.Veuropsychologia.
hrcd
III Great
Vol. 24. No. 1. pp. 151-168.
Bntain.
‘X2%393?, 86 53.00 i O.Cdl
Pergamoo
Press Ltd.
1986.
EVENT-RELATED
POTENTIALS
OF THE BRAIN AND
COGNITIVE
PROCESSES:
APPROACHES
AND APPLICATIONS
D. BRANDEE*? and D.
*Neurology Department,
University
tInstitut fiir vcrhaltenswissenschaften.
LEH~WNN*
Hospitals, 8091 Zurich, Switzerland
ETH, 3091 Zurich, Switzerland
Abstract-Event-related
potentials
(ERPs) are recordings
of the electric field \vhich the brain
produces m fixed time-relation
to an event. ERPs open a time and space window onto covert steps of
brain information
processing
which need not be accompanied
by overt behavior
or private
experiences. ERPs are the only noninvasive method which resolves the dynamic pattern of events in
the human brain down to the millisecond range.
Early ERP components
are valuable tools in clinical testing of the afferent sensory systems in the
absence of anamnestic or clinical pathology. Later components
(e.g. the .P300’) index intermediate.
covert steps of information
processing and have clarified the time course and the contingencies
of
processes in attention. decisions and language.
ERP waveshapes show electric potential differences between two recording points. Conventional
analysis often ignores the fact that there is no unique voltage amplitude or signal latency for a single
point. and interprets
ambiguous
results. Although
important
insights have emerged with such
strategies,
full utilization
of ERP data requires unambiguous
ERP assessment and converging
evidence from neuropsychological
and cognitive experimentation.
Sequences of field distribution
maps offer an unbiased display of ERP data. Spatial analysis yields unambiguous
values for further
comprehensive
assessment, and should precede analysis over time.
Examples of spatial analysis have shown that different ERP field configurations
follow the
presentation
of noun and verb meaning of homophone
words; that the ERP effects to subjective
contours
resemble those to attention
m time course and topography;
that the ‘cognitive’ P300
component
reflects the specific stimulus location: and that subliminal information
influences the
configuration
of late ERP fields.
1. WHY STUDIES ON EVENT-RELATED POTENTIALS
COGNITION?
IN STUDIES OF
of electric brain events in psychological experiments may pose fruitful constraints
on interpretations of behavioral or introspective data. because the electric data can make
strong suggestions about the relative timing and strength of processes, and about the
nonidentity of processes invoked by different experimental manipulations. Electric brain
events reflect covert internal states which need not be accessible to introspection or
behavioral observations. They can occur before, after or without a behavioral response, and
have an exactly measurable latency. To know the relative timing of covert processing steps in
the brain can effectively restrict the range of plausible information processing models, since
only an earlier event can affect the outcome of a later one.
For example, the same electric brain event is systematically delayed by stimulus
degradation, but not by increased motor task demands (Fi g. 11.although in both cases the
tasks are subjectively more difficult and result in longer reaction times [37,39]. This indicates
that the electric brain event is only affected by perceptual demands, whereas reaction time is
affected by the sum of perceptual and motor demands. Thus at least two different resources or
ANALYSIS
*To where correspondence
should
be addressed.
151
lS2
D.
BRAXDEIS and D. LEH_YA~S
400 MSEC BETWEEN TICK MARKS
FIG. 1. Average ERP waveshapes, recorded in one channel in four experimental conditions. The ERPs
were evoked by the tachistoscopic word stimuli (targets) “right” or “left”, presented at the time
indicated by the dashed vertical line. The targets were either embedded in visual noise (surrounding
random letters), or appeared on a no noise background. The targets were preceded by the cue word
“same” for compatible trials, or “opposite” for incompatible trials. These cue words specified the hand
for a motor response after the target stimulus. Motor responses in compatible trials were to be made
with the hand designated by the target word, and in incompatible trials with the other hand.
Recordings are from a midline electrode over the parietal area (Pz) vs linked mastoid electrodes.
Relative positivity at Pz= downward deflection. Tick marks on horizontal axis at 400-msec intervals.
Vertical calibration bar: 5 pV. Dots indicate the latency of the Pz-positive component which occurred
early in both ‘no noise’ conditions, and which was delayed in both ‘noise’ conditions, regardless
whether the motor response to the target stimulus had to be done with the same or opposite hand; this
Pz-positive component, whose earliest occurrence is about 300 msec poststimulus, traditionally is
labelled P300, disregarding its exact, particular latency. (Modified after Fig. 12 in MAGLIERO et al.
f37]; zero voltage baseline not available.)
processes, one perceptual and one motoric, determine reaction time and subjective difficulty
in the task. None of the two measures (reaction time or latency of the electric brain event) by
itself would lead to this conclusion, but in conjunction they may be used to validate or revise
the hypothesized sequence and interaction of events, in this case a model of one vs more than
one resource which influence performance of the task.
Recent developments in psychological models underline the usefulness of a direct measure
of mental timing. Increasingly complex interactions and contingencies between processing
stages are currently discussed in experimental psychology [40, 411, parallel to the
developments in experimental neurophysiology (see Cl]), superceding the assumption of a
sequential, hierarchical order of processing stages Under such less restrictive assumptions,
unambiguous interpretation of reaction time patterns requires converging evidence from
other measures, and event-related potentials offer a direct brain measure with very high time
resolution.
EVEh’T-RELATED
153
POTENTIALS
2. WHAT ARE EVENT-RELATED
POTENTIALS?
Event-related potentials (ERPs) of the brain reflect that neuronal mass activity which
generates detectable electric scalp fields in fixed time-relation to information arrival or
execution of movement. ERP recording is noninvasive. Its strength is the possibility of
monitoring electric brain events in real time with resolution down to milliseconds, and
locating these brief events in the space domain.
For the measurement of the ERPs, electrodes are attached to the scalp (sometimes, a
nonscalp location is also used) with a conductive substance. Before, during and after
exposure to a stimulus or performance of a task, the brain’s electric activity (the
electroencephalogram-EEG)
is recorded as potential differences between pairs of
electrodes. The potential differences between a given pair of electrodes (one ‘recording
channel’) are sampled several hundred times per second. A large amount of data is typically
generated, as there are usually several channels, sometimes up to 48 [30, 31, 35, 361.
