Paper Citation Record · LEDGER

A Review of Latent Representation Models in Neuroimaging

As of 20 August 2026, this Paper Citation Record lists 81 of 81 outbound references and 2 inbound Pith citation observations for arXiv:2412.19844.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.19844 v1

Coverage vector

measured 81 of 81 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:38:38.949993Z

measured 83 of 83 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:40:35.374309Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T23:52:17.214177Z

Reference resolution

81 of 81 outbound references displayed

verified exact1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6fdd937d-583b-4c06-b16c-2ffd85e8b469 · outbound

This paper cites Medgan: Medical image translation using gans.

A Review of Latent Representation Models in Neuroimaging Medgan: Medical image translation using gans

Reference 1

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This paper cites 7t-guided super- resolution of 3t mri.

A Review of Latent Representation Models in Neuroimaging 7t-guided super- resolution of 3t mri

Reference 2

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This paper cites Re- construction of 7t-like images from 3t mri.

A Review of Latent Representation Models in Neuroimaging Re- construction of 7t-like images from 3t mri

Reference 3

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This paper cites Early prediction of alzheimer’s disease progression using variational autoencoders.

A Review of Latent Representation Models in Neuroimaging Early prediction of alzheimer’s disease progression using variational autoencoders

Reference 4

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A Review of Latent Representation Models in Neuroimaging Unresolved cited work

Reference 5

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This paper cites Dissecting psychiatric spectrum disorders by generative embedding.

A Review of Latent Representation Models in Neuroimaging Dissecting psychiatric spectrum disorders by generative embedding

Reference 6

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This paper cites The economy of brain network organization.

A Review of Latent Representation Models in Neuroimaging The economy of brain network organization

Reference 7

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This paper cites Imunity: a general- izable vae-gan solution for multicenter mr image harmonization.

A Review of Latent Representation Models in Neuroimaging Imunity: a general- izable vae-gan solution for multicenter mr image harmonization

Reference 8

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A Review of Latent Representation Models in Neuroimaging Unresolved cited work

Reference 9

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This paper cites t-bne: Tensor-based brain network embedding.

A Review of Latent Representation Models in Neuroimaging t-bne: Tensor-based brain network embedding

Reference 10

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This paper cites An image feature mapping model for continuous longitudinal data completion and generation of synthetic patient trajectories.

A Review of Latent Representation Models in Neuroimaging An image feature mapping model for continuous longitudinal data completion and generation of synthetic patient trajectories

Reference 11

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This paper cites Predicting aging of brain metabolic topography using variational autoencoder.

A Review of Latent Representation Models in Neuroimaging Predicting aging of brain metabolic topography using variational autoencoder

Reference 12

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This paper cites Neural population geometry: An approach for understanding biological and artificial neural networks.

A Review of Latent Representation Models in Neuroimaging Neural population geometry: An approach for understanding biological and artificial neural networks

Reference 13

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This paper cites Abductive inference and delusional belief.Cognitive neuropsychiatry, 15(1-3):261–287, 2010.

A Review of Latent Representation Models in Neuroimaging Abductive inference and delusional belief.Cognitive neuropsychiatry, 15(1-3):261–287, 2010

Reference 14

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This paper cites Reduced prefrontal-parietal effective connectivity and working memory deficits in schizophrenia.

A Review of Latent Representation Models in Neuroimaging Reduced prefrontal-parietal effective connectivity and working memory deficits in schizophrenia

Reference 15

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This paper cites A disentangled latent space for cross-site mri harmonization.

A Review of Latent Representation Models in Neuroimaging A disentangled latent space for cross-site mri harmonization

Reference 16

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This paper cites Discover- ing functional brain networks with 3d residual autoencoder (resae).

A Review of Latent Representation Models in Neuroimaging Discover- ing functional brain networks with 3d residual autoencoder (resae)

Reference 17

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This paper cites Spatiotemporal attention autoencoder (staae) for adhd classification.

A Review of Latent Representation Models in Neuroimaging Spatiotemporal attention autoencoder (staae) for adhd classification

Reference 18

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This paper cites Multimodal analysis of func- tional and structural disconnection in a lzheimer’s disease using multiple kernel svm.

A Review of Latent Representation Models in Neuroimaging Multimodal analysis of func- tional and structural disconnection in a lzheimer’s disease using multiple kernel svm

Reference 19

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This paper cites On bias, variance, 0/1—loss, and the curse-of-dimensionality.

A Review of Latent Representation Models in Neuroimaging On bias, variance, 0/1—loss, and the curse-of-dimensionality

Reference 20

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This paper cites Learning and inference in the brain.

A Review of Latent Representation Models in Neuroimaging Learning and inference in the brain

Reference 21

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This paper cites A theory of cortical responses.

A Review of Latent Representation Models in Neuroimaging A theory of cortical responses

Reference 22

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This paper cites Computational and dynamic models in neuroimaging.

A Review of Latent Representation Models in Neuroimaging Computational and dynamic models in neuroimaging

Reference 23

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A Review of Latent Representation Models in Neuroimaging Generative models, brain function and neuroimaging

Reference 24

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This paper cites Fusing multimodal neuroimaging data with a variational autoencoder.

A Review of Latent Representation Models in Neuroimaging Fusing multimodal neuroimaging data with a variational autoencoder

Reference 25

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This paper cites The generative adversarial brain.

A Review of Latent Representation Models in Neuroimaging The generative adversarial brain

Reference 26

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This paper cites Bridging imaging, genetics, and diagnosis in a coupled low-dimensional framework.

A Review of Latent Representation Models in Neuroimaging Bridging imaging, genetics, and diagnosis in a coupled low-dimensional framework

Reference 27

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This paper cites Generative adversarial nets.

A Review of Latent Representation Models in Neuroimaging Generative adversarial nets

Reference 28

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This paper cites Decoding natural image stimuli from fMRI data with a surface-based convolutional network.

A Review of Latent Representation Models in Neuroimaging Decoding natural image stimuli from fMRI data with a surface-based convolutional network

Reference 29

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This paper cites Mindldm: Reconstruct visual stimuli from fmri using latent diffusion model.

A Review of Latent Representation Models in Neuroimaging Mindldm: Reconstruct visual stimuli from fmri using latent diffusion model

Reference 30

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This paper cites Variational autoencoder: An unsupervised model for encoding and decoding fmri activity in visual cortex.

A Review of Latent Representation Models in Neuroimaging Variational autoencoder: An unsupervised model for encoding and decoding fmri activity in visual cortex

Reference 31

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This paper cites Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity.

A Review of Latent Representation Models in Neuroimaging Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity

Reference 32

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This paper cites Gene-to-image: Decoding brain images from genetics via latent diffusion models.

A Review of Latent Representation Models in Neuroimaging Gene-to-image: Decoding brain images from genetics via latent diffusion models

Reference 33

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This paper cites Mr image synthesis by contrast learning on neighborhood ensembles.

A Review of Latent Representation Models in Neuroimaging Mr image synthesis by contrast learning on neighborhood ensembles

Reference 34

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This paper cites Optimal anticipatory control as a theory of motor preparation: A thalamo-cortical circuit model.

A Review of Latent Representation Models in Neuroimaging Optimal anticipatory control as a theory of motor preparation: A thalamo-cortical circuit model

Reference 35

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This paper cites Brainnetcnn: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

A Review of Latent Representation Models in Neuroimaging Brainnetcnn: Convolutional neural networks for brain networks; towards predicting neurodevelopment

Reference 36

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This paper cites Neural processes underlying memory attribution on a reality-monitoring task.

A Review of Latent Representation Models in Neuroimaging Neural processes underlying memory attribution on a reality-monitoring task

Reference 37

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This paper cites Adaptive latent diffusion model for 3d medical image to image translation: Multi-modal magnetic resonance imaging study.

A Review of Latent Representation Models in Neuroimaging Adaptive latent diffusion model for 3d medical image to image translation: Multi-modal magnetic resonance imaging study

Reference 38

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This paper cites Auto-Encoding Variational Bayes.

A Review of Latent Representation Models in Neuroimaging Auto-Encoding Variational Bayes

Reference 39

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This paper cites Metric learning with spectral graph convolutions on brain connectivity networks.

A Review of Latent Representation Models in Neuroimaging Metric learning with spectral graph convolutions on brain connectivity networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:40.583639Z

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This paper cites Autoen- coding beyond pixels using a learned similarity metric.

A Review of Latent Representation Models in Neuroimaging Autoen- coding beyond pixels using a learned similarity metric

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:40.564550Z

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This paper cites Latent factor decoding of multi-channel eeg for emotion recognition through autoencoder-like neural networks.

A Review of Latent Representation Models in Neuroimaging Latent factor decoding of multi-channel eeg for emotion recognition through autoencoder-like neural networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:40.545016Z

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This paper cites Uncovering Hidden Dimensions in Brain Signals.

A Review of Latent Representation Models in Neuroimaging Uncovering Hidden Dimensions in Brain Signals

Reference 43

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This paper cites Is image-to-image translation the panacea for multimodal image registration? a comparative study.

A Review of Latent Representation Models in Neuroimaging Is image-to-image translation the panacea for multimodal image registration? a comparative study

Reference 44

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This paper cites Neu- rocognitive latent space regularization for multi-label diagnosis from mri.

A Review of Latent Representation Models in Neuroimaging Neu- rocognitive latent space regularization for multi-label diagnosis from mri

Reference 45

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This paper cites Least squares generative adversarial networks.

A Review of Latent Representation Models in Neuroimaging Least squares generative adversarial networks

Reference 46

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This paper cites Bridging imaging and clinical scores in parkinson’s progression via multimodal self-supervised deep learning.

A Review of Latent Representation Models in Neuroimaging Bridging imaging and clinical scores in parkinson’s progression via multimodal self-supervised deep learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:40.177921Z

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This paper cites Deep neural generative model of func- tional mri images for psychiatric disorder diagnosis.

A Review of Latent Representation Models in Neuroimaging Deep neural generative model of func- tional mri images for psychiatric disorder diagnosis

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:40.156893Z

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Observation d4253f0d-e541-417b-94f3-bf37166429f8 · outbound

This paper cites Parametric empirical bayes inference: theory and applications.

A Review of Latent Representation Models in Neuroimaging Parametric empirical bayes inference: theory and applications

Reference 49

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Observation 00327bd0-b165-4fdb-afa8-e1ad618a0382 · outbound

This paper cites Medical Image Com- puting and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III , volume 9351.

A Review of Latent Representation Models in Neuroimaging Medical Image Com- puting and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III , volume 9351

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:40.109448Z

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Observation 3b79396c-1263-4170-84c8-60405421fe57 · outbound

This paper cites Natural scene reconstruction from fmri signals using generative latent diffusion.

A Review of Latent Representation Models in Neuroimaging Natural scene reconstruction from fmri signals using generative latent diffusion

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A Review of Latent Representation Models in Neuroimaging Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-11T04:38:40.075597Z

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This paper cites Brain imaging generation with latent diffusion models.

A Review of Latent Representation Models in Neuroimaging Brain imaging generation with latent diffusion models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:40.057105Z

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This paper cites Does the chimpanzee have a theory of mind? Behavioral and brain sciences, 1(4):515–526, 1978.

A Review of Latent Representation Models in Neuroimaging Does the chimpanzee have a theory of mind? Behavioral and brain sciences, 1(4):515–526, 1978

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This paper cites Deep variational autoencoder for mapping functional brain networks.

A Review of Latent Representation Models in Neuroimaging Deep variational autoencoder for mapping functional brain networks

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This paper cites Wavelet-based semi-supervised adversarial learning for synthesizing realistic 7t from 3t mri.

A Review of Latent Representation Models in Neuroimaging Wavelet-based semi-supervised adversarial learning for synthesizing realistic 7t from 3t mri

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Observation 65869fe1-8861-46ad-9e20-94cc295d3b2a · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

A Review of Latent Representation Models in Neuroimaging Learning Transferable Visual Models From Natural Language Supervision

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This paper cites Three laws of qualia: What neurology tells us about the biological functions of consciousness.

A Review of Latent Representation Models in Neuroimaging Three laws of qualia: What neurology tells us about the biological functions of consciousness

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This paper cites Nonlinear dimensionality reduction by locally linear embed- ding.

A Review of Latent Representation Models in Neuroimaging Nonlinear dimensionality reduction by locally linear embed- ding

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.879197Z

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This paper cites Palette: Image-to-image diffusion models.

A Review of Latent Representation Models in Neuroimaging Palette: Image-to-image diffusion models

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This paper cites Generative adversarial networks for reconstructing natural images from brain activity.

A Review of Latent Representation Models in Neuroimaging Generative adversarial networks for reconstructing natural images from brain activity

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This paper cites The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

A Review of Latent Representation Models in Neuroimaging The feature-weighted receptive field: an interpretable encoding model for complex feature spaces

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This paper cites Generative adversarial networks conditioned on brain activity reconstruct seen images.

A Review of Latent Representation Models in Neuroimaging Generative adversarial networks conditioned on brain activity reconstruct seen images

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.796769Z

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This paper cites Discriminating schizophrenia and bipolar disorder by fusing fmri and dti in a multimodal cca+ joint ica model.

A Review of Latent Representation Models in Neuroimaging Discriminating schizophrenia and bipolar disorder by fusing fmri and dti in a multimodal cca+ joint ica model

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This paper cites High-resolution image reconstruction with latent diffusion models from human brain activity.

A Review of Latent Representation Models in Neuroimaging High-resolution image reconstruction with latent diffusion models from human brain activity

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This paper cites A global geometric framework for nonlinear dimensionality reduction.

A Review of Latent Representation Models in Neuroimaging A global geometric framework for nonlinear dimensionality reduction

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This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

A Review of Latent Representation Models in Neuroimaging Gomez, Lukasz Kaiser, and Illia Polosukhin

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Observation b98e39e0-12f5-4d72-ad9b-a04cdee513f0 · outbound

This paper cites Modelling the distribution of 3d brain mri using a 2d slice vae.

A Review of Latent Representation Models in Neuroimaging Modelling the distribution of 3d brain mri using a 2d slice vae

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Observation 6d4cdbdd-8abb-4fa7-b314-e7e2c84bd061 · outbound

This paper cites Spatial-intensity transforms for medical image-to-image translation.

A Review of Latent Representation Models in Neuroimaging Spatial-intensity transforms for medical image-to-image translation

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Observation 9ae9740c-e2e3-488f-a265-e25a2b53e3b4 · outbound

This paper cites Comparison and evaluation of retrospective intermodality brain image registration techniques.Jour- nal of computer assisted tomography , 21(4):554–568, 1997.

A Review of Latent Representation Models in Neuroimaging Comparison and evaluation of retrospective intermodality brain image registration techniques.Jour- nal of computer assisted tomography , 21(4):554–568, 1997

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This paper cites Disentangled Latent Energy-Based Style Translation: An Image-Level Structural MRI Harmonization Framework.

A Review of Latent Representation Models in Neuroimaging Disentangled Latent Energy-Based Style Translation: An Image-Level Structural MRI Harmonization Framework

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This paper cites Consistent brain ageing synthesis.

A Review of Latent Representation Models in Neuroimaging Consistent brain ageing synthesis

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.640206Z

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Observation fc099dda-2601-45aa-a6e8-51d1bfeccd54 · outbound

This paper cites Mri cross- modality image-to-image translation.

A Review of Latent Representation Models in Neuroimaging Mri cross- modality image-to-image translation

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.606167Z

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Observation 4d1b7fed-10be-4196-bd2c-6d0934ac9d1a · outbound

This paper cites Neural mechanisms of belief inference during cooperative games.

A Review of Latent Representation Models in Neuroimaging Neural mechanisms of belief inference during cooperative games

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.491939Z

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Observation 10924ac4-3602-421a-a024-40085a59ee22 · outbound

This paper cites Skrgan: Sketching-rendering unconditional generative adversarial networks for medical image synthesis.

A Review of Latent Representation Models in Neuroimaging Skrgan: Sketching-rendering unconditional generative adversarial networks for medical image synthesis

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.387629Z

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Observation 6a7a57e6-e3e8-40a7-8f26-6ed71fbddd08 · outbound

This paper cites Deep representation learning for multi- modal brain networks.

A Review of Latent Representation Models in Neuroimaging Deep representation learning for multi- modal brain networks

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.314024Z

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Observation 88e64d48-9252-4177-94ee-fdf825b0ceff · outbound

This paper cites Dual-domain cascaded regression for synthesizing 7t from 3t mri.

A Review of Latent Representation Models in Neuroimaging Dual-domain cascaded regression for synthesizing 7t from 3t mri

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.289061Z

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Observation 542738a6-e052-4c63-b331-88c3615b800f · outbound

This paper cites Deep multi-modal latent representation learning for automated dementia diagnosis.

A Review of Latent Representation Models in Neuroimaging Deep multi-modal latent representation learning for automated dementia diagnosis

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.269125Z

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Observation cb32ca53-44ab-49d3-9d05-46d84a087c6b · outbound

This paper cites Make- a-volume: Leveraging latent diffusion models for cross-modality 3d brain mri synthesis.

A Review of Latent Representation Models in Neuroimaging Make- a-volume: Leveraging latent diffusion models for cross-modality 3d brain mri synthesis

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.249317Z

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Observation a3b1a1ec-1e3d-493b-8409-024ff2553554 · outbound

This paper cites Unsupervised anomaly localization using variational auto-encoders.

A Review of Latent Representation Models in Neuroimaging Unsupervised anomaly localization using variational auto-encoders

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.231745Z

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Observation 68c435fd-235e-42de-ae52-dcdca4de55ea · outbound

This paper cites Unsupervised mr harmonization by learning disentangled representations using information bottleneck theory.

A Review of Latent Representation Models in Neuroimaging Unsupervised mr harmonization by learning disentangled representations using information bottleneck theory

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T04:38:39.213462Z

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Pith citing papers

Observation e8ed3f1d-980c-43a9-af6d-c94ea5033a17 · inbound

Characterizing higher-order representations through generative diffusion models explains human decoded neurofeedback performance cites this paper.

Characterizing higher-order representations through generative diffusion models explains human decoded neurofeedback performance A Review of Latent Representation Models in Neuroimaging

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Resolution: verified exact; arxiv_id, observed 2026-05-22T23:52:17.217546Z

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Observation 02bb0e23-9d31-4fcb-b8a3-2dd47946863f · inbound

How brains build higher order representations of uncertainty cites this paper.

How brains build higher order representations of uncertainty A Review of Latent Representation Models in Neuroimaging

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Resolution: unresolved; no resolver link, observed 2026-08-15T18:40:35.374309Z

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