Why the study?
Identifying pain from brain activity may provide a neural code for pain and offer useful information for pain diagnosis and treatment.
This review highlights state-of-the-art methods for decoding pain from brain signals to aid in pain diagnosis and biomarker discovery.
Answers are grounded in this paper and cite their sources.
Hypothesis-generating for neural pain decoding in diagnosis; leaves open prospective validation of chronic pain neurobiomarkers.
Pain is a dynamic, complex and multidimensional experience. The identification of pain from brain activity as neural readout may effectively provide a neural code for pain, and further provide useful information for pain diagnosis and treatment. Advances in neuroimaging and large-scale electrophysiology have enabled us to examine neural activity with improved spatial and temporal resolution, providing opportunities to decode pain in humans and freely behaving animals. This topical review provides a systematical overview of state-of-the-art methods for decoding pain from brain signals, with special emphasis on electrophysiological and neuroimaging modalities. We show how pain decoding analyses can help pain diagnosis and discovery of neurobiomarkers for chronic pain. Finally, we discuss the challenges in the research field and point to several important future research directions.
No takes yet. Share an insight, caveat, or question.
Zhe Chen (2021) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: