LORETA for source analysis, Ocular Correction ICA, PCA Principal Component Analysis - Cognitive Neuroscience of Volition, Neuroscience 2023 NIRS-fNIRS EEG NIRS for research

Wednesday, 24 de May de 2023

EEG ERP LORETA for source analysis Ocular Correction ICA PCA Principal Component Analysis

Mental Health and Neuroscience | Neuroscience 2023

Neuroscience 2023 NIRS-fNIRS EEG NIRS for research Neuroscience 2023 EEG Publication EEG ERP EEG NIRS TMS EyeTracking VideoSync EEG NIRS Data Analysis BrainSupport Solution for Neuroscience ResearchersNeuroscience to improve Latin American Identity. Scientific questions and experimental designs for the development of culture, behavior, perception and Latin American consciousness.

EEG Data Analysis I | EEG Data Analysis

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

EEG Data Analysis II | EEG Data Analysis

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

Cognitive Neuroscience of Volition II | Cognitive Neuroscience

Cognitive Neuroscience CNS 2023

Alta Performance Desktop Laptop

Cognitive Brain Aging Biomarkers Lifestyle Genetics | Cognitive Neuroscience

Mental Health and Neuroscience | Neuroscience 2022

00:00:00 - 06:17:00

Neuroscience 2022Neuroscience 2022 Lectures - Brain Support Latam HighlightsNeuroscience 2022 NIRS Publication NIRS-fNIRSNeuroscience 2022 EEG NIRS for researchNeuroscience 2022 EEG Publication EEG ERPEEG NIRS TMS EyeTracking VideoSync EEG NIRS Data Analysis BrainSupport Solution for Neuroscience ResearchersNeuroscience to improve Latin American Identity. Scientific questions and experimental designs for the development of culture, behavior, perception and Latin American consciousness.

EEG Data Analysis I | EEG Data Analysis

06:17:00 - 09:57:00

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