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

By Bertrand Thirion, Edouard Duchesnay, Edward M. Hubbard, Jessica Dubois, Jean-Baptiste Poline, Denis Le Bihan, Stanislas Dehaene. NeuroImage, 2006

377 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/e665ee88047777155acbc4ec3606f7fde23c84a1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. John-Dylan Haynes
2. Nikolaus Kriegeskorte
3. Shinji Nishimoto
4. Jack L. Gallant
5. Thomas Naselaris
6. James V. Haxby
7. Kendrick Norris Kay
8. Yukiyasu Kamitani

Citations in the corpus

• Visual image reconstruction from human brain activity using a combination of multiscale local image decoders. (2008, methodology): “To further quantify reconstruction performance, we conducted image identification analysis (Kay et al., 2008; Thirion et al., 2006) in which the presented image was identified among a number of candidate images using an fMRI activity pattern (Figure 3A).”
• Decoding brain states from fMRI connectivity graphs (2011, background): “…on a classi fi er to predict the subject's brain state from the BOLD responses in a set of selected voxels, such as visual (Cox and Savoy, 2003; Haynes and Rees, 2005; Kamitani and Tong, 2005; Thirion et al., 2006; Kay et al., 2008; Miyawaki et al., 2008) or auditory cortices (Ethofer et al., 2009).”
• Reconstructing visual experiences from brain activity evoked by natural movies (2011, positive): “[6] first reconstructed static imaginary patterns from BOLD signals in early visual areas.”
• Visual field maps in human cortex. (2007, positive): “Thirion et al. (2006) developed an analysis to use all the time-series information to decode the visual stimulus in the occipital lobe.”
• Bayesian reconstruction of natural images from human brain activity (2009, neutral): “This property of fMRI makes it an excellent tool for brain reading, in which the responses of multiple voxels are used to decode the stimulus that evoked them (Haxby et al., 2001; Carlson et al., 2002; Cox and Savoy, 2003; Haynes and Rees, 2005; Kamitani and Tong, 2005; Thirion et al., 2006; Kay et ”
• Encoding and decoding in fMRI (2010, methodology): “(See Thirion et al., 2006 for a similar study.)”
• Imaging retinotopic maps in the human brain (2010, methodology): “A recent approach is to replace the subtraction methodology with more extensive models aimed at improving our understanding of the neural computations performed within the visual pathways (Dumoulin & Wandell, 2008; Kay, Naselaris, Prenger, & Gallant, 2008; Smith et al., 2001; Thirion et al., 2006 ).”
• Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream (2014, background): “…DNN-based decoding of stimuli from neural activity patterns may allow probing of internally generated percepts that occur during, e.g., imagery (Thirion et al., 2006), memory retrieval (Harrison and Tong, 2009), visual illusions (Kok and de Lange, 2014), and dreaming (Horikawa et al., 2013),…”
• A voxel-wise encoding model for early visual areas decodes mental images of remembered scenes (2014, positive): “Most studies on mental imagery have in fact adopted this approach, using extremely reduced visual stimuli such as blobs (Thirion et al., 2006), wedges (Slotnick et al.”
• Cognitive computational neuroscience (2018, background): “A particularly impressive form of decoding is stimulus reconstruction.(87,88,89) Like ordinary decoding, reconstruction maps brain activity patterns to stimuli.”
• Population receptive field estimates in human visual cortex (2008, methodology): “Furthermore, we note that some investigators include visual field maps and 2D Gaussian pRF models in algorithms for inferring the stimulus from the fMRI response (Thirion et al., 2006).”
• Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision (2016, methodology): “Thus, the decoding in this study does not simply invert retinotopy (Thirion et al. 2006) to reconstruct the original image, but tends to reconstruct the image parts relevant to visual perception.”
• Identifying natural images from human brain activity (2008, background): “(3) Select the image ( ) whose predicted brain activity is most similar to the measured brain activity Measured voxel activity pattern Brain Image”