workshop: erp testing -...

Workshop: ERP Testing©

DOE 993511NIH R01 HL0100602 NIH R01 DC005994 NIH R41 HD47083NIH R01 DA017863NASA SA42-05-018NASA SA23-06-015

Dennis L. Molfese, Ph.D.University of Nebraska - Lincoln

Friday, January 14, 2011

Workshop Goals

Concepts & Definitions

Workshop Goals

Concepts & DefinitionsCommon Practices

Workshop Goals

Concepts & DefinitionsCommon PracticesAnalysis Approaches

Workshop Goals

Concepts & DefinitionsCommon PracticesAnalysis ApproachesDealing with Artifacts

Workshop Goals

Concepts & DefinitionsCommon PracticesAnalysis ApproachesDealing with ArtifactsProblem Solving

Workshop Daily Schedule

ERP Theory, Methodology, IssuesElectrode issuesArtifactsEquipmentVideos -

Unpack & Setup ERP SystemElectrode Net ApplicationNet Station Operation

Preprocessing of ERP DataData Management & AnalysesVideos -

Packing up ERP System

Workshop Daily Schedule

Ultimate Goal

You Become An Independent Neuroscience Investigator who can:1. Design & conduct independent studies.2. Develop the Skills to run data analyses.3. Draft and submit imaging manuscripts.4. Develop grant applications.5. Revolutionize your major field of study.

The Training Plan

1. Two-day ERP workshop2. Experiment planning session(s)3. Hands-on training on ERP equipment4. Conducting YOUR experiment5. Data Analysis Assistance6. Manuscript Development Assistance7. Grant Application Assistance

1.Overview of ERP Theory, Methodology & Issues.

Why ERPs?

Correlation with cognitive & physiological eventsTime resolution (ms)Spatial resolutionPortabilityNo age limitsUseful with or without behavioral responseCost

General Methodology Principles

Same as in any research:

Same as in any research:Screen & control participant variables

Same as in any research:Screen & control participant variablesControl stimulus & experimental factors

Same as in any research:Screen & control participant variablesControl stimulus & experimental factorsData quality

Same as in any research:Screen & control participant variablesControl stimulus & experimental factorsData qualityDatabase

Same as in any research:Screen & control participant variablesControl stimulus & experimental factorsData qualityDatabaseData analyses

Same as in any research:Screen & control participant variablesControl stimulus & experimental factorsData qualityDatabaseData analysesReplication

HistoryDefinitionsElectrodesTesting IssuesApplications

Where we have come from....

OscilloscopeTracings &Photographs

Where are we now....

ERPs to CVC WordsBelow Average Readers Average Readers Above Average Readers

Event-Related Potentials

ERPPortion of Ongoing EEG

Time-Locked to Stimulus Onset

Time-Locked to Stimulus OnsetTemporal Information

Spatial Information

Spatial InformationComparability across the lifespan

EEG Activity

Sampling (Digitizing) Rates

Brain Stem Evoked Response (BSER) 1 - 15 ms

Brain Stem Evoked Response (BSER) 1 - 15 ms Peak Duration 1 - 1.5 ms

Brain Stem Evoked Response (BSER) 1 - 15 ms Peak Duration 1 - 1.5 ms 5-7 peaks to resolve

Brain Stem Evoked Response (BSER) 1 - 15 ms Peak Duration 1 - 1.5 ms 5-7 peaks to resolve Sample 1/5 - 1/10 ms

Middle Latency Response 15 - 65 ms

Middle Latency Response 15 - 65 ms Peak Duration 3 - 5 ms

Middle Latency Response 15 - 65 ms Peak Duration 3 - 5 ms Sample 1/2 - 1 ms

Cognitive components 65 - 1000 ms

Cognitive components 65 - 1000 ms Peak Duration 20 - 100 ms

Cognitive components 65 - 1000 ms Peak Duration 20 - 100 ms Sample 4 - 5 ms

CNV - Contingent Negative Variation 2 S - 10 S

CNV - Contingent Negative Variation 2 S - 10 S Peak Duration 5 - 10 S

ERPs - Extracellular

Event Related Potentials (ERPs)

Time-locked to an evoking or eliciting event or stimulus.

Sequence of serially activated "processes" (components) detected at the scalp (or some biological surface) as distinct positive-negative fluctuations.

Measures:

Measures: ! (1) peak latency from evoking stimulus onset (ms)

Measures: ! (1) peak latency from evoking stimulus onset (ms)! (2) peak amplitude in microvolts µV

Measures: ! (1) peak latency from evoking stimulus onset (ms)! (2) peak amplitude in microvolts µV (3) polarity (deflection from baseline to + or -)

Definitions for ERP displays x-axis

horizontal abscicca time - ms

y-axis vertical ordinate voltage amplitude - µV

ERP Nomenclature

After Desmedt, 1974

ERP Nomenclature

Display Positive vs. Negative Up

Arbitrary

ArbitraryTradition: 70% show Negative Up

Creates some confusion in comparing work across studies

Good to practice inverting waves to gain rapid visual recognition of peaks

Positive Up Negative Up

Display Positive Up

.3 - 100 Hz

60 Hz Notch

.3 - 100 Hz

60 Hz Notch

Display Positive Down

Variations in ERPs Trial by Trial

10 trials selected every 10 trials across 100 trials

500 ms

Note amplitude

Variations inAmplitude &Latency

Peak Latency Variations Produce Different Width Peaks Peak Amplitude Variations Produce Different Size Peaks

More Latency Shift Less Latency Shift

ERP Temporal - Spatial Dynamics

Assess effects that differ in:

•Time (ms)

•Time (ms)•Scalp region distribution (2-D scalp

surface space)

•Time (ms)•Scalp region distribution (2-D scalp

surface space)•Dipole effects (Time and 3-D space)

Basic Measurements

Amplitude Peak amplitude (maximum/minimum point) Mean peak amplitude (average # of points)

Latency Peak latency (maximum/minimum point) Mean peak latency (average # of time points)

Area (Under the Curve) Area for specific region

ERP Amplitude & Latency Measures

Amplitude Peak amplitude

(maximum/minimum point)

Mean peak amplitude (average # of points)

Basic Measurements

Latency Peak latency

(maximum/minimum point)

Mean peak latency (average # of time points)

Basic Measurements

Area (Under the Curve) Area for specific region 50% area (midpoint)

a b c c

Basic Measurements

Peak & Latency Analysis

Pros: Traditional approach Appears straight forward & logical

Cons:- Peaks are not always clear- Developmental issues (changes in latency & amplitude)- Latency shift across scalp & subjects- Subjective judgments- Variations in criteria across journal reports- Very time consuming in training & execution- Replication problems within/across labs- Inter-rater reliability (typically not conducted/reported)

Sample Neonate Responses

ERPs & Averaging

Individual (single trial) ERPs are VERY small- depends on age (e.g., ~.5 to 30µV)

Amplifier/environmental noise are large- varies across amps & manufacturers and models- ~10 µV RMS (same size to 20x larger than single trial ERP)

Thus, single trial ERPs can be OBSCURED by large electrical events, i.e., amplifier noise, environmental signals, artifacts

TO SOLVE PROBLEM:Repeat same stimulus & average resultant single trial ERPs together to increase S/N ratio to improve ERP (signal) quality.

