Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex
Regions of human medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) are part of the default network (DN), and additionally are implicated in diverse cognitive functions ranging from autobiographical memory to subjective valuation. Our ability to interpret the apparent co-localizati...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2020-01-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811919308961 |
| _version_ | 1829495554329018368 |
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| author | Claudio Toro-Serey Sean M. Tobyne Joseph T. McGuire |
| author_facet | Claudio Toro-Serey Sean M. Tobyne Joseph T. McGuire |
| author_sort | Claudio Toro-Serey |
| collection | DOAJ |
| description | Regions of human medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) are part of the default network (DN), and additionally are implicated in diverse cognitive functions ranging from autobiographical memory to subjective valuation. Our ability to interpret the apparent co-localization of task-related effects with DN-regions is constrained by a limited understanding of the individual-level heterogeneity in mPFC/PCC functional organization. Here we used cortical surface-based meta-analysis to identify a parcel in human PCC that was more strongly associated with the DN than with valuation effects. We then used resting-state fMRI data and a data-driven network analysis algorithm, spectral partitioning, to partition mPFC and PCC into “DN” and “non-DN” subdivisions in individual participants (n = 100 from the Human Connectome Project). The spectral partitioning algorithm identified individual-level cortical subdivisions that varied markedly across individuals, especially in mPFC, and were reliable across test/retest datasets. Our results point toward new strategies for assessing whether distinct cognitive functions engage common or distinct mPFC subregions at the individual level. |
| first_indexed | 2024-12-16T07:12:12Z |
| format | Article |
| id | doaj.art-410a7da3b20d4e2a9641d8b41536a5ad |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-16T07:12:12Z |
| publishDate | 2020-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-410a7da3b20d4e2a9641d8b41536a5ad2022-12-21T22:39:52ZengElsevierNeuroImage1095-95722020-01-01205116305Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortexClaudio Toro-Serey0Sean M. Tobyne1Joseph T. McGuire2Department of Psychological and Brain Sciences, Boston University, Boston, USA; Center for Systems Neuroscience, Boston University, Boston, USA; Corresponding author. Department of Psychological and Brain Sciences, Boston University, Boston, USA.Department of Psychological and Brain Sciences, Boston University, Boston, USA; Graduate Program for Neuroscience, Boston University, Boston, USADepartment of Psychological and Brain Sciences, Boston University, Boston, USA; Center for Systems Neuroscience, Boston University, Boston, USA; Corresponding author. Department of Psychological and Brain Sciences, Boston University, Boston, USA.Regions of human medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) are part of the default network (DN), and additionally are implicated in diverse cognitive functions ranging from autobiographical memory to subjective valuation. Our ability to interpret the apparent co-localization of task-related effects with DN-regions is constrained by a limited understanding of the individual-level heterogeneity in mPFC/PCC functional organization. Here we used cortical surface-based meta-analysis to identify a parcel in human PCC that was more strongly associated with the DN than with valuation effects. We then used resting-state fMRI data and a data-driven network analysis algorithm, spectral partitioning, to partition mPFC and PCC into “DN” and “non-DN” subdivisions in individual participants (n = 100 from the Human Connectome Project). The spectral partitioning algorithm identified individual-level cortical subdivisions that varied markedly across individuals, especially in mPFC, and were reliable across test/retest datasets. Our results point toward new strategies for assessing whether distinct cognitive functions engage common or distinct mPFC subregions at the individual level.http://www.sciencedirect.com/science/article/pii/S1053811919308961Functional connectivityDefault networkNetwork neuroscienceMedial prefrontal cortexSpectral partitioning |
| spellingShingle | Claudio Toro-Serey Sean M. Tobyne Joseph T. McGuire Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex NeuroImage Functional connectivity Default network Network neuroscience Medial prefrontal cortex Spectral partitioning |
| title | Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex |
| title_full | Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex |
| title_fullStr | Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex |
| title_full_unstemmed | Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex |
| title_short | Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex |
| title_sort | spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex |
| topic | Functional connectivity Default network Network neuroscience Medial prefrontal cortex Spectral partitioning |
| url | http://www.sciencedirect.com/science/article/pii/S1053811919308961 |
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