Back

Individual-level metabolic connectivity captures cortical morphology and their coupling strengthens with age

Facca, M.; Tarricone, C.; Ridolfo, A.; Corbetta, M.; Vlassenko, A. G.; Goyal, M. S.; Bertoldo, A.

2026-03-04 neuroscience
10.64898/2026.03.03.709267 bioRxiv
Show abstract

PurposeCerebral glucose metabolism and cortical morphology are known to undergo significant changes across the lifespan, yet their network-level coordination remains poorly understood. This study aimed to investigate whether individual-level metabolic connectivity (MC) reflects underlying inter-areal morphometric similarity, and to determine how this metabolic-morphometric coupling evolves across the adult lifespan. MethodsDynamic [18F]FDG-PET and structural MRI data were acquired from 67 healthy adults (age range: 38-86 years). Individual MC networks were estimated based on the similarity between regional time-activity curves. Corresponding structural similarity networks were generated using the morphometric inverse divergence (MIND) framework, which integrates multiple vertex-wise features of cortical morphology. The correspondence between metabolic and structural networks was quantified at both global and local scales using Spearman correlations. General linear models were employed to assess age-related effects on MC-MIND similarity. ResultsMC demonstrated a robust positive association with cortical morphometric similarity ({rho} = 0.32, p < 0.0001), an association that persisted after distance correction and was replicated at the individual level. Regional coupling followed a topographic gradient, peaking in heteromodal association cortices and reaching its minimum in paralimbic areas. Crucially, morphology-metabolism alignment systematically strengthened with age at the global level ({beta} = 0.59, p < 0.001). Local age-related increases were spatially heterogeneous, predominantly affecting visual, dorsal parietal, and premotor cortices alongside adjacent multimodal regions. ConclusionIndividual-level MC captures the morphometric organisation of the brain. The age-related increase in morphology-metabolism coupling indicates that metabolic coordination becomes progressively more aligned with cortical architecture, consistent with reduced neuroenergetic flexibility in the ageing brain.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Human Brain Mapping
295 papers in training set
Top 0.1%
28.6%
2
NeuroImage: Clinical
132 papers in training set
Top 0.3%
10.4%
3
NeuroImage
813 papers in training set
Top 2%
7.4%
4
Frontiers in Aging Neuroscience
67 papers in training set
Top 0.4%
7.0%
50% of probability mass above
5
Imaging Neuroscience
242 papers in training set
Top 0.5%
6.6%
6
Scientific Reports
3102 papers in training set
Top 34%
3.7%
7
Brain Structure and Function
83 papers in training set
Top 0.1%
2.7%
8
Communications Biology
886 papers in training set
Top 6%
2.0%
9
GeroScience
97 papers in training set
Top 0.8%
2.0%
10
Cerebral Cortex
357 papers in training set
Top 0.7%
1.8%
11
Frontiers in Human Neuroscience
67 papers in training set
Top 1%
1.7%
12
Brain Research
35 papers in training set
Top 0.9%
1.5%
13
Network Neuroscience
116 papers in training set
Top 0.7%
1.4%
14
Neurobiology of Aging
95 papers in training set
Top 1%
1.4%
15
PLOS ONE
4510 papers in training set
Top 59%
1.3%
16
PLOS Computational Biology
1633 papers in training set
Top 21%
1.0%
17
Aging Cell
144 papers in training set
Top 3%
0.9%
18
Psychophysiology
64 papers in training set
Top 0.4%
0.8%
19
eneuro
389 papers in training set
Top 9%
0.8%
20
Cortex
102 papers in training set
Top 0.5%
0.8%
21
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
62 papers in training set
Top 1%
0.8%
22
Translational Psychiatry
219 papers in training set
Top 4%
0.7%
23
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 44%
0.7%
24
Advanced Science
249 papers in training set
Top 21%
0.7%
25
The Journal of Neuroscience
928 papers in training set
Top 9%
0.5%
26
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
38 papers in training set
Top 1%
0.5%