Dissociation of Reliability, Heritability, and Predictivity in Coarse- and Fine-Scale Functional Connectomes during Development Article Swipe
Erica L. Busch
,
Kristina M. Rapuano
,
Kevin Anderson
,
Monica D. Rosenberg
,
Richard Watts
,
B.J. Casey
,
James V. Haxby
,
Ma Feilong
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1523/jneurosci.0735-23.2023
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1523/jneurosci.0735-23.2023
The functional connectome supports information transmission through the brain at various spatial scales, from exchange between broad cortical regions to finer-scale, vertex-wise connections that underlie specific information processing mechanisms. In adults, while both the coarse- and fine-scale functional connectomes predict cognition, the fine scale can predict up to twice the variance as the coarse-scale functional connectome. Yet, past brain-wide association studies, particularly using large developmental samples, focus on the coarse connectome to understand the neural underpinnings of individual differences in cognition. Using a large cohort of children (age 9–10 years; n = 1,115 individuals; both sexes; 50% female, including 170 monozygotic and 219 dizygotic twin pairs and 337 unrelated individuals), we examine the reliability, heritability, and behavioral relevance of resting-state functional connectivity computed at different spatial scales. We use connectivity hyperalignment to improve access to reliable fine-scale (vertex-wise) connectivity information and compare the fine-scale connectome with the traditional parcel-wise (coarse scale) functional connectomes. Though individual differences in the fine-scale connectome are more reliable than those in the coarse-scale, they are less heritable. Further, the alignment and scale of connectomes influence their ability to predict behavior, whereby some cognitive traits are equally well predicted by both connectome scales, but other, less heritable cognitive traits are better predicted by the fine-scale connectome. Together, our findings suggest there are dissociable individual differences in information processing represented at different scales of the functional connectome which, in turn, have distinct implications for heritability and cognition.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1523/jneurosci.0735-23.2023
- OA Status
- green
- Cited By
- 6
- References
- 85
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390225839
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4390225839Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1523/jneurosci.0735-23.2023Digital Object Identifier
- Title
-
Dissociation of Reliability, Heritability, and Predictivity in Coarse- and Fine-Scale Functional Connectomes during DevelopmentWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-12-26Full publication date if available
- Authors
-
Erica L. Busch, Kristina M. Rapuano, Kevin Anderson, Monica D. Rosenberg, Richard Watts, B.J. Casey, James V. Haxby, Ma FeilongList of authors in order
- Landing page
-
https://doi.org/10.1523/jneurosci.0735-23.2023Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://pmc.ncbi.nlm.nih.gov/articles/PMC10866091/pdf/jneuro-44-e0735232023.pdfDirect OA link when available
- Concepts
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Connectome, Cognition, Connectomics, Functional connectivity, Human Connectome Project, Scale (ratio), Computer science, Neuroscience, Psychology, Cartography, GeographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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6Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 3Per-year citation counts (last 5 years)
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85Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.brain-wide | 58 |
| abstract_inverted_index.cognition, | 40 |
| abstract_inverted_index.cognition. | 80, 239 |
| abstract_inverted_index.connectome | 2, 70, 144, 159, 195, 229 |
| abstract_inverted_index.fine-scale | 36, 136, 143, 158, 208 |
| abstract_inverted_index.functional | 1, 37, 54, 120, 151, 228 |
| abstract_inverted_index.heritable. | 171 |
| abstract_inverted_index.individual | 77, 154, 217 |
| abstract_inverted_index.processing | 27, 221 |
| abstract_inverted_index.understand | 72 |
| abstract_inverted_index.association | 59 |
| abstract_inverted_index.connections | 22 |
| abstract_inverted_index.connectome. | 55, 209 |
| abstract_inverted_index.connectomes | 38, 178 |
| abstract_inverted_index.differences | 78, 155, 218 |
| abstract_inverted_index.dissociable | 216 |
| abstract_inverted_index.information | 4, 26, 139, 220 |
| abstract_inverted_index.mechanisms. | 28 |
| abstract_inverted_index.monozygotic | 100 |
| abstract_inverted_index.parcel-wise | 148 |
| abstract_inverted_index.represented | 222 |
| abstract_inverted_index.traditional | 147 |
| abstract_inverted_index.vertex-wise | 21 |
| abstract_inverted_index.coarse-scale | 53 |
| abstract_inverted_index.connectivity | 121, 129, 138 |
| abstract_inverted_index.connectomes. | 152 |
| abstract_inverted_index.finer-scale, | 20 |
| abstract_inverted_index.heritability | 237 |
| abstract_inverted_index.implications | 235 |
| abstract_inverted_index.individuals; | 93 |
| abstract_inverted_index.particularly | 61 |
| abstract_inverted_index.reliability, | 113 |
| abstract_inverted_index.transmission | 5 |
| abstract_inverted_index.(vertex-wise) | 137 |
| abstract_inverted_index.coarse-scale, | 167 |
| abstract_inverted_index.developmental | 64 |
| abstract_inverted_index.heritability, | 114 |
| abstract_inverted_index.individuals), | 109 |
| abstract_inverted_index.resting-state | 119 |
| abstract_inverted_index.underpinnings | 75 |
| abstract_inverted_index.hyperalignment | 130 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.5099999904632568 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.80114842 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |