Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities

Lonike K Faes; Federico De Martino; Laurentius (Renzo) Huber

doi:10.1371/journal.pone.0280855

. 2023 Feb 9;18(2):e0280855. doi: 10.1371/journal.pone.0280855

Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities

Lonike K Faes ^1,^*, Federico De Martino ^1,^2,^‡, Laurentius (Renzo) Huber ^1,^‡

Editor: Jyrki Ahveninen³

PMCID: PMC9910709 PMID: 36758009

Abstract

The development of ultra high field fMRI signal readout strategies and contrasts has led to the possibility of imaging the human brain in vivo and non-invasively at increasingly higher spatial resolutions of cortical layers and columns. One emergent layer-fMRI acquisition method with increasing popularity is the cerebral blood volume sensitive sequence named vascular space occupancy (VASO). This approach has been shown to be mostly sensitive to locally-specific changes of laminar microvasculature, without unwanted biases of trans-laminar draining veins. Until now, however, VASO has not been applied in the technically challenging cortical area of the auditory cortex. Here, we describe the main challenges we encountered when developing a VASO protocol for auditory neuroscientific applications and the solutions we have adopted. With the resulting protocol, we present preliminary results of laminar responses to sounds and as a proof of concept for future investigations, we map the topographic representation of frequency preference (tonotopy) in the auditory cortex.

Introduction

Ultra high field (UHF) magnetic resonance imaging allows the acquisition of functional data with increased sensitivity [1]. This increased sensitivity can be used to breach into the mesoscopic scale in humans [2–9], and the layered functional responses can be leveraged as a proxy for cortical architecture [10].

Gradient-echo blood oxygenation level dependent (GE-BOLD) functional magnetic resonance imaging (fMRI) is the conventional approach to collect submillimeter data, due to its relatively high signal-to-noise ratio (SNR) [11]. However, T2*-weighted images collected at 7 Tesla (and higher fields) still contain contributions of both macro- and micro-extravasculature compartments [11,12]. The macrovascular contribution to GE-BOLD originates from both pial vessels and draining vessels that penetrate the cortex orthogonally [13]. This results in two effects: the signal in superficial cortical depths is larger and the layer dependent spatial specificity is reduced as activation is drained away from the original locus of neural activity [14–17]. Regardless, the increased sensitivity, coverage and temporal efficiency of GE-BOLD makes it the most common approach for laminar fMRI (for a recent review see e.g. [18]), also when considering auditory studies [19–23].

While draining effects in GE-BOLD can be reduced with modeling and analyses approaches (see e.g. [24,25]), alternative acquisitions have been proposed to minimize the contribution of macrovasculature. For example, spin-echo (SE) echo planar imaging (EPI) has been used to collect T2-weighted functional data [7,8]. To retain T2-weighted specificity, these applications used segmented EPI acquisitions, while non segmented acquisitions introduce unwanted T2* contributions [26]. 3D gradient-echo and spin-echo (3D-GRASE) [27,28], has also been used to investigate human laminar and columnar function in both visual and auditory cortices [2,9,29–31]. However, the limited field of view (FOV) of early 3D-GRASE approaches has allowed only the investigation of small portions of cortex and, in auditory studies in particular, often in a single hemisphere ([2,30]; for a review see [32]). More recent 3D-GRASE advancements can mitigate FOV constraints [33]. Furthermore, a large spectrum of alternative approaches is currently under development to optimize the sensitivity and specificity of layer-fMRI experiments [34–44].

Cerebral blood volume (CBV) based imaging is one of the approaches to collect functional data with high spatial specificity. The most commonly used approach to measure functional CBV changes is vascular space occupancy (VASO) [39,45,46]. Previous studies have acquired CBV functional responses alongside conventional BOLD [47–50]. A concomitant acquisition approach of BOLD and VASO has the potential to combine their complementary aspects and facilitate a more comprehensive understanding of the physiology underlying laminar activation changes. Furthermore, a combined acquisition of BOLD and VASO allows researchers to benefit from cumulative quality metrics of both methods, e.g. a high detection sensitivity (in BOLD compared to VASO) and a high localization specificity (in VASO compared to BOLD). VASO has been used to investigate laminar functional responses in visual [51], motor [3,52], somatosensory [53] and prefrontal [54] cortices.

To date, VASO has not been successfully applied to investigate layer dependent functional responses in the human auditory cortex. Despite its lower power compared to BOLD [55], the use of VASO has proven useful outside of auditory cortical areas [3,51–54] and this warrants the need for developing an effective VASO protocol for auditory neuroimaging. Here, we present the results of the exploration of a wide parameter space aimed at mitigating methodological and physiological challenges encountered when using VASO to image the auditory cortex at submillimeter resolution. We evaluated functional images collected at 7T using concurrent measurements of GE-BOLD and VASO. Specifically, we investigated the difference between a 2D- and a 3D-EPI readout and their stability across several participants. The resulting 3D-EPI protocol was then also tested for stability of responses within an extensive session with one volunteer. Lastly, we present preliminary results for laminar profiles of VASO data, and the use of VASO for auditory neuroscience applications by characterizing VASO acquisitions of cortical sound frequency preference (i.e. tonotopic maps).

Materials and methods

Ethics

The scanning procedures were approved by the Ethics Review Committee for Psychology and Neuroscience (ERCPN) at Maastricht University, following the principles expressed in the Declaration of Helsinki. Informed consent was obtained from all participants.

Participants

Participants were healthy volunteers with normal hearing and no history of hearing or neurological disorders. Participants were excluded if they had any standard MRI contraindications (e.g. any metal implants etc.).

Eleven healthy volunteers participated in three separate studies. In study 1 (N = 4), we addressed challenges we encountered in the development of our VASO protocol. In study 2 (N = 5), we evaluated the stability of the protocol with 2D and 3D readouts in four volunteers. Additionally, in one volunteer we investigated the stability of responses with the 3D-EPI. In study 3 (N = 2), we applied the resulting 3D protocol for tonotopic mapping as a proof of principle.

Scanner

Scanning was performed on a MAGNETOM “classic” 7T scanner (Siemens Healthineers) hosted by Scannexus (Maastricht) equipped with a 32-channel Nova Head Coil (Nova Medical, Wilmington, MA, USA). Sequences were implemented using the vendor provided IDEA environment (VB17A-UHF). We used an in-house developed 3^rd order B₀-shim system (Scannexus) that depends on the vendor provided "3rdOrder ShimSet" feature.

Auditory stimulation

Sounds were presented to participants in the MRI scanner using MRI compatible ear buds of Sensimetrics Corporation (www.sens.com).

Slice-saturation slab-inversion VASO

We used a slice-saturation slab-inversion VASO (SS-SI-VASO—[46]) acquisition with either a 3D-EPI [56] or 2D-EPI readout [57]. VASO uses an inversion recovery pulse to effectively null the contribution from the blood magnetization [39,45]. For all of the tested protocols, the inversion delay (i.e. the dead time between the inversion pulse and the VASO signal readout module) was chosen to have the readout block roughly centered around the expected blood nulling time. In SS-SI-VASO, VASO and BOLD images are acquired in an interleaved fashion, which allows for a straightforward combination of the two datasets.

Reconstruction

The reconstruction of the data was conducted as described in previous studies for SMS-VASO [57] and 3D-EPI VASO [58], respectively. In short, the vendor’s in-plane GRAPPA [59] reconstruction algorithms were applied using a 3 × 2 (read direction x phase direction) kernel. Partial Fourier reconstruction [60] was done with the projection onto convex sets (POCS) algorithm [61] with 8 iterations. Finally, the complex coil images were combined using the vendor’s implementation of sum-of-squares.

SMS unaliasing was performed on-line on the scanner using a combination of the vendor software and the SMS reconstruction as distributed with the MGH blipped-CAIPI C2P (http://www.nmr.mgh.harvard.edu/software/c2p/sms). SMS signals were first un-aliased with an implementation of SplitSlice-GRAPPA with LeakBlock [62] and a 3 × 3 SliceGRAPPA kernel before entering in-plane reconstruction as described above.

The 3D-EPI reconstruction was based on a previous 3D-EPI implementation [56] using a combination of standard scanner software and a vendor-provided work-in-progress implementation of GRAPPA CAIPIRINHA (Siemens software identifier: IcePAT WIP 571).

