P50 and P300 Event Related Potentials in Patients with Schizophrenia Recorded from High-Density EEG

Banea, Ovidiu C.; Pegolo, Elena; Marcu, Sara; Friðriksdóttir, Rún; Ívarsson, Eysteinn; Jónasson, Aron Dalin; Jónasson, Viktor Díar; Magnúsdóttir, Brynja B.; Wassermann, Eric M.; Gargiulo, Paolo

doi:10.1007/978-3-030-31635-8_130

Cited by 2 publications

(2 citation statements)

References 12 publications

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“… Willett et al (2021) achieved previously science-fictional technologies, such as writing with thoughts. A BCI not only enable humans to control external devices subjectively but also facilitate a deeper understanding of ourselves, assisting medical professionals in monitoring patient sleep status ( Michielli et al, 2019 ), evaluating newborn health ( Ansari et al, 2019 ), classifying emotions ( He et al, 2020 ), and obtaining subject status through P300 event-related potential analysis ( Banea et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Design of virtual BCI channels based on informer

Sun

Zhang

2023

Front. Hum. Neurosci.

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The precision and reliability of electroencephalogram (EEG) data are essential for the effective functioning of a brain-computer interface (BCI). As the number of BCI acquisition channels increases, more EEG information can be gathered. However, having too many channels will reduce the practicability of the BCI system, raise the likelihood of poor-quality channels, and lead to information misinterpretation. These issues pose challenges to the advancement of BCI systems. Determining the optimal configuration of BCI acquisition channels can minimize the number of channels utilized, but it is challenging to maintain the original operating system and accommodate individual variations in channel layout. To address these concerns, this study introduces the EEG-completion-informer (EC-informer), which is based on the Informer architecture known for its effectiveness in time-series problems. By providing input from four BCI acquisition channels, the EC-informer can generate several virtual acquisition channels to extract additional EEG information for analysis. This approach allows for the direct inheritance of the original model, significantly reducing researchers’ workload. Moreover, EC-informers demonstrate strong performance in damaged channel repair and poor channel identification. Using the Informer as a foundation, the study proposes the EC-informer, tailored to BCI requirements and demanding only a small number of training samples. This approach eliminates the need for extensive computing units to train an efficient, lightweight model while preserving comprehensive information about target channels. The study also confirms that the proposed model can be transferred to other operators with minimal loss, exhibiting robust applicability. The EC-informer’s features enable original BCI devices to adapt to a broader range of classification algorithms and relax the operational requirements of BCI devices, which could facilitate the promotion of the use of BCI devices in daily life.

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Section: Introductionmentioning

confidence: 99%

Design of virtual BCI channels based on informer

Sun

Zhang

2023

Front. Hum. Neurosci.

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“…The data were sampled at 1024 Hz and re-referenced to the average of left and right mastoid electrodes (R19R, L19L). A bandpass filter was set between 0.1-80 Hz, 20,21 and notch filter from 49-51 Hz was used to remove undesired monomorphic artifacts from 50 Hz mains electricity. 22 Bad channels were removed when EEG voltage was greater than ±80 μV; if more than 10% of the channels showed to much noise or bad signal, the whole trial was rejected.…”

Section: P50 Suppressionmentioning

confidence: 99%

Using high density EEG to assess TMS treatment in patients with schizophrenia

et al. 2020

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We present preliminary results from the ongoing study entitled “Icelandic AVH-TMS” which aim is to study the effectiveness of repetitive transcranial magnetic stimulation (rTMS) treatment for patients with schizophrenia and with persistent auditory verbal hallucinations (AVH) using symptoms and psychometric scales and high-density EEG system (256 channels). The aim of the present work was to describe cortical topography of the auditory evoked responses like P50 and N100-P300 complex in healthy participants and patients with schizophrenia and to define a robust methodology of signal quantification using dense-array EEG. Preliminary data is shown for three healthy participants and three patients in baseline conditions and for two patients we show the results recorded before and after 10 days rTMS treatment. Our results show differences in sensory gating (P50 suppresion) and a stronger N100-P300 response to rare audio stimulus after the treatment. Moreover we show the value of assessing brain electrical activity from high-density EEG (256 channels) analyzing the results in different regions of interest. However, it is premature and hazardous to assume that rTMS treatment effectiveness in patients with AVH can be assessed using P50 suppression ratio.

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P50 and P300 Event Related Potentials in Patients with Schizophrenia Recorded from High-Density EEG

Cited by 2 publications

References 12 publications

Design of virtual BCI channels based on informer

Design of virtual BCI channels based on informer

Using high density EEG to assess TMS treatment in patients with schizophrenia

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