The electric scalp field which varies over time in strength and spatial distribution
(topography) offers a spatial and temporal window on the brain’s activity. Only some of this
variance is time-related to a reference event. Time-locked signal averaging is necessary to
extract ERPs from the raw data. In each recording channel, data points at identical times
before or after the reference event are averaged across the replications of one experimental
condition. For studies of changes which follow an event, ‘forward averaging’ in time is used.
To study brain phenomena which precede a spontaneous movement [24] or a particular
class of response, ‘backward averaging’ from the reference event is used. The resulting
averages are traditionally viewed as curves of potential differences over time (Fig. 1) in one or
more recording channels.
2.1. ‘Components’ of ERPs
Conventionally, a peak or trough of the curve of the ERP waveshape is identified as a
‘component’, which is hypothesized to reflect maximal activation of a specific brain process
associated with a particular task in information processing. Principal component analysis
(PCA) is a statistical approach to component identification [7]. PCA components reflect
statistically-independent contributions to the variance across the different waveshapes and
need not coincide with waveshape peaks or troughs.
‘Exogenous’ components are always obtained with a given stimulus, vary mainly with the
physical stimulus characteristics and tend to occur early after the stimulus. ‘Endogenous’
components tend to occur late and may or may not occur for a given stimulus, depending on
the role of the stimulus in the experiment; thus cognitive factors mainly account for their
variance. Statistical testing of the ERP components’ amplitude and latency reveals
experimental effects (e.g. [19]). Multivariate approaches (e.g. [S]) or nonlinear pattern
recognition [lo] have been used to assess experimental effects on many ERP measures
simultaneously.
ERP components are usually labelled after their alleged polarity and occurrence time after
the stimulus (‘latency’), and after their location on the scalp. Thus, ‘P300’ means a positive
extreme (peak or trough depending on the display convention) of the waveshape which in a
classical paradigm occurs at 300 msec latency. The scalp location of its largest amplitude is
added, e.g. ‘parietal’; because of the problem of ambiguity of waveshape at a given location,
the reference electrode location should always be specified. Component latency often varies
greatly between experimental conditions, so that ‘P300’ components might be recognized as
late as 450 msec post-stimulus. The later event is usually considered to be the ‘same’
D. BRANDEIS and D. LEHMAW
154
component if systematic changes of experimental conditions, such as stimulus degradation,
cause graded increases of latency (Fig. 1).
3. SELECTED
FINDINGS
WITH TRADITIONAL
DAT.4 ASSESSMENT
Early components of ERPs evoked via different modalities are successfully used in clinical
routine diagnostics, testing the afferent brain systems [13]. Click stimuli, electric stimuli to
peripheral nerves and visual checkerboard reversal stimuli are most commonly used. Very
early (2-10 msec), low amplitude components (below 1 LLV,requiring several thousand
stimuli per average) are examined in tests of the auditory brain stem system. Components at
latencies around 20 msec are used in somatosensory system evaluation. Checkerboard
stimuli produce a consistent. occipitally positive component around 100 msec latency. These
tests use robust stimulation methods which result in very small latency variability in normals.
Latencies obtained from patients are compared to these normative values. Increased
latencies indicate functional or structural lesions. The value of clinical ERP testing is the
possibility of detecting disturbances in specific afferent systems which show no anamnestic or
clinical abnormalities.
Studies on late ERP components have examined the electric manifestations of perceptual
and cognitive aspects of information processin,.0 Overviews of ERP work in cognition are
found in [6, 8,9, 18, 22, 26, 321. In the followin g, selected examples of studies which use the
conventional, waveshape-oriented analysis oflate ERP components are presented. Although
intriguing results on abnormality of late ERP components in patient populations
(schizophrenia, depression, dementia; see [47. 52, 541, etc.) have been reported. late ERP
components are not widely used in clinical routine diagnostics.
3.1. Selective attention and temporal resolution of ERPs
Psychological theories of selective attention differ on the time course of selective
processing. ‘Filter’ theories (e.g. [3]) suggested that attended stimuli are selected early in the
information processing sequence, while ‘late selection theories’ (e.g. [44]) maintain that
selection occurs after complete stimulus analysis.
ERP research has identified the time when attending to a given stimulus becomes
electrically manifest. A typical paradigm to probe selective attention is the dichotic listening
task, where subjects attend to rapid sequences of tones in one ear (one input ‘channel’), and
ignore the sequence in the other ear (the other input ‘channel’). If simple physical
characteristics such as pitch or location in space separate the input channels clearly, ERP
effects start to differentiate between tones in the attended and the ignored input channel as
early as 60-80 msec after information delivery, i.e. after tone onset. HILLYARD et al. [19]
showed that the NlOO component was enhanced to all stimuli in the attended ear. HINK et al.
[20] not only used two input channels, but presented four different stimuli in each channel.
One of these four stimuli in the attended channel was defined as the target stimulus. While the
early, exogenous NlOO was enhanced for all stimuli in the attended ear. a P300 component
was found only for targets in the attended ear (Fi g. 2). The results provided support for a
hierarchy of selection steps, consistent with early selection models (e.g. [59]). Later evidence
[14, 421 however suggested that the NlOO enhancement is due to an additional negative
endogenous component, which only accidentally coincides with NlOO in some paradigms,
but in other paradigms occurs at different latencies and lasts for several hundred
milliseconds. HILLYARD and KU-AS [18] have argued that while this evidence excludes a
EVE&i-RELATED
Attend
15.5
POTEhTlALS
Attend
Right
Left
*1
Left
Ear
Stimuli
I
0
I
1
I
I
I
500
1
mscc
0
1
I
I
1
500
FIG. 2. ERP waveshapes recorded between vertex and mastoid (upwards = vertex negative) in one
subject. Stimuli were random sequences of four syllables presented to left and right ears on a SO/SO
random basis. Dotted lines: ERPs to ‘target’ syllable (one per run) that had to be counted in one
(attended) ear at a time. Solid lines: ERPs evoked by the other three ‘non-target’ syllables. While the
NlOO amplitude is slightly increased for all attended syllables, the P300 is present only to the attended
targets (after HINK et al. [lo]).
mechanism for peripheral gating which operates by simple modulation of an exogenous
component, it is compatible with relatively early stimulus selection.