Study 1: Protocol development in pilot experiments

We aimed at implementing and testing a VASO protocol for the auditory cortex that can mitigate a series of methodological challenges. The purpose of study 1 was to explore the protocol parameter space of previously described 2D and 3D VASO sequences with respect to temporal signal-to-noise ratio (tSNR) and minimal artifact level in auditory cortical regions. The protocol resulting from this study will then be subject to quantitative investigations and validations in a subsequent study (study 2). Often, results of these pilot experiments are not reported in manuscripts. However, after encountering several artifacts, we decided to describe the rationale behind the steps we have taken in our mitigation strategies. This might benefit other researchers that encounter similar artifacts and can potentially use the same (or similar strategies) to mitigate their own artifacts.

While developing a protocol we encountered several artifacts of a physiological nature and had to consider different readout strategies. To mitigate physiological noise artifacts, across several sessions, we explored the effect of using a phase-skipped adiabatic inversion pulse with B1-independent partial inversion (based on shapes of a TR-FOCI pulse—[64]) and looked at several readout times (700 ms and 1235 ms) and strategies (2D using multiband and different GRAPPA reference acquisition schemes, and 3D acquisitions).

During the development stages, we tested the protocols for activation elicited by sound presentation. We presented pure tones (800 ms) within the inherent 900 ms dead time of the SS-SI-VASO sequence. The choice of this approach stems from the fact that in auditory fMRI studies, sounds are generally presented inside the silent gap between volume acquisitions (sparse design) [63]. However, this approach resulted in weak auditory evoked fMRI responses in the VASO (and simultaneously acquired BOLD) data. A possible reason for this reduced effectiveness of the sparse design is the relatively short duration of the gap and sound (900 ms and 800 ms respectively) compared to the noise of the BOLD/VASO acquisition time (~2.5 seconds depending on the protocol) [64]. Following this rationale, in studies 2 and 3 we continuously presented auditory stimuli (e.g. the auditory stimulation overlapped with the scanner noise) and played them loud enough to be audible compared to the scanner noise. This approach resulted in larger evoked responses (see results study 2 and 3).

Study 2: 2D versus 3D comparison

With the resulting protocol of study 1 (see results for an explanation of why specific parameters were selected), we collected two datasets of both BOLD and VASO (0.9 mm isotropic and 12 slices), one with a 2D readout (TR = 1833.5 ms; TE = 21 ms; flip angle = 70°; GRAPPA = 3; reference scan = segmented) and one with a 3D readout (TR = 1609 ms; TE = 22 ms; variable flip angles between 16°(first segment of readout block) and 30° (last segment of readout block); GRAPPA = 3; reference scan = FLASH [65]) in four volunteers.

Participants were asked to passively listen to a series of sounds consisting of multi-frequency sweeps. Stimuli were presented following a blocked design with 20 volumes of sound stimulation followed by 20 volumes of rest. Each run consisted of thirteen stimulation blocks lasting about 11 minutes. A recording of the stimuli is available here: https://layerfmri.page.link/aud_stim. In each participant we collected two runs (S1 and S4 Figs) or 3 runs (S2 and S3 Figs) with a 2D readout and a 3D readout.

To further test the reliability of the 3D acquisition protocol (see results for why we opted for a 3D readout), we scanned one additional volunteer in an extensive session in which we collected 12 runs with the same block design explained above to measure stability of responses across independent splits of the data. We opted for scanning this volunteer in one long session, instead of scanning the same participant twice in two shorter sessions, because alignment across sessions with our current experimental setup is challenging due to the small coverage.

Study 3: Tonotopy

Simultaneous BOLD and VASO data were collected using the 3D sequence (after finalizing study 2) described above (0.9 mm isotropic; 12 slices; TR = 1609 ms; TE = 22 ms; GRAPPA = 3; reference scan = FLASH), variable flip angles between 16° (first segment of readout block) and 30° (last segment of readout block). In addition, we collected anatomical data (with optimized gray/white matter contrast) using MP2RAGE (TR = 6000 ms, TE = 2.39 ms, TI1/TI2 = 800/2750 ms, FA1/FA2 = 4°/5°, GRAPPA = 3 and 256 slices) [66] at a resolution of 0.7 mm isotropic.

Participants passively listened to tones varying slightly around 7 different center frequencies (130, 246.2, 466.3, 883.2, 1673, 3168 and 6000 Hz). Center frequencies were presented following a blocked design. Stimulation blocks (23 seconds) contained forty-six tones (500 ms each) varying 0.2 octaves around the center frequency. Each stimulation block was followed by a rest period (23 seconds). Functional runs consisted of fourteen stimulation blocks with a total duration of approximately 11 minutes per run. In one participant we collected four runs and in a second participant five runs. Before each tonotopic experiment tones were equalized for perceived loudness.

Functional data analysis

Preprocessing in all studies was done in the same way. All functional images were sorted by contrast, resulting in a (BOLD-contaminated) VASO and a BOLD time series. The first three volumes of each time series were removed to account for the steady state. Each time series was motion corrected using SPM12 (Functional Imaging Laboratory, University College London, UK). The estimation of the motion parameters was restricted to a mask of the temporal lobe. Next, the time series were temporally upsampled by a factor of 2. This resulted in an interpolated TR of 1.15 seconds in the 3D readout and about 1.3 seconds in the 2D readout. As in previous studies, we corrected for the BOLD contamination in the VASO data using the open software suite LayNii (version 2.2.0) [67].

In study 2, activation maps were created using AFNI (3dDeconvolve—version 21.2.04 and Matlab). We used a General Linear Model and normalized the time course to z-scores (when comparing 2D versus 3D) and to percent signal change (to test the reliability of the 3D protocol). The resulting F-maps portray normalized differences between periods of auditory stimulation and rest. Two-dimensional ROI’s were drawn manually in spatially upsampled EPI space and were divided in 7 equivolume layers [68] with which layer plots were created using LayNii.

In study 3, after preprocessing, functional data were first aligned to the anatomical data using Brainvoyager (version 22.2—Brain Innovation, Maastricht, The Netherlands). Anatomical images were processed in BrainVoyager (BV). We used an automatic segmentation pipeline of BV with which we created a mid gray matter surface. For statistical analysis we used a General Linear Model with one predictor for each center frequency. Time series were normalized to percent signal change prior to statistical analysis. Tonotopic maps were created using best frequency mapping [69] and were interpolated across depths and projected on the mid gray matter surface.

Results

Study 1: Protocol development

In study 1, we aimed to mitigate several methodological and physiological challenges that we encountered while exploring the use of different parameters. In the following section, we will discuss the rationale behind the use of specific parameters and how they have helped reduce the artifacts in our data.

First, compared to other cortical areas, the auditory cortex has an exceptionally short arterial arrival time of approximately 0.5–0.8s (see reference [70], in particular the results reported in its Fig 7B). This is approximately 1-2s earlier than the primary visual cortex. Such short arterial arrival times can result in the unwanted inflow of fresh (uninverted) blood during the VASO readout. The inflow effects result in very bright vessels in both the BOLD and the VASO data. However, the ratio between the background signal and the signal from the vessels is higher in the BOLD data compared to the VASO data. This results in lower relative contrast between tissue types in the VASO data compared to the BOLD data (Fig 1A). To mitigate this challenge, we explored the usage of a phase-skipped adiabatic inversion pulse with B1-independent partial inversion (based on shapes of a TR-FOCI pulse—[71]) that minimized these contaminants at the cost of SNR. Reducing the inversion efficiency by means of the phase skipped adiabatic inversion pulse can reduce the blood nulling time so that it is shorter than the arterial arrival time, mitigating inflow artifacts. Depending on the TR, the inversion efficiency and excitation flip angles that are used, the tissue signal can be reduced by about 30%.

Fig 1 — (A) Inflow effects were found in both GE-BOLD and VASO in temporal regions. However, the VASO signal seemed to be more affected by the inflow of not-nulled blood. (B) Cardiac pulsation effects reduced image contrast due to long 3D-EPI readouts. In the functional images, the contrast in our region of interest seemed to be particularly affected. Additional ICA analysis (left bottom) showed the main components around Heschl’s gyrus. (C) In the presence of physiological noise, there is a tradeoff in the amount of ghosts and the tSNR when evaluating different GRAPPA auto calibration signal (ACS) acquisitions. The first row contains the percentage of background signal compared to signal in the auditory cortex. The second row gives an impression of the ghost level and the third row gives an illustration of the tSNR. These tests were conducted for the protocol with 2D-SMS readouts. (D) 2D-SMS VASO resulted in T1-weighted slice-wise intensity differences that were most visible in the middle of the slab. The two axial slices show the intensity differences between two “consecutive” slices (with the same signal intensity scaling). (E) Schematic depiction of one TR of the final SS-SI-VASO sequence. An inaudible phase-skipped adiabatic pulse is used in the inherent silent gap of this sequence. This is followed by the acquisition of a volume of VASO and a volume of BOLD.

