practical method for layer-fMRI analyses. Although not ideal, this approach allows\nconsistent sampling across individuals despite anatomical variability in cortical folding and\nthickness, and was therefore retained.\nLaminar groups (1–2 = superficial, 4–5 = middle, 7–8 = deep) were defined using equidistant\nbinning. To validate this scheme, we examined quantitative T1 (qT1) profiles and their second\nderivatives, which revealed an inflection point around bin 4—consistent with the location of\npresumed layer IV. This finding supports the validity of our middle-layer definition and indicates\nthat the equidistant grouping provides a reasonable approximation of underlying cortical\narchitecture (see Fig. 2c,d and also see the figure below). While we agree that incorporating\ncytoarchitectonic priors would further improve precision, individual histological data are not yet\navailable for in vivo human subjects at this resolution. We have clarified these points in the\nrevised manuscript.\nFig. 2c-d: c Functional ROIs were segmented along the cortical depth axis into 8 equidistant\nbins using anatomical boundaries derived from GE/SE BOLD contrast. d Second derivatives of\nquantitative T (qT ) profiles across cortical depth were used to assign laminar groups:\n1 1\nsuperficial (Bins 1–2), middle (Bins 4–5), and deep (Bins 7–8), corresponding to classical\ncortical layers (see Supplementary Fig. 3). The peak of the qT second derivative profile\n1\nindicates the location of layer 4 (Doehler et al., 2023). In our layer definition, layer 1 was not\nseparately specified due to its low neuronal density and was included in the superficial layer.\np.17 (Discussion) “We used a 0.8 mm isotropic voxel size—typical for layer-specific\nfMRI (Han et al., 2021, 2022; Kok et al., 2016; Lawrence, Norris, et al., 2019)—but\ninsufficient to cleanly separate signals from the three cortical layers, given the ~2 mm\nthickness of human S1. As shown in Fig. 2g, our middle-layer ROI spans both layer 4\n(true middle) and layer 5. Because layer 4 is thinner than a single 0.8 mm voxel, partial\nvolume effects likely introduced layer 5 contributions into the “middle”-layer signals.\nMoreover, the point spread function (PSF) further blurs signals across layers (Fukuda\net al., 2021; Kim & Ogawa, 2012; Logothetis, 2008; Logothetis et al., 2001; Logothetis\n& Wandell, 2004; Poplawsky et al., 2019), and variability in neurovascular coupling\nadds additional complexity (Buxton et al., 2004; Heeger & Ress, 2002; Kim & Ogawa,\n2012; Logothetis, 2008). Achieving higher spatial resolution with advanced imaging\ntechnologies will be critical for more precise layer-specific mapping in humans.”\nR3-11. (4) On line 250, “superficial” is spelled as “superfical.” A quick search for similar minor\ntypos might be useful.\nResponse: Thank you for catching this typo. We have corrected it.\nOverall, these results are a strong contribution to our understanding of layer-specific attentional\nmodulation in the somatosensory cortex.\nResponse: Thank you for your supportive review.\nReferences\nBuffalo, E. A., Fries, P., Landman, R., Buschman, T. J., & Desimone, R. (2011). Laminar\ndifferences in gamma and alpha coherence in the ventral stream. Proc Natl Acad Sci U\nS A, 108(27), 11262-11267. https://doi.org/10.1073/pnas.1011284108\nBuschman, T. J., & Miller, E. K. (2007). Top-down versus bottom-up control of attention in the\nprefrontal and posterior parietal cortices. Science, 315(5820), 1860-1862.\nhttps://doi.org/10.1126/science.1138071\nBuxton, R. B., Uludag, K., Dubowitz, D. J., & Liu, T. T. (2004). Modeling the hemodynamic\nresponse to brain activation. Neuroimage, 23 Suppl 1, S220-233.\nhttps://doi.org/10.1016/j.neuroimage.2004.07.013\nDinse, J., Hartwich, N., Waehnert, M. D., Tardif, C. 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Selective attention gates visual processing in the extrastriate\ncortex. Science, 229(4715), 782-784. https://doi.org/10.1126/science.4023713\nMuckli, L., De Martino, F., Vizioli, L., Petro, L. S., Smith, F. W., Ugurbil, K., Goebel, R., &\nYacoub, E.\n(2015). Contextual Feedback to Superficial Layers of V1. Curr Biol, 25(20),\n2690-2695. https://doi.org/10.1016/j.cub.2015.08.057\nPoplawsky, A. J., Fukuda, M., & Kim, S. G. (2019). Foundations of layer-specific fMRI and\ninvestigations of neurophysiological activity in the laminarized neocortex and olfactory\nbulb of animal models. Neuroimage, 199, 718-729.\nhttps://doi.org/10.1016/j.neuroimage.2017.05.023\nReynolds, J. H., & Chelazzi, L. (2004). Attentional modulation of visual processing. Annu Rev\nNeurosci, 27, 611-647. https://doi.org/10.1146/annurev.neuro.26.041002.131039\nMs. No.: NCOMMS-24-86161-T\nWe thank the editors and reviewers for their thoughtful and constructive feedback. We have carefully\nrevised the manuscript to address all remaining concerns. Below, we provide point-by-point responses\nand indicate where corresponding revisions were made in the manuscript.\nReviewer #1\n“The authors have made substantial revisions, which are successful to mitigate the issues I raised in\nmy first round review.”\nResponse: We thank the reviewer for their positive assessment.\nReviewer #2\n“I thank the authors for substantially revising significant parts of the manuscript in order to address my\nraised concerns. This improved the quality of the manuscript.