Dildine, T. C. | Search bioRxiv

bioRxiv2025

Differential encoding of noxious heat and self-reported pain along corticospinal networks: a simultaneous spinal cord-brain fMRI study

Chronic pain poses a substantial public health burden. Elucidating how the healthy central nervous system (CNS) differentially encodes objective stimulus intensity and subjective experiences of pain perception may offer key insights into the central mechanisms contributing to chronic pain. Functional MRI (fMRI) combined with controlled noxious stimulation provides a powerful means to explore neural representations of nociception and pain perception. Here, we applied noxious heat at three intensities (46 {degrees}C, 47 {degrees}C, 48 {degrees}C, 8 trials each randomized) to the right forearm of 28 healthy women during simultaneous spinal cord-brain fMRI to investigate how distributed corticospinal activity and connectivity encode stimulus intensity and subjective pain. Activity increased with stimulus temperature across regions involved in pain processing--including somatosensory, motor, prefrontal, insular, and subcortical areas--as well as in the ipsilateral dorsal and ventral spinal cord. Spinal- brain functional connectivity was observed between the right dorsal horn and pain-related brain regions such as primary and secondary somatosensory cortex, insula, anterior cingulate cortex, thalamus, and periaqueductal gray, and was positively associated with individual pain ratings. Using representational similarity analysis (RSA), we found that multivoxel activation patterns in the brain and spinal cord, as well as corticospinal connectivity patterns, reliably tracked stimulus temperature, while only subsets of cortical regions (e.g., insula, sensorimotor, and frontal cortices) encoded subjective pain. Notably, spinal cord representations were primarily organized by stimulus temperature rather than perceived pain intensity. These findings demonstrate that simultaneous spinal cord-brain fMRI combined with multivariate modeling can identify sensory and perceptual components of nociceptive processing across the neuroaxis. Such approaches advance mechanistic understanding of pain and may inform the development of CNS-based biomarkers for chronic pain assessment and intervention.

neuroscience↗

bioRxiv2021

Instructions and experiential learning have similar impacts on pain and pain-related brain responses but produce dissociations in value-based reversal learning

Recent data suggest that interactions between systems involved in higher order knowledge and associative learning drive responses during appetitive and aversive learning. However, it is unknown how these systems impact subjective responses, such as pain. We tested how instructions and reversal learning influence pain and pain-evoked brain activation. Healthy volunteers (n = 40) were either instructed about contingencies between cues and aversive outcomes or learned through experience in a paradigm where contingencies reversed three times. We measured predictive cue effects on pain and heat-evoked brain responses using functional magnetic resonance imaging. Predictive cues dynamically modulated pain perception as contingencies changed, regardless of whether participants received contingency instructions. Heat-evoked responses in the insula, anterior cingulate, and putamen updated as contingencies changed, whereas the periaqueductal gray and thalamus responded to initial contingencies throughout the task. Quantitative modeling revealed that expected value was shaped purely by instructions in the Instructed Group, whereas expected value updated dynamically in the Uninstructed Group as a function of error-based learning. These differences were accompanied by dissociations in the neural correlates of value-based learning in the rostral anterior cingulate, medial prefrontal cortex, and orbitofrontal cortex. These results show how predictions impact subjective pain. Moreover, imaging data delineate three types of networks involved in pain generation and value-based learning: those that respond to initial contingencies, those that update dynamically during feedback-driven learning as contingencies change, and those that are sensitive to instruction. Together, these findings provide multiple points of entry for therapies designs to impact pain.

neuroscience↗