Second, we explored the effect of readout time (and its relationship to the cardiac cycle) on VASO data in the temporal cortex. Initially, we used a readout time of about 1235 ms (in one participant), which is longer than the cardiac cycle. Such a long readout time resulted in loss of contrast around Heschl’s gyrus (HG). Therefore, we opted for using a readout time shorter than the cardiac cycle (700 ms) in subsequent volunteers in all three studies, to mitigate this artifact. An additional independent component analysis (FSL MELODIC, 30 components) on the VASO time series (Fig 1B) collected with a readout longer than the cardiac cycle showed that the component with the largest variance was a typical vascular artifact centered on the large vessels in the auditory cortex. These two results exemplify the effect of physiological noise originating from the cardiac cycle after which we decided to shorten the readout time.

These physiological noise artifacts additionally made us consider different readout strategies. High-resolution VASO is commonly used in combination with a 3D signal readout (e.g. 3D-EPI). However, since the auditory cortex, especially the medial portion of HG, is located right next to large feeding arteries, the partitioned 3D-EPI approach can result in higher susceptibility to physiological noise. To compare it to a 2D-EPI readout (study 2), the optimization of parameters specific to the 2D readout was required. In particular, the location of the auditory cortex requires large in-plane imaging FOVs, resulting in a large matrix size, and low bandwidth in the phase encoding direction for submillimeter acquisition protocols. The correspondingly long readout duration makes the acquisition protocol more susceptible to Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) [59] artifacts. To find an effective protocol we compared the tSNR over 40 volumes resulting from an SS-SI-VASO acquisition with 2D readout at 0.9 mm isotropic employing different GRAPPA references: single-shot, segmented and FLEET [16] with three different flip angles (2, 30 and 90 degrees) (Fig 1C). We calculated the ghost level by taking the ratio of intensity values of a region outside of the brain and one region centered on the auditory cortex. We expressed this as a percentage value that can be found in the first row of Fig 1C. The FLEET ACS approach exhibited worse ghosting compared to single-shot and segmented in our experimental setup. Therefore we decided to refrain from using FLEET in the following experiments. Since the echo time and the phase evolution of single-shot GRAPPA reference lines are approximately three times longer/stronger for single-shot ACS compared to the segmented approach, we expected that using a segmented approach would mitigate intermittent ghosting across the time series. This is expected to result in stable tSNR values across protocols and participants. Thus, we decided to use the segmented approach for the remainder of the study as this is expected to be the best compromise between artifact level and tSNR in temporal areas.

Finally, we considered the use of 2D simultaneous multi slice (SMS—also known as multiband) [72,73] EPI readouts in VASO in order to ‘freeze’ cardiac-induced vessel pulsation artifacts. The use of SMS results in different effective inversion times across slices and in our investigations this translated to sudden jumps of signal intensity in the VASO data (Fig 1D). As this complicates the performance of retrospective motion correction and results in spatially heterogeneous tSNR we did not use SMS in the comparison in study 2.

A schematic depiction of the final protocol is illustrated in Fig 1E (and a complete parameter list is made available here: https://github.com/layerfMRI/Sequence_Github/tree/master/Auditory). In particular, we used an (inherently) inaudible adiabatic inversion pulse with a 30 degree phase skip, a readout time of 700 ms (which is shorter than the cardiac cycle) and a 70 degree reset-pulse [74] at the end of each acquisition of a VASO-BOLD pair. The purpose of the reset pulse was to effectively saturate stationary M_z-magnetization of cerebrospinal fluid (CSF) and gray matter (GM) before the application of the consecutive inversion pulse. At the blood nulling time in the subsequent TR, this results in a positive M_z-magnetization of CSF with a magnitude smaller than GM. Having a positive CSF M_z-magnetization in SS-SI-VASO is in contrast to the negative CSF magnetization in the traditional VASO approach. The suppressed CSF signal (see contrast in Fig 1E) mitigates potential biases of dynamic CSF volume changes that have previously been reported to impose a source of bias for VASO applications in the auditory cortex [75]. The effective temporal resolution was 2.3 seconds.

Study 2: 3D-EPI versus 2D-EPI

The presentation of auditory stimuli resulted in reliable responses in the bilateral auditory cortex for VASO (except for participant 2 in the 2D readout acquisition—see Fig 2A) and for BOLD (S1 Fig). For VASO, the 3D readout resulted in higher z-scores in bilateral auditory cortex, while this benefit was not directly visible in the BOLD data at these resolutions (S1 Fig). Even though the activation scores in VASO are relatively weak, they are within the expected regime of sub-millimeter protocols [58]. These results are somewhat consistent with previous 2D vs. 3D comparisons of VASO in the primary motor cortex [76]. Here we extend these findings for the physiological-noise constrained primary auditory cortex.

Average time courses of active voxels calculated in percent signal change are plotted in Fig 2B against our experimental paradigm (yellow bars). These time courses exemplify the negative percent signal change of VASO following auditory stimulation.

Since the VASO signal is a composite signal from blood-nulled and not-nulled (BOLD) images, its detection sensitivity is indirectly dependent on the noise level of BOLD too. We believe the result that VASO benefits from 3D-EPI more strongly than BOLD, is thus mostly driven by the relatively lower tSNR of blood-nulled images compared to non-nulled BOLD images.

Cortical depth-dependent responses

Fig 3 shows the layer profiles obtained in 2D regions of interest (ROIs; covering Heschl’s Gyrus [HG]). In VASO, the signal had a tendency to increase within gray matter. However, the cortical depth dependent signal also showed a reduction at the pial surface (CSF/GM in Figs 3 and 4), indicating its reduced sensitivity to macrovasculature. Separate analysis on the BOLD data using the same ROI definition, showed a monotonic increase in functional activation towards the cortical surface (S2 Fig) and no decrease on the pial surface. Similar results were obtained when defining ROIs based on functional activation (response to sounds) in the medial anterior part of HG on the left hemisphere (Fig 4 for VASO and S3 Fig for BOLD). Both the activation maps and the laminar analysis indicate that a 3D readout is beneficial for collecting VASO data (higher z-scores and increased reliability).

Fig 4 — The ROI was drawn on an axial slice as shown in Fig 3A and was based on functional activation. (A) The fMRI layer-dependent changes across depths for each participant. (B) Average z-scored layer-dependent activation changes across participants.

Reliability of responses

To measure the reliability of auditory responses in our 3D acquisition protocol, we collected 12 runs with the 3D acquisition protocol in one volunteer. By analyzing two independent splits of the data (6 runs each) we evaluated the stability of the responses (Fig 5). Whole brain GLM’s were computed for each split independently. In Fig 5A, we show the F-maps thresholded at p<0.05 uncorrected (and a minimum cluster size of 10 voxels) for both splits to illustrate the spatial reliability of activation maps obtained across splits. The time course of active voxels (in percent signal change, Fig 5B) demonstrates the expected negative responses upon stimulation. Compared to Fig 2B, time courses in Fig 5B are less noisy, illustrating the benefit of averaging over more runs.

To investigate the reliability of laminar responses, we also present the laminar activation plots for the two independent data splits (Fig 5C) extracted from an ROI (drawn based on functional activation on an axial slice).

Study 3: Tonotopic maps

In study 3, the presentation of pure tones resulted in responses in the bilateral auditory cortex for both BOLD and VASO. Mid-gray matter anatomical surfaces were created from a WM/GM segmentation and inflated (Fig 6) to visualize HG (outlined in black) and the planum temporale/polare. The analysis was confined to voxels showing both a positive signal change for BOLD (at a threshold of p<0.05 uncorrected) and a negative VASO signal change. Tonotopic maps (Fig 6) show the expected high-low-high frequency gradient along HG in VASO (see e.g. [77] for a comprehensive discussion on the expected topography of tonotopic maps). The same gradient is present in the BOLD data (S4 Fig) as shown in previous studies using GE-BOLD [77].

Fig 6 — Inflated mid-gray matter surface meshes were created to visualize tonotopic maps coming from the VASO data. Red boxes outline the part of the mesh from which the tonotopic data was sampled. Heschl’s gyrus is outlined in black. On the right of each inflated surface, tonotopic maps are displayed for both hemispheres of the two participants. The expected tonotopic high-low-high frequency preference gradient is respected.

