Activations of deep convolutional neural networks are aligned with gamma band activity of human visual cortex.
Activations of deep convolutional neural networks are aligned with gamma band activity of human visual cortex.
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DOI：
10.1038/s42003-018-0110-y
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发表时间：
2018
影响因子：
5.9
通讯作者：
Aru J
中科院分区：
文献类型：
--
作者：
Kuzovkin I;Vicente R;Petton M;Lachaux JP;Baciu M;Kahane P;Rheims S;Vidal JR;Aru J
人工智能领域的最新进展揭示了神经处理的原理，特别是关于视觉的原理。以前的工作表明，人类视觉区域的层次结构与用于视觉对象识别的深层卷积神经网络(DCNN)层之间存在直接对应关系。我们使用DCNN来研究哪些频段与腹侧视觉通路上日益复杂的特征转换相关。通过利用100名患者的颅内深度记录，我们评估了DCNN和不同频段信号之间的对准。我们发现，伽马活动(30-70 HZ)与DCNN中日益增长的视觉特征表征的复杂性相匹配。这些发现表明，DCNN的活动不仅在空间和时间上捕捉到了生物物体识别的本质特征，而且在频域上也捕捉到了生物物体识别的本质特征。这些结果表明，人工智能算法在促进我们对大脑的理解方面具有潜力。Ilya Kuzovkin等人。将在视觉识别任务中采集的人类受试者的颅内深度记录与深层卷积神经网络(DCNN)的激活进行比较。他们发现，录音中伽马频段的信号与DCNN的分层结构一致，表明DCNN捕捉到了生物物体识别的重要特征。
Recent advances in the field of artificial intelligence have revealed principles about neural processing, in particular about vision. Previous work demonstrated a direct correspondence between the hierarchy of the human visual areas and layers of deep convolutional neural networks (DCNN) trained on visual object recognition. We use DCNN to investigate which frequency bands correlate with feature transformations of increasing complexity along the ventral visual pathway. By capitalizing on intracranial depth recordings from 100 patients we assess the alignment between the DCNN and signals at different frequency bands. We find that gamma activity (30–70 Hz) matches the increasing complexity of visual feature representations in DCNN. These findings show that the activity of the DCNN captures the essential characteristics of biological object recognition not only in space and time, but also in the frequency domain. These results demonstrate the potential that artificial intelligence algorithms have in advancing our understanding of the brain. Ilya Kuzovkin et al. compare intracranial depth recordings from human subjects taken during a visual recognition task to activations of deep convolutional neural networks (DCNNs). They find that signals in gamma frequency bands in the recordings are aligned with the hierarchical layer structure of the DCNN, showing that DCNNs capture important characteristics of biological object recognition.
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影响因子：
16.2
作者：
Fries P
通讯作者：
Fries P
影响因子：
13.9
作者：
Buzsáki G;Wang XJ
通讯作者：
Wang XJ
影响因子：
5.7
作者：
Eickenberg, Michael;Gramfort, Alexandre;Thirion, Bertrand
通讯作者：
Thirion, Bertrand
DOI：
10.1073/pnas.86.5.1698
发表时间：
1989-03-01
影响因子：
11.1
作者：
GRAY, CM;SINGER, W
通讯作者：
SINGER, W
影响因子：
5.7
作者：
Genovese, CR;Lazar, NA;Nichols, T
通讯作者：
Nichols, T