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The ERP Boot Camp

The ERP Boot Camp. Baselines, Difference Waves, and the MONSTER Paradigm. Segmenting & Baselining. Prior to averaging, we must extract segments (epochs) of the EEG surrounding the relevant events Baseline correction is usually performed at this point

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The ERP Boot Camp

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  1. The ERP Boot Camp Baselines, Difference Waves, and the MONSTER Paradigm

  2. Segmenting & Baselining • Prior to averaging, we must extract segments (epochs) of the EEG surrounding the relevant events • Baseline correction is usually performed at this point • This is important for some types of artifact rejection procedures (e.g., absolute voltage thresholds) • For most purposes, baseline correction can be performed at any time Voltage Time

  3. Reason 1: DC Offset 115 µV

  4. Reason 2: Baseline Drift

  5. How to Correct Baseline Goal: Subtract estimate of DC offset from the waveform Mean prestimulus voltage is usually a reasonable estimate Subtract this value from each point in the waveform Note: Anything that messes up the baseline (e.g., noise, overlap) will be propagated to your amplitude measurements

  6. Baseline Distortion Example 1 Entire waveform shifted down (negative) because of positive noise blip

  7. Baseline Distortion Example 2

  8. How to Correct Baseline • What to use for response-locked averages? • A period that is equivalent across conditions • Often, only the prestimulus period is guaranteed to be equivalent • Simple option- • Average using a long pre-response interval and use a time range that is prior to the stimulus for every response • Complex option- • Use the prestimulus period for each individual trial

  9. Difference Waves w1,1 C1 C2 C3 E1 w2,1 w3,1 w1,2 w2,2 E2 w3,2 w1,3 w2,3 E3 w3,3 E1 E2 If a single component varies across conditions, it can be isolated by means of a difference wave For this to work, the conditions must be so similar that only one component varies across conditions C3 E3 C1 C2

  10. Example: N170 This voltage reflects face-related activity plus everything else that is active at 170 ms Rossion & Jacques (2009)

  11. Example: N170 This difference reflects only brain activity that differentiates between faces and cars Rossion & Jacques (2009)

  12. N170 and Development Faces Scrambled Faces Cars Scrambled Cars Kuefner et al (2010, Frontiers in Human Neuroscience)

  13. It looks like the N170 scalp distribution changes over development But this could be due to other components in this time range Kuefner et al (2010, Frontiers in Human Neuroscience)

  14. Subtracting scrambled faces removes nonspecific activity The face-specific activity has the same distribution over development Kuefner et al (2010, Frontiers in Human Neuroscience)

  15. Shortcomings of Difference Waves • May not isolate a single component • Example: Rare-Frequent yields P2, N2, P3 • If Cond1–Cond2 difference wave is reduced, cannot distinguish between smaller Cond1 and larger Cond2 • For most components, need to look at original waveforms as well as difference waves (not for N2pc/LRP) • Ask Emily how we solved this problem for LRP • Changes in latency between Cond1 and Cond2 produce an apparent difference in amplitude • Not a problem if you view difference wave as simply meaning a difference in the time course of amplitude

  16. The MONSTER Approach • Manipulation of Orthogonal Neural Systems Together in Electrophysiological Recordings • General approach in which multiple components are simultaneously isolated with high efficiency by means of a factorial design and difference waves • Each factor used to create a difference wave that isolates a specific component • Our version of MONSTER isolates 4 components • C1- Sensory processing in primary visual cortex • N2pc- Shift of visual attention • P3- Task-governed stimulus categorization • Lateralized Readiness Potential (LRP)- Response activation in primary motor cortex

  17. Isolating the C1 Wave • Onset 40-60 ms; peak ca. 80-100 ms • Thought to arise from area V1 • Negative for upper-field stimuli; positive for lower-field stimuli • When positive, merges together with P1 • Largest at midline occipital-parietal sites Mangun, Hillyard, & Luck (1993)

  18. Isolating the C1 Wave Mangun, Hillyard, & Luck (1993)

  19. Isolating the C1 Wave

  20. Isolating the LRP Left Hemisphere (Ipsi) Right Hemisphere (Ipsi) Right Hemisphere (Contra) Left Hemisphere (Contra) LRP = Contra minus ipsi, averaged over left & right hands Smulders & Miller (2010)

  21. Isolating the LRP LRP = Contra minus ipsi, averaged over left & right hands Smulders & Miller (2010)

  22. Isolating the LRP Left Hemisphere (Ipsi) Right Hemisphere (Ipsi) Right Hemisphere (Contra) Left Hemisphere (Contra) Nonlateralized components eliminated by subtraction Smulders & Miller (2010)

  23. Isolating the LRP Left Hemisphere (Ipsi) Right Hemisphere (Ipsi) Right Hemisphere (Contra) Left Hemisphere (Contra) Overall hemisphere differences eliminated by subtraction (RHem more positive than LHem for both hands)

  24. Isolating the LRP Left Hemisphere (Ipsi) Right Hemisphere (Ipsi) Right Hemisphere (Contra) Left Hemisphere (Contra) Overall hand differences eliminated by subtraction (RHand more positive than LHand for both hemispheres) Smulders & Miller (2010)

  25. Isolating the LRP LRP provides a pure measure of the relative activation of correct vs incorrect response at each moment in time Smulders & Miller (2010)

  26. Isolating the N2pc Component

  27. Isolating the P3 Wave • P3 amplitude depends on the probability of a task-defined stimulus category, not the probability of a physical stimulus • P3 probability effect cannot begin until after categorization occurs • Rare-minus-frequent difference wave isolates processes that occur after perception and categorization • P3 latency indexes “stimulus evaluation time”

  28. P3 Difference Waves

  29. The MONSTER Approach • Manipulation of Orthogonal Neural Systems Together in Electrophysiological Recordings • Goal- Efficiently measure the speed and integrity of a broad set of specific neurocognitive processes • First step in determining the nature of deficits in a given patient group • Possibly useful for diagnosis of disease subtypes (e.g., in multiple sclerosis) • Use orthogonal subtractions to isolate specific ERP components that reflect well-characterized neurocognitive processes • Same data divided different ways to isolate different components

  30. Stimuli and Task Task: Attend to black or white Press left for A (p = .80 or p = .20) Press right for B (p = .20 or p = .80) Left/Right and .80/.20 are counterbalanced Stim: Duration = 200 ms SOA = 1500 ± 150 ms 2 blocks of 512 stimuli

  31. Stimuli and Task C1: Upper Checks minus Lower Checks N2pc: Contra target minus Ipsi target P3: Rare minus Frequent LRP: Contra to response hand minus Ipsito response hand These subtractions are orthogonal -- same 1024 trials divided into different pairs of subsets and then subtracted

  32. Electrode Sites LRP P3 N2pc C1

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