透過大腦看見：從人類腦信號重建視覺知覺的影像

摘要

眼見為實，然而，人類視覺知覺如何與我們的認知緊密相關的基本機制仍然是一個謎。感謝近期在神經科學和人工智慧領域的進步，我們已經能夠記錄受視覺誘發的腦部活動並通過計算方法模仿視覺知覺能力。在本文中，我們專注於透過可攜式訪問的腦電圖（EEG）數據，通過重建觀察到的圖像來重建視覺刺激。由於EEG信號以時間序列格式呈現且因其嘈雜而臭名昭著，處理和提取有用信息需要更多專注的努力；在本文中，我們提出了一個名為NeuroImagen的全面流程，用於從EEG信號重建視覺刺激圖像。具體來說，我們結合了一種新穎的多層次感知信息解碼，以從給定的EEG數據中獲得多層次的輸出。然後，一個潛在擴散模型將利用提取的信息來重建高分辨率的視覺刺激圖像。實驗結果顯示了圖像重建的有效性以及我們提出的方法在量化性能上的優越性。

English

Seeing is believing, however, the underlying mechanism of how human visual perceptions are intertwined with our cognitions is still a mystery. Thanks to the recent advances in both neuroscience and artificial intelligence, we have been able to record the visually evoked brain activities and mimic the visual perception ability through computational approaches. In this paper, we pay attention to visual stimuli reconstruction by reconstructing the observed images based on portably accessible brain signals, i.e., electroencephalography (EEG) data. Since EEG signals are dynamic in the time-series format and are notorious to be noisy, processing and extracting useful information requires more dedicated efforts; In this paper, we propose a comprehensive pipeline, named NeuroImagen, for reconstructing visual stimuli images from EEG signals. Specifically, we incorporate a novel multi-level perceptual information decoding to draw multi-grained outputs from the given EEG data. A latent diffusion model will then leverage the extracted information to reconstruct the high-resolution visual stimuli images. The experimental results have illustrated the effectiveness of image reconstruction and superior quantitative performance of our proposed method.

透過大腦看見：從人類腦信號重建視覺知覺的影像

Seeing through the Brain: Image Reconstruction of Visual Perception from Human Brain Signals

摘要

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