相关实验视频

Updated: Jun 18, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

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st-DenseViT:一个弱监督的时空视觉转换器,用于动态大脑网络的密集预测

Behnam Kazemivash, Pranav Nadigapu Suresh, Dong Hye Ye

    bioRxiv : the preprint server for biology
    |December 9, 2024
    PubMed
    概括

    我们开发了一种新的弱监督模型,从fMRI数据中生成动态的4D大脑网络. 这种方法捕捉了时空大脑活动,有助于区分临床人群,如精神分裂症患者与健康对照.

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    Vision01:24

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    Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
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    Deconvolution

    Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
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    Discrete-time Fourier transform01:26

    Discrete-time Fourier transform

    The Discrete-Time Fourier Transform (DTFT) is an essential mathematical tool for analyzing discrete-time signals, converting them from the time domain to the frequency domain. This transformation allows for examining the frequency components of discrete signals, providing insights into their spectral characteristics. In the DTFT, the continuous integral used in the continuous-time Fourier transform is replaced by a summation to accommodate the discrete nature of the signal.
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