\nA few points remain:”\nResponse: We thank Reviewer 2 for their careful reading and thoughtful suggestions. Below, we\nreproduce each comment in italics and provide our responses, followed by the exact revised text\ninserted into the manuscript.\nR2-1. “1. I thank the authors for reformulating parts of their introduction in order to avoid confusion and\nmisunderstanding. However, the sentence ‘To address this gap, we hypothesized that attention would\nmodulate neural responses differently in attended and unattended regions, with each cortical layer\nexhibiting a distinct pattern of modulation rather than a uniform change across layers’ is a bit confusing\nbecause the modulatory factor of attention is repeated. Please formulate here more clearly such as\n‘attentional enhancement would represent with a different layer profile compared to attention-related\nsuppression’ or similar. It should also be noted in the introduction already that it were always the fingers\nthat were attended (and the wrist being suppressed) already giving a hint to the reader that this is also\nabout somatotopic mapping of more than the fingers alone.”\nResponse: We appreciate this insightful suggestion. We revised the sentence to avoid repetition of the\nword “attention,” and we clarified the somatotopic structure of the paradigm by explicitly noting that the\nfingers were always attended while the wrist served as the unattended distractor.\np. 3. “Therefore, we hypothesized that attention-related suppression would exhibit a laminar\nprofile different from that of attentional enhancement, reflecting distinct layer-specific\ninfluences in attended versus unattended regions.\nTo test our hypothesis, we investigated layer-specific attentional modulation in the primary\nsomatosensory cortex (S1) of 17 human participants using microvascular-specific spin-echo\nBOLD fMRI at 7 T. In our paradigm, attention was consistently directed to the fingers (target\nsite), while the wrist (distractor site) was concurrently stimulated but unattended, enabling us\nto investigate somatotopically organized modulation of attended versus unattended\nrepresentations within S1”\nR2-2. “2. The heading ‘Attention suppresses BOLD responses in task-irrelevant brain regions’ is too\nunspecific as only another area in S1 (that is not often exposed to discriminative touch) was measured;\nthis would have to be formulated more carefully, for example by saying ‘Attentional modulation\ndifferently affects the targeted hand area compared to the non-targeted wrist area’ or similar.”\nResponse: We agree and revised the subsection heading to more accurately reflect the somatotopic\nspecificity of the comparison.\np. 8. “Attentional modulation differently affects the targeted finger area and the non-targeted\nwrist area in S1”\nR2-3. “3. This study needs a spelling and grammar check by a native speaker, there are many errors\nand unclear formulations, such as ‘We found that passive stimulation elicited higher BOLD signals in\nthe middle (layers 4/5) and deep layers (layer 6) of both finger and wrist S1 compared with the\nsuperficial layer (layers 2/3).’ - it should read ‘representation of finger and wrist in S1’ or similar. Please\nlet this manuscript being checked thoroughly by a native speaker.”\nResponse: We thank the reviewer for this comment. We have revised the sentence mentioned by the\nreviewer and additionally performed a full, line-by-line language revision across the entire manuscript to\nensure grammatical clarity and more fluent scientific writing.\np.4. “We found that passive stimulation elicited greater BOLD signals in the middle (layers 4/5)\nand deep layers (layer 6) than in the superficial layer (layers 2/3) across both the finger and\nwrist representations in S1. When attention is directed to the fingers, however,”"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have made substantial revisions, which are successful to mitigate the issues I raised in my first round review.", "reviewer_2": "I thank the authors for substantially revising significant parts of the manuscript in order to address my raised concerns. This improved the quality of the manuscript.\nA few points remain:\n- I thank the authors for reformulating parts of their introduction in order to avoid confusion and misunderstanding. However, the sentence \"To address this gap, we hypothesized that attention would modulate neural responses differently in attended and unattended regions, with each cortical layer exhibiting a distinct pattern of modulation rather than a uniform change across layers.\" is a bit confusing because the modulatory factor of attention is repeated. Please formulate here more clearly such as \"attentional enhancement would represent with a different layer profile compared to attention-related suppression\" or similar. It should also be noted in the introduction already that it were always the fingers that were attended (and the wrist being suppressed) already giving a hint to the reader that this is also about somatotopic mapping of more than the fingers alone.