S/N = Signal-to-Noise-Ratio

43Goff, 1971

ERPs & Averaging

ERP noise level varies with number of trials tocreate the average

- square root “law” (conservative)- noise level = square root of the number of trials: 9 trials = 32 or 33.33% of signal could be noise 16 trials = 42 or 25.00% of signal could be noise 25 trials = 52 or 20.00% of signal could be noise 36 trials = 62 or 16.67% of signal could be noise 49 trials = 72 or 14.29% of signal could be noise 64 trials = 82 or 12.50% of signal could be noise 81 trials = 92 or 11.11% of signal could be noise100 trials = 102 or 10.00% of signal could be noise

ERPs & Averaging

Relation of Trials to Signal Noise

1 2 3 4 5 6 7 8

ERP Signal Improvement

# Trials per Average

% of ERP that is Noise

Trade-off between improving S/N and completing an experiment.

ERPs & Averaging

Average ERP obtained early during test differs from later in the same test period.

Trial #s combinedto make averageERP

Reference =linked mastoids

First 25 Trails

Last 25 Trails

The MORE trials presented, the better the S/N ratio.

The MORE trials presented, the LONGER the test session.

The LONGER the test session, the LESS LIKELY the infant/child will complete session.

The LONGER the test session, the LESS LIKELY later ERPs will resemble earlier trial ERPs.

The REAL key to testing populations is to obtain the best S/N ratio without overtaxing the subject (e.g., infant, child, adult).

ERPs & Averaging

“ba”

Another Way To Look At ERPs

IncreasingPositiveVoltage

IncreasingNegativeVoltage

Yellow

Dark Blue

Purple

Neonate ERP to Speech Syllable

Yellow

Dark Blue

Purple

Adult ERP to Speech Syllable

Yellow

Dark Blue

Purple

QUESTIONS ???

Dipoles

a) Dipole used as description of ERP generation.

Dipoles

b) Dipoles perpendicular to surface (since cortex folds, not necessarily perpendicular

Dipoles

to scalp surface).

Dipoles

to scalp surface).

Dipoles

to scalp surface).

c) Reflects differences in soma and dendrite ion flow across cortical layers.

Dipoles

d) Model activity.

Dipoles

d) Model activity.

Dipoles

d) Model activity.

e) Activity at scalp not necessarily result of ion movements immediately below electrode.

Dipoles

d) Model activity.

Dipoles

d) Model activity.

f) Caution: Dipoles generated in one hemisphere may generate higher shifts in other hemisphere.

Dipoles

Low GRTR Scores 1-dipole Model 200 ms

Match Mismatch -1.600

-1.400

-1.200

-1.000

-0.800

-0.600

-0.400

-0.200

0 36 72 108 144 180 216 252 288 324 360 396 432 468 504 540 576 612 648 684

High GRTR Scores2-dipole Model 200 ms

Match Mismatch -1.600

-1.400

-1.200

-1.000

-0.800

-0.600

-0.400

-0.200

0 36 72 108 144 180 216 252 288 324 360 396 432 468 504 540 576 612 648 684

3/1/01 5/2/01

Left Hand Right Hand Left Hand Right Hand

Are Dipoles “Real” ?

Lantz, G., Grave de Peralta, R., Spinelli, L., Seeck, M., & Michel, C. M. (2003). Epileptic source localization with high density EEG: How many electrodes are needed? Clinical Neurophysiology, 114, 63-69.

Michel, C. M., Lantz, G., Spinelli, L., Grave de Peralta Menendez, R., Landis, T., & Seeck, M. (2004a). 128-channel EEG source imaging in epilepsy: Clinical yield and localization precision. Journal of Clinical Neurophysiology.

Michel, C. M., Murray, M. M., Lantz, G., Gonzalez, S., Spinelli, L., & Grave de Peralta, R. (2004b). EEG source imaging. Clinical Neurophysiology, 115, 2195-2222.

Tucker, D. M., Luu, P., Frishkoff, G., Quiring, J. M., & Poulsen, K. (2003). Corticolimbic response to negative feedback in clinical depression. Journal of Abnormal Psychology, 112, 667-678.

QUESTIONS ???

Digitizing Rate

How fast to sample the ERP signal? Convention = 250 Hz (4 ms intervals) Ultimately dependent on signal

characteristics

Nyquist's theorem: Analog waveform may be uniquely reconstructed, without error, from samples taken at equal time intervals. Sampling rate must be equal to, or greater than, twice the highest frequency component in the analog signal (3x works better).

Example: 9 Hz wave sampled 9 times/Sec = 1 Hz waveformFriday, January 14, 2011

Alias - appear as more energy (higher amplitude) at lower frequency

Nyquist - 9 Hz signal

Sampled at 14 Hz

Yields 4.5 Hz Signal

Sampled at 29 Hz

Yields 9 Hz Signal

Srinivasan, Tucker & Murias, 1985

Nyquist - Signal is sum of Sinusoidal Frequencies of 6.5, 10, 19 Hz

How Many Electrodes Should You Use ?

Depends on :Research Question.Availability of Equipment.

Source Localization AND Scalp DistributionStudies ALWAYS require LARGE number ofElectrodes adults = 256 infants = 128

Resolution of Scalp Signals

Simulationof Infant &Child ScalpERP Signals.

Simulationof Adult ScalpERP Signals.

If spatial sampling is too sparse, high spatial details will alias into low spatial frequencies, distorting topographic maps & source localization !

Srinivasan, Tucker & Murias, 1985

The smallest topographic feature that can beresolved accurately by a 32-channel array is 7 cm in diameter - about the size of an ENTIRE lobe of the brain !!!

Nyquist

QUESTIONS ???

Impedance

Before lab computers EEG quality depended on paper recorded signal.

Noise from power lines (50 or 60 Hz) difficult to separate once introduced,

Procedure involved abrading skin to achieve a scalp-electrode impedance < 5 kilo Ohms.

Abrasion removes surface epidermal layer that has greater impedance than underlying tissue.

http://www.sengpielaudio.com/calculator-ohmslaw.htm

Impedance

Voltage (V) = Current(I) X Resistance(R)

If Resistance increases, Current flow will decrease: V/R = IIf Voltage increases, Current flow increases: V = C x R

Current measured in AmpsVoltage measured in VoltsResistance measured in Ohms

Plumbing Analogy:Voltage ~ Water pressure (in a tank)Current ~ Flow Rate (from the tank)Resistance ~ pipe size (allowing water to escape from tank)

Impedance

High vs. Low Impedance Amplifiers

Impedance

High vs. Low Impedance Amplifiers (elec) vs. (amp) High vs. High: 5x10-10

.00000000005 Low vs. Low: 5x10-9

.0000000005

Practice electric circuits:http://www.phy.hk/wiki/englishhtm/Circuit.htm

Impedance

Ferree, T., Luu, P., Russel, J. S., & Tucker, D. M. (2001). Scalp electrode impedance, infection risk, and EEG data quality. Clinical Neurophysiology, 112, 536-544.

