Cargando…

Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings

Pain is a complex experience involving sensory, emotional, and cognitive aspects, and multiple networks manage its processing in the brain. Examining how pain transforms into a behavioral response can shed light on the networks’ relationships and facilitate interventions to treat chronic pain. Howev...

Descripción completa

Detalles Bibliográficos
Autores principales: Caston, Rose M., Smith, Elliot H., Davis, Tyler S., Singh, Hargunbir, Rahimpour, Shervin, Rolston, John D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028876/
https://www.ncbi.nlm.nih.gov/pubmed/36945412
http://dx.doi.org/10.1101/2023.03.08.531576
_version_ 1784910035966492672
author Caston, Rose M.
Smith, Elliot H.
Davis, Tyler S.
Singh, Hargunbir
Rahimpour, Shervin
Rolston, John D.
author_facet Caston, Rose M.
Smith, Elliot H.
Davis, Tyler S.
Singh, Hargunbir
Rahimpour, Shervin
Rolston, John D.
author_sort Caston, Rose M.
collection PubMed
description Pain is a complex experience involving sensory, emotional, and cognitive aspects, and multiple networks manage its processing in the brain. Examining how pain transforms into a behavioral response can shed light on the networks’ relationships and facilitate interventions to treat chronic pain. However, studies using high spatial and temporal resolution methods to investigate the neural encoding of pain and its psychophysical correlates have been limited. We recorded from intracranial stereo-EEG (sEEG) electrodes implanted in sixteen different brain regions of twenty patients who underwent psychophysical pain testing consisting of a tonic thermal stimulus to the hand. Broadband high-frequency local field potential amplitude (HFA; 70–150 Hz) was isolated to investigate the relationship between the ongoing neural activity and the resulting psychophysical pain evaluations. Two different generalized linear mixed-effects models (GLME) were employed to assess the neural representations underlying binary and graded pain psychophysics. The first model examined the relationship between HFA and whether the patient responded “yes” or “no” to whether the trial was painful. The second model investigated the relationship between HFA and how painful the stimulus was rated on a visual analog scale. GLMEs revealed that HFA in the inferior temporal gyrus (ITG), superior frontal gyrus (SFG), and superior temporal gyrus (STG) predicted painful responses at stimulus onset. An increase in HFA in the orbitofrontal cortex (OFC), SFG, and striatum predicted pain responses at stimulus offset. Numerous regions including the anterior cingulate cortex, hippocampus, IFG, MTG, OFC, and striatum, predicted the pain rating at stimulus onset. However, only the amygdala and fusiform gyrus predicted increased pain ratings at stimulus offset. We characterized the spatiotemporal representations of binary and graded painful responses during tonic pain stimuli. Our study provides evidence from intracranial recordings that the neural encoding of psychophysical pain changes over time during a tonic thermal stimulus, with different brain regions being predictive of pain at the beginning and end of the stimulus.
format Online
Article
Text
id pubmed-10028876
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Cold Spring Harbor Laboratory
record_format MEDLINE/PubMed
spelling pubmed-100288762023-03-22 Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings Caston, Rose M. Smith, Elliot H. Davis, Tyler S. Singh, Hargunbir Rahimpour, Shervin Rolston, John D. bioRxiv Article Pain is a complex experience involving sensory, emotional, and cognitive aspects, and multiple networks manage its processing in the brain. Examining how pain transforms into a behavioral response can shed light on the networks’ relationships and facilitate interventions to treat chronic pain. However, studies using high spatial and temporal resolution methods to investigate the neural encoding of pain and its psychophysical correlates have been limited. We recorded from intracranial stereo-EEG (sEEG) electrodes implanted in sixteen different brain regions of twenty patients who underwent psychophysical pain testing consisting of a tonic thermal stimulus to the hand. Broadband high-frequency local field potential amplitude (HFA; 70–150 Hz) was isolated to investigate the relationship between the ongoing neural activity and the resulting psychophysical pain evaluations. Two different generalized linear mixed-effects models (GLME) were employed to assess the neural representations underlying binary and graded pain psychophysics. The first model examined the relationship between HFA and whether the patient responded “yes” or “no” to whether the trial was painful. The second model investigated the relationship between HFA and how painful the stimulus was rated on a visual analog scale. GLMEs revealed that HFA in the inferior temporal gyrus (ITG), superior frontal gyrus (SFG), and superior temporal gyrus (STG) predicted painful responses at stimulus onset. An increase in HFA in the orbitofrontal cortex (OFC), SFG, and striatum predicted pain responses at stimulus offset. Numerous regions including the anterior cingulate cortex, hippocampus, IFG, MTG, OFC, and striatum, predicted the pain rating at stimulus onset. However, only the amygdala and fusiform gyrus predicted increased pain ratings at stimulus offset. We characterized the spatiotemporal representations of binary and graded painful responses during tonic pain stimuli. Our study provides evidence from intracranial recordings that the neural encoding of psychophysical pain changes over time during a tonic thermal stimulus, with different brain regions being predictive of pain at the beginning and end of the stimulus. Cold Spring Harbor Laboratory 2023-03-10 /pmc/articles/PMC10028876/ /pubmed/36945412 http://dx.doi.org/10.1101/2023.03.08.531576 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Caston, Rose M.
Smith, Elliot H.
Davis, Tyler S.
Singh, Hargunbir
Rahimpour, Shervin
Rolston, John D.
Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings
title Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings
title_full Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings
title_fullStr Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings
title_full_unstemmed Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings
title_short Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings
title_sort characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028876/
https://www.ncbi.nlm.nih.gov/pubmed/36945412
http://dx.doi.org/10.1101/2023.03.08.531576
work_keys_str_mv AT castonrosem characterizationofspatiotemporaldynamicsofbinaryandgradedtonicpaininhumansusingintracranialrecordings
AT smithellioth characterizationofspatiotemporaldynamicsofbinaryandgradedtonicpaininhumansusingintracranialrecordings
AT davistylers characterizationofspatiotemporaldynamicsofbinaryandgradedtonicpaininhumansusingintracranialrecordings
AT singhhargunbir characterizationofspatiotemporaldynamicsofbinaryandgradedtonicpaininhumansusingintracranialrecordings
AT rahimpourshervin characterizationofspatiotemporaldynamicsofbinaryandgradedtonicpaininhumansusingintracranialrecordings
AT rolstonjohnd characterizationofspatiotemporaldynamicsofbinaryandgradedtonicpaininhumansusingintracranialrecordings