Discussion

Despite the fact that layer-fMRI VASO can provide valuable information in sub-millimeter and layer-fMRI applications [3,51–54], it has not been successfully applied in the human auditory cortex. This is in contrast to GE-BOLD, which has been used to image laminar and columnar responses in the temporal lobe [2,19–21,23]. In this study, we aimed to develop a VASO protocol for laminar fMRI investigations of the auditory cortices by mitigating methodological and physiological challenges.

Starting from a protocol that was previously successfully used [51], the location and vascular physiology of the auditory cortex resulted in several artifacts. This required us to reconsider acquisition parameters and approaches that have helped to improve layer-fMRI applications but whose proof of generalizability across brain areas is still limited. The need to account for the specific vascular physiology of the auditory cortex, resulted in the use of a readout time shorter than the cardiac cycle and optimization of the inversion pulse (Fig 1). To evaluate possible physiological contamination when using the standard 3D readout in VASO, we considered the use of a 2D readout. To develop an efficient 2D protocol for VASO, we combined techniques (such as FLEET for GRAPPA reconstruction and SMS acquisition) which are often used (in auditory neuroscience studies) when collecting submillimeter GE-BOLD data. To our surprise, while these approaches showed the expected utility in the GE-BOLD data, they did not result in the expected increase in sensitivity when considering the VASO data (Fig 1). Study 1 resulted in two protocols (2D and 3D readout) for VASO fMRI in the temporal lobe.

A few words are warranted on the possible influence of CSF volume changes. Assuming the skull as a container of a fixed volume, increase of one compartment, e.g., CBV, must be compensated by volume decrease in another compartment, e.g., GM or CSF. VASO signal change is based on the idea that CBV increase is compensated by GM volume decrease only. However, depending on the brain region stimulated, a small dynamic change in CSF volume in the range of 0.5% (for neurally-induced tasks) to 10% (for systemic gas-breathing induced hypercapnia) has been experimentally observed [75,78]. Such stimulus-dependent variations in CSF volume could cause an incorrect calculation of CBV changes from the VASO signal change [75,78,79]. In contrast with to CSF-nulled ACDC VASO [80] and VASO FLAIR [78] techniques, the SS-SI VASO signal changes in this study (with the employment of a 70 deg spin-reset pulse) reflect a positive CSF z-magnetization. Thus, the CBV change presented here reflects both components of the CBV change—the CBV increase that is compensated by a GM volume decrease as well as the CBV increase that is compensated by CSF volume decrease—with similar weighting.

The comparison of the 2D and 3D protocols resulting from study 1 (study 2) showed an increased stability and SNR when using the 3D-EPI readout, despite its susceptibility to physiological noise. Note that the benefit for the 3D readout was particularly visible in the VASO time series (and not the BOLD data). It has been previously shown that the superiority of 2D-SMS or 3D-EPI readout strategies at 7T in conventional BOLD is highly dependent on and specific to the acquisition and analysis details including the TR, acceleration factor, resolution, physiological noise correction and number of slices [76,81–84]. The BOLD results presented here are in agreement with this literature (see S1–S3 Figs).

We examined laminar profiles of activation elicited by the sounds presented in study 2. Similarly to previous studies investigating the specificity of laminar functional responses in auditory cortex [30] (using 3D-GRASE), we did not observe a clear peak in functional response in middle cortical depths in the 2D versus 3D comparison. Firstly, this could be due to limited power for the data reported in Figs 3 and 4 (2 or 3 runs depending on the volunteer). A larger data sample (6 runs) resulted in reproducible (across independent splits) laminar profiles with a more pronounced peak in middle gray matter (Fig 5C). Nevertheless the variability in laminar profiles we observed in study 2 could also be caused by the nature of the stimulation and analysis steps. As the auditory stimuli in study 2 were composed of complex dynamic sounds presented for about 20 seconds, it is unclear what the expected neural laminar profile would be in absence of any control for attention or another task. Second, we defined regions of interest for the laminar profiles based on macro-anatomy (anterior HG) or activation. The effect that this has on sampling the laminar activation profiles in auditory regions, whose cytoarchitecture overlaps only partly with macro-anatomical features (see e.g. [85]), is beyond the scope of this paper but could be an interesting venue for future investigations. What we did observe was that while the signal in the upper layers has the tendency to be larger than in middle and deeper layers, the signal decreases again at the pial surfaces. This is expected due to VASO’s insensitivity to large pial veins. As expected, GE-BOLD data resulted in an increased response towards superficial layers (S2 and S3 Figs) without a reduction on the pial surface. This profile is characteristic of GE-BOLD submillimeter acquisitions and is resulting from vascular draining and the contribution of large vessels on the cortical surface. If confirmed when analyzing a larger sample, a more controlled stimulus design, and within a more extended portion of temporal areas, the fact that vein-free VASO signal changes [49] within GM decrease as a function of cortical depth, could be interpreted as a validation of previous BOLD results (e.g. indicating that the signal trends visible in the BOLD signal in temporal areas cannot be solely explained by draining vein effects alone). It is important to note that while we here demonstrate that VASO auditory responses are not affected by draining and large vascular contributions on the cortical surface, we do not imply that in presence of careful controls [4,5,30] or with the use of modeling techniques [24,25] GE-BOLD data cannot be used to investigate laminar cortical processing.

To assess the reliability of functional responses collected with our 3D VASO protocol, we measured functional responses in an extended session in one additional volunteer. The resulting data were split into two independent sessions (6 runs each). F-maps, time courses and laminar profiles obtained from the two independent splits indicate that the acquisition (with our 3D VASO protocol) of functional responses in auditory cortical regions is spatially reliable and results in stable temporal responses (with an expected negative response upon stimulation) and reproducible laminar profiles.

With the resulting 3D protocol, as a first proof of concept of the usability of VASO fMRI for the investigation of cortical processing in the temporal lobe, we presented results from a tonotopic experiment. Neurons throughout the auditory pathway display preferential tuning to the sound frequency [86] and using fMRI the topographic arrangement of frequency preference (tonotopy) can be mapped in single individuals [19,69,77,87]. Tonotopy shows a typical topography with a low frequency region residing primarily on the HG and regions preferring high frequency bordering it both posterior medially and anterior laterally (for a description see [77]). This characteristic topography makes tonotopy a possible benchmark for auditory functional acquisitions. The large scale tonotopic gradient covering the superior temporal plane was visible in the VASO data. This initial promising result opens the venue to further investigations on the specificity of the VASO signal across cortical depths [30].

Despite the shown applicability of VASO for auditory fMRI, we deem it necessary to outline some limitations (many not specific to auditory studies) that require consideration when setting up a neuroscientific (laminar) fMRI study. While VASO is more sensitive to microvascular CBV increases, it is also characterized by a reduced detection sensitivity (as indicated by generally lower z-scores in Figs 2–4 than in S1–S3 Figs). To compensate for this effect a typical approach is to average across runs. As a result, extending averaging across sessions would require careful consideration of approaches for inter session alignment (and placement) of the relatively small slab (12 slices in our case). Future investigations may have to address issues related to detection sensitivity and its dependence on experimental design and sound presentation schemes. In addition, when using VASO, functional runs are typically acquired with an identical design as averaging is performed on the raw time series before BOLD correction to limit noise amplification. This calls for careful balancing of conditions within functional runs. To increase sensitivity we also employed long stimulation periods (block design). Evaluating the sensitivity of event-related functional responses with VASO [88] would increase its usability (e.g. to prediction-error related responses in typical oddball designs). Moreover, alternative approaches for increasing sensitivity such as denoising (e.g. NORDIC—[89]), should be considered in future investigations. Finally, while to compensate for physiological noise effects we decided to use a readout train shorter than the cardiac cycle, in the future it may be interesting to consider higher order physiological noise correction methods in k-space.

We believe that the significance of this work is multi-fold. In study 1, we describe the approach we followed to tackle the main challenges encountered when using VASO for submillimeter auditory investigations. Following these steps may prove useful in case the resulting protocol we describe here would not generalize outside of the specific applications (as well as coils and imaging resolutions) we present. Nevertheless, we believe our results represent a first necessary step towards generalization as the protocol resulting from study 2 is made available for the user base of application-focused neuroscientists for testing in a wider range of application settings. The sequence binaries and the importable protocols are publicly available via ‘SIEMENS’ sequence ‘app-store’ on TEAMPLAY for any users of a ‘classical’ MAGNETOM 7T, which is the most widely used 7T scanner version around the world today. Users of other scanner versions and vendors can benefit from this protocol-development study as they can re-implement the acquisition approaches as described in study 1.

A first step towards a generally applicable VASO protocol for auditory neuroscientific studies is furthermore relevant as VASO may allow application studies that are not straightforwardly addressable with the vein-bias of conventional GE-BOLD, such as single-task condition experiments. In such experiments, utilizing VASO protocols (such as the one we developed) alongside with BOLD can be useful to augment the understanding of the neurovascular origin of the fMRI signals. Other example studies, where acquiring VASO and GE-BOLD simultaneously may be beneficial, might be related to research questions of altered vascular baseline physiology (e.g. in studies about pharmacological interventions, aging and surgical interventions). Furthermore, we think that the concomitantly acquired VASO and BOLD data can be useful to calibrate existing layer-fMRI BOLD models [14,24,25,90–93] and extend their applicability across brain areas. For example, future GE-BOLD studies that want to apply venous-deconvolution model-inversion and may not find an increased response in the middle layers, can use the data we present here to increase the confidence in their results. The imaging protocol developed here may have implications beyond the auditory cortex. The auditory cortex is not the only brain area challenged by proximal macro-vessels with substantial physiological noise. There are many other brain areas in which sub-millimeter VASO was not successfully applied until now, for example, hippocampus, insular cortex, claustrum, entorhinal cortex, and thalamic nuclei. Researchers investigating areas with similar artifacts could test whether following similar strategies might benefit them in these challenging areas. Finally, the main aim of this work was to provide the auditory research community with a viable VASO protocol for laminar fMRI studies, which is now available for testing by the community.

To conclude, our results demonstrate that, when using carefully chosen parameters, VASO can be used to investigate cortical responses in the bilateral temporal cortex. While VASO has a lower detection threshold compared to GE-BOLD, it is believed to be dominated by microvascular CBV increase close to the site of neural activity changes. A combined acquisition approach of BOLD and VASO, as described here, may allow benefitting from the quality features of each method.

Supporting information

S1 Fig. Activation maps of BOLD.

Z-scored activation maps overlayed on distortion corrected mean GE-BOLD EPI images (per participant and readout). The color map was chosen to match the VASO data displayed in Fig 2A.

(TIF)

Click here for additional data file.^{(1.6MB, tif)}

S2 Fig. Z-scored cortical depth-dependent activation changes for the 2D- and 3D-EPI BOLD data.

(A) Functional layer-dependent changes across depths for each participant. The BOLD data is coming from the same anatomically-based ROI that was used to calculate the layer-dependent VASO changes in Fig 3. (B) Average z-scored layer-dependent activation changes across participants.

(TIF)

Click here for additional data file.^{(712.5KB, tif)}

S3 Fig. Z-scored cortical depth-dependent activation changes for the 2D- and 3D-EPI BOLD data.

(A) Functional layer-dependent changes across depths for each participant. The BOLD data is coming from the same functional activation-based ROI that was used to calculate the layer-dependent VASO changes in Fig 4, drawn on an axial slice as shown in Fig 3. (B) Average z-scored layer-dependent activation changes across participants.

(TIF)

Click here for additional data file.^{(524.3KB, tif)}

S4 Fig. Tonotopic maps BOLD.

Inflated mid-gray matter surface meshes were created to visualize tonotopic maps created with the BOLD data. On the right of each inflated surface, tonotopic maps are displayed for both hemispheres of the two participants. Heschl’s Gyrus is outlined in black. A tonotopic high-low-high frequency preference gradient is visible in the data.

(TIF)

Click here for additional data file.^{(988.2KB, tif)}

Acknowledgments

The sequence used here is based on sequence code kindly written and provided by Benedikt Poser. We thank Steve Cauley at MGH for sharing the interface of their image reconstruction for use with the SMS acquisition. We thank Miriam Heynckes for advice on the use of auditory stimulation setups. We thank Omer Faruk Gulban for early contributions to this work. We thank Chris Wiggins for providing the 3rd order shimming tools used here. Scanning was supported by FPN (Faculty of Psychology and Neuroscience) via the MBIC grant scheme.

Diversity statement

Recent work in several fields of science has identified a bias in citation practices such that papers from women and other minorities are under-cited relative to the number of such papers in the field [94]. In the human layer-fMRI community the average of the gender citation bias is 84% male, 15% female (https://layerfmri.com/papers/). We obtained the gender of the first author of each reference. By this measure (and excluding self-citations to all authors of our current paper), our references contain 78% male first and 22% female first. This method is limited in that: (i) names, pronouns, and social media profiles used to construct the databases may not, in every case, be indicative of gender identity, and (ii) it cannot account for intersex, non-binary, or transgender people. We look forward to future work that could help us to better understand how to support equitable practices in science.

Data Availability

The anonymized raw data of this study is available and can be downloaded from https://doi.org/10.34894/WCUTUL. The scripts that were used in the analysis can be found on https://github.com/layerfMRI/repository.

Funding Statement

This study was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 101001270) to FDM, authors LKF and FDM were supported by the National Institute for Health grant (RF1MH116978-01), and the Netherlands Organisation for Scientific Research (NWO), NWO VENI grant (016.Veni.198.032) to LH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0280855.r001

Decision Letter 0

Jyrki Ahveninen

29 Sep 2022

PONE-D-22-23894Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilitiesPLOS ONE

Dear Dr. Faes,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Both reviewers felt that the study is very interesting and that it makes a potentially very important contribution. There were, however, also certain concerns, particularly in the comments of Reviewer 1, which would need to be addressed. Some of these concerns might be addressable by textual modifications, by toning down the assertions, more frank discussion of the relative weaknessess, such at the weakness of effect sizes that Reviewer 1 mentions. However, please also consider the suggestions for providing additional data/analysis results to address these concerns.

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Reviewer #1: Partly

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: ** What are the main claims of the paper and how significant are they for the discipline?

The paper develops a protocol for imaging of cerebral blood volume (CBV) weighted signals in the auditory cortex at 7T. This had not previously been attempted because of technical challenges that are specific to the auditory cortex, such as short arterial transit times and stronger sensitivity to cardiac pulsation.

The developed protocol attempts to overcome these limitations.

The work is significant since there are currently no other non-invasive technique capable of imaging CBVw signals in the auditory cortex. This advancement is important not only for the cognitive neuroscientific applications that the authors mention, but also to study the VASO signal contrast, which has implications for fMRI in general.

** Are the claims properly placed in the context of the previous literature? Have the authors treated the literature fairly?

Yes.

** Do the data and analyses fully support the claims? If not, what other evidence is required?

Partially. The protocol optimization section contains insightful details about crafting protocols specific for the auditory cortex, but it is debatable whether all of those optimatizations would generalize for other coils or other imaging resolutions - especially the highly specific reconstruction optimization. The claim that the protocol is ready to be used for the user base of application-focused neuroscientists is also not debatable, since the protocol hasn't actually been tested in any other settings/centers (at least according to the paper).

Also regarding VASO protocol optimization, the low auditory activation found after optimization is atributed to a sparse experimental task design, but readers may ask themselves whether that is truly the case, or if there is still something else going on with the sequence.

Beyond the sequence, and with focus on the auditory cortex, Scouten 2007 noted that VASO in the auditory cortex may have a large CSF signal contribution, though granted in their data they don't account for everything else that the current manuscript is accounting for (such as the short transit time), but CSF contamination could be a concern for readers (AFAIK the cited reference regarding magnetisation reset in VASO does not comment on fully adressing dynamic partial CSF). Perhaps another sentence or two explaining how magnetisation reset accounts for dynamic partial CSF would be beneficial.

Regarding the 2D vs 3D study, and the tonotopic mapping, the low number of subjects and the extremely low sensitivity of VASO (as seen by the low z-scores) are a potential concern. Even with BOLD studies in the visual/motor cortex one would be wary of making any conclusions from data with such small dataset / low z-scores.

But even assuming that the z-scores are reliable, the results on tonotopic mapping and cortical depth dependency would also vastly benefit from more data and/or analysis: the cortical depth profiles differ substantially between participants even after pooling data across layers, and the tonotopic maps from both subjects and both hemispheres are all different - no clear pattern can be seen in the VASO data. Attempts at tonotopic mapping would also imply that VASO has sufficient signal at or close to the voxel level to extract detailed information, but that cannot be concluded based on the results shown, and so it is hard to known whether the results correspond to inherent subject variability, or indeed something is still off with the sequence / analysis / experimental design.

What other evidence is required?

More control experiments would be extremely helpful. Simpler experiments to validate VASO, even if the conclusion is that VASO has low sensitivity, as mentioned in the discussion. More sanity checks that the signal follows a reproducible pattern are important.

Some potential ideas:

- Compare tonotopic maps from neighboring cortical depths. There should be some similarity.

- Show time-series of VASO and BOLD timeseries against the experimental paradigm and % signal changes. Are % signal changes negative upon activation?

- Compare tonotopic maps and cortical depth profiles against maps generated from resting-state data (perhaps even from experiment 2?).

- Show that cortical depth dependent profiles and tonotopic maps are reproducible in the same participant in two different sessions if data is or can be made available.

- monoaural stimulation? -> compare right and left hemisphere profiles. Some studies (see Gutschalk 2014) suggest that slow amplitude modulated noise should elicit mostly contralateral activation. Task could be used as a benchmark for task CNR. Auditory cortex is not my area of expertise, so maybe there are even simpler tasks that would do the job.

Of course, the suggestion is not to do all of the above, but to implement some form of sanity check that shows that the signals are reliable and could be interpreted as robust CBVw signals.

** PLOS ONE encourages authors to publish detailed protocols and algorithms as supporting information online. Do any particular methods used in the manuscript warrant such treatment? If a protocol is already provided, for example for a randomized controlled trial, are there any important deviations from it? If so, have the authors explained adequately why the deviations occurred?

The authors share all necessary information and are open about both the data and processing tools. No clear deviations.

** If the paper is considered unsuitable for publication in its present form, does the study itself show sufficient potential that the authors should be encouraged to resubmit a revised version?

Absolutely.

** Are original data deposited in appropriate repositories and accession/version numbers provided for genes, proteins, mutants, diseases, etc.?

Yes.

** Does the study conform to any relevant guidelines such as CONSORT, MIAME, QUORUM, STROBE, and the Fort Lauderdale agreement?

Yes.

** Are details of the methodology sufficient to allow the experiments to be reproduced?

Yes.

** Is any software created by the authors freely available?

Yes.

** Is the manuscript well organized and written clearly enough to be accessible to non-specialists?

Yes.

** Is it your opinion that this manuscript contains an NIH-defined experiment of Dual Use concern?

No.

Reviewer #2: In this manuscript, the authors presented a technical study to optimize the VASO fMRI pulse sequence for laminar fMRI in the human auditory cortex on 7T. The authors did a great job describing technical details to address particular challenges in this brain region and discussing potential advantages and limitations. I also like the open access to the imaging protocol which can be used and disseminated easily in the research community. The manuscript is well written and it is certainly of interest to readers. I have the following minor suggestions for the authors to consider:

1. The presentation of study 1 is a little strange to me. Normally, the methods and results should be in respective sections. As it is written now, the results of study 1 are also presented in the Methods section. While I understand that this is mainly because results from study 1 are needed to determine the parameters in studies 2 and 3, I still think that it is better to separate the methods and results for each study. For instance, one can say in methods for study 2 that the parameters used in this study are based on our results from study 1, see Results, etc. Alternatively, the authors can completely remove study 1, but instead just describe the optimized sequence and parameters. But I feel the later would reduce the technical importance of this work.

2. “When collecting simultaneous VASO and BOLD, these effects were more pronounced in the VASO data (Fig 1A).” Could the authors explain why the images in Fig. 1A support this statement. I cannot find it in the text or in the caption.

3. “Readout time longer than the cardiac cycle resulted in loss of contrast around Heschl’s gyrus (HG) and in typical vascular artifacts in components extracted with independent component analysis (ICA) from VASO time series (figure 1B)” Could the authors provide more details, for instance, what readout durations did they test, in how many subjects, other parameters, how was the ICA performed, how are the ICA components selected, why did Fig. 1B support this statement, etc. Again, I cannot find these information in the text or in the caption. I understand that some of these can go into the supplement. But I feel that these information is critical for the readers to fully appreciate this study.

4. “The segmented reference resulted in the best compromise between artifact level and tSNR in temporal areas.” I’d appreciate some quantitative results here if the authors choose to keep study 1 as one of the sub-studies.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2023 Feb 9;18(2):e0280855. doi: 10.1371/journal.pone.0280855.r002

Author response to Decision Letter 0

18 Nov 2022

We have uploaded a separate 'Response to Reviewers' file which contains a response to the reviewers and the editor. We copy here the text as requested by the system, but please note that figures are not uploaded here so please refer to the separate file.

Comments of Editor (Ahveninen)

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

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All the requirements have been fulfilled.

2. Please upload a copy of Figure 7, to which you refer in your text on page 7. If the figure is no longer to be included as part of the submission please remove all reference to it within the text.

We thank the editor for this comment, but we believe that this stems from a misunderstanding. The original manuscript included five original figures, which were referred to as Fig 1-5. In page 7 of the original version of the manuscript (now page 11), we refer to figure 7 of an already published manuscript from authors Mildner et al., 2014. To avoid confusion, we have now rephrased the way we refer to these results:

“see reference [63], in particular the results reported in its Fig 7B”

We hope that in this way we have clarified that this figure has to be found in a separate paper.

This requirement has been fulfilled.

Reviewer 1

Reviewer #1: ** What are the main claims of the paper and how significant are they for the discipline?

The developed protocol attempts to overcome these limitations.

We thank the reviewer for her/his comment in their appreciation of this work. In what follows we reply to each of the issues raised point by point.

** Do the data and analyses fully support the claims? If not, what other evidence is required?

We thank the reviewer for the comment, which we agree with. In the revised version of the manuscript we have toned down the claims of generalizability of the developed protocol and have clarified what the main contribution of this work is - that is, the investigation of the challenges that developing a VASO protocol for the auditory has, and the strategies that we have followed to overcome them.

In the abstract we have removed the claim of developing an optimized protocol for auditory neuroscientific applications, but clearly state that:

“We describe the main challenges we encountered when developing a VASO protocol for auditory neuroscientific applications and the mitigation strategies we have adopted.”

In the introduction (page 4) we emphasize the exploratory aim of the study by tackling challenges we encountered and state that:

“Here, we present the results of the exploration of a wide parameter space aimed at mitigating methodological and physiological challenges encountered when using VASO to image the auditory cortex at submillimeter resolution.”

In the methods and results section we have rephrased any reference to an optimal protocol and in the discussion (page 18-19) we clearly state that:

“In this study, we aimed to develop a VASO protocol for laminar fMRI investigations of the auditory cortices by mitigating methodological and physiological challenges.”

We agree with the referee that all of these protocol optimizations might not generalize across a wider range of brain areas and hardware configurations. In the revised version of the manuscript we tone down our claims. Therefore, in the discussion (page 23) we toned down the significance of our work by stating that:

“We believe that the significance of this work is multi-fold. In study 1, we describe the approach we followed to tackle the main challenges encountered when using VASO for submillimeter auditory investigations. Following these steps may prove useful in case the resulting protocol we describe here would not generalize outside of the specific applications (as well as coils and imaging resolutions) we present. Nevertheless, we believe our results represent a first necessary step towards generalization as the protocol resulting from study 2 is made available for the user base of application-focused neuroscientists for testing in a wider range of application settings. The sequence binaries and the importable protocols are publicly available via ‘SIEMENS’ sequence ‘app-store’ on TEAMPLAY for any users of a ‘classical’ MAGNETOM 7T, which is the most widely used 7T scanner version around the world today. Users of other scanner versions and vendors can benefit from this protocol-development study as they can re-implement the acquisition approaches as described in study 1.”

We have removed any reference to an optimal protocol and specified that we do not suggest that this protocol can be used immediately in other challenging areas without any testing or changes. But we would like to note that the steps we have undertaken might help other researchers in their endeavors to image challenging areas. The discussion section of the manuscript contains the following vague outlook (without strong claims).

“The imaging protocol developed here may have implications beyond the auditory cortex. The auditory cortex is not the only brain area challenged by proximal macro-vessels with substantial physiological noise. There are many other brain areas in which sub-millimeter VASO was not successfully applied until now, for example, hippocampus, insular cortex, claustrum, entorhinal cortex, and thalamic nuclei. Researchers investigating areas with similar artifacts could test whether following similar strategies might benefit them in these challenging areas. Finally, the main aim of this work was to provide the auditory research community with a viable VASO protocol for laminar fMRI studies, which is now available for testing by the community.”

We would like to note that the phrasing of the above mentioned paragraphs is not in contrast with the reviewer’s comment. We do not claim that the generalizability is not debatable. We only think that our increased understanding of potential signal artifacts and how to mitigate them may be informative to the process of developing a protocol for other brain areas.

These paragraphs are motivated by feedback that we have gotten from three previous international conferences to abstracts of this work (Benelux ISMRM 2022, ISMRM London 2022, OHBM 2022). Following these comments, other labs have asked our advice when using a similar strategy to set up layer-fMRI protocols for medial-temporal cortex.

We thank the reviewer for the comment which requires some clarification.

In the original manuscript we referred to results obtained with a sparse design at the end of the description of study 1 and then in the discussion. The reason for this is that we thought it necessary to justify our choice to use continuous sound stimulation (study 2 and 3) in long blocks when this is not conventional in auditory fMRI (where sparse designs are commonly employed). When preparing the acquisitions of study 2 and 3, we followed the conventional use of long blocks in VASO studies. In choosing how to present sounds within these long blocks we initially followed a more “auditory conventional” sparse approach (900 ms in a TR of 3.4 seconds [that is a noise period of 2.5 seconds and a silent period of 900 ms in every TR]). These initial attempts, which we do not show, did not result in strong cortical responses. Following our past experience, in which we investigated the interplay between the length of silent gaps and scanner noise in eliciting auditory responses (De Martino et al., 2015), we reasoned that these weak activations could be due to the relatively low level of auditory stimulation compared to scanner noise.

To clarify this we have made several changes to the manuscript. Following the comment of reviewer 2, we decided to put the results of study 1 in the results section. This allowed us to present aur rationale for choosing a continuous stimulation paradigm in the methods section already (now page 8) and remove any reference to this issue from the discussion. We consider it reassuring that with this less conventional sound presentation approach, tonotopic maps resulting from the VASO (Fig 6) and BOLD acquisition (S4 Fig) conform to the expected topography.

We hope these changes have clarified this issue.

For reference see: De Martino F, Moerel M, Ugurbil K, Formisano E, Yacoub E. Less noise, more activation: Multiband acquisition schemes for auditory functional MRI: Multiband Acquisition Schemes for Auditory fMRI. Magn Reson Med 2015;74:462–7. https://doi.org/10.1002/mrm.25408.

We agree with the reviewer that traditional VASO methods can be significantly affected by dynamic CSF redistributions (Scouten 2007; Donahue 2006). We would like to note, however, that this is not the case for SS-SI VASO as it is for traditional VASO. Different from traditional steady-state VASO, in SS-SI VASO the blood nulling time is not based on steady-state blood magnetization, but it is based on once-inverted blood. Thus, in SS-SI VASO, the CSF z-magnetization is not negative (as it was for Scouten, Donnaue and others). In fact, in SS-SI VASO the CSF magnetization can be adjusted by the user to a desired value. Here, we employed an additional spin-reset pulse (Lu, 2008) of 70 deg in SS-SI VASO. This allowed us to maintain the CSF magnetization between the blood nulling and GM-magnetization. This is schematically depicted in the figure below:

Furthermore we would like to note that we used tasks that engage a focal part of the brain (auditory cortex) only. This is different from systemic global tasks (like hypercapnia) used by Scouten and Constable. It is believed that these focal tasks do not affect CSF volume at a measurable level (Huber 2014b).

For more explanations on the different CSF sensitivity of SS-SI VASO compared to traditional VASO see also:

● Empirical evidence for visual tasks in PhD thesis: https://drive.google.com/file/d/1OU5fUJHS87VCQPvVIbNPgVZynJI5wmUb/view?usp=sharing (see section 5.4.3 Changes in CSF volume starting at page 176).

● See discussion section in the original SS-SI VASO paper Huber 2014. See section “Dynamic Changes of CSF Volume” on page 8.

In the revised version of the manuscript, we followed the reviewer's advice and added a few additional sentences that summarize the above explanations.

In the methods (page 14) we clarify that:

“The purpose of the reset pulse was also to effectively saturate stationary Mz-magnetization of cerebrospinal fluid (CSF) and gray matter (GM) before the application of the consecutive inversion pulse. At the blood nulling time in the subsequent TR, this results in a positive Mz-magnetization of CSF with a magnitude smaller than GM. Having a positive CSF Mz-magnetization in SS-SI-VASO is in contrast to the negative CSF magnetization in the traditional VASO approach. The suppressed CSF signal (see contrast in Fig 1E) mitigates potential biases of dynamic CSF volume changes that have previously been reported to impose a source of bias for VASO applications in the auditory cortex [75]. ”

In the discussion on page 19:

“Assuming the skull as a container of a fixed volume, increase of one compartment, e.g., CBV, must be compensated by volume decrease in another compartment, e.g., GM or CSF. VASO signal change is based on the idea that CBV increase is compensated by GM volume decrease only. However, depending on the brain region stimulated, a small dynamic change in CSF volume in the range of 0.5% (for neurally-induced tasks) to 10% (for systemic gas-breathing induced hypercapnia) has been experimentally observed (Scouten 2007; Donahue 2006). Such stimulus-dependent variations in CSF volume could cause an incorrect calculation of CBV changes from the VASO signal change (Scouten 2007; Donahue 2006, Jin 2010). In contrast with to CSF-nulled ACDC VASO (Scouten and Constable 2008) or VASO FLAIR (Donahue et al 2006) techniques, the SS-SI VASO signal changes in this study (with the employment of a 70 deg spin-reset pulse) reflect a positive CSF z-magnetization. Thus, the CBV change presented here reflects both components of the CBV change—the CBV increase that is compensated by a GM volume decrease as well as the CBV increase that is compensated by CSF volume decrease—with similar weighting.”

Since such CSF magnetization manipulations are widely adopted in the VASO community, and since are standardly applied in almost all VASO studies of the last decade, we refrained from including more explanations into the revised manuscript.

References:

● Donahue MJ, Lu H, Jones CK, Edden RAE, Pekar JJ, van Zijl PCM. Theoretical and experimental investigation of the VASO contrast mechanism. Magn Reson Med 2006;56:1261–73. https://doi.org/10.1002/mrm.21072.

● Jin T, Kim SG. Change of the cerebrospinal fluid volume during brain activation investigated by T1ρ-weighted fMRI. NeuroImage. 2010 Jul;51(4):1378–83.

● Huber et al., 2014, MRM “Slab-Selective, BOLD-Corrected VASO at 7 Tesla Provides Measures of Cerebral Blood Volume Reactivity with High Signal-to-Noise Ratio.”

● Huber L, Kennerley AJ, Gauthier CJ, Krieger SN, Maria Guidi DI, Turner R, et al. Cerebral blood volume redistribution during hypercapnia. Imaging Cerebral Physiology: Manipulating Magnetic Resonance Contrast through Respiratory Challenges. Talk presented at Leipzig Symposium 2014b;2:O4 https://doi.org/10.7490/f1000research.1115082.1

● Lu H. Magnetization “reset” for non-steady-state blood spins in Vascular-Space-Occupancy ( VASO ) fMRI. Proceedings of the 16th Annual Meeting ISMRM. 2008;16(1):2008.

● Scouten A, Constable RT. Applications and limitations of whole-brain MAGIC VASO functional imaging. Magn Reson Med 2007;58:306–15. https://doi.org/10.1002/mrm.21273.

What other evidence is required?

We thank the reviewer for the following suggestions and agree that our study could benefit from more reproducibility checks. Therefore, we followed some of the potential ideas expressed below. In particular, we have collected more data aimed at evaluating test-retest reliability. We did this by collecting (in one participant) enough data to compare results across two independent splits. In particular, we collected 12 runs of the 3D acquisition protocol. We divided these in two independent splits of six runs each. Each split thus includes more data than what we originally had in study 2 (three runs) and is more comparable to the length of acquisitions in study 3 (five runs). Yet collecting 6 runs of functional data is within a reasonable time span ~1 hour of scanning.

We used the experimental stimulation paradigm used in study 2, to focus primarily on the replication of activation maps and layer profiles. These new results are presented in the revised manuscript after study 2 (new figure 5).

Below we will discuss the reviewer’s original suggestions and elaborate how we have incorporated these suggestions into the revised manuscript or the reason why we decided not to further investigate a specific suggestion.

Some potential ideas:

- Compare tonotopic maps from neighboring cortical depths. There should be some similarity.

We thank the reviewer for this suggestion. Although there have been a few studies on the existence of frequency preference across cortical depths - columnarity should not be expected throughout the temporal lobe (see e.g. Moerel et al., J Neurosc (2018) and De Martino et al., PNAS (2015)). This may be true only for very limited portions of primary cortical areas. This makes the use of stability of tonotopy across depth not an optimal measure of data quality in our opinion.

We believe that to showcase the reliability of the estimated auditory responses is sufficient to focus on the reproducibility of the cortical activations elicited by the broadband stimuli used in Study 2. The tonotopy data remain an initial showcase of the utility of VASO and more studies will be needed to dive into the information that VASO can provide to the understanding of frequency preference.

