Descending regulation of spinal cord responses to nociceptive signaling has a strong influence on pain perception. Previous studies using functional magnetic resonance imaging (fMRI) have indicated that in addition to reactive responses to nociceptive signals, there is a continuous component to regulation, and that it may vary with differences in pain sensitivity. We hypothesize that this continuous regulation component occurs routinely in fMRI studies before noxious stimulation, as well as during, and after stimulation. This hypothesis was tested by analyzing data from 59 healthy participants in 4 previous fMRI studies in our laboratory using noxious heat stimuli. Analyses included structural equation modeling to identify coordinated blood oxygenation-level-dependent (BOLD) signal variations between regions (ie, connectivity) and Bayesian regression of BOLD time-series responses in relation to pain ratings and stimulus temperatures. The results demonstrate the periaqueductal gray-rostral ventromedial medulla-spinal cord descending modulation pathway, influenced by input from the hypothalamus, parabrachial nucleus, and nucleus tractus solitarius. Connectivity between specific regions is observed to vary in relation to pain sensitivity. The results support the conclusion that homeostatic autonomic control influences the net descending pain regulation, and therefore influences pain sensitivity. The results describe the overall properties of pain processing (specifically pain elicited by heat) in the healthy human brainstem and spinal cord, and mechanisms for variation across individuals. This understanding is expected to be important for studies of how pain processing is altered in chronic pain conditions.

A comprehensive review of the literature-to-date on functional magnetic resonance imaging (fMRI) of the spinal cord is presented. Spinal fMRI has been shown, over more than two decades of work, to be a reliable tool for detecting neural activity. We discuss 10 key points regarding the history, development, methods, and applications of spinal fMRI. Animal models have served a key purpose for the development of spinal fMRI protocols and for experimental spinal cord injury studies. Applications of spinal fMRI span from animal models across healthy and patient populations in humans using both task-based and resting-state paradigms. The literature also demonstrates clear trends in study design and acquisition methods, as the majority of studies follow a task-based, block design paradigm, and utilize variations of single-shot fast spin-echo imaging methods. We, therefore, discuss the similarities and differences of these to resting-state fMRI and gradient-echo EPI protocols. Although it is newly emerging, complex connectivity and network analysis is not only possible, but has also been shown to be reliable and reproducible in the spinal cord for both task-based and resting-state studies. Despite the technical challenges associated with spinal fMRI, this review identifies reliable solutions that have been developed to overcome these challenges.

Functional magnetic resonance imaging (fMRI) research on the human brainstem (BS) and spinal cord (SC) has identified extensive BS/SC resting-state networks (RSNs) by showing spontaneous coordinated blood oxygenation-level dependent (BOLD) signal fluctuations in the absence of a stimulus. Studies have shown that these networks can be influenced by participants’ level of arousal or attention (e.g., watching a video), and linked network function to autonomic homeostatic regulation. Here we explore how the cognitive state of expecting pain can influence connectivity in these networks. Data from two studies (a predictable pain stimulus study, and a resting-state study) were compared to show the effects of expecting pain on BS/SC networks, and how networks differed from networks associated with the resting-state. In each study, BOLD fMRI data were obtained from the cervical SC and brainstem in healthy participants at 3 tesla using a T2-weighted single-shot fast spin-echo imaging method. Functional connectivity was investigated within the entire 3D volume by means of structural equation modeling (SEM) and analyses of covariance (ANCOVA). Results showed extensive connectivity within/across BS and SC regions during the expectation of pain, and ANCOVA analyses showed that connectivity in specific components of these networks varied with individual pain sensitivity. Comparing these results to RSN fluctuations revealed commonalities in coordination between BS and SC regions, and specific BS–BS connectivity fluctuations unique to the expectation of pain. Based on the regions involved, these results provide evidence of brainstem regulation specific to the expectation of pain.

No abstract

No abstract