Impedance

Note: Watts = Amps x Volts

Electrode Paste vs. Collodian

Adhesive paste EC2 vs. collodion for long-term scalp electrodes placement 40 patients

20: electrode placement on scalp with collodion - Group C(ollodian)

20: EC2 used - Group P(aste). impedance of electrodes measured after electrode

placement (T1) and after 24 h of recording (T2), Application time calculated for all patients

RESULTS: At each observation, group C showed mean values of electrode impedance significantly higher than group P

Collodion: T1: 16.8 kohm; T2: 6.5 kohm EC2 Paste: T1: 2.4 kohm; T2: 4.0 kohm, p < 1 x 10(-5).

Time required to make montage and provide daily maintenance was significantly shorter in group P than in group C

Collodion: 44.3 and 19.7 min EC2 Paste: 20.8 and 10.5 min, p < 1 x 10(-5).

CONCLUSIONS: EC2 paste attaches scalp electrode in less time,

with better recording quality as a result of lower electrode impedance values, than collodion.

SIGNIFICANCE: EC2 paste can substitute for collodion in electrode placement for long-term video-EEG monitoring, with an optimal cost-benefit ratio in terms of recording performance, time consumption, & safety.

Electrode Paste vs. Collodian

QUESTIONS ???

Filters

ERPs (and EEG) are electrical signals that vary in their frequencies and amplitude.

Filters

Filter determines the way in which amplifier sensitivity changes as frequency is reduced.

Filters

Filter determines the way in which amplifier sensitivity changes as frequency is reduced.

Frequency response - bandwidth of amplifier determined by its high & low frequency filters.

Filters

D.C. Amplifier

Filters

D.C. Amplifier Sensitivity does not change with

decreasing frequency.

Filters

Subject to very slow change of output level (drift).

Filters

Low Pass Filter - attenuates HIGH frequency while “saving” or passing through the LOW frequencies (high frequency filter, high band pass filter)

Filters

High Pass Filter - attenuates LOW frequency while “saving” or passing through the HIGH frequencies (low frequency filter, low band pass filter)

Filters

Amplifier Filter Settings

Amplifier Filter Settings Signals are reduced 50% already

when frequency reaches setting depicted on most amplifiers.

Referred to as “Half-Amplitudes”

Referred to as “Half-Amplitudes” E.G., Setting on an amplifier of 2Hz

and 30Hz means signal already reduced by 50% at filter boundaries.

Filters

Filtering - sometimes represented as a Time Constant (TC)

Filters

Describes how amplifier responds to a voltage change

Filters

Voltage -> amplifier is changed.

Filters

Voltage -> amplifier is changed. Amplifier output changed but gradually

returns to baseline, producing a curve (exponential curve) that approaches its final value at a decreasing rate.

Filters

Voltage -> amplifier is changed. Amplifier output changed but gradually

returns to baseline, producing a curve (exponential curve) that approaches its final value at a decreasing rate.

This curve has time constant (the time it takes for the AMPLITUDE to FALL to 37% of its INITIAL VALUE).

Filters

As TIME CONSTANT (TC) increases, high pass filter frequency decreases (memorize ***)

Filters

TIME CONSTANT = C Frequency = f Pi = 3.1415

1/(2 x Pi x C) = f 0.159/C = f 0.159/0.3 = 0.5 Hz (cut off point of low-

frequency.)

TC = 0.1, low frequency passed = 1.59 Hz TC = 0.5, low frequency passed = 0.318 Hz TC = 1.0, low frequency passed = 0.159 Hz

Filters

86!"#$%

)% *% +% ),%

./010234%

Filters: ERP amplitude and latency WILL change when applying different filters.

High Pass Filter Low Pass Filter

NOTE: Filters do NOT cut off the signal at filter settings !Friday, January 14, 2011

Filters .3 - 100 Hz

Filters - .3 - 30 Hz (60 Hz notch filter)

Filters - .3 - 30 Hz

Note: 60 Hz filter has no effect on ERP waveform if LOW PASS = 30 Hz

As LOW PASS filter setting DECREASES, Peak Latencies will INCREASE (occur later) and slower frequencies will become more prominent in the ERP waveform as higher frequencies are filtered out (excluded).

Filters

aka: Peak Latencies will occur later in the ERP waveform.

Filters .3 - 100 Hz

Filters - .3 - 30 Hz

Filters - 0.3 - 10 Hz

Filters - .3 - 5.0 Hz

As LOW PASS filter setting INCREASES, Peak Latencies will DECREASE and higher (faster) frequencies will become more prominent in the ERP waveform as higher frequencies are included (not filtered out).

Filters

aka: Peak Latencies will occur EARLIER in the ERP waveform.

Lower Low Pass gives Longer Latencies !!!Friday, January 14, 2011

Filters - 2.0 - 100 Hz (60 Hz notch filter)

As HIGH PASS filter setting INCREASES, Peak Latencies will DECREASE and higher (faster) frequencies will become more prominent in the ERP waveform as lower frequencies are excluded (filtered out).

Amplitudes will appear to decrease (get smaller).

Filters

aka: Peak Latencies will occur EARLIER in the ERP waveform.aka: Peak Amplitudes will decrease in size.

Filters - signals change with filtering

Filters: Topography 2.0 - 100 Hz (60hz)

Filters: Topography .3 - 100 Hz

Filters: Topography 5.0 - 10 Hz

Filters: Topography 5.0 - 15 Hz

Filters: Topography 5.0 - 100 Hz (60hz)

Filters: Topography 10 - 100 Hz (60hz)

Filters: Topography 10 - 30 Hz

Take Home Memory

Different Filters produce different ERP waveforms Latency shifts Amplitude variations (positive & negative peaks) Slope changes Component structure impacted

When reading the literature ALWAYS pay strict attention to filter settings and gain settings used by investigators.

DIFFERENT RESULTS with DIFFERENT FILTERS and GAIN (amplitude) settings.

CRITICAL

QUESTION

If 2 ERPs are collected but with different filter settings, which is the REAL data?

Will the REAL ERP please stand up!

QUESTIONS ???

Adult Peak Components

ERPs usually described in terms of Peaks (positive or negative) Latency (post stimulus onset) Duration (e.g., slow wave) Scalp topography (maximal peak

location) Source (location within the brain)

Scalp Volume Conduction

Current flow across the scalp Produces latency shifts from one part of

scalp to another Also produces amplitude shifts across

scalp Signals sum across the scalp

large positive wave on scalp meeting large negative wave could sum to flat line!

EXPERIMENTAL DESIGN ISSUES:Types of Experiments

Common approaches

Common approaches Odd-ball tasks (P3 or P300)

Common approaches Odd-ball tasks (P3 or P300) Sentence completion (N400)

Common approaches Odd-ball tasks (P3 or P300) Sentence completion (N400) Mismatch negativity (MMN)

Common approaches Odd-ball tasks (P3 or P300) Sentence completion (N400) Mismatch negativity (MMN) Error-related negativity (ERN)

Common approaches Odd-ball tasks (P3 or P300) Sentence completion (N400) Mismatch negativity (MMN) Error-related negativity (ERN) Feedback-Related Negativity (FRN)

Common approaches Odd-ball tasks (P3 or P300) Sentence completion (N400) Mismatch negativity (MMN) Error-related negativity (ERN) Feedback-Related Negativity (FRN) Habituation

Common approaches Odd-ball tasks (P3 or P300) Sentence completion (N400) Mismatch negativity (MMN) Error-related negativity (ERN) Feedback-Related Negativity (FRN) Habituation Contingent Negative Variation (CNV)

Common approaches Odd-ball tasks (P3 or P300) Sentence completion (N400) Mismatch negativity (MMN) Error-related negativity (ERN) Feedback-Related Negativity (FRN) Habituation Contingent Negative Variation (CNV) Random order of presentation

Adult Peak Components: Some Descriptions

P1 or P50 (auditory)

Adult Peak Components: Some Descriptions

P1 or P50 (auditory)- Not always present

- Occurs earlier over posterior than anterior scalp electrode sites

- Larger amplitudes over frontal and/or central regions

P1 or P50 (auditory)- Distribution symmetrical over both hemispheres except for anterior temporal regions where larger amplitudes occur over left hemisphere;

-Overall, peak amplitude and latency decrease with age to the point where the peak disappears (Coch, et al., 2002).

