Feature Pyramid Networks and Long Short-Term Memory for EEG Feature Map-Based Emotion Recognition.

The original EEG data collected are the 1D sequence, which ignores spatial topology information; Feature Pyramid Networks (FPN) is better at small dimension target detection and insufficient feature extraction in the scale transformation than CNN. We propose a method of FPN and Long Short-Term Memory (FPN-LSTM) for EEG feature map-based emotion recognition. According to the spatial arrangement of brain electrodes, the Azimuth Equidistant Projection (AEP) is employed to generate the 2D EEG map, which preserves the spatial topology information; then, the average power, variance power, and standard deviation power of three frequency bands (α, ß, and γ) are extracted as the feature data for the EEG feature map. BiCubic interpolation is employed to interpolate the blank pixel among the electrodes; the three frequency bands EEG feature maps are used as the G, R, and B channels to generate EEG feature maps. Then, we put forward the idea of distributing the weight proportion for channels, assign large weight to strong emotion correlation channels (AF3, F3, F7, FC5, and T7), and assign small weight to the others; the proposed FPN-LSTM is used on EEG feature maps for emotion recognition. The experiment results show that the proposed method can achieve Value and Arousal recognition rates of 90.05% and 90.84%, respectively.

Erratum: Stronger Interlayer Interactions Contribute to Faster Hot Carrier Cooling of Bilayer Graphene under Pressure [Phys. Rev. Lett. 126, 027402 (2021)].

This corrects the article DOI: 10.1103/PhysRevLett.126.027402.

Stronger Interlayer Interactions Contribute to Faster Hot Carrier Cooling of Bilayer Graphene under Pressure.

We perform femtosecond pump-probe spectroscopy to in situ investigate the ultrafast photocarrier dynamics in bilayer graphene and observe an acceleration of energy relaxation under pressure. In combination with in situ Raman spectroscopy and ab initio molecular dynamics simulations, we reveal that interlayer shear and breathing modes have significant contributions to the faster hot-carrier relaxations by coupling with the in-plane vibration modes under pressure. Our work suggests that further understanding the effect of interlayer interaction on the behaviors of electrons and phonons would be critical to tailor the photocarrier dynamic properties of bilayer graphene.