Zoumpoulaki, A. | bioRxiv Science

bioRxiv2018

Countering Cross-Individual Variance in Event Related Potentials with Functional Profiling

In this study, a simple method called the Weight Template (WT) is proposed for classifying brain responses of individuals into deceiving and non-deceiving. The performance of our method was evaluated on a number of identity deception data sets and on artificial EEG data sets. A comparison was made with a standard method used to measure P3 presence, called Peak-to-Peak. In the real experimental data, the WT showed higher performance in terms of sensitivity and specificity. In the artificial EEG data, in ERPs with low Signal-to-Noise Ratio (SNR), the WT was more resistant to noise and provided more accurate measures. HighlightsO_LIWe propose a method for classifying ERPs of the P3 Concealed Information Tests. C_LIO_LIThe new method is based on computing a weighted template (WT) for each individual. C_LIO_LIThe WT is used to characterize the shape of each individuals P3. C_LIO_LIThe performance of the WT was compared with the standard Peak-to-Peak method. C_LIO_LIThe WT showed higher performance in terms of sensitivity and specificity. C_LI

bioengineering↗

bioRxiv2017

Identification of Memory Reactivation during Sleep by EEG Classification

Memory reactivation during sleep is critical for consolidation, but also extremely difficult to measure as it is subtle, distributed and temporally unpredictable. This article reports a novel method for detecting such reactivation in standard sleep recordings. During learning, participants produced a complex sequence of finger presses, with each finger cued by a distinct audio-visual stimulus. Auditory cues were then re-played during subsequent sleep to trigger neural reactivation through a method known as targeted memory reactivation (TMR). Next, we used electroencephalography data from the learning session to train a machine learning classifier, and then applied this classifier to sleep data to determine how successfully each tone had elicited memory reactivation. Above chance classification was significantly higher in slow wave sleep than in stage 2, suggesting differential efficacy of TMR in these two sleep stages. Interestingly, classification success reduced across numerous repetitions of the tone cue, suggesting either a gradually reducing responsiveness to such cues or a plasticity-related change in the neural signature as a result of cueing. We believe this method will be invaluable for future investigations of memory consolidation.

neuroscience↗