Identification of emotional response areas in the human brain under language stimulation

Abstract

Under the current research, it has not yet been revealed how various emotions are expressed in the brain under verbal stimuli. In order to clarify this point, we will use fMRI Datasets, which contains BOLD responses measured by functional MRI while human subjects listen to a reading as a language stimulus, to investigate how sentences given as a verbal stimulus affect emotions in the human brain. First, in order to obtain the emotion ratings for each sentence, we placed 80 annotators for each emotion and obtained the emotion ratings. Next, we fine-tuned the pre-trained BERT with GoEmotions, then fine-tuned it with another 80 emotion ratings, and obtained the emotion features for each sentence. Then, based on the model obtained by regression of the concatenated language and emotion features with the measured brain activity, we retrieved the predictive brain activity for each emotion, and investigated and discussed how the predictive brain activity responds to each emotion.