P1 or P50 (auditory)- Frequently associated with auditory inhibition in sensory gating paradigm where paired clicks presented at short ISIs.

Amplitude of averaged ERP to second of paired clicks is typically reduced compared to averaged response to the first click.

Magnitude of suppression commonly interpreted as neurophysiological index of sensory gating.

- Reduced suppression frequently reported for schizophrenic patients.

- In some neuropsychiatric disorders (schizophrenia, mania), peak amplitude to paired stimuli approximately equal.

- P1 latency clinically used to diagnose neurodegenerative diseases (multiple sclerosis, Parkinson’s Disease).

- Buchwald et al. (1992) proposed that P50 response associated with ascending reticular activating system (RAS) and its post-synaptic thalamic targets.

- Thoma et al. (2003) and Huotilainen (1998) independently localized sources of P50 in superior temporal gyrus using MEG approach.

-Weisser et al (2001) co-registered auditory evoked potentials & magnetic fields (AEFs). The resulting equivalent dipole model for ERPs consisted of one source in auditory cortex of each hemisphere and a radially oriented medial frontal source.

P1 or P50 (visual)

- Visual P1 differs from auditory P1 in terms of evoking stimulus, neurocognitive and neurophysiological mechanism, peak latency, scalp distribution, neural sources.

- Visual P1 typically recorded in a checkerboard-reversal task or similar light-flashes paradigms but can also be present for other visual stimuli (e.g., faces) & is largest over the occipital regions.

- Negative peak may be present at same latency over frontal, central areas.

P1 or P50 (visual)

- P1 amplitude generally varies with amount of attention in Posner’s attention cueing paradigm & in spatial selective attention experiments.

- P1 reflects suppression of noise because amplitude decreased for unattended locations but did not increase for attended stimuli.

- P1 amplitude also increased when speed of response was emphasized, suggesting that P1 may also reflect level of arousal.

P1 or P50 (visual)

- Sources identified using PET, BESA, and LORETA methods in ventral and lateral occipital regions (Clark, et al., 1996; Gomez, et al., 1994).

- Suggests striate (Strik, et al., 1998) or extrastriate (posterior fusiform gyrus) origin (Heinze, et al., 1994).

- Rossion, et al. (1999) in a face identification paradigm reported similar sources and sources in posterior-parietal regions, suggesting additional involvement of dorsal and ventral neural components.

N1 (N100)

N1 typically occurs approximately 100 ms after stimulus onset.

One of easiest components to identify regardless of specific analysis approach.

Good convergence in findings based on analyses of PCA factor scores (Beauducel, et al., 2000), baseline to peak amplitude (Pekkonen, et al., 1995; Sandman & Patterson, 2000), and baseline to peak latency (Segalowitz & Barnes, 1993).

N1 assumed to reflect selective attention to basic stimulus characteristics, initial selection for later pattern recognition, & intentional discrimination processing.

Peak latency & amplitude depend on stimulus modality. Auditory stimuli elicit a larger N1 with shorter latency than visual stimuli (Hugdahl, 1995).

N1 (N100)

N1 or N100 (Auditory) Maximum amplitude over frontocentral areas (Vaughn &

Ritter, 1970) or vertex (Picton, et al., 1974).

Some studies differentiate into 3 different components with maximum amplitudes over temporal areas (latency 75 ms and 130 ms) & over vertex (latency 100 ms; McCallum & Curry, ‘80; Giard, et al., ‘94).

Naatanen and Picton (1987) reviewed the 3 components of N1. Proposed that early temporal and vertex components reflect sensory and physical properties of the stimuli (e.g., intensity, location, timing in regards to other stimuli) while later temporal component are less specific and reflect transient arousal.

NOTE, majority of studies treat N1 as single component occurring 100 ms after stimulus onset with maximum amplitude at the vertex electrode.

N1 amplitude enhanced by increased attention to stimuli (Hillyard et al, 1973;

Knight, et al., 1981; Ritter, et al., 1988; Mangun, 1995) increasing inter-stimulus interval (Hari, et al., 1982).

N1 or N100 (Auditory)

N1 most likely generated by sources in primary auditory cortex in the temporal lobe (Vaughn & Ritter, 1970).

MEG, BESA, and lesions studies consistently localize auditory N1 in superior temporal plane (e.g., Papanicolaou, et al., 1990; Scherg, et al., 1989; Knight, et al., 1988).

However, several studies proposed additional sources in frontal lobe that could be activated from temporal lobe (e.g., Giard, et al., 1994).

N1 or N100 (Auditory)

Usually largest (maximum) over occipital region (Hopf, et al., 2002) or inferior temporal regions (Bokura, et al., 2001).

Amplitude larger in discrimination tasks, but smaller if short ISIs. [** could disappear]

N1 discrimination effect attributed to enhanced processing of attended location (Luck, 1995), not due to arousal because amplitudes are larger in tasks placing no emphasis on the speed of response .

N1 or N100 (VISUAL)

Not affected by inhibition (no Go/No-Go response differences).

Like auditory N1, visual N1 occurs at 100 ms over central midline sites & 165 ms over posterior sites.

Anterior N1 = response preparation because eliminated if no motor response required.

N1 or N100 (VISUAL)

Located visual N1 sources in inferior occipital lobe and occipito-temporal junction using a combination of techniques (MEG, ERP, and MRI), Hopf et al. (2002).

However, Bokura et al., (2001) using the LORETA approach, identified additional sources of the visual N1 in the inferior temporal lobe.

N1 or N100 (VISUAL)

QUESTIONS ???

Like N1 and P1, long considered “obligatory cortical potential” since it has low inter-individual variability and high replicability

Identified in many different cognitive tasks including selective attention, stimulus change, feature detection processes, and short-term memory.

P2 sensitive to stimulus physical parameters such as loudness.

Participant differences such as reading ability also change P2 amplitude to auditory stimuli.

P2 (Auditory)

P2 often occurs together with N1, yet peaks can be dissociated.

P2 scalp distribution less localized than N1 & has its highest amplitude over central region.

Temporal peak of P2 can occur over a broader latency range than the preceding peaks, ranging from 150 - 275 ms.

P2 can be double-peaked.

Similar to N1, P2 has been consistently identified by analysis procedures:

PCA factor scores (Beauducel, et al., 2000)

Baseline to peak amplitude (Beauducel, et al., 2000; Sandman, & Patterson, 2000)

Baseline to peak latency (Segalowitz & Barnes, 1993)

P2 (Auditory)

Generators for auditory P2 thought centered mainly in primary & secondary auditory cortices.

