Guiding functional near-infrared spectroscopy optode-layout design using individual (f)MRI data: effects on signal strength.

Significance: Designing optode layouts is an essential step for functional near-infrared spectroscopy (fNIRS) experiments as the quality of the measured signal and the sensitivity to cortical regions-of-interest depend on how optodes are arranged on the scalp. This becomes particularly relevant for fNIRS-based brain-computer interfaces (BCIs), where developing robust systems with few optodes is crucial for clinical applications. Aim: Available resources often dictate the approach researchers use for optode-layout design. We investigated whether guiding optode layout design using different amounts of subject-specific magnetic resonance imaging (MRI) data affects the fNIRS signal quality and sensitivity to brain activation when healthy participants perform mental-imagery tasks typically used in fNIRS-BCI experiments. Approach: We compared four approaches that incrementally incorporated subject-specific MRI information while participants performed mental-calculation, mental-rotation, and inner-speech tasks. The literature-based approach (LIT) used a literature review to guide the optode layout design. The probabilistic approach (PROB) employed individual anatomical data and probabilistic maps of functional MRI (fMRI)-activation from an independent dataset. The individual fMRI (iFMRI) approach used individual anatomical and fMRI data, and the fourth approach used individual anatomical, functional, and vascular information of the same subject (fVASC). Results: The four approaches resulted in different optode layouts and the more informed approaches outperformed the minimally informed approach (LIT) in terms of signal quality and sensitivity. Further, PROB, iFMRI, and fVASC approaches resulted in a similar outcome. Conclusions: We conclude that additional individual MRI data lead to a better outcome, but that not all the modalities tested here are required to achieve a robust setup. Finally, we give preliminary advice to efficiently using resources for developing robust optode layouts for BCI and neurofeedback applications.

Tonotopic maps in human auditory cortex using arterial spin labeling.

A tonotopic organization of the human auditory cortex (AC) has been reliably found by neuroimaging studies. However, a full characterization and parcellation of the AC is still lacking. In this study, we employed pseudo-continuous arterial spin labeling (pCASL) to map tonotopy and voice selective regions using, for the first time, cerebral blood flow (CBF). We demonstrated the feasibility of CBF-based tonotopy and found a good agreement with BOLD signal-based tonotopy, despite the lower contrast-to-noise ratio of CBF. Quantitative perfusion mapping of baseline CBF showed a region of high perfusion centered on Heschl's gyrus and corresponding to the main high-low-high frequency gradients, co-located to the presumed primary auditory core and suggesting baseline CBF as a novel marker for AC parcellation. Furthermore, susceptibility weighted imaging was employed to investigate the tissue specificity of CBF and BOLD signal and the possible venous bias of BOLD-based tonotopy. For BOLD only active voxels, we found a higher percentage of vein contamination than for CBF only active voxels. Taken together, we demonstrated that both baseline and stimulus-induced CBF is an alternative fMRI approach to the standard BOLD signal to study auditory processing and delineate the functional organization of the auditory cortex. Hum Brain Mapp 38:1140-1154, 2017. © 2016 Wiley Periodicals, Inc.

The effect of spatial resolution on decoding accuracy in fMRI multivariate pattern analysis.

Multivariate pattern analysis (MVPA) in fMRI has been used to extract information from distributed cortical activation patterns, which may go undetected in conventional univariate analysis. However, little is known about the physical and physiological underpinnings of MVPA in fMRI as well as about the effect of spatial smoothing on its performance. Several studies have addressed these issues, but their investigation was limited to the visual cortex at 3T with conflicting results. Here, we used ultra-high field (7T) fMRI to investigate the effect of spatial resolution and smoothing on decoding of speech content (vowels) and speaker identity from auditory cortical responses. To that end, we acquired high-resolution (1.1mm isotropic) fMRI data and additionally reconstructed them at 2.2 and 3.3mm in-plane spatial resolutions from the original k-space data. Furthermore, the data at each resolution were spatially smoothed with different 3D Gaussian kernel sizes (i.e. no smoothing or 1.1, 2.2, 3.3, 4.4, or 8.8mm kernels). For all spatial resolutions and smoothing kernels, we demonstrate the feasibility of decoding speech content (vowel) and speaker identity at 7T using support vector machine (SVM) MVPA. In addition, we found that high spatial frequencies are informative for vowel decoding and that the relative contribution of high and low spatial frequencies is different across the two decoding tasks. Moderate smoothing (up to 2.2mm) improved the accuracies for both decoding of vowels and speakers, possibly due to reduction of noise (e.g. residual motion artifacts or instrument noise) while still preserving information at high spatial frequency. In summary, our results show that - even with the same stimuli and within the same brain areas - the optimal spatial resolution for MVPA in fMRI depends on the specific decoding task of interest.

Cortical lamina-dependent blood volume changes in human brain at 7 T.

Cortical layer-dependent high (sub-millimeter) resolution functional magnetic resonance imaging (fMRI) in human or animal brain can be used to address questions regarding the functioning of cortical circuits, such as the effect of different afferent and efferent connectivities on activity in specific cortical layers. The sensitivity of gradient echo (GE) blood oxygenation level-dependent (BOLD) responses to large draining veins reduces its local specificity and can render the interpretation of the underlying laminar neural activity impossible. The application of the more spatially specific cerebral blood volume (CBV)-based fMRI in humans has been hindered by the low sensitivity of the noninvasive modalities available. Here, a vascular space occupancy (VASO) variant, adapted for use at high field, is further optimized to capture layer-dependent activity changes in human motor cortex at sub-millimeter resolution. Acquired activation maps and cortical profiles show that the VASO signal peaks in gray matter at 0.8-1.6mm depth, and deeper compared to the superficial and vein-dominated GE-BOLD responses. Validation of the VASO signal change versus well-established iron-oxide contrast agent based fMRI methods in animals showed the same cortical profiles of CBV change, after normalization for lamina-dependent baseline CBV. In order to evaluate its potential of revealing small lamina-dependent signal differences due to modulations of the input-output characteristics, layer-dependent VASO responses were investigated in the ipsilateral hemisphere during unilateral finger tapping. Positive activation in ipsilateral primary motor cortex and negative activation in ipsilateral primary sensory cortex were observed. This feature is only visible in high-resolution fMRI where opposing sides of a sulcus can be investigated independently because of a lack of partial volume effects. Based on the results presented here, we conclude that VASO offers good reproducibility, high sensitivity and lower sensitivity than GE-BOLD to changes in larger vessels, making it a valuable tool for layer-dependent fMRI studies in humans.