Inverse retinotopy: Inferring the visual content of images from brain activation patterns

Manfred Nettekoven, Ulrich Hackenberg, Entwicklungsvorstand Marke Volkswagen · NeuroImage · 2006

Summary

This work uses the well-known retinotopy of the visual cortex to infer the visual content of real or imaginary scenes from the brain activation patterns that they elicit, and presents two decoding algorithms that could reconstruct and predict with significant accuracy a pattern imagined by the subjects.

Type: article
Published: 2006-12-01
Cited by: 377
References: 40
DOI: https://doi.org/10.1016/j.neuroimage.2006.06.062
PubMed: https://pubmed.ncbi.nlm.nih.gov/17029988/
OpenAlex: https://openalex.org/W17029988
Semantic Scholar: https://api.semanticscholar.org/CorpusID:13361917

Keywords

Plenary session, Political science, Computer science, Library science

References

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Cited by

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The Fusion of Mental Imagery and Sensation in the Temporal Association CortexMarshall Alhassan Adams, Craig C. Brandt, S.W. Christensen — 2014
Reconstruction of Arm Movement Directions from Human Motor Cortex Using fMRIM. Rajagopalan — 2017
Multimodal evidence on shape and surface information in individual face processingОльга Москалева — 2018
Similarities and differences between imagery and perceptionin early and late visual cortexAnke Marit Albers — 2011
Feature selection and classification of imbalanced datasets: Application to PET images of children with autistic spectrum disordersÉdouard Duchesnay, Arnaud Cachia, Nathalie Boddaert — 2011
Generating descriptive text from functional brain imagesFrancisco Pereira, Greg Detre, Matthew Botvinick — 2011
エンコーディングモデルを用いた視覚情報処理研究：情報表現，予測，デコーディングShinji Nishimoto — 2012
Understanding the visual cortex by using classification techniques. (Améliorer la compréhension du cortex visuel à l'aide de techniques de classification)Vincent Michel — 2010
Large-scale functional MRI analysis to accumulate knowledge on brain functions. (Analyse à grande échelle d'IRM fonctionnelle pour accumuler la connaissance sur les fonctions cérébrales)Yannick Schwartz — 2015
Scene Vision: Making Sense of What We SeeK. Kveraga, M. Bar — 2014
Visual scene recognition with biologically relevant generative modelsTayyaba Azim — 2014
Understanding the Role of Top-Down Attentional Modulation in the Acquisition and Transfer of Perceptual Learning /Anna Byers — 2014
Hidden Markov Models for Reading Words from the Human BrainSanne Schoenmakers, Tom Heskes, Marcel van Gerven — 2015
Neural convergence and divergence in the mammalian cerebral cortex: from experimental neuroanatomy to functional neuroimagingKingson Man, Jonas Kaplan, Hanna Damásio — 2013
Retinopatia, a imagem como sintoma, o desenho como cicatrizPaulo Oliveira Freire Almeida — 2013
A Genetic algorithm based feature selection technique for classification of multiple-subject fMRI dataI V Accamma, H. N. Suma, M. Dakshayini — 2015
Sparse models for visual image reconstruction from fMRI activityLinyuan Wang, Li Tong, Bin Yan — 2014
A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives.John–Dylan Haynes — 2015
Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral StreamU. Guclu, Marcel van Gerven — 2014

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