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time s eeg device egi 128 geodesic sensor net eye tracker tobii pro glasses 3 t raw eeg pretrained language model texts eye tracking  (Welcony)


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    Welcony time s eeg device egi 128 geodesic sensor net eye tracker tobii pro glasses 3 t raw eeg pretrained language model texts eye tracking
    Fig. 1 Overview of the experiment and the modalities included in the dataset. (a) Equipment utilized in the experiment, including the EGI device for collecting EEG data and the Tobii Pro Glasses 3 eye-tracker for tracking eye movements. (b) The experiment setup. Participants were instructed to sit quietly approximately 67 cm from the screen and sequentially read the highlighted text. (c) The experimental protocol. Participants’ 128-channel EEG signals <t>and</t> <t>eye-tracking</t> data were recorded while reading the highlighted text. (d) The data modalities in the dataset. The dataset comprises raw data such as the original textual stimuli, eye movement data, EEG data, and derivatives such as text embeddings from pre-trained NLP models and pre-processed EEG data.
    Time S Eeg Device Egi 128 Geodesic Sensor Net Eye Tracker Tobii Pro Glasses 3 T Raw Eeg Pretrained Language Model Texts Eye Tracking, supplied by Welcony, used in various techniques. Bioz Stars score: 97/100, based on 2673 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/eye-eeg/Geodesic+Sensor+Net/pm38811613-115-9-12
    Average 97 stars, based on 2673 article reviews
    time s eeg device egi 128 geodesic sensor net eye tracker tobii pro glasses 3 t raw eeg pretrained language model texts eye tracking - by Bioz Stars, 2026-11
    97/100 stars

    Images

    1) Product Images from "ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding."

    Article Title: ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding.

    Journal: Scientific data

    doi: 10.1038/s41597-024-03398-7

    Fig. 1 Overview of the experiment and the modalities included in the dataset. (a) Equipment utilized in the experiment, including the EGI device for collecting EEG data and the Tobii Pro Glasses 3 eye-tracker for tracking eye movements. (b) The experiment setup. Participants were instructed to sit quietly approximately 67 cm from the screen and sequentially read the highlighted text. (c) The experimental protocol. Participants’ 128-channel EEG signals and eye-tracking data were recorded while reading the highlighted text. (d) The data modalities in the dataset. The dataset comprises raw data such as the original textual stimuli, eye movement data, EEG data, and derivatives such as text embeddings from pre-trained NLP models and pre-processed EEG data.
    Figure Legend Snippet: Fig. 1 Overview of the experiment and the modalities included in the dataset. (a) Equipment utilized in the experiment, including the EGI device for collecting EEG data and the Tobii Pro Glasses 3 eye-tracker for tracking eye movements. (b) The experiment setup. Participants were instructed to sit quietly approximately 67 cm from the screen and sequentially read the highlighted text. (c) The experimental protocol. Participants’ 128-channel EEG signals and eye-tracking data were recorded while reading the highlighted text. (d) The data modalities in the dataset. The dataset comprises raw data such as the original textual stimuli, eye movement data, EEG data, and derivatives such as text embeddings from pre-trained NLP models and pre-processed EEG data.

    Techniques Used:

    Fig. 3 File structure of the dataset. (a) Eye-tracking data: Each experimental run is associated with a .rar file that contains eye-tracking data. (b) Electrode information files: These include detailed information of electrodes such as the location, type, and sampling rate, as well as information on any channels marked as bad during pre- processing. (c) EEG data and event-related files: Including EEG data in BrainVision format and event files that record marker information. (d) ICA-related files: Containing independent components in numpy format, records of removed components during pre-processing, and topographic maps of the components. (e) Text materials: Containing original and segmented text. (f) Text embedding files: Each file corresponds to an experimental run and is stored in .npy format. (g) Raw EEG data.
    Figure Legend Snippet: Fig. 3 File structure of the dataset. (a) Eye-tracking data: Each experimental run is associated with a .rar file that contains eye-tracking data. (b) Electrode information files: These include detailed information of electrodes such as the location, type, and sampling rate, as well as information on any channels marked as bad during pre- processing. (c) EEG data and event-related files: Including EEG data in BrainVision format and event files that record marker information. (d) ICA-related files: Containing independent components in numpy format, records of removed components during pre-processing, and topographic maps of the components. (e) Text materials: Containing original and segmented text. (f) Text embedding files: Each file corresponds to an experimental run and is stored in .npy format. (g) Raw EEG data.