In the visual modality, HARTER and PREVIC [17] showed that ERP effects for attending to
checks of a specific size in checkerboard pattern targets reach their full specificity only after
250 msec. At that time, ERP amplitude was maximal for the attended check size and
decreased with increasingly deviant check sizes, yielding a size-specific tuning function
similar to that obtained in psychophysics for sensory brain mechanisms of size analysis.
HARTER and AINE [ 161 propose a physiologically-oriented
hierarchy of selection processes
in visual attention, where location, contour, colour and spatial frequency reflect successively
selected dimensions. Such a model seems to contradict the data of HANSEXand HILLY.+RD
[15], who showed in the auditory domain that the sequence of the ERP effects for selective
processing of pitch and location cues can be reversed by manipulating the relative
discriminability. It remains to be seen whether in the visual modality, the sequence of ERP
selection effects is determined to a larger extent by hard-wired processing hierarchies than in
the auditory domain.
3.2. Decision processes
and the P300 component
Studies of the P300 component [SS] have established this component as an index of a
distinct subset of information processing. P300, an endogenous component, is strongly
156
D. BRA~FISand D.
LEHMAN~V
affected by stimulus probability and task relevance, and is largely independent of the physical
characteristics of the stimulus [48]. KUTAS ef al. [27] used single-trial analysis of P300
latency to show that with the emphasis on speed of performance. reaction time in a
discrimination task covaried only poorly with the latency of P300, while with emphasis on
accuracy of the motor response, significant correlations were obtained. The result supports a
model of P300 being contingent upon complete stimulus evaluation. MAGLIEROet al. [37]
replicated the results of MCCARTHY and DOSCHIN [39] that stimulus quality, but not
stimulus-response compatibility affects P300 latency. In these experiments, the cue word
“same” or “opposite” preceded the target word “right” or “left”. The task was to press a
button with one hand. The cue word “same” specified the hand indicated by the target word
(compatible trials). whereas the cue word “opposite” specified the other hand (incompatible
trials). Degrading the target words by embedding them into a background of random letters
(‘visual noise’) instead of homogeneous visual structure (‘no noise’) increased reaction times
as well as P300 latencies (Fig. 1). The cue word had no effect on P300 latency, but on reaction
time; the cue word “opposite” increased reaction time. The results were interpreted as
supporting the notion of P300 indexing perceptual and decision-related, but not responserelated processes.
ROSLER [Sl] has examined P300 in a double priming task in order to test the hypothesis
that the role of P300 is context updating [6]. Subjects had to decide whether two letters on
one of the diagonals in a 2 x 2 letter display were the same. Two priming stimuli preceded
these targets: a first prime indicated the task relevant diagonal, while the second prime
indicated either confirmation (‘no shift’) or reversal (‘shift’) of this instruction. The second
prime contained its information either explicitly, actually showing the diagonal, or implicitly,
showing an asterisk with preassigned meaning (‘shift’ for one, ‘no shift’ for the other subject
group). Although explicit and implicit ‘shift’ instructions should involve equal context
updating, a larger P300 was obtained under the implicit ‘shift’ condition, where subjects had
to access and use the information from the first prime. Riisler concludes that P300 is invoked
if controlled processing [55] is required.
3.3. Language and ERPs
OS~D
[46] has shown that the semantic, connotative meaning of words can be described
by ratings on the three orthogonal scales of evaluation, potency and activity. CHAPMANet al.
[5] have studied ERP correlates of connotative meaning with a large sample of words which
load highly on the six extremes of Osgood’s three scales. Subjects either rated the words on
one of the three scales, or read them aloud. ERP components discriminated equally well
among the six presented word classes in the rating and reading conditions. Classification by
ERP measurements was above chance for five of the six word classes. This suggested that
similar neurophysiological representations of connotative meaning exist across subjects,
parallelling the universality of the Osgood scales at the behavioral level.
An intriguing aspect of ERP studies is that minor variations in an experimental paradigm
may result in strikingly different ERPs. KGTAS and HILLYARD [25] recorded ERPs to
meaningful sentences shown word by word. Unexpected, semantically-inappropriate words
were occasionally presented at the end of the sentence. They elicited a late negative wave
(N400) which was largest at central and parietal electrodes referred to the linked mastoids,
rather than the expected P300 which occurs to task-relevant, surprising events. Since then,
N400 components have been observed in a variety of experimental situations such as writing
words [43], naming pictures [57] or matching sequentially-presented words as to whether
EVE&T-RELATED
157
POTETl7ALS
they rhyme or not [53]. The critical experimental factors which elicit an X400 are not yet
fully understood.
4. THE AMBIGUITY
OF TRADITIONAL
ERP RESULTS
The above results have been collated from potential differences (voltages) recorded
between several locations (say, ‘A’) on the scalp and a reference location (say, ‘B’). The
voltages over time are waveshapes which, at each moment in time, show by how many
microvolts ‘B’ is more positive or negative than ‘A’. Although there is no possible proof for
electric inactivity at a given location [23], the search for an ideal reference has caused much
futile work in the field. Often the ears have been used as reference locations. Since the ears
frequently belong to the most positive or the most negative locations in the scalp field [29],
the statements arrived at with these measurements might well have no general physiological
validity. The measured voltage always involves IWOlocarions, and there is no unique voltage
(latency, polarity, phase angle) of the waveshape at one location. For each electrode, as many
different and correct voltages can be measured as there are additional electrodes [for N
electrodes, N x (N - 1) waveshapes are possible]. Figure 3 shows an example of the different
waveshapes, which can be obtained with four electrodes. All are correct, but none is
privileged. The lack of an absolute zero voltage reference is no hindrance for brain studies
which concern the electric relationships between different locations. Traditional ERP work,
however, often reports analyses of preselected subsets of waveshapes as if there were unique
statements about voltages at single locations.
