  Current neuroscience focused approaches for evaluating the effectiveness of a
design do not use direct visualisation of mental activity. A recurrent neural
network is used as the encoder to learn latent representation from
electroencephalogram (EEG) signals, recorded while subjects looked at 50
categories of images. A generative adversarial network (GAN) conditioned on the
EEG latent representation is trained for reconstructing these images. After
training, the neural network is able to reconstruct images from brain activity
recordings. To demonstrate the proposed method in the context of the mental
association with a design, we performed a study that indicates an iconic design
image could inspire the subject to create cognitive associations with branding
and valued products. The proposed method could have the potential in verifying
designs by visualizing the cognitive understanding of underlying brain
activity.
