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--></style></head><body lang=EN-US link="#0563C1" vlink="#954F72" style='word-wrap:break-word'><div class=WordSection1><p class=MsoNormal style='margin-bottom:7.5pt;line-height:115%'><span style='font-size:12.0pt;line-height:115%;color:black'>Dear community,<o:p></o:p></span></p><p class=MsoNormal style='margin-bottom:7.5pt;text-align:justify;text-justify:inter-ideograph;line-height:115%'><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'>As we are approaching deadline (<b><u>January 30</u></b>) for registering for </span><b><span style='font-size:16.0pt;line-height:115%;color:#C00000'>"EEG/ERPs Recording and Analysis: A multifaceted approach to EEG signals"</span></b><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'> Online Course, here is a reminder for the interested researchers who haven’t been registered yet.<o:p></o:p></span></p><p class=MsoNormal style='margin-bottom:7.5pt;text-align:justify;text-justify:inter-ideograph;line-height:115%'><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'>The <b>"EEG/ERPs Recording and Analysis: A multifaceted approach to EEG signals"</b> Online Course is going to be held by <strong><span style='font-family:"Calibri",sans-serif'>Dr. Raphaël Fargier</span></strong>, PhD in Cognitive Neuroscience, Université Claude Bernard Lyon 1, France, who is a researcher in cognitive neuroscience with 10 years of experience and his research is focused on semantic cognition and the neurobiology of language.<br>Through the course you will learn about the basics of EEG signal and how to record it. You will learn different approaches to EEG signal processing, that are more or less commonly adopted in cognitive neuroscience, including the study of Event-Related Potentials, Microstates/Topographic patterns, and Brain oscillations. You will learn about EEG signal preprocessing and how to compute ERPs, Microstates and Time-frequency maps in relationship with the constraints linked to experimental manipulations and designs.<br>There will be a heavy focus on critical thinking about the choices of analyses as a function of research questions, challenges depending on experimental designs, and parameters to pay attention to. The variety and appropriateness of statistical methods currently used to validate (or not) hypotheses about cognitive processes will also be discussed. All of that will be evidenced through the presentation and discussion of case studies in electrophysiology of language.<br>At the end of the course, you will know the strengths and weaknesses of these tools, and will be able to decide which measure is best adapted to your own scientific investigations about cognition.<o:p></o:p></span></p><p class=MsoNormal style='margin-bottom:7.5pt;text-align:justify;text-justify:inter-ideograph;line-height:115%'><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><o:p> </o:p></span></p><p class=MsoNormal style='line-height:115%'><b><span style='font-size:16.0pt;line-height:115%;color:#6F6F6F'>Prospective overview of the sessions</span></b><b><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'> <i><br><em><span style='font-family:"Calibri",sans-serif'>1. Basics of EEG signal and EEG recordings</span></em></i></span></b><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><br>* Overview of the theory behind neural signals<br>* Contrasting neuroimaging methods<br>* Presentation of different EEG recording systems and their classical features<br>* Tips on EEG recordings<br>* Principles of experimental designs using EEG in cognitive neuroscience (events, timing etc)<o:p></o:p></span></p><p class=MsoNormal style='line-height:115%'><b><i><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><br><em><span style='font-family:"Calibri",sans-serif'>2.</span></em></span></i></b><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'> <em><b><span style='font-family:"Calibri",sans-serif'>EEG pre-processing</span></b></em><br>Goal: Mastering the successive pre-processing steps including principles and challenges of:<br>* Artifact rejection and correction (e.g. ICA; 3D Spline electrode interpolation)<br>* Filtering (e.g. parameters, band widths etc)<br>* Re-referencing (e.g. mastoid, average reference, Laplacian)<br>* single-to-noise and number of trials<o:p></o:p></span></p><p class=MsoNormal style='line-height:115%'><b><i><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><br><em><span style='font-family:"Calibri",sans-serif'>3. ERPs</span></em></span></i></b><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><br>* Presentation of classical ERPs as markers of cognitive processes(e.g. N1/P2, P1, N400, etc.)<br>* Computing single-subject and group-average ERPs:<br>Pre-stimulus baseline correction (rationale, parameters, tips)<br>Methods used to extract measures including amplitudes, latencies and topographies<br>of ERPs<br>Methods for statistical evaluation of differences across experimental manipulations<br>* Differences between stimulus-aligned and response-aligned epochs, and associated challenges for signal processing<o:p></o:p></span></p><p class=MsoNormal style='line-height:115%'><b><i><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><br><em><span style='font-family:"Calibri",sans-serif'>4. Spatio-temporal segmentation</span></em></span></i></b><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><br>* Origin of microstates<br>* Rationale of Spatio-temporal segmentation (StS) and presentation of successive steps of<br>analyses (e.g. Topography consistency test, Tanova)<br>* Presentation of two ways to compute StS (different toolboxes) and the respective<br>parameters to take care of<br>* Extraction of measures, and statistical evaluations of differences across experimental<br>manipulations via fitting (e.g. global explained variance, duration, presence, etc.)<br>* Single-trials and mixed models<o:p></o:p></span></p><p class=MsoNormal style='line-height:115%'><b><i><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><br><em><span style='font-family:"Calibri",sans-serif'>5. Time-frequency analyses</span></em></span></i></b><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><br>* Rationale of oscillatory dynamics in EEG signal (evoked vs. induced activity)<br>* Challenges in pre-processing to obtain time-frequency maps as compared to ERPs<br>* Different methods used for time-frequency decomposition<br>* Challenges of baseline normalization (the case of response-aligned epochs)<br>* The various measures that can be extracted from time-frequency maps and the variety of approaches for statistical validation<o:p></o:p></span></p><p class=MsoNormal style='line-height:115%'><span style='font-size:12.0pt;line-height:115%;color:#6F6F6F'><o:p> </o:p></span></p><p class=MsoNormal style='line-height:115%'><span style='font-size:14.0pt;line-height:115%;color:#6F6F6F'>You can watch the introductory webinar to this course using the linke below:<o:p></o:p></span></p><p class=MsoNormal style='line-height:115%'><span style='font-size:14.0pt;line-height:115%;color:#6F6F6F'><a href="https://sciencebeam.com/raphael-fargier-webinar/">https://sciencebeam.com/raphael-fargier-webinar/</a> <o:p></o:p></span></p><p class=MsoNormal style='line-height:115%'><span style='font-size:14.0pt;line-height:115%;color:#6F6F6F'><o:p> </o:p></span></p><p class=MsoNormal style='line-height:115%'><span style='font-size:14.0pt;line-height:115%;color:#6F6F6F'>For more information and registration click on the link below:<o:p></o:p></span></p><p class=MsoNormal style='line-height:115%'><span style='font-size:14.0pt;line-height:115%'><a href="https://sciencebeam.com/eeg-erps-recording-and-analyses/">https://sciencebeam.com/eeg-erps-recording-and-analyses/</a> <o:p></o:p></span></p><p class=MsoNormal style='line-height:115%'><span style='font-size:14.0pt;line-height:115%'><o:p> </o:p></span></p><p class=MsoNormal style='line-height:115%'><span style='font-size:14.0pt;line-height:115%'>Don’t miss this opportunity!<o:p></o:p></span></p></div></body></html>