    Techniques Used: Sampling, Marker

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    Electroencephalography:

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    Article Title: Probing the role of left inferior frontal gyrus in vocal motor control: Evidence from TMS and causal inference analysis.
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    Oligomer Restriction:

    Article Title: Foster care intervention protects cognitive control skills in young adults exposed to institutional rearing
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    Article Snippet: .. Recordings were obtained using a 128-channel high-density EEG system (MicroCel Geodesic Sensor Net, Electrical Geodesics Inc., Eugene, OR, USA) together with ECG and standard polysomnographic channels. ..

    Amplification:

    Article Title: Neural processing of facial expressions: An ERP study in athletes and non-athletes.
    Article Snippet: .. Continuous EEG signals were amplified and recorded using a NeurOne system (Bittium Biosignals Ltd., Finland) with a 128-channel electrode cap (HydroCel Geodesic Sensor Net; Electrical Geodesics Inc., USA). ..

    Analysis:

    Article Title: Probing the role of left inferior frontal gyrus in vocal motor control: Evidence from TMS and causal inference analysis.
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    Software:

    Article Title: Probing the role of left inferior frontal gyrus in vocal motor control: Evidence from TMS and causal inference analysis.
    Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Deposited data CIA analysis code This paper https://github.com/zhaoshuhzi/CIA-IFG Software and algorithms G*Power 3.1 Heinrich Heine University Düsseldorf https://www.psychologie.hhu.de/arbeitsgruppen/ allgemeine-psychologie-und-arbeitspsychologie/gpower Visor 2.0 ANT Neuro https://www.ant-neuro.com/products/visor2 Max/MSP 6.1 Cycling ’74 https://cycling74.com/downloads/older LabChart 7.0 ADInstruments https://www.adinstruments.com/labchart NetStation 4.5 Electrical Geodesics Inc. https://www.egi.com/ IGOR Pro 6.0 WaveMetrics Inc. https://www.wavemetrics.com/downloads Praat Boersma https://www.fon.hum.uva.nl/praat/ SPSS 20.0 IBM https://www.ibm.com/products/spss-statistics Brainstorm 3.2 University of Southern California and McGill University https://neuroimage.usc.edu/brainstorm/ OpenMEEG INRIA Sophia-Antipolis https://openmeeg.github.io/ Other MRI scanner (3 T) Siemens Verio TMS stimulator YIRUIDE Co. CCY-I Optical motion tracking system Northern Digital Inc. Polaris Spectra Dynamic microphone Takstar Inc. DM2200 Pitch-shifting processor Eventide Eclipse Harmonizer Audio interface MOTU UltraLite-mk3 FireWire Headphone amplifier ICON NeoAmp Insert earphones Etymotic Research Inc. ER-1 A/D converter ADInstruments PowerLab ML880 Geodesic Sensor Net Electrical Geodesics Inc. N/A EEG amplifier Electrical Geodesics Inc. Net Amps 300 14 iScience 29, 117790, November 20, 2026 .. As a prerequisite for neuronavigated TMS, all participants underwent structural MRI scanning (Siemens Verio 3-T scanner, Germany).

    Magnetic Resonance Imaging:

    Article Title: Probing the role of left inferior frontal gyrus in vocal motor control: Evidence from TMS and causal inference analysis.
    Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Deposited data CIA analysis code This paper https://github.com/zhaoshuhzi/CIA-IFG Software and algorithms G*Power 3.1 Heinrich Heine University Düsseldorf https://www.psychologie.hhu.de/arbeitsgruppen/ allgemeine-psychologie-und-arbeitspsychologie/gpower Visor 2.0 ANT Neuro https://www.ant-neuro.com/products/visor2 Max/MSP 6.1 Cycling ’74 https://cycling74.com/downloads/older LabChart 7.0 ADInstruments https://www.adinstruments.com/labchart NetStation 4.5 Electrical Geodesics Inc. https://www.egi.com/ IGOR Pro 6.0 WaveMetrics Inc. https://www.wavemetrics.com/downloads Praat Boersma https://www.fon.hum.uva.nl/praat/ SPSS 20.0 IBM https://www.ibm.com/products/spss-statistics Brainstorm 3.2 University of Southern California and McGill University https://neuroimage.usc.edu/brainstorm/ OpenMEEG INRIA Sophia-Antipolis https://openmeeg.github.io/ Other MRI scanner (3 T) Siemens Verio TMS stimulator YIRUIDE Co. CCY-I Optical motion tracking system Northern Digital Inc. Polaris Spectra Dynamic microphone Takstar Inc. DM2200 Pitch-shifting processor Eventide Eclipse Harmonizer Audio interface MOTU UltraLite-mk3 FireWire Headphone amplifier ICON NeoAmp Insert earphones Etymotic Research Inc. ER-1 A/D converter ADInstruments PowerLab ML880 Geodesic Sensor Net Electrical Geodesics Inc. N/A EEG amplifier Electrical Geodesics Inc. Net Amps 300 14 iScience 29, 117790, November 20, 2026 .. As a prerequisite for neuronavigated TMS, all participants underwent structural MRI scanning (Siemens Verio 3-T scanner, Germany).