\n- The heading \"Attention suppresses BOLD responses in task-irrelevant brain regions\" is too unspecific as only another area in S1 (that is not often exposed to discriminative touch) was measured; this would have to be formulated more carefully, for example by saying \"Attentional modulation differently affects the targeted hand area compared to the non-targeted wrist area\" or similar\n- This study needs a spelling and grammar check by a native speaker, there are many errors and unclear formulations, such as \"We found that passive stimulation elicited higher BOLD signals in the middle (layers 4/5) and deep layers (layer 6) of both finger and wrist S1 compared with the superficial layer (layers 2/3).\" - it should read \"representation of finger and wrist in S1\" or similar. Please let this manuscript being checked thoroughly by a native speaker."}, "author_response": "Ms. No.: NCOMMS-24-86161-T\nWe thank the editors and reviewers for their thoughtful and constructive feedback. We have carefully\nrevised the manuscript to address all remaining concerns. Below, we provide point-by-point responses\nand indicate where corresponding revisions were made in the manuscript.\nReviewer #1\n“The authors have made substantial revisions, which are successful to mitigate the issues I raised in\nmy first round review.”\nResponse: We thank the reviewer for their positive assessment.\nReviewer #2\n“I thank the authors for substantially revising significant parts of the manuscript in order to address my\nraised concerns. This improved the quality of the manuscript.\nA few points remain:”\nResponse: We thank Reviewer 2 for their careful reading and thoughtful suggestions. Below, we\nreproduce each comment in italics and provide our responses, followed by the exact revised text\ninserted into the manuscript.\nR2-1. “1. I thank the authors for reformulating parts of their introduction in order to avoid confusion and\nmisunderstanding. However, the sentence ‘To address this gap, we hypothesized that attention would\nmodulate neural responses differently in attended and unattended regions, with each cortical layer\nexhibiting a distinct pattern of modulation rather than a uniform change across layers’ is a bit confusing\nbecause the modulatory factor of attention is repeated. Please formulate here more clearly such as\n‘attentional enhancement would represent with a different layer profile compared to attention-related\nsuppression’ or similar. It should also be noted in the introduction already that it were always the fingers\nthat were attended (and the wrist being suppressed) already giving a hint to the reader that this is also\nabout somatotopic mapping of more than the fingers alone.”\nResponse: We appreciate this insightful suggestion. We revised the sentence to avoid repetition of the\nword “attention,” and we clarified the somatotopic structure of the paradigm by explicitly noting that the\nfingers were always attended while the wrist served as the unattended distractor.\np. 3. “Therefore, we hypothesized that attention-related suppression would exhibit a laminar\nprofile different from that of attentional enhancement, reflecting distinct layer-specific\ninfluences in attended versus unattended regions.\nTo test our hypothesis, we investigated layer-specific attentional modulation in the primary\nsomatosensory cortex (S1) of 17 human participants using microvascular-specific spin-echo\nBOLD fMRI at 7 T. In our paradigm, attention was consistently directed to the fingers (target\nsite), while the wrist (distractor site) was concurrently stimulated but unattended, enabling us\nto investigate somatotopically organized modulation of attended versus unattended\nrepresentations within S1”\nR2-2. “2. The heading ‘Attention suppresses BOLD responses in task-irrelevant brain regions’ is too\nunspecific as only another area in S1 (that is not often exposed to discriminative touch) was measured;\nthis would have to be formulated more carefully, for example by saying ‘Attentional modulation\ndifferently affects the targeted hand area compared to the non-targeted wrist area’ or similar.”\nResponse: We agree and revised the subsection heading to more accurately reflect the somatotopic\nspecificity of the comparison.\np. 8. “Attentional modulation differently affects the targeted finger area and the non-targeted\nwrist area in S1”\nR2-3. “3. This study needs a spelling and grammar check by a native speaker, there are many errors\nand unclear formulations, such as ‘We found that passive stimulation elicited higher BOLD signals in\nthe middle (layers 4/5) and deep layers (layer 6) of both finger and wrist S1 compared with the\nsuperficial layer (layers 2/3).’ - it should read ‘representation of finger and wrist in S1’ or similar. Please\nlet this manuscript being checked thoroughly by a native speaker.”\nResponse: We thank the reviewer for this comment. We have revised the sentence mentioned by the\nreviewer and additionally performed a full, line-by-line language revision across the entire manuscript to\nensure grammatical clarity and more fluent scientific writing.\np.4. “We found that passive stimulation elicited greater BOLD signals in the middle (layers 4/5)\nand deep layers (layer 6) than in the superficial layer (layers 2/3) across both the finger and\nwrist representations in S1. When attention is directed to the fingers, however,”"}, {"round": 3, "reviewer_comments": {"reviewer_2": "I thank the authors for incorporating my suggested changes."}, "author_response": ""}]

Decision letter