In addition, traditional work has often not recognized that zero voltage between two
electrodes can be determined. Using technical zero as ‘baseline’ which corresponds to a flat
electric field, one can state without ambiguity whether electrode ‘A’is more positive or more
negative than electrode ‘B’ at a given time-either of which is possible, even at a waveshape
peak or trough (a ‘component’). Usually, approximations such as the mean of the data points
preceding the event are used as baselines in ERP studies. This baseline typically is a nonzero
(nonflat-field) state, and ERP data measured against this baseline represent the amount of
change introduced by the event, not the absolute state. Clarity about the nature of the
measured values is a prerequisite for interpretation.
Successful diagnoses and classijications
of subjects or conditions can be based on
preselected data subsets, as illustrated by the clinical usage and the examples in Section 3.
However, considering the ambiguity of magnitude and polarity of the potential at a given
scalp location, comprehensive functional or physiological interpretations of ERP data
cannot be based on examinations of preselected result subsets. It remains to be seen which
conclusions can be drawn when reference-independent strategies are used for data analysis.
Re-evaluation of published data is usually not possible since zero baselines are not reported.
5. VIA SPATIAL ANALYSIS TO UNAMBIGUOUS
ERP VALUES
For unambiguous statements about the electric field at single locations, an initial analysis
over space must precede any analysis over time. Possible ways are the computation of local
potential differences vs the average reference (i.e. vs the mean of all momentary values in the
field [45]) which is a spatial high pass filtering strategy, or of local potential gradients (first
spatial derivative of the potential field), or of local current source densities (second spatial
derivative of the field) as proposed by R~YOND [SO]. Another way is the map-by-map
D.
158
BZUUNDEIS
and D. LEHMNN
REFERENCE
El
E2
ELECTRODE
E3
E4
---El
E4
AR
-w-u
I
I
t
I
,
FIG. 3. Example of all waveshapes which are possible using one given data set which was recorded
with four electrodes (El-E4). Five time points were used (tick marks on the horizontal axes). The
array of waveshapes illustrates all possible direct deviations. and the derivations
vs the computed
average reference (‘AR’, which corresponds
to a spatial high pass filtering procedure).
Only the
derivations vs the computed average reference are privileged (see text). Positive values white, negative
hatched, relative to reference value. Note the different ‘Ia:encies’ and polarities of the early component
at active electrode E3 when referred to El (time point 2; negative) and when referred to E4 (time point
3; positive). Note also that the different references do not affect the instantaneous,
spatial distribution
of the potential: E2 shows the most positive value and E4 the most negative value at times 1,2 and 3,
and E4 is most positive and E2 most negative at times 4 and 5, regardless which reference is used.
These conclusions
illustrate that the flat traces also carry meaningful information;
e.g. E4 vs E4
reflects extreme field values at all sampling times.
extraction of reference-independent
parameters such as the locations of the maximum and
minimum potential,
and the potential difference between these locations, or the global
electric field power [33, 341.
5.1. Scalp field mapping of ERP data
Map sequences of the scalp fields (Fig. 4) display ERP data in an unambiguous
way [30,
31, 35, 361. For mapping, equipotential
contour lines, grey or color levels are interpolated
between measured locations, similar to the procedure for geographical
maps. At every
sampling point in time a map is displayed. The configuration
of a map, i.e. the locations ofthe
maximal and minimal values and the shape of the equipotential
lines, is independent
of the
chosen reference. Only the numeric labelling depends on it. The reference is important when
maps are to be compared over time, subjects and conditions,
since the reference location
always gives a difference of zero and is thus privileged. As mapping is no data reduction,
extraction of the reference-free parameters is required in further analysis [30, 31, 33, 341.
Parallel to the conventional
definition of the ERP component
as time of maximal voltage
E\+\7-RELATED
159
POTEb7lALS
between two electrodes, one can use the occurrence time of maximal electric strength of the
entire map as component
definition (‘hilliness’, or global field power [33]). This approach
gives equal weight to all locations. At component
latency, the map is characterized
by the
locations of its most positive and most negative values. Since there must be both a most
positive and a most negative point in every map, the traditional
nomenclature
of ‘positive’ or
*negative’ components is not satisfying. If one of the extreme values in the field is surrounded
by steeper gradients than the other, the component might be given the first extreme’s polarity,
since the net generating process can be assumed to be closer to that location.
5.2. Segmentation
of ERPjield
sequences:
components
defined by field configuration
The strength criterium for component
definition
is not convincing.
A specific neural
activity which is associated with a specific processing step may have the same strength as a
different, preceding activity. The new activity might only be detectable as a change in the
spatial configuration
of the field, since dfferentjeld
configurations must have been produced
by different generators. (Similar fields may or may not have been produced by the same
generators.) Accordingly,
LEHMANN and SKRANDIES [33] suggested the computation
of an
index of global dissimilarity
of successive maps, and the acceptance
of times of high
dissmilarity as terminators
ofcomponents.
In a more direct approach, the sequences of ERP
fields are segmented into epochs of stable field configurations,
using the locations of their
maxima1 and minimal potential values as characteristics
[34]. Spatially homogenous epochs
are considered to be ERP components
(Figs 4 and 5).
5.3, ERP generator
locakation
in the brain
Inferences
about the source location
of the scalp-recorded
ERPs are in principle
impossible: while the field produced by a given dipole generator can be computed without
by other combinations
of dipoles. If
ambiguity,
the same field can also be generated
additional (anatomical, physiological) knowledge offers constraints, dipole modelling might
approach three-dimensional
reality (e.g. for very early components
of the afferent auditory
system, see e.g. [l 11).
