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Ballistocardiogram (BCG) artifact remains a major challenge that renders electroencephalographic (EEG) signals hard to interpret in simultaneous EEG and functional MRI (fMRI) data acquisition. Here, we propose an integrated learning and inference approach that takes advantage of a commercial high-density EEG cap, to estimate the BCG contribution in noisy EEG recordings from inside the MR scanner. To estimate reliably the full-scalp BCG artifacts, a near-optimal subset (20 out of 256) of channels first was identified using a modified recording setup. In subsequent recordings inside the MR scanner, BCG-only signal from this subset of channels was used to generate continuous estimates of the full-scalp BCG artifacts via inference, from which the intended EEG signal was recovered. The reconstruction of the EEG was performed with both a direct subtraction and an optimization scheme. We evaluated the performance on both synthetic and real contaminated recordings, and compared it to the benchmark Optimal Basis Set (OBS) method. In the challenging non-event-related-potential (non-ERP) EEG studies, our reconstruction can yield more than fourteen-fold improvement in reducing the normalized RMS error of EEG signals, compared to OBS. [ABSTRACT FROM AUTHOR]

Despite considerable effort to remove it, the ballistocardiogram (BCG) remains a major artifact in electroencephalographic data (EEG) acquired inside magnetic resonance imaging (MRI) scanners, particularly in continuous (as opposed to event-related) recordings. In this study, we have developed a new Direct Recording Prior Encoding (DRPE) method to extract and separate the BCG and EEG components from contaminated signals, and have demonstrated its performance by comparing it quantitatively to the popular Optimal Basis Set (OBS) method. Our modified recording configuration allows us to obtain representative bases of the BCG- and EEG-only signals. Further, we have developed an optimization-based reconstruction approach to maximally incorporate prior knowledge of the BCG/EEG subspaces, and of the signal characteristics within them. Both OBS and DRPE methods were tested with experimental data, and compared quantitatively using cross-validation. In the challenging continuous EEG studies, DRPE outperforms the OBS method by nearly sevenfold in separating the continuous BCG and EEG signals. [ABSTRACT FROM AUTHOR]

Behavioral problems, school failure, and memory impairment are common among children with epilepsy. Currently, no effective treatment exists to promote recovery and neuron regeneration after seizures. To investigate the efficacy of environmental enrichment in reversing early-life seizure-induced changes in exploratory behavior and gene expression, we injected postnatal day 20 to 25 rats with kainic acid or saline and placed them either singly in a cage or as a group of eight in an enriched environment for 7 to 10 days. Exploratory behavior was quantified in an open field, and hippocampal gene analysis was performed on oligonucleotide microarrays. Exploratory behavior in kainic acid isolated rats were decreased in open field, whereas kainic acid rats exposed to an enriched environment behaved similarly to controls (n = 37, analysis of variance, P < .001). Correlated with an improvement in behavior, genes involved in synaptic plasticity and memory consolidation, such as Arc, Homer1a, and Egr1, were significantly increased in rats exposed to environmental enrichment. Real-time quantitative reverse transcriptase-polymerase chain reaction confirmed our microarray data on select genes. Our results provide an experimental basis for promoting enriching education programs for children with epilepsy. [ABSTRACT FROM AUTHOR]