# Brain Age Prediction

In two-view data, each view has its own covariance and a cross-view covariance links them, yet covariance neural networks handled only single-view data and could not distinguish these structures once the views were concatenated. CANE splits the model into an in-view covariance filtering stage and a cross-view covariance filtering stage, replacing the whitening and singular-vector selection of canonical correlation analysis with learnable polynomial responses on the covariance spectrum, and trains directly on the downstream task. Across seven brain-imaging and motion-sensing datasets, CANE is best or tied for best on six, reaching a mean absolute error of 4.97 years for age prediction on ADNI1, often with fewer parameters than a two-view VNN.

In two-view data, each view has its own covariance and a cross-view covariance links them, yet covariance neural networks handled only single-view data and could not distinguish these structures once the views were concatenated. CANE splits the model into an in-view covariance filtering stage and a cross-view covariance filtering stage, replacing the whitening and singular-vector selection of canonical correlation analysis with learnable polynomial responses on the covariance spectrum, and trains directly on the downstream task. Across seven brain-imaging and motion-sensing datasets, CANE is best or tied for best on six, reaching a mean absolute error of 4.97 years for age prediction on ADNI1, often with fewer parameters than a two-view VNN.

Brain-connectivity differences in autism and other neurodevelopmental disorders have mostly been read from group-average case-control contrasts, which flatten individual variation. BRIDGE combines a graph variational autoencoder with normative modeling to learn an age-varying reference trajectory of structural connectomes from 1,164 neurotypical participants, then reports a global deviation score from brain-age difference and an individualized regional deviation map from regional embeddings. In 229 autistic children, the global score correlated with ADOS (Spearman R=−0.291) and IQ (Pearson R=0.195) in males, and brain-age prediction error was 3%–9% lower than comparable deep-learning models.

Brain-connectivity differences in autism and other neurodevelopmental disorders have mostly been read from group-average case-control contrasts, which flatten individual variation. BRIDGE combines a graph variational autoencoder with normative modeling to learn an age-varying reference trajectory of structural connectomes from 1,164 neurotypical participants, then reports a global deviation score from brain-age difference and an individualized regional deviation map from regional embeddings. In 229 autistic children, the global score correlated with ADOS (Spearman R=−0.291) and IQ (Pearson R=0.195) in males, and brain-age prediction error was 3%–9% lower than comparable deep-learning models.

Brain-age models trained mostly on Global North data lose accuracy when applied to Nigerian adults. A population-specific Gaussian process regression model trained on clinical T1-weighted MRI from 309 Nigerian adults reached a mean absolute error of 9.82 years on a 47-participant held-out test set without age-bias correction; on the 44-participant head-to-head set it reached 10.24 years, against 10.52 years for PyBrainAge, 12.33 for SynthBA, 17.51 for ENIGMA-Brain Age and 7.87 for SPARROW. After correction it reached 6.39 years internally but 8.78 years on a separate Nigerian cohort, where every model's R2 was negative.

Brain-age models trained mostly on Global North data lose accuracy when applied to Nigerian adults. A population-specific Gaussian process regression model trained on clinical T1-weighted MRI from 309 Nigerian adults reached a mean absolute error of 9.82 years on a 47-participant held-out test set without age-bias correction; on the 44-participant head-to-head set it reached 10.24 years, against 10.52 years for PyBrainAge, 12.33 for SynthBA, 17.51 for ENIGMA-Brain Age and 7.87 for SPARROW. After correction it reached 6.39 years internally but 8.78 years on a separate Nigerian cohort, where every model's R2 was negative.