The investigation of spontaneous fluctuations of the blood-oxygen-level-dependent (BOLD) signal has recently been extended from the brain to the spinal cord, where it has also generated initial interest from a clinical perspective. A number of resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated robust functional connectivity between the time-series of BOLD fluctuations in bilateral dorsal horns and between those in bilateral ventral horns, in line with the functional neuroanatomy of the spinal cord. A necessary step prior to extension to clinical studies is assessing the reliability of such resting-state signals, which we aimed to do here in a group of 45 healthy young adults at the clinically prevalent field-strength of 3T. When investigating connectivity in the entire cervical spinal cord, we observed fair to good reliability for dorsal-dorsal and ventral-ventral connectivity, whereas reliability was poor for within- and between-hemicord dorsal-ventral connectivity. Considering how prone spinal cord fMRI is to noise, we extensively investigated the impact of distinct noise sources and made two crucial observations: removal of physiological noise led to a reduction in functional connectivity strength and reliability - due to the removal of stable and participant-specific noise patterns - whereas removal of thermal noise considerably increased the detectability of functional connectivity without a clear influence on reliability. Finally, we also assessed connectivity within spinal cord segments and observed that while the pattern of connectivity was similar to that of whole cervical cord, reliability at the level of single segments was consistently poor. Taken together, our results demonstrate the presence of reliable resting-state functional connectivity in the human spinal cord even after thoroughly accounting for physiological and thermal noise, but at the same time urge caution if focal changes in connectivity (e.g. due to segmental lesions) are to be studied, especially in a longitudinal manner.

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Functional magnetic resonance imaging (fMRI) of the human spinal cord faces many challenges, such as signal loss due to local magnetic field inhomogeneities. This issue can be addressed with slice-specific z-shimming, which compensates for the dephasing effect of the inhomogeneities using a slice-specific gradient pulse. Here, we aim to address outstanding issues regarding this technique by evaluating its effects on several aspects that are directly relevant for spinal fMRI and by developing two automated procedures in order to improve upon the time-consuming and subjective nature of manual selection of z-shims: one procedure finds the z-shim that maximizes signal intensity in each slice of an EPI reference-scan and the other finds the through-slice field inhomogeneity for each EPI-slice in field map data and calculates the required compensation gradient moment. We demonstrate that the beneficial effects of z-shimming are apparent across different echo times, hold true for both the dorsal and ventral horn, and are also apparent in the temporal signal-to-noise ratio (tSNR) of EPI time-series data. Both of our automated approaches were faster than the manual approach, lead to significant improvements in gray matter tSNR compared to no z-shimming and resulted in beneficial effects that were stable across time. While the field-map-based approach performed slightly worse than the manual approach, the EPI-based approach performed as well as the manual one and was furthermore validated on an external corticospinal data-set (N > 100). Together, automated z-shimming may improve the data quality of future spinal fMRI studies and lead to increased reproducibility in longitudinal studies.

The spinal cord is of fundamental importance for somatosensory processing and plays a significant role in various pathologies, such as chronic pain. However, knowledge on spinal cord processing in humans is limited due to the vast technical challenges involved in its investigation via non-invasive recording approaches. Here, we aim to address these challenges by developing an electrophysiological approach — based on a high-density electrode-montage — that allows for characterizing spinal cord somatosensory evoked potentials (SEPs) and combining this with concurrent recordings of the spinal cord's input (peripheral nerve action potentials) and output (SEPs in brainstem and cortex). In two separate experiments, we first methodologically validate the approach (including replication and robustness analyses) and then assess its application in the context of a neuroscientific question (integrative processes along the neural hierarchy). Critically, we demonstrate the benefits of multi-channel recordings in terms of enhancing sensitivity via spatial filtering, which also allows for obtaining spinal cord SEPs at the single-trial level. We make use of this approach to demonstrate the feasibility of recording spinal cord SEPs in low-signal scenarios (single-digit stimulation) and — most importantly — to provide evidence for bottom-up signal integration already at the level of the spinal cord. Taken together, our approach of concurrent multi-channel recordings of evoked responses along the neural hierarchy allows for a comprehensive assessment of the functional architecture of somatosensory processing at a millisecond timescale.

Functional magnetic resonance imaging (fMRI) of the human spinal cord faces many challenges, one of which is signal loss due to local magnetic field inhomogeneities. This issue can be addressed with slice-specific z-shimming, which compensates for the dephasing effect of the inhomogeneities using a single, slice-specific gradient pulse. Since the original demonstration of its utility, this technique has already been employed in several spinal fMRI studies. Here, we aim to address two outstanding issues regarding this technique: on the one hand, we evaluate its effects on several parameters that are directly relevant for spinal fMRI (but have not yet been assessed) and on the other hand, we improve upon the manual selection of slice-specific z-shims by developing automated procedures. First, we demonstrate that the beneficial effects of z-shimming i) are apparent across a large range of echo times, ii) hold true for both the dorsal and ventral horn gray matter, and iii) are also clearly apparent in the temporal signal-to-noise ratio (tSNR) of gradient-echo EPI time-series data. Second, and more importantly, we address the time-consuming and subjective nature of manual selection of slice-specific z-shims by developing two automated approaches: one is based on finding the z-shim that maximizes spinal cord signal intensity in each slice of an EPI z-shim reference-scan and the other is based on finding the strength of the gradient-field that compensates the through-slice inhomogeneity in field map data. Both automated approaches i) were much faster than the manual approach, ii) lead to significant improvements in spinal cord gray matter tSNR compared to no z-shimming and iii) resulted in beneficial effects that were stable across time. While the field map-based approach performed slightly worse than the manual approach, the EPI-based approach performed at least as well as the manual one and was furthermore validated on an independently acquired corticospinal data-set (N > 100). Together, we believe that automated z-shimming will improve the data quality of future spinal fMRI studies and — by removing the subjective step of manual z-shim selection — may also lead to increased reproducibility in longitudinal studies.