Nevertheless,
any brain information
processing
involves many thousands
of simultaneously active cells which are not arranged in parallel, and which are, particularly
for late
ERP components,
distributed
over large areas. An equivalent dipole model of a co_titive
ERP component can serve as reduction of the instantaneous
electrical data. Such reduction
can also be obtained directly, using the major landmarks
of the field such as peak/trough
FIG. 4. Sequence of average ERP scalp field maps for brief (40 msec) tachistoscopic,
visual figure
(Kanizsa triangle) stimuli, extending about 3” visual angle in the left (A) or right (B) visual hemifield.
which implies direct input to the right (A) or left(B) hemisphere. Next stimulus after 512 msec. Grand
mean maps ofrecordings
of 12 subjects with 16 channels, electrodes between vertex (Cz) and inion as
in inset. Maps of scalp fields at 16-msec intervals; head seen from above, nose up. left ear left;
equipotential
lines interpolated
in steps of 0.5 PV; dotted areas negative, white positive, relative to
mean of all instantaneous
values (=average
reference=spatiai
high pass filter). Numbers give poststimulus times in msec. Note that clearly mirrored scalp field configurations
occur between 80 and
304 msec latency, lateralized
depending
on the stimulated
hemifield. The maps show ma.ximal
potential gradients centered over the input-receiving
(‘correct’) hemisphere for the small targets. Note
how the mirror symmetries are well described by-the locations of the maximal and minimal field
values. Some fields show little lateralization
(e.g. at 240-256 msec). Fields that are ‘hillv’ fe.e. 96.
208-240 msec) and suggestive
of conventional
amplitude-defined
components
alternate-with
relatively flat fields (e.g. O-64 msec, 176192 msec). Marked changes in configuration
(e.g. from 96 to
160 msec) may occur without major changes in ‘hilliness’ or global field power.
160
D. BRODEIS and D. LBHMA~~
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SEGMENT
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BRAATIEISand
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34
D.
LEHMAYN
5
6
8
7
64
128
192
256
320
384
443
512
NSEC
64
128
192
256
320
384
:la
512
1
z
-0
FIG. 5. Time segmentation of an ERP map sequence, based on reference-free field configuration
criteria. Shown are scalp field locations (vertical) ofmaximal (+) and minimal (-) field values in the
posterior-anterior (P-A, upper graph) and left-right (L-R, lower graph) dimension as function of
time. A 16-electrode array between vertex (Cz) and inion was used as shown in inset. Data is the grand
mean to all tachistoscopic 40-msec stimuli of about 3’ arc targets in 12 subjects. Every 16 msec, the
location of the maximal and minimal value in the mapped average evoked field was determined and
averaged over conditions and subjects. The grand means were entered in the A-P and L-R graphs.
Starting with data point 1 as base, the segment was terminated (vertical line) when the location of a
new entry exceeded the window of0.5 electrode distances around the base entry. The first data point
of the new segment was used to re-set the window for all four entries. Dots indicate the entries which
started a new segment. Eight segments were identified (vertical lines) during the 512 msec after
stimulus onset. Further statistics tested the differences of extrema locations between experimental
conditions for each segment. Same data set as in Figs 4, 6 and 7.
locations, maximal voltage, and location of maximal gradient for the description. In
summary, cautious interpretation of the data in terms of source location is suggested.
Functional conclusions about the net activity are possible using ERP fields. Lateralized vs
symmetric distributions around the anterior-posterior
axis suggest hemisphere-oriented vs
symmetrically-distributed net activity.
6. SPATIAL ANALYSIS OF ERP DATA IN STUDIES OF COGNITIVE PROCESSES
Subjective or illusionary contour figures [21] are perceived in homogeneous regions of the
visual field (Fig, 6). GREGORY[12] has argued that the subjective contour effect could be
explained both in physiological and cognitive terms. PRITCHARDand W.*RSI [49] have
163
VISUAL FIELD STIMULI: LEFT
KANIZSA STIMULUS
Fig. 6. ERP field extrema (maximal value= +, minimal value= -) for Kanizsa-type subjective
contour figures and for no-figure control stimuli, shown to left and right visual hemifields, during the
data segment 16&200 msec after stimulus onset (see Fig. 5). The locations of the maximal and
minimal field values were extracted from all originally averaged scalp field maps of the 12 subjects,
and the mean values entered in the present illustration. There was a statistically significant increase of
the anterior-posterior distance (for stimuli in either visual hemifield) and of the right-left distance
(depending on the stimulated visual hemifield) between scalp field maxima and minima for Kanizsa
figure stimuli compared with controls, indicating the activation of a different neural population by the
figure stimuli. The lateralization of the minimum shows that only for the Kanizsa-type subjective
figure stimuli and not for control stimuli, the location of the activated neural population during the
segment depended on the hemisphere which had received the input.
explored the cognitive notion that attention may play a role in subjective contour perception.
They hypothesized
that subjective
contour
perception
should suffer from concurrent
demands on attentional resources if it requires attention. Indeed they found that concurrent
memory load interacted with subjective contour discriminations.
Related ERP effects for
selective attention and figure perception were obtained by LANDIS et al. [28].
We investigated the notion of a common process in selective attention and perception of
subjective contour perception. The subjective contour stimuli (Kanizsa triangles [Zl]) and
the control stimuli (see Fig. 6) alternated in one visual half-field, and subjects were instructed
to attend to either the subjective contour or the control stimulus. Averaged ERP maps from
16 scalp electrodes were segmented
(Fig. 5), using the procedure
discussed above. For
individual
segments, the mean scalp distances
between the potential
minimum
and
maximum locations were subjected to ANOVAs. The effects of attention
and subjective
contour were similar and resulted in greater scalp distances between voltage minimum and
maximum
in the anterior-posterior
direction
(Fig. 6). Figure 7 illustrates
the similar
topography of the attention effect (map of attended minus map ofignored conditions) and of
the subjective contour effect (map of subjective contour minus map of control conditions) in
an earlier and a later segment. The similarity in time course and topography
support the
notion that subjective contour perception and attention are mediated by a common process.
The stimulus type in addition affected the left-right distances between the minimum and
maximum.
Subjective
contour
figures elicited more eccentric fields between
168 and
200 msec, with the basic lateralization
determined by the stimulated visual half-field (Fig. 6).
