Brain Products Press Release
October 2011, Volume 40
User Research
How DC-recorded slow potentials can aid in studying dynamic retrieval-control processes
by Jasmin M. Kızılırmak, Philipps-University Marburg, Germany
In our daily life, we are constantly faced with the necessity of
selecting relevant stimuli, tasks, and memories to achieve our
goals. Sometimes, we even need to focus on information we had to
ignore just previously. What kind of control mechanisms enable us
to alternately switch between what is selected and what is ignored?
In the field of selective attention and task switching, by changing
which stimulus/task is relevant from trial to trial, evidence has
been obtained for the inhibition of irrelevant information by means
of ‘negative priming‘ [1], for the enhancement of the relevant
information [2], and for both in conjunction [3]. In contrast,
for memory retrieval, research has predominately focused on
paradigms where subjects did never have to switch between which
information has to be retrieved and which to be ignored until final
testing [4].
In the study presented here, which has recently been published
online [5], we tackled the question of what kind of dynamic
cognitive-control processes enable the alternating retrieval
of to-be-retrieved and to-be-ignored long-term-memory (LTM)
representations. For this aim, we measured DC-recorded slow
cortical potentials (SCPs) as an electrophysiological correlate of
task-related cortical activation [6]. SCPs are known to last for at
least 300 ms up to several seconds [7], and do not have a defined
peak such as earlier event-related potentials (ERPs) like, e.g.,
P3 or N4. SCP amplitudes are known to vary with manipulations
of cognitive load, and one characteristic that distinguishes
such DC potentials from most other ERPs is the fact that their
neurophysiological origin is relatively well understood: SCP shifts
represent a sustained field potential arising from the depolarization
of the apical dendrites of pyramidal cells in the neocortex [8]. This
depolarization shows up as a slow negative deflection in the scalprecorded EEG and indexes increased activation of the underlying
cortical tissue. The topographic maximum of an SCP lies mostly
above its cortical origin, and there is a high correlation between
blood-oxygenation-level-dependent (BOLD) activity as measured
by fMRI and SCPs [8, 9]. Thus, SCP maps can provide information
about which cortical regions are probably involved in a particular
cognitive process. As we manipulated control demands during
retrieval, we expected effects with a frontal topography, and
conditions that are more cognitively demanding to have a higher
negative SCP amplitude [10].
For our retrieval task, participants first had to learn associations
between cues (animals) and three feature values each that were
body weight, sociability, e.g., if the animal species is usually
running around alone, or in small groups, etc., and the distance
of their natural habitat to the town of our university in Marburg,
Germany. The material had to be memorized by means of photos
of the animals and symbolized features (differently scaled mass
symbols, different amounts/circular patterns of dots, differently
long arrows on a flat Europe-centered world map). In the later
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retrieval task, the to-be-retrieved
association was indicated by the name
of the animal and abstract feature
scales to ensure active recall. The task
was to decide whether the retrieved
value matched the marking on the
scale (see Fig. 1).
Jasmin M. Kızılırmak
Figure 1: Retrevial Phase- Retrieving feature values
according to markings on a scale
Exemplary trial of the retrieval task. While the associations between 25 animals
and three feature values each were learned visually, retrieval was triggered by
means of the animal‘s name (cue) and feature scales where the one scale with
a small marking indicated the relevant feature that needed to be retrieved.
To trigger dynamic adjustments of retrieval-control processes,
we manipulated changes and repetitions of the cue and
features for two-trial sequences each. This way, we generated
the following conditions: sequences where one feature had
to be retrieved in trial n and another in trial n-1 with either (1)
no repetition, (2) feature repetition, i.e., consecutive retrieval
targets were associated with different cues but were of the
same feature dimension, or (3) cue repetition i.e., consecutive
retrieval targets were associated with the same cue (see Table 1).
Sequence
Condition
Cue
Feature
Example sequence
1
no repetition
change
change
Lion – weight,
Bat – sociability
2
feature
repetition
change
repetition
Lion – weight,
Bat – weight
3
cue
repetition
repetition
change
Bat – weight,
Bat – sociability
Table 1: The experimental conditions were generated by manipulating
cue and feature changes/repetitions for all two-trial sequences.
In the retrieval task, cues (animal name) and feature scales
(indication of retrieval target) were presented temporally disjunct
to enable separate analyses of the electrophysiological correlates
of cue and retrieval processing. A trial began with a 1000 ms
presentation of a fixation cross, followed by the presentation of
the cue for 600 ms, followed by the presentation of the feature
scales that were shown for at least 3000 ms, or until a response
was made, respectively (see Fig. 1). Cue presentation was chosen
to be long enough to read the word, but short enough to prevent
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Brain Products Press Release
active retrieval of all three features in advance. The minimum
duration of the scales‘ presentation was chosen to be long enough
to allow an uncontaminated interval for the analysis of the SCPs.
Between trials, there was a blink period for 2000 ms (blank screen).
Subjects were asked to only blink during this interval to avoid
a contamination of the EEG with blink artifacts. This procedure
usually works very well, probably as for most of the subjects it
becomes some kind of conditioned/automated response to blink
during the blank screen.