- Show time-series of VASO and BOLD timeseries against the experimental paradigm and % signal changes. Are % signal changes negative upon activation?

We have followed this suggestion and now we present time courses for VASO in Fig. 2 and in the new Fig. 5. The time courses are presented in percent signal change, they allow evaluating the stability of the response across presentation blocks (trials) and are as expected negative in response to the stimulation. In figure 5 time courses are presented separately for the two independent splits and together with the F-maps (activation maps) obtained by analyzing the two independent splits. We believe these results highlight the stability of the cortical responses and reproducibility of the effects despite the low percent signal changes (which are expected in VASO).

New figure 2:

- Compare tonotopic maps and cortical depth profiles against maps generated from resting-state data (perhaps even from experiment 2?).

We thank the reviewer for this suggestion. We present improved tonotopic maps in now figure 6 (figure 5 in the previous version). We have applied standard processing steps that we previously did not consider - that is, as we focus on overall topographic responses we have smoothed moderately the maps (see e.g. Moerel et al., 2014). We believe this improves the interpretation of the tonotopic maps compared to expectations set by the literature.

New figure 6:

- Show that cortical depth dependent profiles and tonotopic maps are

reproducible in the same participant in two different sessions if data is or can be made available.

We have followed this suggestion, we provide a proof of reproducibility in two independent splits. As clarified above, we do this on the experimental paradigm of study 2 and for this data we also provide independent estimation of the layer profiles in the two splits of the data (figure 5).

New figure 5:

We thank the reviewer for the suggestion. We believe that if reproducibility was to be assessed the better choice was (as suggested by the reviewer) to acquire the same data twice and compare results. The presentation of time courses (as suggested by the reviewer) in addition gives an idea of the stability of the response. The suggestion to use tasks (monaural stimulation or others) would in our opinion deserve a whole new publication.

Of course, the suggestion is not to do all of the above, but to implement some form of sanity check that shows that the signals are reliable and could be interpreted as robust CBVw signals.

We hope that by presenting time courses and having done a reproducibility study we now present enough evidence of the robustness of the CBVw signal.

Reviewer 2

We thank the reviewer for her/his comment in their appreciation of this work. In what follows we reply to each of the issues raised point by point.

Before addressing all the specific comments, we would like to make one clarification about the nature of study 1. Study 1 is aimed at describing the procedures we followed to mitigate artifacts that we encountered during the development of our protocol. We did not aim to quantify if any of the chosen parameters results in statistically significantly better results compared to others. Furthermore, we did not aim to make ultimate claims about our protocol being superior to other protocols. That is, study 1 is a qualitative description of why and how we chose our protocol parameters to be used for later quantitative assessments of the usability (in study 2 and 3). We think of study 1 as being comparable to the conventional ’pilot scans’, that most neuroscience-focused studies perform in 1 to 3 participants to see if there is anything obviously wrong with the setup that needs rectification. In conventional publications, these kinds of qualitative pilot tests are not shared with the public.

We believe that by presenting the reasoning that we followed to derive an effective protocol will help the community understand the reasoning underlying our choices and (as we clarify) hopefully aid future applications of VASO that may have to follow similar steps. While the data shown in Fig. 1 are qualitative in nature, with questionable generalizability across other study setups, they give the reader an idea about our reasoning of why we focused our quantitative assessment in study 2 on the specific protocols at hand.

We agree with the reviewer and in the revised version, we have changed the structure of the manuscript and have included the results of study 1 in the results and we have taken these results out of the methods section. Additionally, we tried to make the purpose of study 1 clearer in the revised version of the manuscript by changing the description of Study 1 to:

“Study 1: Protocol development in pilot experiments”

We thank the reviewer for this comment and we agree it should be clarified further. Therefore on page (11-12) we put clarify that:

“The inflow effects result in very bright vessels in both the BOLD and the VASO data. However, the ratio between the background signal and the signal from the vessels is higher in the BOLD data compared to the VASO data. This results in lower relative contrast between tissue types in the VASO data compared to the BOLD data (Fig 1A). ”

We thank the reviewer for this comment and agree that some clarification is necessary. We have now included information on which readout times we have tested and added information on the independent component analysis (page 12):

“Second, we explored the effect that the readout time (and its relationship to the cardiac cycle) has on VASO data in the temporal cortex. Initially, we used a readout time of about 1235 ms (one participant), which is longer than the cardiac cycle. Such a long readout time resulted in loss of contrast around Heschl’s gyrus (HG). Therefore, we opted for using a readout time shorter than the cardiac cycle (700 ms) in subsequent volunteers in all three studies, to mitigate this artifact. An additional independent component analysis (FSL MELODIC, 30 components) on the VASO time series (Fig 1B) collected with a readout longer than the cardiac cycle showed that the component with the largest variance was a typical vascular artifact centered on the large vessels in the auditory cortex. These two results exemplify the effect of physiological noise originating from the cardiac cycle after which we took the approach to shorten the readout time. ”

We agree with the reviewer that providing a more quantitative assessment and providing more background of our choice of scan parameters would be helpful.

We focused on a combination of two quality metrics: 1) first and foremost the ghost level, and 2) the expected phase consistency between ACS data and time series data, with its implication on tSNR stability across experiments.

We added a new row in Fig. 1C quantifying the ghost level as the signal ratio between auditory cortex and background. It can be seen that the FLEET ACS approach exhibits worse ghosting values compared to segmented and single-shot. This result made us refrain from using FLEET in the following experiments. Since the echo time and the phase evolution of single-shot GRAPPA reference lines are approximately three times longer/stronger for single-shot ACS compared to the segmented approach, we expected that this would mitigate intermittent ghosting across the time series. This is expected to result in stable tSNR values across protocols and participants. Thus, we decided to use the segmented approach for the remainder of the study.

We now clarify this in the text (page 13):

“The FLEET ACS approach exhibited worse ghosting compared to single-shot and segmented in our experimental setup. Therefore we decided to refrain from using FLEET in the following experiments. Since the echo time and the phase evolution of single-shot GRAPPA reference lines are approximately three times longer/stronger for single-shot ACS compared to the segmented approach, we expected that using a segmented approach would mitigate intermittent ghosting across the time series. This is expected to result in stable tSNR values across protocols and participants. Thus, we decided to use the segmented approach for the remainder of the study as this is expected to be the best compromise between artifact level and tSNR in temporal areas.”.

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PLoS One. doi: 10.1371/journal.pone.0280855.r003

Decision Letter 1

Jyrki Ahveninen

10 Jan 2023

Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities

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PLoS One. doi: 10.1371/journal.pone.0280855.r004

Acceptance letter

Jyrki Ahveninen

27 Jan 2023

PONE-D-22-23894R1

Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities

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Supplementary Materials

S1 Fig. Activation maps of BOLD.

Z-scored activation maps overlayed on distortion corrected mean GE-BOLD EPI images (per participant and readout). The color map was chosen to match the VASO data displayed in Fig 2A.

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S2 Fig. Z-scored cortical depth-dependent activation changes for the 2D- and 3D-EPI BOLD data.

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S3 Fig. Z-scored cortical depth-dependent activation changes for the 2D- and 3D-EPI BOLD data.

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S4 Fig. Tonotopic maps BOLD.

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Data Availability Statement

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PERMALINK

Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities

Lonike K Faes

Federico De Martino

Laurentius (Renzo) Huber

Roles

Abstract

Introduction

Materials and methods

Ethics

Participants

Scanner

Auditory stimulation

Slice-saturation slab-inversion VASO

Reconstruction

Study 1: Protocol development in pilot experiments

Study 2: 2D versus 3D comparison

Study 3: Tonotopy

Functional data analysis

Results

Study 1: Protocol development

Fig 1. Overview of the challenges encountered when acquiring VASO data in the auditory cortex.

Study 2: 3D-EPI versus 2D-EPI

Fig 2. Activation maps and time courses of VASO.

Cortical depth-dependent responses

Fig 3. Z-scored cortical depth-dependent activation changes for the 2D- and 3D-EPI VASO data.

Fig 4. Z-scored cortical depth-dependent activation changes for the 2D- and 3D-EPI VASO data.

Reliability of responses

Fig 5. Stability of responses.

Study 3: Tonotopic maps

Fig 6. Tonotopic maps VASO.

Discussion

Supporting information

Acknowledgments

Diversity statement

Data Availability

Funding Statement

References

Decision Letter 0

Jyrki Ahveninen

Roles

Author response to Decision Letter 0

Decision Letter 1

Jyrki Ahveninen

Roles

Acceptance letter

Jyrki Ahveninen

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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