Conference talk | Activations of deep convolutional neural networks are aligned with gamma band activity of human visual cortex @ SfN 2018
Conference talk based on the research paper by
Ilya Kuzovkin, Raul Vicente, Mathilde Petton, Jean-Philippe Lachaux, Monica Baciu, Philippe Kahane, Sylvain Rheims, Juan R. Vidal, Jaan Aru
Activations of deep convolutional neural networks are aligned with gamma band activity of human visual cortex
Society for Neuroscience (SfN) 2018 annual meeting
We have analyzed human brain activity during the task of visual categorization. The activity was recorded using intracranial electrodes from over 100 human subjects. We compared the activity in different frequency bands and temporal windows to the activation of an artificial neural network trained to perform the same task of visual categorization on the same set of test images.
You can download the slides of the talk here: http://www.ikuz.eu/materials/slides/Ilya-Kuzovkin-Activations-of-deep-convolutional-neural-networks-are-aligned-with-gamma-band activity-of-human-visual-cortex-SfN-2018.pdf
We consistently found that signals in low-gamma (31–70 Hz) frequencies across all time windows and high-gamma (71–150 Hz) frequencies in 150–350 ms window are aligned with the DCNN in a specific way: increase of the complexity of features along the layers of the DCNN was roughly matched by the transformation in the representational geometry of responses to the stimuli along the ventral stream. In other words, the lower and higher layers of the DCNN explained gamma band signals from earlier and later visual areas, respectively.
Our second important observation was that the volume of responses (sum of significant correlations) had a clear pattern when compared across layers of a DCNN: convolutional layers elicited correlation with gamma and high gamma band activity, while the fully connected layers correlated with early responses in the lower (under 30 Hz) frequencies.