SKRANDIES
[56] had subjects compare alphanumeric
or geometric stimuli which were
randomly shown in the center, to the left, or to the right. ERPs were recorded using 16 scalp
electrodes. Principal component
analysis expectedly identified a parietal P300 component
for task relevant stimuli. However, this positivity was asymmetric for the lateralized stimuli,
D. BRA~~DEIS
and D.
164
LEHMAW
FIGURE MINUS NO-FIGURE
.63
..*.....co?
ATTENDED MINUS
IGNORED
x.....
m-200
msec
296-376 msec
T
..’
.
.
1
b-4
FIG. 7. Four maps of differences of mean ERP field distributions which were averaged over 12
subjects, and over the indicated segments. The upper two maps illustrate the spatial distributions of
the differences between maps evoked by ‘figure’ minus those evoked by ‘no figure’ stimuli (see Fig. 6),
for the time segments 16&200 and 296-376 msec after the stimuli. For the same two segments (same
data), the spatial distributions of the difference between ‘attended’ minus ‘ignored’ stimuli are shown
in the lower two difference maps. Equipotential lines in steps of 0.1 gV. Dotted areas indicate that the
difference was negative, i.e. figure (or attended) stimuli had produced more negative values than nofigure(or ignored) stimuli; white areas indicate a positive difference. The average reference(mean of all
instantaneous data = spatial high-pass filter) was used for computation of differences, and for display.
From same data set as Figs 4, 5 and 6.
being more prominent ipsilateral to the side of stimulation. The finding that stimulus
position affects the topography of an endogenous component is interesting since it suggests
that late, high-level, generalizing information processing occurs in brain areas which deal
with information from specific sections of the surrounding world. It is also in line with the
results of NEVILLE et al. [43] who reported similar lateralization of a P450 component to
laterally presented words, using conventional multichannel ERP waveshape analysis.
BROWN and LEHMGN [4] studied ERP fields which were evoked by homophone nouns
and verbs at the end of sentences (e.g. he “rows”; the **rose”). Such homophone words
differing in meaning were taken from two different languages, together with an unintelligible
sound sequence with suggested noun or verb meanings. The three sets of stimuli were
presented to three subject groups. Scalp locations of the most positive and most negative
potential at each time point were determined. Figure 8 illustrates the results: during the
analysis epoch, the mean locations of most positive values evoked by noun meaning were
significantly more anterior than those evoked by verb meaning; the opposite was true for the
locations of the mean of the most negative values. The results agreed over the two different
languages, the two different lexical meanings, and the suggested meanings. The conclusion
must be that distinctly different generator populations process the incoming information,
depending on grammatical or contextual verb or noun meaning, and not depending on
language or lexical meaning.
A recent study followed up MARCEL’S [38] observations that masked words which are not
detected at better than chance level may produce semantic priming. Unconscious processing
is often viewed as a kind of early, automatic processing. To assess the time course of
unconscious processing, we recorded 16-channel ERPs to words and meaningless nonwords
consisting of letter-like elements. All stimuli were shown in a subliminal viewing condition,
EVENT-RELATED
165
POTEXTIALS
SUGGESTED
MEANING
0
0
l
3 3-174msec
N=lO
l =NOUN
‘rose’ ‘fliige’
0 =VEftB
‘rows’ ‘flijge’
FIG. 8. Reference-free
characteristics
of ERP scalp fields to acoustically
presented noun and verb
meanings of homophone,
but lexically different words in English and Swiss German, and to identical
sounds with suggested noun and verb meaning. Simultaneous
recordings from twelve electrodes in a
3 x 4 electrode array (= 15 x 20 cm, indicated by the rectangle) which was centered around the vertex
(Cz). Between 33 and 174 msec after word/sound
onset, the locations of the field maximal and
minimal value were determined for each subject and condition. Mean locations over all analysis times
and all seven subjects per group are shown. For real or suggested noun meaning, field maxima were
significantly
more anterior than for verb meaning; field minima showed the opposite difference,
indicating the activity of two distinctly different neural populations after presentation
of noun vs verb
meaning regardless of language or lexical content (after data from BROWN and LEHXL’X [4]).
C41).
of
FIG. 9. Reference-free characteristics
(field extrema)
ERP scalp maps to subliminal stimuli (without
conscious perception)at
fixation point, containing words or non-words (which consisted ofletter-like
elements). Simultaneous
recordings from 16 scalp electrodes between vertex (Cz) and inion. At all
analysis times, the locations of the maximal and minimal field values were determined for the two
conditions and the 10 subjects. The grand mean data were segmented into time epochs of stable
spatial characteristics
as discussed in the text. The figure illustrates the mean locations of the maximal
and minimal field values during the most discriminating
segment between 296 and 416 msec latency.
The lateral distance between the evoked mean locations of the maximal and minimal potential was
significantly larger for subliminal words than for subliminal non-words, indicating that processing of
subliminal stimuli long after input is handled by different neural populations,
depending on the (not
consciously perceived) information
content.
166
D. BRAXDEIS and D. LEHX.~XS
i.e. masked to prevent recognition.
Half the stimuli were also shown in a supraliminal
(perceivable) condition. Subliminal items could be ‘old’. i.e. from the supraliminal
items. or
‘new’. Supra- and subliminal stimuli alternated every 512 msec. Subjects had to decide after
each block whether the subliminal stimulus had been a word or nonword, and an ‘old’ or
‘new’item. They were not better than chance at discriminating
the items. ERP map sequences
were segmented, and ANOVAs tested scalp distances between the locations of maximal and
minimal potential in the anterior-posterior
and the left-right
direction. The left-right
distances between extrema locations discriminated
between subliminally
presented words
and nonwards during a late segment (Fig. 9). Although the effect discriminates
letters from
similar nonletters, it need not indicate a semantic discrimination.
The timing of the observed
effects suggests continued, specific processing of subliminal information
long after input. and
the different map configurations
indicate that processing of subliminal words and nonwords
involves different neural populations.
The results are consistent with an earlier study [2]
where similarly late, lateralized ERP effects discriminated
between more and less familiar
subliminal words.
