Overview of Methodology. Human Electrophysiology. Computing and Displaying Difference Waves. Plotting The Averaged ERP

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1 Human Electrophysiology Overview of Methodology This Week: 1. Displaying ERPs 2. Defining ERP components Analog Filtering Amplification Montage Selection Analog-Digital Conversion Signal-to-Noise Enhancement averaging artifact rejection digital filtering Display waveforms topographical maps SCDs, deblurring source analysis Component Analyses Measurement amplitudes latencies Plotting The Averaged ERP Computing and Displaying Difference Waves! Plot ERPs over sufficiently long epoch! Include pre-stimulus baseline! Indicate voltage scale (in microvolts)! Indicate polarity (negative up?)! Indicate time denoted by ticks on x-axis! Indicate electrode location Nd1 Nd2 McDonald, Teder-Sälejärvi, and Hillyard (2001) McDonald, Teder-Sälejärvi, and Hillyard (2001)

2 Overview of Methodology Analog Filtering Analog-Digital Conversion Amplification Signal-to-Noise Enhancement Montage Selection averaging artifact rejection digital filtering Mapping of ERPs! mapping the distribution of ERPs across the scalp is the first step in characterizing the spatial structures in the scalprecorded waveforms (ERP scalp topologies) and their temporal evolvement. Display waveforms topographical maps SCDs, deblurring source analysis Visual LDAP Component Analyses Measurement amplitudes latencies ms McDonald, Green, & Teder-Sälejärvi (2004) Interpolating Scalp Distributions of ERPs Mapping of ERPs! mapping the distribution of ERPs across the scalp is the first step in characterizing the spatial structures in the scalp-recorded waveforms (ERP scalp topologies) and their temporal evolvement. Lateralized selection negativities in visual search! ERP waveforms vary across space as well as time! Spherical splines allow voltages between and beyond the recording electrodes to be estimated

3 EEG vs. MEG ERP EEG ERP ERF Picton et al (1995) Timing, Topography, and Beyond 3D Mapping Time Green, Teder-Sälejärvi, & McDonald (2004)

4 Timing, Topography, and Beyond Timing, Topography, and Beyond Waveforms Waveforms Scalp distributions Time Time -2 µv -2 µv 100 ms 100 ms Contralateral to cued side Ipsilateral to cued side Green, Teder-Sälejärvi, & McDonald (2004) Timing, Topography, and Beyond Waveforms Scalp distributions Neural generators Contralateral to cued side Ipsilateral to cued side Green, Teder-Sälejärvi, & McDonald (2004) Overview of Methodology Analog Filtering Analog-Digital Conversion Amplification Signal-to-Noise Enhancement Montage Selection Time -2 µv averaging artifact rejection digital filtering Display waveforms topographical maps SCDs, deblurring source analysis Component Analyses 100 ms Measurement amplitudes latencies Contralateral to cued side Ipsilateral to cued side McDonald, Green, & Teder-Sälejärvi (2004)

5 Topographical Maps of Voltages and SCDs Scalp Current Density (SCD)! Also called current source density (CSD), surface Laplacian! SCDs reflect the current flowing in (sink) and out (source) of the head! SCD maps are derived by computing the 2nd spatial derivative of the scalp electric field! SCD maps depict sources and sinks of radial current flow! Sharpened spatial picture; deblurred! Reference-free! McDonald and Ward (2000) Deblurring Overview of Methodology Analog Filtering Analog-Digital Conversion Amplification Signal-to-Noise Enhancement Montage Selection averaging artifact rejection digital filtering Display waveforms topographical maps source analysis Component Analyses Measurement amplitudes latencies

6 Defining Components More Considerations! Simple view: A component is a feature (peak or trough) in an individual ERP waveform! Problems:! Waves reflect the activity of multiple simultaneously active brain regions! Relating features on different waveforms! Physiological definition: a component is measurable electrical activity from a specific neuroanatomical locus in the brain! Psychological or functional definition: a component is electrical activity that arises from brain processes involved in performing a specific information processing function! Exogenous versus endogenous components! Some early, some late! Some components visible only in the difference between two conditions or waveforms! Mismatch negativity (deviant ERP minus standard ERP)! N2pc (contralateral ERP minus ipsilateral ERP)! Peaks are not special (Luck, 2005, Fig 2.1)! More on this next week The ERP Cookbook Auditory ERP! Visual ERPs: C1 (NP80), P1, N1, etc.! Auditory ERPs: ABRs, mid-latency ERPs, N1, P2, etc.! Mismatch Negativity (MMN)! P3! Processing Negativity (PN; Negative Difference, Nd)! Error-related Negativity (ERN)! Lateralized Readiness Potential (LRP)! N2pc

7 Mismatch Negativity (MMN) Mismatch Negativity (MMN)! The MMN is elicited by an infrequent change in a repetitive stream of auditory stimulation! Oddball paradigm (week 7)! Elicited by any discriminable change in auditory stimulation, including:! Frequency: beep beep beep boop beep! Intensity: beep beep beep BEEP beep! Waveforms, and difference waves From Sams et al. (1985) Mismatch Negativity (MMN) Mismatch Negativity (MMN)! topography Fz EEG M2 MEG Todd et al. (2010) From Garrido et al. (2007) Hirayasu et al. (1998) From Besle et al. (2007)

8 Explanations of Mismatch Negativity (MMN) Mismatch Negativity (MMN) 1. sensory-memory model (Näätänen, 1990, 1992) Rinne et al. (2000) See Garrido et al. (2009) Explanations of Mismatch Negativity (MMN) Visual Search 2. sensory adaptation model (Näätänen, 1990, 1992) What is going on during search? What can ERPs tell us about these processes?

9 Tracking attention with lateralized ERPs: The N2pc Tracking attention with lateralized ERPs: The N2pc Ipsilateral to target Contralater al to target 0 N2pc -2 µv ms 0 contralateral ipsilateral [N2pc = N2 posterior contralateral] [N2pc = N2 posterior contralateral] Tracking attention with lateralized ERPs: The N2pc Tracking attention with lateralized ERPs: The N2pc Distractor suppression (e.g. Luck & Hillyard, 1994) (e.g., Eimer, 1996) [N2pc = N2 posterior contralateral] processing [N2pc = N2 posterior contralateral]

10 Tracking stimulus processing in visual search Tracking stimulus processing in visual search " multiple stages of processing indexed by lateralized selection negativities " multiple stages of processing indexed by lateralized selection negativities ms ms 400 ms ms ms 400 ms N2pc attentional selection ACN access to VSTM? SPCN VSTM maintenance -2 µv 800 ms contralateral ipsilateral

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