Both auditory N1 and P2 often represented by 2 dipoles: one in primary auditory cortex and one in secondary auditory cortex.

Using BESA and LORETA to identify dipole locations for the N1/P2 component, Mulert et al. (2002) identified one in superior temporal region with a tangential orientation while second was located in temporal lobe with a radial orientation. These dipoles reflected primary and secondary cortices, respectively.

P2 (Auditory)

P2 amplitude increases with complexity of the stimuli.

Topographic distribution of visually elicited P2 is characterized by a positive shift at the frontal sites around 150-200 ms after stimulus onset and a large negativity, approximately 200 ms following stimulus onset at the occipital sites

Using BESA dipole analysis, Talsma and Kok (2001) reported a symmetrical dipole pair localized in the inferior occipital (extrastriate) areas. Findings suggest that both topographic distribution and dipole position varied slightly when attending vs. not attending to visual images.

P2 (VISUAL)

QUESTIONS ???

Influenced by features of the experiment, such as modality and stimuli presentation parameters.

Shares some of its functional interpretation with mismatch negativity (MMN) because both indicate a detection of a deviation between a particular stimulus and the subject’s expectation.

However, unlike the MMN, the subject MUST pay attention to the stimuli.

Ken Squires, et al. (1975) first reported this component. Ss viewed 2 stimuli. When the following image did NOT MATCH what was expected, a larger N2 occurred over frontal regions.

N2 has multiple psychological interpretations including:

orienting response (Loveless, 1983), stimulus discrimination (Satterfield, et al., 1990), target selection (Donchin, et al., 1978), reflecting task demands (Johnson, 1989; Duncan, et al.,

1994).

N2 has more inter-individual variation (Michalewski, et al., 1986; Pekkonen, et al. 1995).

N2 is smaller in amplitude & shorter in latency for shorter ISIs (Polich & Bondurant, 1997).

N2 topographic distribution depends on sensory stimulus modality:

Auditory elicit largest N2 amplitude at vertex. Scalp current density analysis indicate bilateral sources in supratemporal auditory cortex.

Visual elicited highest N2 amplitude over preoccipital region.

N2 to visual stimuli varied based on the stimuli type, such as written words, pictures of objects, or human faces.

N2 Topography

Using intracranial electrodes placed directly on cortex, letter-strings of recognizable nouns produced N2 component at 4th occipital gyrus near occipitotemporal sulci. Pictures of complex objects, (cars, butterflies) resulted in N2 response over inferior lingual gyrus medially & middle occipital gyrus laterally. Effect not present for scrambled pictures.

Face recognition tasks elicit N2 over fusiform gyrus & inferior temporal or occipital gyri just lateral to the occipito-temporal or inferior occipital sulci (see N170).

Such differing distributions indicate N2 may reflect category-specific processing (Allison, et al., 1999).

N2 Sources

N2 and Inhibition

N2 associated with Go/No-Go paradigm, in which subject responds to some stimuli (Go trials), but inhibits response to another class of stimuli (No-Go trials).

ERPs on No-Go trials are characterized by a large negative peak relative to the Go trials between 100 and 300 ms after stimulus onset (response inhibition ??).

N2 occurred both in relation to overt & covert responses, indicating that N2 Go/ No-Go effect not due only to motor responses. Instead, N2 present whenever responses must be interrupted.

Amplitude and polarity of N2 inhibition response changes depending on the complexity of the task.

In some instances, the Go/No-Go response has been reported as a positive peak, suggesting this pattern was due to large amplitude of the P300 in difficult tasks.

N2 was larger when subjects have less time to respond.

N2 and Inhibition

N2 for the visual & auditory task is especially strong over fronto-central electrodes when the Go response is withheld.

Scalp distribution differs from Error Related Negativity (ERN) that occurs approximately 125 ms after an incorrect response.

N2 response engages different processes than the error monitoring processes reflected in the ERN.

N2 and Inhibition

Mathalon et al. (2003) using ERP and fMRI identified activation of caudal and motor anterior cingulate cortices during both correctly and incorrectly inhibited responses.

These sources differed from ERN responses that were related to caudal and rostral anterior cingulate cortices.

Reinforces view the N2 reflects inhibitory responses distinct from error-related negativity.

N2 and Inhibition

QUESTIONS ???

Mismatch Negativity (MMN).

Mismatch Negativity (MMN). Naatanen et al. (1978) first described MMN wave as a

negative deflection, latency = 100 - 250 ms.

Amplitude largest frontal & central electrode sites.

MMN is elicited using an “oddball paradigm” where an occasional deviant stimulus is presented in a stream of more frequent standard stimuli.

Test-retest reliability.

Because MMN paradigms require no attention to the stimuli, widely used in developmental research.

Calculating the MMN

Traditional: Subtract the averaged waveform of all standard stimuli FROM the averaged waveform of all deviant stimuli collected during the same test session.

Alternative (2004): Present uninterrupted string of standard stimuli midway through experimental session to provide a alternative baseline for calculating the MMN.

Kraus, McGee, Carrell, Zecker, Nicol, & Koch, 1996

Mismatch Negativity (MMN)

MMN evoked by any perceivable physical deviance from the standard stimulus (e.g., changes in tone duration, frequency, intensity, and ISI).

Numerous theories ”Memory trace" - MMN elicited in response to violations of simple rules

governing properties of information - violation of an automatically formed, short-term neural model or memory trace of physical or abstract environmental regularities

Population of sensory afferent neuronal elements that respond to sound, and; ii) a separate population of memory neuronal elements that build a neural model of standard stimulation and respond more vigorously when the incoming stimulation violates that neural model

"Fresh afferent" - sensory afferent neuronal elements that are tuned to properties of the standard stimulation respond less vigorously upon repeated stimulation. Thus when a deviant activates a distinct new population of neuronal elements that is tuned to the different properties of the deviant rather than the standard, these fresh afferents respond more vigorously.

Sensory afferents are memory neurons.164

Mismatch Negativity (MMN) Auditory MMN often used to test ability of subject to

discriminate linguistic stimuli (e.g., speech sounds with different voice onset time or place of articulation.

Data analyzed by subtracting average ERP elicited by standard stimuli from average ERPs for the deviants.

This subtracted component generally displays an onset latency as short as 50 ms and a peak latency = 100 - 200 ms (Naatanen, 1992).

Mismatch Negativity (MMN) Sources for auditory stimuli

MEG: significant differences between dipoles produced by deviants differing in intensity, frequency and duration (Rosburg, 2003).

Dipoles for frequency and duration deviants located significantly inferior in comparison to the source of intensity deviants and differed significantly from each other in the anterior-posterior direction.

All dipoles located within temporal lobes. Leibenthal et al. (2003) recorded fMRI and ERP data

simultaneously to an MMN task. Main areas of increased BOLD signal in right superior

temporal gyrus & right superior temporal plane.

Mismatch Negativity (MMN) Features influencing MMN Negative wave usually associated with

Reports of positive wave around 200 ms corresponding to the MMN response (Leppanen, et al., 2002).

The reason for this difference may be due to differences in filter settings. **

Mismatch Negativity (MMN) Features influencing MMN

Some reports indicate substantially reduced MMN response in subjects not attending to the stimuli

Probability deviant stimuli influences effect.

