Emotion Recognition for Brain Machine Interface: Non-linear Spectral Analysis of EEG Signals Using Empirical Mode Decomposition.

Emotions are a fundamental part of the human experience but currently there are no methods that can objectively detect and categorize them. This study utilizes the empirical mode decomposition (EMD) method to categorize emotions from encephalography (EEG) recordings. In the past, EMD has proven to be a very useful signal analysis tool because of its ability to decompose nonstationary signals, like those from an EEG, into component signals with varying frequency content called intrinsic mode functions (IMFs).

Long-Range GABAergic Inputs Regulate Neural Stem Cell Quiescence and Control Adult Hippocampal Neurogenesis.

The quiescence of adult neural stem cells (NSCs) is regulated by local parvalbumin (PV) interneurons within the dentate gyrus (DG). Little is known about how local PV interneurons communicate with distal brain regions to regulate NSCs and hippocampal neurogenesis. Here, we identify GABAergic projection neurons from the medial septum (MS) as the major afferents to dentate PV interneurons.