.~cknorvledyemenrs-Supported
in part by the Swiss National
Science Foundation.
and Hartmann
Foundation
and EMDO Foundation,
Ziirich. We thank M. E&n, A. Horst, D. Weniger, W. Skrandies
anonymous
reviewers for constructive comments.
Miiiler
and tw-o
REFERENCES
8.
9
10.
11.
I?.
13.
14.
15.
16.
17.
18.
19.
BAUMGART?~~, G. Organization
and function of the neocortex. Neuro-Ophrhalmol.
3, 1-1-t. 1983.
BRANDEIS,D. U. An electrocortical
investigation
of word recognition in a backward masking paradigm. Bioi.
Ps,vchol. 18, 294295,
1984.
BROADBENT,D. E. Perception and Communication.
Pergamon Press, London, 1948.
BROWN, W. S. and LEH~NN, D. Verb and noun meaning of homophone
words activate different cortical
generators: a topographical
study of evoked potential fields. Expl Brain Res. (Suppl.) 2, 15%168, 1979.
&APMAN,
R. M., MCCRARY. J. W., CHAP~N, J. A. and Mfittx.
J. K. Behavioral and neural analyses of
connotative
meaning: word classes and rating scales. Brain Lang. 11, 3 19-339, 1980.
DONCHIN. E. (Editor) Cognitive Psychophysiology:
Etent-Related
Potentials and the .S~ud! of Cognition.
Lawrence Erlbaum, Hillsdale, NJ, 1984.
DOrXHIN, E. and &FFLEY, E. Multivariate
Analysis of event-related
potential data: a tutorial review. In
Multidisciplinary Perspectires in Ecent-related Brain Potentiul Research, D. OTTO (Editor). C.S. Government
Printing Office, Washington,
DC, 1978.
GAILLARD. A. W. K. and RIT-TER.W. (Editors) Tutorials in Erent Related Potential Research: Endogeneow
Components. North Holland, Amsterdam.
1983.
GEVINS. A. S. Brain ootential (BP) evidence for lateralization
of higher cognitive functions.
In Cerebral
Hemisphere Asymmetry, _I. B. &LL;GE. (Editor). Praeger. New York,-1983.
GEVINS, A.. SCHAFFER. R.. DOYLE. J.. CUTILLO, B.. TANNEHILL, R. and BRESSLER.S. Shadows of thought:
shifting lateralization
of human brain electric patterns during a briefvisuomotor
task. Science 220,97-99. 19S3.
GRANDORI, F. Dipole localization methods (DLM) and auditory evoked brainstem potentials. Rewe Lary.
Otol. Rhino/. (Suppl.) 105, 171-178, 1984.
GREGORY. R. L. Cognitive contours. IVature 238, 51-52. 1972.
HALLIDAY, A. M. (Editor) Evoked Potentials in Clinica! Testing. Churchill Livingstone, Edinburgh,
1982.
HANSEN. J. C. and HILLYARD, S. A. Endogenous
brain potentials associated with selective auditory attention.
Electroenceph. clin. Neurophysiol. 49, 277-290, 1980.
HANSEN, J. C. and HILLYARD. S. A. Selective attention to multi-dimensional
auditory stimuli. J. exp. Psychol..
Human Percept. Perform. 9, l-19. 1983.
HARTER. M. R. and AISE. C. J. Brain mechanisms
of visual selective attention. In Varieties of Attention. R.
PARASURA~N, R. DAVIS and J. BEATTY (Editors). pp. 293-321. Academic Press. New York. 1984.
HARTER, M. R. and PREVIC. F. H. Size-specific information
channels and selective attention: visual evoked
potentials and behavioral measures. Electroenceph. clin. Neurophysioi. 45, 628-640. 1975.
HILLYARD. S. A. and KUTAS. M. Electrophysiology
of cognitive processing. A. Rec. Psychol. U, 33-61. 1983.
HILLYARD. S. A.. HINK. R. F.. SCHWENT. V. L. and F'ICTON,T. W. Electrical signs of selective attention in the
human brain. Science 182, 177-180. 1973.
EWST-ELATED
20
21
22
‘3
24
25.
26
27
2s.
29
30.
31.
32.
33.
34.
35.
36.
31.
3s.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
5 1.
POTEXMLS
167
fiNK, R. F.. I-hlly~.
S. A. and BENSON. P. J. Event-related
brain potentials and selective attention to
acoustic and phonetic cues. Eiol. PsychoI. 6, l-16. 1978.
KANIZSA. G. Grnmmarica del cledere. Mulino. Bologna, 1980.
KhRRu(. R.. COHEN. J. and TL?TING. P. (Editors) Brain and Information: Event-Related Potentials. Ann. .Vetr
York Acad. Sci.. Vol. 425. Academy of Sciences. New York. 1984.
QTZNELSON. R. D. EEG recording, electrode placement and aspects of generator Iocalization.
In Electric
Fields of the Brain: the Neurophysics of EEG, P. L. NUXEZ (Editor), pp. 176213. Oxford University Press,
London, 198 1.
KOR?~HUBER, H. H. and DEECKE. L. Himpotentialinderungen
bei Willkiirbewegungen
und passiven
Bewegungen des Menschen: Bereitschaftspotential
und reafferente Potentiale. PJ%ger’s Arch. 284, l-17. 1965.
K~TAS, M. and HILLYARD, S. A. Reading senseless sentences: brain potentials reflect semantic incongruity.
Science 207, 203-205, 1980.
KUTAS, M. and HILLY~.
S. A. Event-related
potentials in cognitive science. In Handbook of Cognirice
Neuroscience. M. GAZZAXGA (Editor), pp. 387309.
Plenum Press. New York, 1984.
KUTAS. M., MCCARTHY. G. and DONCHIN, E. Augmenting
mental chronometry:
the P300 as a measure of
stimulus evaluation time. Science 197, 792-795. 1977.
LANDIS, T., LEH,MA~~, D.. ,MITA. T. and SKRA~~IES, W. Evoked potentialcorrelates
offigure and ground. Inr. J.
Psychophysiol. 1, 345-348. 1983.
