Context
Adult male, born preterm in 1974 (~1.5 kg, no incubator). Lifelong sensory hypersensitivity (cutaneous, emotional, interoceptive) and chronic fatigue with preserved cognitive and physical function.
MRI performed at 3 T (isotropic T1).
Processing independently conducted for research purposes using FreeSurfer 7.4, CAT12 v12, and volBrain v1.
Main structural findings (consistent across methods)
- Lateral ventricles: Left = 5,585 mm³ | Right = 10,051 mm³ → ~80 % asymmetry.
- Amygdala: Left = 575 mm³ | Right = 1,674 mm³ → ~191 % asymmetry.
- Thalamus: Left = 14,141 mm³ | Right = 12,277 mm³.
- Hippocampus: Left = 3,795 mm³ | Right = 4,175 mm³ → relatively preserved.
- Global cortical volume: 257,528 mm³ (within normal range).
- Cortical thickness mean: ≈ 1.68 mm bilaterally.
- WM-hypointensities: 76,225 mm³ (moderate for age 51).
- Intracranial volume (eTIV): 1,875,692 mm³ → BrainSeg/eTIV = 0.867.
Amygdala subnuclei (FreeSurfer v22 module segmentHA_T1.sh)
- Lateral nucleus: Left = 535 mm³ | Right = 1,009 mm³ → +88.5 %
- Basal nucleus: Left = 338 mm³ | Right = 475 mm³
- Whole amygdala: Left = 1,374 mm³ | Right = 2,160 mm³ → +57 %
This subnuclear pattern indicates that the asymmetry is primarily driven by the right lateral nucleus hypertrophy, the amygdaloid component most related to sensory-emotional input and associative learning.
Disconnectome estimate
Lesion-based structural disconnectivity models suggest ≈ 80 % thalamo-cortical and fronto-limbic disconnection on the right hemisphere, coherent with the volumetric asymmetries above.
Functional context
Despite these findings:
- Resting heart rate ≈ 46 bpm — athlete-level parasympathetic tone, verified by cardiological assessment.
- Federated athlete (football, endurance sports).
- University degree and stable professional activity.
The coexistence of major limbic and ventricular asymmetries with intact cognitive and physical performance suggests long-term compensatory reorganization rather than pathology.
Aim of posting
- To ask whether similar extreme yet functional asymmetries have been documented in the literature or public datasets.
- To inquire which tract-based or connectivity-based tools (e.g. RTP2, MRtrix, FSL) could best complement this morphometric evidence, given that DWI data are currently limited.
- To discuss how such findings are interpreted in non-clinical research frameworks (plasticity, compensatory adaptation, neurodevelopmental resilience).
Notes
This post is not for medical diagnosis but for methodological discussion on individual-level morphometry.
Raw output files (aseg.stats, aparc.stats, CAT12 and volBrain reports) are available upon request for scientific verification.
All analyses were performed personally, without institutional support; I am neither a neuroscientist nor a computer scientist, so apologies for any technical inaccuracies.