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In order to analyze our data as accurately as possible, it is important that we filter out the extreme high and low frequency waves in our data, as these recordings are most likely due to the environment and other artifacts. Typically, frequencies less than 0.01 Hz - 0.1 Hz and greater than 40 Hz - 50 Hz are filtered out. BESA automatically turns on low and high cutoff filters that can be edited if desired. Keep in mind that filters distort data, and filtering too much can alter waveforms and wave amplitudes significantly. Filtering tutorial day 1 of the BESA workshop: 52:10 - 1:06:17

Affected data segments may be rejected (deleted) or replaced (interpolated) with estimations based on nearby non-artifact contaminated data. Interpolation should be less than 5% of the total channels (so interpolate 3-4 channels max if you have 64 channels total) This is due to the data warping interpolation does to nearby data. Deleting Channels We may want to delete bad channels that contain too many artifacts (noise, movement, blinking, etc.). Right click on the desired channel and click “Define this channel as bad”. The channel will automatically delete. This process can be reversed by clicking “Define this channel as bad” again. Interpolating Channels Interpolating creates a new, computer generated version of a bad channel using the data from the channels directly above and below it. This is not actual data and is merely an approximation. The channel label will turn pink when this is done.

BESA is capable of automatically recognizing the electrode coordinates and their labels for certain EEG caps. Channels that have been successfully identified by BESA have 10-10 names (E.g. Fp1, C1, P3) and are called Scalp Channels. Channels that have not been successfully identified by BESA have different names (E.g. EXG1, EA7, EB28) and are called Polygraphic Channels. In order to match up polygraphic channels with their locations, additional files containing EEG cap information must be imported into BESA. Dr. Thom has several of these files stored in the computer. If none of the channels are polygraphic, you do not need to manually set channel locations. Click on “Load Channel Configuration…” under the file tab This warning will pop up. Click “Yes” All the files on the computer will pop up. Go to… Windows (C:)→Users→Public→Public Documents→BESA→Research_7_0→Montages→Channels In the channels folder, there are folders of four different companies and the type of EEG caps they use. If you don’t know the type of cap used in the experiment, try counting the number of channels and finding a file in the StandardElectrodes that has around the same number of channels. In the example above, I was able to find a file (81 electrodes) within the StandardElectordes folder that allowed BESA to recognize and locate each of the electrodes. Here is a before and after setting the channel locations. Notice how the polygraphic channels are all black, with little readable data. Also, if you need to upload files into BESA in order to add additional information about channel configuration (*.ela), digitized head surface points (*.sfp, *.eps), labels (*.sfn), etc., watch the tutorial in day 1 of the BESA workshop: 22:02 - 23:00

Introduction Level 0 is the basic layout of the Brain Hygiene Lab. Level 1 contains broad information about our focuses. Level 2 contains pertinent review articles, textbook chapters, and information about the methods used to gather data, as well as other important information. Please review these pages to gain a greater understanding of the research being conducted by the Brain Hygiene Lab. Level 0 Level 1 Level 2

Methods EEG Next The brain is made up of a vast array of neural networks that can be measured with electroencephalography (EEG). From resting-state activity, to the detection of emotional processing and cognitive function, EEG literally provides a window into the brain. The Brain Hygiene Lab uses a high-density EEG system designed and manufactured by Electrical Geodesic, Inc. HRV Next An active brain communicates with the body via the somatic and autonomic nervous systems. The somatic system manages voluntary muscle movement, while the autonomic system regulates internal organs during stress. It comprises the sympathetic and parasympathetic branches, and heart-rate variability measurement indicates their influence on the heart. Questionnaires Next Surveys and questionnaires collect qualitative information that provides a detailed summary of your experiences. Researchers use these surveys to get to know you, to interpret your EEG and HRV data, and to develop a comprehensive, personalized Behavioral Health Report. fNIRS Next Brain cells require oxygen and fuel for metabolism, which is supplied by the blood. Near-infrared light passing through the scalp can measure oxygenation levels in the blood and its return to the scalp, offering spatially precise metrics for assessing brain activity and function. Eye Tracking Next The eyes are the window to the mind. In many circumstances, we utilize our vision to focus our attention on an object; therefore, we can learn a lot about what people attend to by tracking their eyes. The Brain Hygiene Lab is equipped with a Tobii Pro Spectrum 150 Eye-tracking system, with Tobii Pro Lab software and Eprime integration. Peripheral Psychophysiology Next Our lab is also equipped with a Physio 16 Package from EGI that integrates with our high-density EEG system from EGI. With this system we can seamlessly collect respiration, ECG, Sp02 and other types of peripheral psychophysiological data.

< Back EEG Pipeline EEG stands for electroencephalography, which is a technique used to measure electrical activity in the brain. EEG is a non-invasive way to collect data from the brain. Follow this pipeline to collect and analyze EEG data. 1 Collect Data The recorded data will be saved as a .mff file. This will need to be moved to the appropriate folder in Box. 2 Import Data The data will need to be opened in BESA on one of the analysis computers. 3 Re-reference Data You need to convert the data to an average reference. 4 Set Channel Locations Select the files that specifies the channel locations. 5 Delete or Interpolate Bad Channels You may want to delete channels that are too noisy, such as the ones around the face. 6 Filtering We use filters to take out signals that are definitley not brain data. You need to filter out the very low (<0.01-0.1 Hz) and very high frequencies (>50-100 Hz), as well as the 60 Hz line noise from the ambient electrical wires. 7 Run ICA ICA is used to separate out the data into its various signal sources, which are both neural and non-neural. 8 Epoching For each stimulus, we want to extract a segment of data just before and just after the stimulus. 9 Baseline Removal The signal recorded just before the stimulus is considered the baseline. This is comprised of neural activity that is not in response to the stimulus as well as noise. This baseline is subtracted from the entire epoch, leaving the neural activity that occured in response to the stimulus. 10 Component Rejection Once you've run ICA on a dataset, it is possible to reject non-neural signal sources. This section explains how to do that and explains the Sasica plug in. 11 Sorting by Stimulus Type Separating the data for each stimulus type into its own file. 12 Averaging Trials Separating the data for each stimulus type into its own file. 13 Check the Data Head Plots Plot the head maps for the time ranges of interest ​ Download Waveforms Plot the waveforms of the averaged data ​ Download Grand Averaging Averaging all of the data of one type together (such as all face data / scene data) Download 14 Analyze the Data Average Amplitudes Wavelet Analysis Fourier Transforms Phase Coherence Download Resources Filename Key Download Automation Scripts Download EEGLAB Scripts Download Other Download