    Transcranial Magnetic Stimulation:

    Article Title: Probing the role of left inferior frontal gyrus in vocal motor control: Evidence from TMS and causal inference analysis.
    Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Deposited data CIA analysis code This paper https://github.com/zhaoshuhzi/CIA-IFG Software and algorithms G*Power 3.1 Heinrich Heine University Düsseldorf https://www.psychologie.hhu.de/arbeitsgruppen/ allgemeine-psychologie-und-arbeitspsychologie/gpower Visor 2.0 ANT Neuro https://www.ant-neuro.com/products/visor2 Max/MSP 6.1 Cycling ’74 https://cycling74.com/downloads/older LabChart 7.0 ADInstruments https://www.adinstruments.com/labchart NetStation 4.5 Electrical Geodesics Inc. https://www.egi.com/ IGOR Pro 6.0 WaveMetrics Inc. https://www.wavemetrics.com/downloads Praat Boersma https://www.fon.hum.uva.nl/praat/ SPSS 20.0 IBM https://www.ibm.com/products/spss-statistics Brainstorm 3.2 University of Southern California and McGill University https://neuroimage.usc.edu/brainstorm/ OpenMEEG INRIA Sophia-Antipolis https://openmeeg.github.io/ Other MRI scanner (3 T) Siemens Verio TMS stimulator YIRUIDE Co. CCY-I Optical motion tracking system Northern Digital Inc. Polaris Spectra Dynamic microphone Takstar Inc. DM2200 Pitch-shifting processor Eventide Eclipse Harmonizer Audio interface MOTU UltraLite-mk3 FireWire Headphone amplifier ICON NeoAmp Insert earphones Etymotic Research Inc. ER-1 A/D converter ADInstruments PowerLab ML880 Geodesic Sensor Net Electrical Geodesics Inc. N/A EEG amplifier Electrical Geodesics Inc. Net Amps 300 14 iScience 29, 117790, November 20, 2026 .. As a prerequisite for neuronavigated TMS, all participants underwent structural MRI scanning (Siemens Verio 3-T scanner, Germany).



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    Image Search Results


    Multimodal feature contribution and classification performance for suicide ideation detection in individuals with depression . (A) Variable importance plot derived from the Random Forest model. The Beck Depression Inventory (BDI) score ranks highest in importance, followed by eye movement measures including saccade amplitude (sac_amp), first fixation duration, and EEG features such as rERP and rFRP components at specific time windows (368–628 ms and 564–620 ms) and channels. (B) Receiver Operating Characteristic (ROC) curves comparing classification performance between models using combined eye movement and EEG features (EYE-EEG, Area Under the Curve (AUC) = 0.771) versus eye movement features alone (EYE, AUC = 0.643) for detecting suicide ideation in depressed individuals.

    Journal: Alpha Psychiatry

    Article Title: Neurocognitive Processing of Facial Emotion Recognition in Individuals With Depression and Suicidal Ideation: An Eye-Tracking and EEG Study

    doi: 10.31083/AP44992

    Figure Lengend Snippet: Multimodal feature contribution and classification performance for suicide ideation detection in individuals with depression . (A) Variable importance plot derived from the Random Forest model. The Beck Depression Inventory (BDI) score ranks highest in importance, followed by eye movement measures including saccade amplitude (sac_amp), first fixation duration, and EEG features such as rERP and rFRP components at specific time windows (368–628 ms and 564–620 ms) and channels. (B) Receiver Operating Characteristic (ROC) curves comparing classification performance between models using combined eye movement and EEG features (EYE-EEG, Area Under the Curve (AUC) = 0.771) versus eye movement features alone (EYE, AUC = 0.643) for detecting suicide ideation in depressed individuals.