Must maintain balance between presenting enough deviant trials to obtain low-noise average responses, and not allowing the subject to habituate to the deviant, thus diminishing effect.

Size of MMN response decreased (non linear), Time for habituation varies as function of

stimulus complexity. 168

Mismatch Negativity (MMN) Visual

MMN is found for visual stimuli (Tales, Newton, Troscianko & Butler, 1999).

Source Localization techniques suggest involvement of primary visual cortex and adjacent areas (Gratton, 1997; Gratton, et al. 1998).

N170 Face Processing

N170 N170 ranges between 156 & 189 ms.

Associated with visual processing of human faces.

Topographic distribution for both familiar & unfamiliar faces largest over occipito-temporal regions.

Amplitude significantly larger when viewing faces than other natural or human-made objects.

N170 Prosopagnosia Patients do not show an N170

response to faces.

N170 not specific to human faces but expert object recognition (Tanaka & Curran, 2001)

Intracranial recordings of EP & fMRI point to fusiform gyrus as neuroanatomical substrate of N170. BUT source localization of N170 using BESA identified source in lateral occipitotemporal region outside fusiform gyrus.

QUESTIONS ???

P300 - Two Components P300a component associated with

the automatic 'Orienting Reflex'

P300b component associated with controlled processing (most studied)

P300 Odd-ball tasks

S. Sutton, M. Braren, J. Zublin, and E. John, (1965) Evoked potential correlates of stimulus uncertainty Science, 150, 1187–1188.

P300 Odd-ball tasks P300 amplitude increases to

infrequent stimulus

infrequent stimulus Frequent 80% of trials, infrequent 20%

infrequent stimulus Frequent 80% of trials, infrequent 20% Requires attention & response to

infrequent stimulus

infrequent stimulus Controls important

ERP averages based on same # trials for both frequent and infrequent stimuli

P3a P3a, frontal maximum scalp distribution. Slightly

shorter latency for visual vs. auditory and somatosensory stimuli.

Frontal P3a occurs when subject not required to actively respond to the targets (N. Squires, et al., 1975) or when novel stimulus is added to the standard 2-stimulus oddball paradigm.

Frontal P3a assumed to reflect involuntary attention as well as inhibition. In Go/No-Go paradigms, P3a larger in amplitude in No-Go than Go conditions (maximal at parietal sites for Go).

P3a Neural substrate in medial parietal lobe

(early: 317 ms) and in the left superior prefrontal cortex (late: 651 ms) for Go trials;

Sources for No-Go trials (365 ms) originate in left lateral orbitofrontal cortex.

P3a reduced by lesions to frontal cortex (Knight, 1991).

P3b or “P300”

P3b or P300 Most extensively researched ERP component. Sutton et al., 1965: pronounced positivity occurring in

response to unexpected stimulus approximately 300 ms after stimulus onset.

Oddball most typical paradigm for eliciting P3b component, - a target stimulus presented infrequently among more common distracter stimuli.

To get P3, subject must pay attention and respond to stimuli (unlike MMN) and the ratio of target to distracter stimuli must be low (fewer targets -> larger peak).

P3b or P300 AMPLITUDE affected by attention, stimulus

probability, stimulus relevance, amount of processing resources available (e.g., single vs. dual tasks, quality of selection, and attention allocation.

Interstimulus interval length affects AMPLITUDE independently of stimulus probability with shorter intervals resulting in larger P3b or P300.

LATENCY varies with stimulus complexity, effectiveness of selection, and sustained attention.

P3b or P300 Visual P3 has larger & longer latency than auditory P3.

P3 largest over parietal & midline regions.

Auditory stimuli elicited shorter latency P3 over parietal regions, and longer latency over central sites.

Functional interpretation of classic P3b diverse – indicator of memory updating (Donchin & Coles, 1988) reflects a combination of processes that vary by task and

situation, including more elaborate active stimulus discrimination and responses preparation.

P3b or P300 P3 latency assumed to reflect the duration of stimulus

evaluation.

P3 component attracted attention in clinical studies. Because P3 amplitude varies with the amount of attention paid to stimuli, this component widely studied in populations with attention deficits (e.g., ADHD) - interpreted to reflect information regarding various attentional functions.

P3 latency reported related to cognitive abilities with shorter latencies associated with better performance

P3b or P300 Sources of P3 not clearly identified but some expected to be

in medial temporal lobe, including hippocampal region related to memory (Donchin, 1981; Paller, McCarthy, et al, 1992), parahippocampal gyrus, amygdala, or thalamus (Katayama, et al., 1985).

Lesion data suggest multiple generators, including temporo-parietal junction (Knight et al, 1989). Tarkka et al., (1995) investigated possible sources and reported that combining different locations produced better model.

MEG analyses located sources in floor of Sylvian fissure (superior temporal gyrus) and deeper sources in thalamus-hippocampus.

QUESTIONS ???

“He spread the warm butter with socks.”

N400 Sentence Completion

N400 Sentence Completion N400 larger for unexpected, low

probability endings.

probability endings. Fixed intervals between words

probability endings. Fixed intervals between words Words presented one at a time

probability endings. Fixed intervals between words Words presented one at a time Usual interval 1 S.

N400 Negative component approximately 400 ms after

stimulus onset.

Usually associated with semantic comprehension in both visual and auditory sentence comprehension tasks.

First identified by Kutas and Hillyard (1979).

Elicited by anomalies in American Sign Language.

N400 did not occur when participants presented with anomalies in music (Besson, et al., 1994).

Kutas & Hillyard, 1980

N400 study with children The train runs on a track (CC) The train runs on a crack (CI) Child presses either red or green key to

indicate if the sentence “sounds ok or funny”.

36 sentences for each condition. All sentences 6 words in length. Total data points digitized = 300

ms 0 250 500 700

Wordn=68

IncorrectCorrect

12 year olds

N400 Paradigm Words of a sentence were visually presented one after

another at fixed intervals in a serial manner.

Last word of the sentence either congruous (“He took a sip from the water fountain”) or incongruous but syntactically appropriate (“He took a sip from the transmitter”) with rest of the sentence.

Incongruous words elicited larger amplitude N400 response than congruous words for both auditory and visual stimuli.

N400 amplitude correlated with degree of incongruency of final word to sentence (e.g., “ transmitter”)

N400 Kutas and Hillyard (1983): N400 effect only held true

for semantic, but not syntactic deviations.

Supposedly listeners use information from the wider discourse when interpreting appropriateness of particular word (van Berkum, et al., 2003).

N400 also elicited in semantic word pairs (Rugg, 1985), semantic priming tasks (Bentin, et al., 1985; Ruz, et al., 2003) and matching semantic material to visual displays (Huddy, et al., 2003).

N400 (Modalities) For both visual and auditory displays, the N400 is larger

for anomalous endings than expected endings over the parietal and temporal regions of the right hemisphere.

But there are modality effects: N400 is earlier in the visual (475 ms.) than auditory

(525 ms) modality but only over the temporal, anterior temporal and frontal sites (Holcomb, et al., 1992).

Earliest peak in the visual modality is over parietal & temporal sites, while in the auditory modality it is over parietal & occipital sites (Holcomb, et al., 1992).

N400 (Asymmetries) Activation in left hemisphere occurrs earlier than

activation in the right) in ONLY visual modality (Holcomb, et al., 1992).

