Cognitive Neuroscience, EEG Data Analysis, EEG ERP P300 N400, Physiology and Behavior - NIRS fNIRS Neuroscience Course, Cognitive Neuroscience CNS 2022

Tuesday, 05 de April de 2022

Cognitive Neuroscience NIRS fNIRS Course 


NIRS fNIRS Online Neuroscience Course Instituto do Cerebro


Cognitive Neuroscience CNS 2022

Cognitive Neuroscience CNS 2022 Neurociencia y Sociedad Neuroscience 2022 Behavioral Neuroscience Meetings - Latin American and Intentional Encuentros de Neurociencia Conductual - Latinoamericanos e Intencionales Encontros de Neurociência Comportamental - Latino-Americanos e IntencionaisSociedade Brasileira de Neurociências e ComportamentoSociedad Chilena de Neurociência

EEG fMRI | EEG fMRI Analyzing fMRI data

Analyzing fMRI data | EEG fMRI

EEG Data Analysis I | EEG Data Analysis 

EEG Data Analysis Analyzer: Analysis software for EEG ERP P300 N400 research, Video integration, Raw Data Inspection, interactive ICA, FFT, Wavelets, LORETA, MR and CB artifact correction, Integration for eye-tracking data,CSD Current Source Density, Grand Average, Grand Segmentation, ERS/ERD Event-related synchronization and desynchronization, FFT Fast Fourier Transform, FFT Inverse, ICA Independent Component Analysis, Inverse ICA,Butterworth filter, Linear Derivation, LORETA for source analysis, Ocular Correction ICA based on ICA, PCA Principal Component Analysis, Segmentation,Topographic Interpolation, t-Test paired and unpaired t-Tests, Wavelets, Wavelet ExtractionFunctionalBESA Research:Data review and processing for reviewing and processing of your EEG or MEG data. Digital filtering: high, low, and narrow band pass, notch. Interpolation from recorded to virtual and source channels.Automated EOG and EKG artifact detection and correction. Advanced user-defined instantaneous artifact correction. Spectral analysis: FFT, DSA, power and phase mapping. Independent Component Analysis (ICA): Decomposition of EEG/MEG data into ICA components that can be used for artifact correction and as spatial sources in the source analysis window. Connectivity analysis, a unique feature for viewing brain activity, transforms surface signals into brain activity using source montages derived from multiple source models or beamformer imaging. This allows displaying ongoing EEG/MEG, single epochs, and averages with much higher spatial resolution. Source montages and 3D whole-head mapping. ERP analysis and averaging. Source localization and source imaging. Individual MRI and fMRI integration with BESA MRI and BrainVoyager. Source coherence and time-frequency analysis

EEG Data Analysis II | EEG Data Analysis

Physiology and Behavior 1 | Physiology and Behavior

Behavior Conferences | Physiology and Behavior 

Behavior Conferences

Cognitive Neuroscience, EEG Data Analysis, EEG ERP P300 N400, Physiology and Behavior - NIRS fNIRS Neuroscience Course, Cognitive Neuroscience CNS 2022

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00:00:00 - 05:36:00

Cognitive Neuroscience CNS 2022Neurociencia y SociedadNeuroscience 2022Behavioral Neuroscience Meetings - Latin American and IntentionalEncuentros de Neurociencia Conductual - Latinoamericanos e IntencionalesEncontros de Neurociência Comportamental - Latino-Americanos e IntencionaisSociedade Brasileira de Neurociências e ComportamentoSociedad Chilena de Neurociencia


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05:36:00 - 08:58:00

EEG fMRI


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08:58:00 - 10:58:00

Analyzing fMRI data


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10:58:00 - 14:32:00

EEG Data AnalysisAnalyzer:Analysis software for EEG ERP P300 N400 research, Video integration, Raw Data Inspection, interactive ICA, FFT, Wavelets, LORETA, MR and CB artifact correction, Integration for eye-tracking data,CSD Current Source Density, Grand Average, Grand Segmentation, ERS/ERD Event-related synchronization and desynchronization, FFT Fast Fourier Transform, FFT Inverse, ICA Independent Component Analysis, Inverse ICA,Butterworth filter, Linear Derivation, LORETA for source analysis, Ocular Correction ICA based on ICA, PCA Principal Component Analysis, Segmentation,Topographic Interpolation, t-Test paired and unpaired t-Tests, Wavelets, Wavelet ExtractionFunctionalBESA Research:Data review and processing for reviewing and processing of your EEG or MEG data. Digital filtering: high, low, and narrow band pass, notch. Interpolation from recorded to virtual and source channels.Automated EOG and EKG artifact detection and correction. Advanced user-defined instantaneous artifact correction. Spectral analysis: FFT, DSA, power and phase mapping. Independent Component Analysis (ICA): Decomposition of EEG/MEG data into ICA components that can be used for artifact correction and as spatial sources in the source analysis window. Connectivity analysis, a unique feature for viewing brain activity, transforms surface signals into brain activity using source montages derived from multiple source models or beamformer imaging. This allows displaying ongoing EEG/MEG, single epochs, and averages with much higher spatial resolution. Source montages and 3D whole-head mapping. ERP analysis and averaging. Source localization and source imaging. Individual MRI and fMRI integration with BESA MRI and BrainVoyager. Source coherence and time-frequency analysis


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14:32:00 - 19:16:00

EEG Data AnalysisAnalyzer:Analysis software for EEG ERP P300 N400 research, Video integration, Raw Data Inspection, interactive ICA, FFT, Wavelets, LORETA, MR and CB artifact correction, Integration for eye-tracking data,CSD Current Source Density, Grand Average, Grand Segmentation, ERS/ERD Event-related synchronization and desynchronization, FFT Fast Fourier Transform, FFT Inverse, ICA Independent Component Analysis, Inverse ICA,Butterworth filter, Linear Derivation, LORETA for source analysis, Ocular Correction ICA based on ICA, PCA Principal Component Analysis, Segmentation,Topographic Interpolation, t-Test paired and unpaired t-Tests, Wavelets, Wavelet ExtractionFunctionalBESA Research:Data review and processing for reviewing and processing of your EEG or MEG data. Digital filtering: high, low, and narrow band pass, notch. Interpolation from recorded to virtual and source channels.Automated EOG and EKG artifact detection and correction. Advanced user-defined instantaneous artifact correction. Spectral analysis: FFT, DSA, power and phase mapping. Independent Component Analysis (ICA): Decomposition of EEG/MEG data into ICA components that can be used for artifact correction and as spatial sources in the source analysis window. Connectivity analysis, a unique feature for viewing brain activity, transforms surface signals into brain activity using source montages derived from multiple source models or beamformer imaging. This allows displaying ongoing EEG/MEG, single epochs, and averages with much higher spatial resolution. Source montages and 3D whole-head mapping. ERP analysis and averaging. Source localization and source imaging. Individual MRI and fMRI integration with BESA MRI and BrainVoyager. Source coherence and time-frequency analysis


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19:16:00 - 21:06:00

Physiology and Behavior 1


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21:06:00 - 23:59:00

Behavior Conferences


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Autor:

Jackson Cionek

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