Aberrant Connectivity During Pilocarpine-Induced Status Epilepticus.

Status epilepticus (SE) is a common, life-threatening neurological disorder that may lead to permanent brain damage. In rodent models, SE is an acute phase of seizures that could be reproduced by injecting with pilocarpine and then induce chronic temporal lobe epilepsy (TLE) seizures. However, how SE disrupts brain activity, especially communications among brain regions, is still unclear. In this study, we aimed to identify the characteristic abnormalities of network connections among the frontal cortex, hippocampus and thalamus during the SE episodes in a pilocarpine model with functional and effective connectivity measurements. We showed that the coherence connectivity among these regions increased significantly during the SE episodes in almost all frequency bands (except the alpha band) and that the frequency band with enhanced connections was specific to different stages of SE episodes. Moreover, with the effective analysis, we revealed a closed neural circuit of bidirectional effective interactions between the frontal regions and the hippocampus and thalamus in both ictal and post-ictal stages, implying aberrant enhancement of communication across these brain regions during the SE episodes. Furthermore, an effective connection from the hippocampus to the thalamus was detected in the delta band during the pre-ictal stage, which shifted in an inverse direction during the ictal stage in the theta band and in the theta, alpha, beta and low-gamma bands during the post-ictal stage. This specificity of the effective connection between the hippocampus and thalamus illustrated that the hippocampal structure is critical for the initiation of SE discharges, while the thalamus is important for the propagation of SE discharges. Overall, our results demonstrated enhanced interaction among the frontal cortex, hippocampus and thalamus during the SE episodes and suggested the modes of information flow across these structures for the initiation and propagation of SE discharges. These findings may reveal an underlying mechanism of aberrant network communication during pilocarpine-induced SE discharges and deepen our knowledge of TLE seizures.

Local temporal correlation common spatial patterns for single trial EEG classification during motor imagery.

Common spatial pattern (CSP) is one of the most popular and effective feature extraction methods for motor imagery-based brain-computer interface (BCI), but the inherent drawback of CSP is that the estimation of the covariance matrices is sensitive to noise. In this work, local temporal correlation (LTC) information was introduced to further improve the covariance matrices estimation (LTCCSP). Compared to the Euclidean distance used in a previous CSP variant named local temporal CSP (LTCSP), the correlation may be a more reasonable metric to measure the similarity of activated spatial patterns existing in motor imagery period. Numerical comparisons among CSP, LTCSP, and LTCCSP were quantitatively conducted on the simulated datasets by adding outliers to Dataset IVa of BCI Competition III and Dataset IIa of BCI Competition IV, respectively. Results showed that LTCCSP achieves the highest average classification accuracies in all the outliers occurrence frequencies. The application of the three methods to the EEG dataset recorded in our laboratory also demonstrated that LTCCSP achieves the highest average accuracy. The above results consistently indicate that LTCCSP would be a promising method for practical motor imagery BCI application.