N400 not specific to written words, because spoken words (McCallum, et al., 1984; Holcomb, et al., 1992; Connolly & Phillips, 1994) & pictures (Nigam, et al., 1992) elicit N400.

N400 response also elicited by incongruent solutions to mathematical multiplication problems (Niedeggen, et al., 1999).

N400 & Attention Still Unclear:

Amount of attention necessary to produce N400,

Cognitive processes involved (Osterhout & Holcomb, 1995).

Holcomb (1988) reported N400 more robust when attention required but occurs when participants not attending to stimuli.

N400 & Attention However, Bentin et al. (1995) reported (dichotic

listening task) that N400 was absent for material presented in unattended ear.

Amount of effortful semantic processing required is unclear. Kutas and Hillyard (1993) reported N400 effect even in tasks not requiring semantic processing although Chwilla et al. (1995) found no N400 when attention not directed to meaning of stimuli.

N400 & Sources Likely multiple generators that are functionally (Nobre

& McCarthy, 1994) and spatially (Halgren, et al., 1994; McCarthy, et al., 1995) segregated.

Recent work points to parahippocampal anterior fusiform gyrus as generator (McCarthy et al, 1995).

MEG studies pinpoint lateral temporal region as origin of N400 response (Simos, et al., 1997).

Intracortical depth recordings using written words point to medial temporal structures near hippocampus & amygdala (Halgren, et al., 1994).

Late Positive Component (LPC)

Positive-going ERP component.Studies of explicit recognition memory.Largest over parietal scalp sites (mastoid reference).Begins approximately 400-500 ms after stimulus onset.Duration = 200 ms ERP "old/new" effect.

S given list to learn.ERPs recorded to new list including old and new words.S to indicate old vs. new words.Typical larger LPC to old vs new words.

Also done as continuous test - each trial S indicates if old vs. new item.

ERP & fMRI indicate lateral parietal cortex, perhaps with medial temporal lobe and hippocampus.

QUESTIONS ???

ERNError Related Negativity

ERN reflects activity of a brain system that detects & corrects for errors.

ERN Paradigm Two ways to generate an ERN response:

following an incorrect response during feedback of incorrect choice

Hajcak, Holroyd, Moser, Simons, 2005; Holroyd, & Coles, 2002; Holroyd, Nieuwenhuis, Yeung, Cohen, 2003

ERN Paradigm During speeded

response timing tasks, an incorrect response produces a negative peak ~ 100 ms

Gehring, Goss, Coles, Meyer & Donchin, 1993

For reinforcement tasks, negativity around 250 ms indicates performance was incorrect

Miltner, Baun & Coles, 1997

Negativity changes in amplitude for incorrect responses in high reward conditions or correct responses in low reward condition

Holroyd, Nieuwenhuis, Yeung, & Cohen, 2003

ANALYSIS-Feedback Amplitude for ERN measured from

baseline to peak between 160 ms to 240 ms following feedback

Holroyd, Nieuwenhuis, Yeung & Cohen, 2003

Holroyd et al., (2003) used algorithm to identify amplitude of the greatest negativity in the peak starting at the slope of the first negativity through 325 ms

Latency measures start at the maximum component amplitude

ANALYSIS - Incorrect Response Amplitude measured early: 50 - 110 post

incorrect response Luu et al., 200

Usually look at incongruent trials (i.e. Flanker task/go-no go task)

Generate individual waveforms for error trials **Some groups used smoothing techniques with a

nonphase-shifting single pass 17-point moving average (34 ms, approximately 3 db down at 15 Hz) --Santesso, Segalowitz & Schmidt, 2005

Filters set around 20 Hz offline Holroyd and Colleagues

ERN and Personality High Negative affect

(high neuroticism) results in larger amplitude on initial tasks

Tucker et al., 1999

ERN reflects certainty of loss (greater realization=greater ERN)

Investment in task changes ERN

Holroyd and Coles, 2002; Scheffers and Coles, 2000

10-year old children ranked on Junior Eysenck Personality Questionnaire show different ERN

High psychoticism and low lie scores result in smaller ERN

Similar to adults: see Dikman and Allen (2000)

ERN affected by personality and concern of task performance

Santesso, Segalowitz, & Schmidt,(2005)

Source

Within the anterior cingulate cortex (ACC), mesencephalic dopamine neurons synapse on motor neurons and cause behavior to occur (e.g. pushing correct button)

Basal ganglia mediated by feedback and stimulus input impact ERN generated by the electrical charge of neurons synapsing on the ACC. When events are worse than expected, decrease in

dopamine activity disinhibits dendrites in ACC, resulting in a negative waveform, ERN

Source

The Anterior Cingulate Cortex

Feedback-Related Negativity

• A negative deflection in the waveform approximately 250-350 ms after the participant given negative feedback (Miltner, Braun, & Coles, 1997)

• Thought to originate in the anterior cingulate cortex (Ruchsow, Grothe, Spitzer, Kiefer, 2002).

Feedback-Related Negativity

• Generated without the individual having a choice in responding (Yeung, Holroyd, & Cohen, 2005)

• Generated without the individual responding (Donkers, Nieuwenhuis, & van Boxtel, 2005)

Feedback Negativity

0.1-30Hz @ 250HzFriday, January 14, 2011

Feedback Negativity

0.1-30Hz @ 250HzFriday, January 14, 2011

Scalp Topographies

Win [Average: 19_7622f_rps.ref] Draw [Average: 19_7622f_rps.ref] Lose [Average: 19_7622f_rps.ref]00:00:00.200

Win Draw Lose

You Lose

Rock, Paper, Scissors

CNV - Contingent Negative Variation

Negative deflection.

Typically elicited in a Go/No-go paradigm between a warning stimulus (S1) and an imperative stimulus (S2).

Can sub-divide into early & late components.

Early component = "O" or "Orienting" wave.

Late component = "E" or "Expectancy" wave. Thought to reflect anticipation of a

response to S2.

Habituation

Decline in amplitude & latency after repeated presentations (~ 3 trials)

Habituation

Amplitude rebounds after stimulus change

Habituation

Amplitude rebounds after stimulus change

Fixed, short ISI and repeating same stimulus enhance habituation effects

QUESTIONS ???