    Article Snippet: Eye-tracking data were preprocessed to detect saccades and fixations using EYE-EEG toolbox (version 1.0, available at https://github.com/olafdimigen/eye-eeg/releases/tag/v1.0 , developed by the Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands) [ ].

    Techniques: Derivative Assay

    Fig. 1 Overview of the experiment and the modalities included in the dataset. (a) Equipment utilized in the experiment, including the EGI device for collecting EEG data and the Tobii Pro Glasses 3 eye-tracker for tracking eye movements. (b) The experiment setup. Participants were instructed to sit quietly approximately 67 cm from the screen and sequentially read the highlighted text. (c) The experimental protocol. Participants’ 128-channel EEG signals and eye-tracking data were recorded while reading the highlighted text. (d) The data modalities in the dataset. The dataset comprises raw data such as the original textual stimuli, eye movement data, EEG data, and derivatives such as text embeddings from pre-trained NLP models and pre-processed EEG data.

    Journal: Scientific data

    Article Title: ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding.

    doi: 10.1038/s41597-024-03398-7

    Figure Lengend Snippet: Fig. 1 Overview of the experiment and the modalities included in the dataset. (a) Equipment utilized in the experiment, including the EGI device for collecting EEG data and the Tobii Pro Glasses 3 eye-tracker for tracking eye movements. (b) The experiment setup. Participants were instructed to sit quietly approximately 67 cm from the screen and sequentially read the highlighted text. (c) The experimental protocol. Participants’ 128-channel EEG signals and eye-tracking data were recorded while reading the highlighted text. (d) The data modalities in the dataset. The dataset comprises raw data such as the original textual stimuli, eye movement data, EEG data, and derivatives such as text embeddings from pre-trained NLP models and pre-processed EEG data.

    Article Snippet: Experiment setupEquipment Experiment protocol C ha nn el s Time (s)EEG device EGI 128 geodesic sensor net Eye tracker Tobii pro glasses 3 t Raw EEG Pretrained language model Texts Eye-tracking data Raw data Derivatives Text embeddings t t tTemporal alignment Pre-processed EEG t t t Pre-processsing Data modalities a b c d C ha nn el s Fig. 1 Overview of the experiment and the modalities included in the dataset. (a) Equipment utilized in the experiment, including the EGI device for collecting EEG data and the Tobii Pro Glasses 3 eye-tracker for tracking eye movements. (b) The experiment setup.

    Techniques:

    Fig. 3 File structure of the dataset. (a) Eye-tracking data: Each experimental run is associated with a .rar file that contains eye-tracking data. (b) Electrode information files: These include detailed information of electrodes such as the location, type, and sampling rate, as well as information on any channels marked as bad during pre- processing. (c) EEG data and event-related files: Including EEG data in BrainVision format and event files that record marker information. (d) ICA-related files: Containing independent components in numpy format, records of removed components during pre-processing, and topographic maps of the components. (e) Text materials: Containing original and segmented text. (f) Text embedding files: Each file corresponds to an experimental run and is stored in .npy format. (g) Raw EEG data.

    Journal: Scientific data

    Article Title: ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding.

    doi: 10.1038/s41597-024-03398-7

    Figure Lengend Snippet: Fig. 3 File structure of the dataset. (a) Eye-tracking data: Each experimental run is associated with a .rar file that contains eye-tracking data. (b) Electrode information files: These include detailed information of electrodes such as the location, type, and sampling rate, as well as information on any channels marked as bad during pre- processing. (c) EEG data and event-related files: Including EEG data in BrainVision format and event files that record marker information. (d) ICA-related files: Containing independent components in numpy format, records of removed components during pre-processing, and topographic maps of the components. (e) Text materials: Containing original and segmented text. (f) Text embedding files: Each file corresponds to an experimental run and is stored in .npy format. (g) Raw EEG data.

    Article Snippet: Experiment setupEquipment Experiment protocol C ha nn el s Time (s)EEG device EGI 128 geodesic sensor net Eye tracker Tobii pro glasses 3 t Raw EEG Pretrained language model Texts Eye-tracking data Raw data Derivatives Text embeddings t t tTemporal alignment Pre-processed EEG t t t Pre-processsing Data modalities a b c d C ha nn el s Fig. 1 Overview of the experiment and the modalities included in the dataset. (a) Equipment utilized in the experiment, including the EGI device for collecting EEG data and the Tobii Pro Glasses 3 eye-tracker for tracking eye movements. (b) The experiment setup.

    Techniques: Sampling, Marker