Independent component analysis of EEG data for EGI system

Gajos, Anna; Wójcik, Grzegorz M.

doi:10.1515/bams-2016-0004

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…We recorded EEG at a 500-Hz sampling rate. Impedances were below 50 kΩ, per recommendation [91] and existing standard (e.g., [72,[92][93][94][95]) for high-input impedance amplifiers. All electrodes were referenced to Cz.…”

Section: Eeg Recording and Analysismentioning

confidence: 99%

Attention is required for canonical brain signature of prediction error despite early encoding of the stimuli

Male

O’Shea

2023

PLoS Biol

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Prediction error is a basic component of predictive-coding theory of brain processing. According to the theory, each stage of brain processing of sensory information generates a model of the current sensory input; subsequent input is compared against the model and only if there is a mismatch, a prediction error, is further processing performed. Recently, Smout and colleagues found that a signature of prediction error, the visual (v) mismatch negativity (MMN), for a fundamental property of visual input—its orientation—was absent without endogenous attention on the stimuli. This is remarkable because the weight of evidence for MMNs from audition and vision is that they occur without endogenous attention. To resolve this discrepancy, we conducted an experiment addressing 2 alternative explanations for Smout and colleagues’ finding: that it was from a lack of reproducibility or that participants’ visual systems did not encode the stimuli when attention was on something else. We conducted a similar experiment to that of Smout and colleagues. We showed 21 participants sequences of identically oriented Gabor patches, standards, and, unpredictably, otherwise identical, Gabor patches differing in orientation by ±15°, ±30°, and ±60°, deviants. To test whether participants encoded the orientation of the standards, we varied the number of standards preceding a deviant, allowing us to search for a decrease in activity with the number of repetitions of standards—repetition suppression. We diverted participants’ attention from the oriented stimuli with a central, letter-detection task. We reproduced Smout and colleagues’ finding of no vMMN without endogenous attention, strengthening their finding. We found that our participants showed repetition suppression: They did encode the stimuli preattentively. We also found early processing of deviants. We discuss various explanations why the earlier processing did not extend into the vMMN time window, including low precision of prediction.

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Section: Eeg Recording and Analysismentioning

confidence: 99%

Attention is required for canonical brain signature of prediction error despite early encoding of the stimuli

Male

O’Shea

2023

PLoS Biol

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“…The future plan is to integrate our solution with tools for EEG signal processing such us NetStation [8][9][10][11]. It is also worth considering the adjustment of the existing solution to the capabilities of a particular architecture to achieve even better results.…”

Section: Discussionmentioning

confidence: 99%

“…It is common that one should use external software to take advantage of the aforementioned method. This prompted the authors of the research to write an application with its own implementation of ICA, integrated with the software used in the Department of Neuroinformatics at Maria Curie-Sklodowska University in Lublin (NetStation) [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Performance comparison of parallel fastICA algorithm in the PLGrid structures

2018

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During processing the EEG signal, the methods of cleaning it from artifacts play an important role. One of the most commonly used methods is ICA (independent component analysis) [1-3]. However, algorithms of this type are computationally expensive. Known implementations of ICA type algorithms rarely include the possibility of parallel computing and do not use the capabilities provided by the architecture itself. This paper presents a parallel implementation of the fastICA algorithm using the available libraries and extensions of the Intel processors (such as BLAS, MKL, Cilk Plus) and compares the execution time for two selected architectures in the PLGrid structure (Zeus and Prometheus).

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“…The EEG signal accrued for 45 min per session using an EGI-Net (256-channel HydroCel Geodesic Sensor Net) and covered the whole head with less than 20 mm inter-electrode distances ( Figure 5A ). The 10 − 10 EEG Montage was applied with a reference on Vertex (Cz), recording 1,000 samples per second in a 22-bit analog-to-digital converter (Gajos and Wójcik, 2016 ) using NetStation 5.4.2 software (EGI, Eugene, OR, USA). Clinical setup was illustrated as a 3-Dimensional simulation in Figure 3 .…”

Section: Methodsmentioning

confidence: 99%

Dose-Response Transcranial Electrical Stimulation Study Design: A Well-Controlled Adaptive Seamless Bayesian Method to Illuminate Negative Valence Role in Tinnitus Perception

Ghodratitoostani

Gonzatto

Vaziri

et al. 2022

Front. Hum. Neurosci.

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The use of transcranial Electrical Stimulation (tES) in the modulation of cognitive brain functions to improve neuropsychiatric conditions has extensively increased over the decades. tES techniques have also raised new challenges associated with study design, stimulation protocol, functional specificity, and dose-response relationship. In this paper, we addressed challenges through the emerging methodology to investigate the dose-response relationship of High Definition-transcranial Direct Current Stimulation (HD tDCS), identifying the role of negative valence in tinnitus perception. In light of the neurofunctional testable framework and tES application, hypotheses were formulated to measure clinical and surrogate endpoints. We posited that conscious pairing adequately pleasant stimuli with tinnitus perception results in correction of the loudness misperception and would be reinforced by concurrent active HD-tDCS on the left Dorsolateral Prefrontal Cortex (dlPFC). The dose-response relationship between HD-tDCS specificity and the loudness perception is also modeled. We conducted a double-blind, randomized crossover pilot study with six recruited tinnitus patients. Accrued data was utilized to design a well-controlled adaptive seamless Bayesian dose-response study. The sample size (n = 47, for 90% power and 95% confidence) and optimum interims were anticipated for adaptive decision-making about efficacy, safety, and single session dose parameters. Furthermore, preliminary pilot study results were sufficient to show a significant difference (90% power, 99% confidence) within the longitudinally detected self-report tinnitus loudness between before and under positive emotion induction. This study demonstrated a research methodology used to improve emotion regulation in tinnitus patients. In the projected method, positive emotion induction is essential for promoting functional targeting under HD-tDCS anatomical specificity to indicate the efficacy and facilitate the dose-finding process. The continuous updating of prior knowledge about efficacy and dose during the exploratory stage adapts the anticipated dose-response model. Consequently, the effective dose range to make superiority neuromodulation in correcting loudness misperception of tinnitus will be redefined. Highly effective dose adapts the study to a standard randomized trial and transforms it into the confirmatory stage in which active HD-tDCS protocol is compared with a sham trial (placebo-like). Establishing the HD-tDCS intervention protocols relying on this novel method provides reliable evidence for regulatory agencies to approve or reject the efficacy and safety. Furthermore, this paper supports a technical report for designing multimodality data-driven complementary investigations in emotion regulation, including EEG-driven neuro markers, Stroop-driven attention biases, and neuroimaging-driven brain network dynamics.

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Independent component analysis of EEG data for EGI system

Cited by 8 publications

References 11 publications

Attention is required for canonical brain signature of prediction error despite early encoding of the stimuli

Attention is required for canonical brain signature of prediction error despite early encoding of the stimuli

Performance comparison of parallel fastICA algorithm in the PLGrid structures

Dose-Response Transcranial Electrical Stimulation Study Design: A Well-Controlled Adaptive Seamless Bayesian Method to Illuminate Negative Valence Role in Tinnitus Perception

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