ERP Paradigms

Strengths and weaknesses

ERP Paradigms

Strengths and weaknesses Guides research

ERP Paradigms

Strengths and weaknesses Guides research Often different from main stream

behavior-based literature

ERP Paradigms

Strengths and weaknesses Guides research Often different from main stream

behavior-based literature Can create tunnel-vision effects

Research Paradigm Effects

ERP & Language:Recent Research History

Over The Last Four Decades

ERP Paradigms

1970 - 1979Begleiter & Platz (1969). N100---P160 - N400Buchsbaum & Fedio (1969). P190 - 280Buchsbaum & Fedio (1970). P190 - 280Cohn (1971) N30-50 P125Wood, Goff, & Day (1971).! N100Shelburne (1972). P165 - 245, P285Molfese (1972) N100 - P200Matsumiya et al. (1972). P60-N90-P140- N180Lenhardt (1973). N100 P200Dorman (1974).!! ( N75 - P225) Neville (1974) N100 P180 N220Wood (1975)!!! !N100Friedman et al. (1975) N100 P300Galambos et al. (1975) N100 P300 *Shucard et al. (1977).Chapman et al. (1977). * Kostandov & Arzumanov (1977). N200 P300Chapman et al. (1978). *Molfese (1978a).!!!! N45 P135 ! N450Molfese (1978b).!!!! N70 P300Molfese (1979). N100 P300Molfese (1979). P60 N250 P300 N370Pace, et al. 1979).Molfese (1979).Hillyard & Woods (1979) N100 N500Chapman et al. (1979). *

1980 - 1984

Chapman et al. (1980). *Grabow et al. (1980).Kutas, & Hillyard, 1980 (V) N400Molfese (1980a). (N110 - P190) P330Molfese (1980b).! P170 N460Molfese, Erwin, & Deen (1980).! P198 Neville (1980) N100 P180 Papanicolaou (1980). P92 N133Boddy & Weinberg, (1981) N1 P2 P3Lawson & Galliard (1981a).! N100 - 200Lawson & Galliard (1981b).! N100 - 200Jacobson & Gans (1982).! N100 - 200Kutas & Hillyard (1982) (V) N400Neville et al. (1982).Fischler et. al. (1983) (V) N400Fischler et al (1983). N340Gelfer (1983).! P160Kutas & HIllyard (1983) P200-700 N300-400 P400 - 700 Kutas & Hillyard (1983) (V) N300 - 400, N400 700Molfese & Schmidt (1983).! N70 P170 P290 N460Papanicolaou et al. (1983). N78 P167Polich & McCarthy. (1983) P300Ritter et al. (1983)Rugg (1983a) P670Rugg (1983b) N100 - P187 P300 P637Fischler et al (1984). N320 - N480 McCallum et al. (1984) (A) N212 N456 Molfese (1984). N100 P300 N400 ! P500

1985 - 1989Fischler et al (1985). N320Fischler et. al. (1985) (V) N400Molfese (1985).Molfese & Molfese (1985).Molfese, et al. (1985). P315 ! N475Molfese, Buhrke, & Wang (1985). ! N95 ! Molfese, Buhrke, & Wang (1985). ! ! P340Novick et al. (1985).Pollich (1985). (V) N400Boddy, (1986) N1 P2 N340Erwin (1986). N45 N350 N485Licht et al. (1986). Lovrich et al. (1986) P250 N310 P445 P485 Molfese & Searock (1986). N 100 ! P150 !N260 N390 N470Neville et al., (1986) (V) N150 P220 N410Bentin, (1987) N400Herning et al. (1987) P250 N480Katayama et al (1987). P300 N310Rugg, (1987) P300 N400Rugg, (1987) N140 P200 LPCHolcomb (1988) N400 Licht et al. (1988). N530Lovrich et al. (1988) N310 P350-375 P540 O'Halloran et. al. (1988) (V) N400Pollich et al (1988) P300Czigler & Szenthe (1989) 300 600Segalowitz & Cohen (1989). P35 N135 ! N390Segalowitz & Cohen (1989). N85 N220 ! N435

1990 - 1992Barrett et. al. (1990) (V) N400Holcomb & Neville (1990) N2 N400 *Sams et al. (1990) N100 N220Stewart & Connolly (1990) (V) N200 N400Van Petten & Kutas (1990) (V) N400 Ardal et. al. (1991) (V) N400Erwin et al. (1991). N200Neville et al. (1991) N125 P2 N300 - N400 P500 - 700Van Petten et al. (1991) N400 Besson, et al., 1992 (V) N400 Connolly,et al., 1992 (A) N200 N400Gunter et al. (1992) (V) P260 N340 P550Koyama et al. (1992) N370 LPC Kraus et al. (1992) N235Nigam et al. (1992) (V) N400Osterhout &Holcomb (1992) N350 - 500 P600

1993 - 1994 Bentin et al, (1993) N100 N400 Berman et al. (1993) P350 P600 Curran, et al., 1993 (V) N450 LPC Friederici et al. (1993) N180 N400 P600 Hagoort et al. (1993) N250-600 (P500 700 Karniski,et al., 1993 (A) N250 SW (418 - 530) Kraus et al. (1993) N100 N215-N238 P3aKutas (1993) (V) N400Lovrich et al. (1993) P475 Mitchell et. al. (1993) (V) N400Osterhout & Holcomb (1993) [A] P50 300 RH P300 500RH, PZ N500 800LH Praamstra et al. (1993) N400 [late negativity] Rosler et al (1993) N400 _ 700Rosler et al. (1993) N400-700 P700 1200 *Sharma et al (1993). N200 - P300Van Petten (1993) (V) N400Connolly, et al. (1994) (A) N400 Gunter et. al. (1994) (V) N400Lovrich et al. (1994) N2 P300 P600Munte et al. (1994) N100 P580Nobre et al, (1994) (V) N332 N386 N410 Osterhout et al. (1994) N350 - 450 P500 800LHPerez-Abalo et al. (1994) N400 N450Pratarelli et al. (1994) N1 - P2 N400 St George et. al. (1994) (V) N400

1995 - 1998

Chwilla et al. (1995) P300 N400 Connolly, et al., (1995) (V) N270 N365 Friederici (1995) (V/A) N400 Friederici (1995) N200 N400 P600 Hamberger et al (1995) P380 N400 P600 Kraus et al. (1995) N100 N200Kuperman et al. (1995) N400 *Maiste et al (1995) N60-120 N120 - P210 ! P500 - 700Mecklinger et. al. (1995) (V) N400Pulvermuller et al. (1995) N160 P200 N340 - 500 N600 - 1000 Schlaghecken et al. (1995) N400 LPC Friederici et al. (1996) N370 N400 500 Hagoort et al. (1996) P2 N400 McKinnon & Osterhout (1996) N1 P2 N400 Nizikiewicz et al., (1996) (V) N200 N400Kazmerski & Friedman 1997) P3 N400 Lovrich et al. (1997) N480Swab et al. (1997) N400 Brualla et al. (1998) N400 N570 N680Gunter et al. (1998) N1 P2 N400 Kiefer et al. (1998) P2 N400 Kutas et al., (1998) (V) N200 N400McPherson et al. (1998) N350 N450 Moute et al., (1998) (V) N250 N400Paller et al (1998) 300 750 Pratarelli et al. (1998) P2 N400

QUESTIONS ???

workshop: erp testing -...

Documents

smooth and flexible erp migration between heterogeneous...

2. electrodes copy -...

20090429 erp workshop presentation

mitopics workshop selectie en implementatie erp...

a guide for erp concepts - erp for manufacturing | erp for

erp software erp

erp 1949 january erp

raportoinnin kehittäminen tietovaraston...

workshop ii: neue betriebssoftware (erp): auswahl und...

eeglab workshop iii, nov. 15-18, 2005, singapore: julie...

hospital erp( erp system for hospitals ) an opensource erp...

auto genius dms & erp electric vehicle...

school board workshop erp update january 25, 2006

erp와non-erp의효과적인연계실현 erp 22009/05/21...

workshop formularprozesse mit adobe interaktive formulare in...

erp r12 workshop om

erp - 37588925-erp-tcc-3

erp workshop traning ru#5 by double m

a e a real time workshopstally erp 9 peach tree & elective...

erp for granite & marble industry - stone erp solutions,...