LEH~NN. D. Multichannel
topography
of human alpha EEG fields. Elecrroenceph. clin. Neuroph.uiol. 31,
439-439, 1971.
LEH.MANX..D. Human scalp EEG fields: evoked, alpha. sleep and spike-wave patterns. In Swchroni:a!ion of
EEG Activity in Epilepsies. H. H. PETSCHEand M. A. B. BRAZIER (Editors). pp. 307-325. Springer, Wien. 1972.
LEH~NN, D. Spatial analysis of evoked and spontaneous
EEG potentials. In Recent Advances in EEG and
&MC Dara Processing. N. YA.MAGUCHI and K. FUJISAWA (Editors), pp. 117-132. Elsevier. Amsterdam.
1981.
LEHMANN, D. and CALUWAY. E. (Editors) Human Eroked Potentials: Applications and Problems. Plenum
Press, London. 1979.
LEH~NN, D. and SKIWXDIES, W. Reference-free
identification
of components
of checkerboard-evoked
multichannel
potential fields. Electroenceph. clin. Neurophysiol. 48, 609621, 1980.
LEHXANN, D. and SK~UXDIES,W. Spatial analysis of evoked potentials in man-a
review. Prog. Neurobiol. 23,
227-250, 1984.
LEHMANN,D., MELES, H. P. and Mm, 2. Scalp field maps of averaged EEG potentials evoked by checkerboard
inversion. Biomed. Technik, Stuttgart (Biom. Engng) Suppl. 21, 117-l 18. 1976.
LEHMANN, D., MELES, H. P. and MIR, 2. Average multichannel
EEG potential fields evoked from upper and
lower hemiretina:
latency differences. Electroenceph. clin. Neurophysiol. 43, 725-73 1, 1977.
MAGLIERO. A.. BASHORE.T. R., Corzs. M. G. and DONCHIN, E. On the dependence of P300 latency on stimulus
evaluation processes. Psychophysiology 21, 171-186, 1984.
MARCEL. A. J. Conscious and unconscious
perception: experiments on visual masking and word recognition.
Cognit. PsJchol. 15, 197-237, 1983.
MCCARTHY, G. and DONCHIN. E. A metric for thought: a comparison
of P300 latency and reaction time.
Science 211, 77-80, 1981.
MCCLELLAND. J. L. and RU~LHART, D. E. An interactive activation
model of context eff.cts in letter
perception:
Part 1. An account of basic findings. PsychoI. Rec. 88, 375-407, 1981.
MILLER, J. Discrete versus continuous stage models of human information
processing: In search of the partial
output. J. exp. Psychoi.. Human Percept. Perform. 8, 27S296, 1982.
NXXTANE~‘,R. and MICHIE, P. T. Early selective attention effects on the evoked potential. A critical review and
reinterpretation.
Biol. Ps.vchol. 8, 81-136, 1979.
NEVILLE, H. J.. KUTA~, M. and SCHMIDT, A. Event-related
potential studies of cerebral specialization
during
reading. I. Studies of normal adults. Brain Lung. 16, 30&315, 1982.
NORMAN, D. A. Toward a theory of memory and attention. Psychol. Rer. 75, 522-536, 1968.
@FXR, F. F. The EEG as potential mapping: the value of the average monopolar
reference. Electroenceph.
clin. Nerrrophysiol. 2, 2 15-216, 1950.
~CCOD, C. E. The nature and measurement
of meaning. fsychol. Bull. 49, 197-237, 1952.
I?=EFFERBAUM,
A.. WENEGRAT, B. G., FORD, J. IM., ROTH, W. T. and KOPELL, B. S. Clinical applications
of the P3
components
of event-related
potentials:
II. Dementia, depression
and schizophrenia.
Elecrroenceph.
clin.
Neurophysiol. 59, 104-124, 1984.
PRITCHARD, W. S. Psychophysiology
of P300. Psycho/. Bull. 89, X6-540, 1981.
PRITCHARD, W. S. and WARM. J. S. Attentional processing and the subjective contour illusion. J. exp. Psxchol.,
Gen. 112, 145-175, 1983.
R~MOND, A. Poursuite de la significance en EEG. I. ProbKme de Ia reference spatile. Revue Neurol. 102,
411415.
IY6U.
RBSLER, F. Endogenous
ER“P”s and cognition: probes, prospects and pitfalls in matching pieces of the mindbody puzzle. In Tutorials in Event Related Potential Research: Endogeneous Components, A. W. K. GAILL~
and W. RITTER (Editors). North Holland, Amsterdam.
1983.
168
D. BR~NDHSand D. LEHMK\%
52. ROTH, W. T..
BEFFERBAUM,
A., KELLY.A. F.. BERCER.P. A. and KOPELL.B. S. Auditory event-related
potentials in schizophrenia and depression. Psychiaf. Rex. 4, 199-211, 1931.
53. RUGC. 54. D. Event-related potentials and the phonological processing of words and non-words.
.Veuropsychoiogia 22, 435-444. 1984.
54. SHAGASS.C., ROEMER.R. A.. STRM_MA~TS.
J. J. and .%WADEO,
M. Evoked potential correlates of pychosis. Viol.
Psychiar. 13. 163-lS4, 1975.
55. SHIFFRIN,R. M. and SCHXIDER,W. Controlled and automatic human information processing: 11.Perceptual
learning. automatic attending, and a general theory. Psychoi. Rec. 84, 127-190, 1977.
56. SKRINDIES.W. Information processing and evoked potentials: topography of early and late components. Mr.
Biol. Psychiaf. 13, l-12. 1983.
57. Stuss, D. T.. SARAZIN.F. F., LEECH,E. E. and PtCTON,T. W. Event-related potentials during naming and
mental rotation. Eleclroenceph. din. Neurophysiol. 56, 133-146. 1983.
M.. ZUBIN,J. and JOHN,E. R. Evoked potential correlates ofstimulus uncertainty. &ience
58. Sm-ro~. S.. BRAREN,
150, 1187-l 1S8, 1965.
59. TREKMAN,A. M. Strategies and models of selective attention. Psychol. Rec. 76, 282-299, 1969.