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Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression

At the group level, antidepressant efficacy of rTMS targets is inversely related to their normative connectivity with subgenual anterior cingulate cortex (sgACC). Individualized connectivity may yield better targets, particularly in patients with neuropsychiatric disorders who may have aberrant conn...

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Autores principales: Siddiqi, Shan H., Kandala, Sridhar, Hacker, Carl D., Trapp, Nicholas T., Leuthardt, Eric C., Carter, Alexandre R., Brody, David L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008633/
https://www.ncbi.nlm.nih.gov/pubmed/36906616
http://dx.doi.org/10.1038/s41598-022-21905-x
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author Siddiqi, Shan H.
Kandala, Sridhar
Hacker, Carl D.
Trapp, Nicholas T.
Leuthardt, Eric C.
Carter, Alexandre R.
Brody, David L.
author_facet Siddiqi, Shan H.
Kandala, Sridhar
Hacker, Carl D.
Trapp, Nicholas T.
Leuthardt, Eric C.
Carter, Alexandre R.
Brody, David L.
author_sort Siddiqi, Shan H.
collection PubMed
description At the group level, antidepressant efficacy of rTMS targets is inversely related to their normative connectivity with subgenual anterior cingulate cortex (sgACC). Individualized connectivity may yield better targets, particularly in patients with neuropsychiatric disorders who may have aberrant connectivity. However, sgACC connectivity shows poor test–retest reliability at the individual level. Individualized resting-state network mapping (RSNM) can reliably map inter-individual variability in brain network organization. Thus, we sought to identify individualized RSNM-based rTMS targets that reliably target the sgACC connectivity profile. We used RSNM to identify network-based rTMS targets in 10 healthy controls and 13 individuals with traumatic brain injury-associated depression (TBI-D). These “RSNM targets” were compared with consensus structural targets and targets based on individualized anti-correlation with a group-mean-derived sgACC region (“sgACC-derived targets”). The TBI-D cohort was also randomized to receive active (n = 9) or sham (n = 4) rTMS to RSNM targets with 20 daily sessions of sequential high-frequency left-sided stimulation and low-frequency right-sided stimulation. We found that the group-mean sgACC connectivity profile was reliably estimated by individualized correlation with default mode network (DMN) and anti-correlation with dorsal attention network (DAN). Individualized RSNM targets were thus identified based on DAN anti-correlation and DMN correlation. These RSNM targets showed greater test–retest reliability than sgACC-derived targets. Counterintuitively, anti-correlation with the group-mean sgACC connectivity profile was also stronger and more reliable for RSNM-derived targets than for sgACC-derived targets. Improvement in depression after RSNM-targeted rTMS was predicted by target anti-correlation with the portions of sgACC. Active treatment also led to increased connectivity within and between the stimulation sites, the sgACC, and the DMN. Overall, these results suggest that RSNM may enable reliable individualized rTMS targeting, although further research is needed to determine whether this personalized approach can improve clinical outcomes.
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spelling pubmed-100086332023-03-13 Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression Siddiqi, Shan H. Kandala, Sridhar Hacker, Carl D. Trapp, Nicholas T. Leuthardt, Eric C. Carter, Alexandre R. Brody, David L. Sci Rep Article At the group level, antidepressant efficacy of rTMS targets is inversely related to their normative connectivity with subgenual anterior cingulate cortex (sgACC). Individualized connectivity may yield better targets, particularly in patients with neuropsychiatric disorders who may have aberrant connectivity. However, sgACC connectivity shows poor test–retest reliability at the individual level. Individualized resting-state network mapping (RSNM) can reliably map inter-individual variability in brain network organization. Thus, we sought to identify individualized RSNM-based rTMS targets that reliably target the sgACC connectivity profile. We used RSNM to identify network-based rTMS targets in 10 healthy controls and 13 individuals with traumatic brain injury-associated depression (TBI-D). These “RSNM targets” were compared with consensus structural targets and targets based on individualized anti-correlation with a group-mean-derived sgACC region (“sgACC-derived targets”). The TBI-D cohort was also randomized to receive active (n = 9) or sham (n = 4) rTMS to RSNM targets with 20 daily sessions of sequential high-frequency left-sided stimulation and low-frequency right-sided stimulation. We found that the group-mean sgACC connectivity profile was reliably estimated by individualized correlation with default mode network (DMN) and anti-correlation with dorsal attention network (DAN). Individualized RSNM targets were thus identified based on DAN anti-correlation and DMN correlation. These RSNM targets showed greater test–retest reliability than sgACC-derived targets. Counterintuitively, anti-correlation with the group-mean sgACC connectivity profile was also stronger and more reliable for RSNM-derived targets than for sgACC-derived targets. Improvement in depression after RSNM-targeted rTMS was predicted by target anti-correlation with the portions of sgACC. Active treatment also led to increased connectivity within and between the stimulation sites, the sgACC, and the DMN. Overall, these results suggest that RSNM may enable reliable individualized rTMS targeting, although further research is needed to determine whether this personalized approach can improve clinical outcomes. Nature Publishing Group UK 2023-03-11 /pmc/articles/PMC10008633/ /pubmed/36906616 http://dx.doi.org/10.1038/s41598-022-21905-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Siddiqi, Shan H.
Kandala, Sridhar
Hacker, Carl D.
Trapp, Nicholas T.
Leuthardt, Eric C.
Carter, Alexandre R.
Brody, David L.
Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression
title Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression
title_full Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression
title_fullStr Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression
title_full_unstemmed Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression
title_short Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression
title_sort individualized precision targeting of dorsal attention and default mode networks with rtms in traumatic brain injury-associated depression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008633/
https://www.ncbi.nlm.nih.gov/pubmed/36906616
http://dx.doi.org/10.1038/s41598-022-21905-x
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