Attentionally modulated subjective images reconstructed from brain activity | bioRxiv

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Visual image reconstruction from brain activity produces images whose features are consistent with the neural representations in the visual cortex given arbitrary visual instances [[1][1]–[3][2]], presumably reflecting the person’s visual experience. Previous reconstruction studies have been concerned either with how stimulus images are faithfully reconstructed or with whether mentally imagined contents can be reconstructed in the absence of external stimuli. However, many lines of vision research have demonstrated that even stimulus perception is shaped both by stimulus-induced processes and top-down processes. In particular, attention (or the lack of it) is known to profoundly affect visual experience [[4][3]–[8][4]] and brain activity [[9][5]–[21][6]]. Here, to investigate how top-down attention impacts the neural representation of visual images and the reconstructions, we use a state-of-the-art method (deep image reconstruction [[3][2]]) to reconstruct visual images from fMRI activity measured while subjects attend to one of two images superimposed with equally weighted contrasts. Deep image reconstruction exploits the hierarchical correspondence between the brain and a deep neural network (DNN) to translate (decode) brain activity into DNN features of multiple layers, and then create images that are consistent with the decoded DNN features [[3][2], [22][7], [23][8]]. Using the deep image reconstruction model trained on fMRI responses to single natural images, we decode brain activity during the attention trials. Behavioral evaluations show that the reconstructions resemble the attended rather than the unattended images. The reconstructions can be modeled by superimposed images with contrasts biased to the attended one, which are comparable to the appearance of the stimuli under attention measured in a separate session. Attentional modulations are found in a broad range of hierarchical visual representations and mirror the brain–DNN correspondence. Our results demonstrate that top-down attention counters stimulus-induced responses and modulate neural representations to render reconstructions in accordance with subjective appearance. The reconstructions appear to reflect the content of visual experience and volitional control, opening a new possibility of brain-based communication and creation. ### Competing Interest Statement The authors have declared no competing interest. [1]: #ref-1 [2]: #ref-3 [3]: #ref-4 [4]: #ref-8 [5]: #ref-9 [6]: #ref-21 [7]: #ref-22 [8]: #ref-23

Attentionally modulated subjective images reconstructed from brain activity | bioRxiv Skip to main content New Results Attentionally modulated subjective images reconstructed from brain activity View ORCID Profile Tomoyasu Horikawa , View ORCID Profile Yukiyasu Kamitani doi: https://doi.org/10.1101/2020.12.27.424510 Tomoyasu Horikawa 1 Department of Neuroinformatics, ATR Computational Neuroscience Laboratories , Kyoto, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Tomoyasu Horikawa For correspondence: horikawa-t{at}atr.

Attentionally modulated subjective images reconstructed from brain activity | bioRxiv

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