Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics

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Beyond linear regression: mapping models in cognitive neuroscience should align with research goals

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Intermediately synchronised brain states optimise trade-off between subject specificity and predictive capacity

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Using precision approaches to improve brain-behavior prediction

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Genetic influences on the intrinsic and extrinsic functional organizations of the cerebral cortexPreprint

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Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data

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Explainable models of disease progression in ALS: Learning from longitudinal clinical data with recurrent neural networks and deep model explanation

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Unsupervised representation learning of spontaneous MEG data with nonlinear ICA

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Decoding working memory-related information from repeated psychophysiological EEG experiments using convolutional and contrastive neural networks

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Predicting future depressive episodes from resting-state fMRI with generative embedding

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Connectome-based predictive modeling of fluid intelligence: evidence for a global system of functionally integrated brain networks

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Multi-Scale FC-Based Multi-Order GCN: A Novel Model for Predicting Individual Behavior From fMRI

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Exploring the potential of representation and transfer learning for anatomical neuroimaging: Application to psychiatry

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Spatial-Temporal Dynamic Hypergraph Information Bottleneck for Brain Network Classification

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Prediction of total organic acids concentration based on FOS/TAC titration in continuous anaerobic digester fed with food waste using a deep neural network model

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Attention module improves both performance and interpretability of four‐dimensional functional magnetic resonance imaging decoding neural network

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Brain-age models with lower age prediction accuracy have higher sensitivity for disease detection

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A cognitive state transformation model for task-general and task-specific subsystems of the brain connectome

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Decoding task specific and task general functional architectures of the brain

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Deep Neural Regression Prediction of Motor Imagery Skills Using EEG Functional Connectivity Indicators

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Few temporally distributed brain connectivity states predict human cognitive abilities

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Accounting for temporal variability in functional magnetic resonance imaging improves prediction of intelligence

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Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer’s disease—A systematic model evaluation

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Classification and prediction of cognitive performance differences in older age based on brain network patterns using a machine learning approach

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Multilayer meta-matching: Translating phenotypic prediction models from multiple datasets to small data

Chen, P., An, L., Wulan, N., Zhang, C., Zhang, S., Ooi, L. Q. R., Kong, R., Chen, J., Wu, J., Chopra, S., et al. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00233 · Cited by 14

Evaluating deep transfer learning for whole-brain cognitive decoding

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Pattern learning reveals brain asymmetry to be linked to socioeconomic status

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Prediction of cognitive scores by joint use of movie-watching fMRI connectivity and eye tracking via Attention-CensNet

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An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank

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Network-level enrichment provides a framework for biological interpretation of machine learning results

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Anatomical foundation models for brain MRIs

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A Structure–Function Substrate of Memory for Spatial Configurations in Medial and Lateral Temporal Cortices

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Deep Neural Networks Carve the Brain at its JointsPreprint

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Deep learning in resting-state fMRI

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A multicohort geometric deep learning study of age dependent cortical and subcortical morphologic interactions for fluid intelligence prediction

Wu, Y., Besson, P., Azcona, E. A., Bandt, S. K., Parrish, T. B., Breiter, H. C., & Katsaggelos, A. K. (2022) · Scientific Reports · doi:10.1038/s41598-022-22313-x · Cited by 15

Transfer Learning for Neuroimaging via Re-use of Deep Neural Network FeaturesPreprint

Holderrieth, P., Smith, S. M., & Peng, H. (2022) · medRxiv · doi:10.1101/2022.12.11.22283324 · Cited by 10

Is resting state fMRI better than individual characteristics at predicting cognition?Preprint

Omidvarnia, A., Sasse, L., Larabi, D. I., Raimondo, F., Hoffstaedter, F., Kasper, J., Dukart, J., Petersen, M., Cheng, B., Thomalla, G., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.18.529076 · Cited by 10

Enhanced cerebral blood flow similarity of the somatomotor network in chronic insomnia: Transcriptomic decoding, gut microbial signatures and phenotypic roles

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A multi-slice attention fusion and multi-view personalized fusion lightweight network for Alzheimer’s disease diagnosis

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The efficacy of resting-state fMRI denoising pipelines for motion correction and behavioural prediction

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A connectome-based deep learning approach for Early MCI and MCI detection using structural brain networks

Kolahkaj, S., & HodaZare (2023) · Neuroscience Informatics · doi:10.1016/j.neuri.2023.100118 · Cited by 10

A Siamese Network With Node Convolution for Individualized Predictions Based on Connectivity Maps Extracted From Resting-State fMRI Data

Xu, L., Ma, H., Guan, Y., Liu, J., Huang, H., Zhang, Y., & Tian, L. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2023.3304974 · Cited by 9

Individual characteristics outperform resting-state fMRI for the prediction of behavioral phenotypes

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Nonlinear latent representations of high-dimensional task-fMRI data: Unveiling cognitive and behavioral insights in heterogeneous spatial maps

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Transformer3: A Pure Transformer Framework for fMRI-Based Representations of Human Brain Function

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Polygenic Risk, Psychopathology, and Personalized Functional Brain Network Topography in Adolescence

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Computational limits to the legibility of the imaged human brain

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Brain-Age Prediction: Systematic Evaluation of Site Effects, and Sample Age Range and SizePreprint

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Temporal variability of brain–behavior relationships in fine-scale dynamics of edge time series

Cutts, S. A., Chumin, E. J., Betzel, R. F., & Sporns, O. (2025) · Imaging Neuroscience · doi:10.1162/imag_a_00443 · Cited by 7

Translational network neuroscience: Nine roadblocks and possible solutions

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Translating phenotypic prediction models from big to small anatomical MRI data using meta-matching

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A self-supervised deep neural network for image completion resembles early visual cortex fMRI activity patterns for occluded scenes

Svanera, M., Morgan, A., Petro, L. S., & Muckli, L. F. (2021) · Journal of Vision · doi:10.1167/jov.21.7.5 · Cited by 9

Explanatory latent representation of heterogeneous spatial maps of task-fMRI in large-scale datasetsPreprint

Zabihi, M., Kia, S. M., Wolfers, T., de Boer, A. A. A., Fraza, C., Soheili‐Nezhad, S., Dinga, R., Llera, A., Bzdok, D., Beckmann, C. F., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.10.434856 · Cited by 7

Topology-Guided Graph Masked Autoencoder Learning for Population-Based Neurodevelopmental Disorder Diagnosis

Li, Y., Zhang, X., Guan, S., Ma, G., & Kong, Y. (2025) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2025.3562662 · Cited by 7

Beyond network connectivity: A classification approach to brain age prediction with resting-state fMRI

Sorooshyari, S. K. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120570 · Cited by 6

D-MHGCN: An End-to-End Individual Behavioral Prediction Model Using Dual Multi-Hop Graph Convolutional Network

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Measuring the Functioning Human Brain

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Meta-RegGNN: Predicting Verbal and Full-Scale Intelligence Scores Using Graph Neural Networks and Meta-learning

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Deep Recurrent Encoder: an end-to-end network to model magnetoencephalography at scale

Chehab, O., Defossez, A., Loiseau, J.-C., Gramfort, A., & King, J.-R. (2022) · Neurons Behavior Data analysis and Theory · doi:10.51628/001c.38668 · Cited by 8

Performance scaling for structural MRI surface parcellations: a machine learning analysis in the ABCD Study

Hahn, S., Owens, M. M., Yuan, D., Juliano, A., Potter, A., Garavan, H., & Allgaier, N. A. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac060 · Cited by 6

Shared functional connections within and between cortical networks predict cognitive abilities in adult males and femalesPreprint

Dhamala, E., Jamison, K. W., Jaywant, A., & Kuceyeski, A. F. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.17.431670 · Cited by 6

Supervised Phenotype Discovery from Multimodal Brain ImagingPreprint

Gong, W., Bai, S., Zheng, Y., Smith, S. M., & Beckmann, C. F. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.03.458926 · Cited by 6

NeuroAgeFusionNet an ensemble deep learning framework integrating CNN, transformers, and GNN for robust brain age estimation using MRI scans

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Uncertainty-aware multi-view evidence fusion for feature selection in brain network analysis

Chen, Y., Ding, W., Gao, S., Yang, J., Zhou, T., Hua, Q., & Fu, F. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.104083 · Cited by 5

Distinct brain network features predict internalizing and externalizing traits in children, adolescents and adults

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A Multi-Scale Multi-Hop Graph Convolution Network for Predicting Fluid Intelligence via Functional Connectivity

Wen, X., Cao, Q., & Zhang, D. (2022) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm55620.2022.9995097 · Cited by 5

Intermediately Synchronised Brain States optimise trade-off between Subject Identifiability and Predictive CapacityPreprint

Sasse, L., Larabi, D. I., Omidvarnia, A., Jung, K., Hoffstaedter, F., Jocham, G., Eickhoff, S. B., & Patil, K. R. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.30.510304 · Cited by 5

Reliable and generalizable brain-based predictions of cognitive functioning across common psychiatric illnessPreprint

Chopra, S., Dhamala, E., Lawhead, C., Ricard, J. A., Orchard, E. R., An, L., Chen, P., Wulan, N., Kumar, P., Rubenstein, A., et al. (2022) · medRxiv · doi:10.1101/2022.12.08.22283232 · Cited by 5

Distinct brain network features predict internalizing and externalizing traits in children and adultsPreprint

Qu, Y., Chen, J.-Z., Tam, A., Ooi, L., Dhamala, E., Cocuzza, C., Lawhead, C., Yeo, B. T. T., & Holmes, A. (2023) · bioRxiv · doi:10.1101/2023.05.20.541490 · Cited by 4

Digital Twin Brain: Generating Multitask Behavior from Connectomes for Personalized Therapy

Takahashi, Y., Soda, T., Tomita, H., & Yamashita, Y. (2026) · BME Frontiers · doi:10.34133/bmef.0231 · Cited by 4

Finger motor representation supports the autonomy in arithmetic: neuroimaging evidence from abacus training.

Wang, Y., Zhang, Y., Xu, T.-Y., Han, X., Ge, X., & Chen, F.-Y. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhad524 · Cited by 5

Network-based near-scalp personalized brain stimulation targets

Kong, R., Xue, A., Cheng, J., Ooi, L. Q. R., Asplund, C. L., Tan, X. W., Goh, S. E., Lee, J. J., Koh, J. Z. J., Tan, R. S. Y., et al. (2026) · Imaging Neuroscience · doi:10.1162/imag.a.1222 · Cited by 5

Generating synthetic task-based brain fingerprints for population neuroscience using deep learning

Serin, E., Ritter, K., Schumann, G., Banaschewski, T., Marquand, A. F., Walter, H., Schumann, G., Heinz, A., Ralser, M., Twardziok, S. O., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-09158-6 · Cited by 4

Graph Topology Inference Benchmarks for Machine Learning

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Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study

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Stacking models of brain dynamics to improve prediction of subject traits in fMRI

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Predicting Sex from Resting-State fMRI Across Multiple Independent Acquired DatasetsPreprint

Zoubi, O. A., Misaki, M., Tsuchiyagaito, A., Zotev, V. S., White, E. J., Tulsa 1000 Investigators, Paulus, M. P., & Bodurka, J. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.20.259945 · Cited by 4

Improving the reliability of fMRI-based predictions of intelligence via semi-blind machine learningPreprint

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Analysis of Parkinson's Disease Multi-connectivity Brain Functional Networks Based on Graph Convolutional Neural Networks

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Uncovering functional connectivity patterns predictive of cognition in youth using interpretable predictive modeling

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From Big to Small: Emerging Methods for Enhancing Precision Psychiatry Through Transfer Learning

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Accurate and Explainable Image-Based Prediction Using a Lightweight Generative Model

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Is deep learning better than kernel regression for functional connectivity prediction of fluid intelligence?

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Predicting an individual’s functional connectivity from their structural connectome: Evaluation of evidence, recommendations, and future prospects

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The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features

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Discovering individual fingerprints in resting‐state functional connectivity using deep neural networks

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