EEG was recorded in DC mode from 61 scalp electrodes referenced
online to FCz, from one inferior ocular channel (IO), and two
electrodes at both earlobes (A1, A2), and digitized at 500 Hz. We
used a custom-designed BrainCap with Ag/AgCl ring electrodes
arranged according to the traditional 10-20 system, with two
32-channel amplifiers (BrainAmps DC). Average impedance was
kept below 5 kΩ. For recording, BrainVision Recorder 1.2 was
used. It is important to note that no online filtering of frequencies
was applied like it is usually done when recording in AC mode,
where low frequencies are filtered. The SCPs we are interested in
lie in this frequency range. To avoid that the signal drifts out of
the measurement range, manual resets of the amplitude to zero
were made previous to saturation. This was done by means of
the in-built ‚DC reset‘ function of the BrainVision Recorder. Such
offsets in the signal could later be corrected by means of the ‚DC
correction‘ function of the BrainVision Analyzer 2.0.1. DC and
artifact correction, segmentation, etc. were done with BrainVision
Analyzer. EEG was re-referenced offline to averaged earlobes and
low-pass filtered at 30 Hz (24 dB/oct) and an additional 50 Hz notch
filter. The electrooculogram was calculated by re-referencing IO to
Fp1.
EEG was preprocessed to exclude segments including blinks,
eye movements, muscle potentials, and other artifacts by means
of a semi-automatic detection procedure (‘Artifact Correction‘
function). It was then segmented according to the event definitions,
baseline-corrected, and averaged. Segments had a length of 3700
ms, beginning 100 ms before stimulus onset of the cue, this 100
ms fixation interval served as baseline. All segments of trials with
errors, or where no response was made within 6600 ms after scale
onset, were excluded from the analysis. Averages were calculated
with a minimum of 40 segments per condition for each participant.
October 2011, Volume 40
from 1 to 3 seconds after scales onset (BrainVision Analyzer
export function). This length of interval was chosen based on the
minimum duration of an SCP [7], while breaking the SCP interval of
interest down in equally long segments. Comparisons were made
between conditions that only differed in regard to one factor, i.e.,
cue repetition vs. no repetition (sequence 3 vs. 1 in Table 1), and
feature repetition vs. no repetition (sequence 2 vs. 1). ANOVAs were
calculated for each interval with factor condition and electrode
(19 standard electrodes) to gain information about topographic
differences in activation. To avoid alpha inflation, only significant
effects (p < .05) that lasted a minimum of two intervals were taken
into account.
The ERP analysis of the cue-processing interval indicated a
repetition benefit for the cue, i.e., a word-repetition priming,
with a decrease of the negative mean amplitude around 400 ms
compared to the two other (cue change) conditions (see Fig. 2). For
Figure 2: Event related potentials during cue processing and retrieval
ERPs during cue processing (-600 to 0 ms), and during feature retrieval ( 0 to
3000 ms). The analyzed interval for SCPs during retrieval processing was 1-3 s.
the retrieval-processing interval, we again found a cue repetition
effect in the SCPs, while no effect of feature repetition was evident.
Importantly, the cue-repetition effect was now in the complete
opposite direction (see Fig. 2).
Cue repetition showed the most negative mean amplitude for all
analyzed intervals, indicating that it constitutes the condition with
the highest cognitive load. This would be in line with reports of
negative priming [1], i.e., that it is harder to retrieve a previously
ignored or even inhibited association with a cue compared to
switching to a complete different cue-associations net. As expected
for differences in the engagement of control processes, mean
amplitudes differed maximal at frontal electrodes (see Fig. 3).
We expected that SCPs related to feature retrieval would differ
in mean amplitude at frontal electrodes during 1-3 s after scales
onset, reflecting differences in the involvement of prefrontal
cortex regions that have been associated with cognitive control
in neuroimaging studies previously [10]. Because SCP amplitudes
have been found to be more negative when there was higher cortical
activation, we hypothesized that a cognitively more demanding
condition would be associated with relatively higher negative
amplitudes. In line with the high correlation between topographic
SCP maxima and BOLD activation patterns, differences in the
location of the maxima of the effects would suggest differences in
the involved cortex areas.
Figure 3: Slow cortical potential map for retrieval processing
To analyze SCP amplitude differences between conditions, mean
amplitudes were calculated and exported for 250 ms intervals
SCP maps of the three analyzed conditions, and difference map of the
significant cue repetition effect.
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Brain Products Press Release
Thus, because SCP topographies correlate with BOLD activation
patterns [8], the frontal-central topography of the effect could
further indicate a higher activation of the anterior cingulate cortex
(ACC) for cue repetition. ACC activation has been associated
with conflict monitoring [10]. Thus, this finding suggests a higher
conflict when needing to focus on a just previously ignored
association with a cue, compared to switching to a different cueassociation net altogether from which no association has been
retrieved/ignored in the preceding trial. Note that this pronounced
cue-repetition effect in the SCPs had no correlate in the
behavioral data. This might be due to the opposing ERP effects,
i.e., it is likely that the cue-change effect in the SCPs does not
become visible in the behavioral data, because the disadvantage
of retrieving a previously ignored association is canceled out by
a repetition benefit for cue processing per se. – This finding is a
good example for the strength of ERPs in informing us about covert
processes that are hard to deduce from behavioral parameters
alone that reflect only the sum of all processes from stimulus
October 2011, Volume 40
onset to response.
The present study demonstrates that selection processes during
LTM retrieval can be successfully studied by manipulating the
history of processing demands in trial sequences, as it has been
done before in perceptual and task-switching paradigms. We found
evidence that accessing a previously ignored association with the
same cue imposes higher processing load on the system compared
to when associations related to different cues had to be accessed
in successive trials. This suggests that accessing different
representations belonging to one and the same associative
network creates more interference than accessing associations
belonging to distinct networks. These extra control demands
became manifest in an SCP negativity over the mid-frontal cortex,
suggesting an involvement of the ACC. However, SCP maps can
only give a coarse estimation of the involved cortical areas, and
this finding needs to be evaluated with methods of higher spatial
resolution like fMRI.
References
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& Cognition, 16, 64-70.
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3. Scherbaum, S., Fischer, R., Dshemuchadse, M., Goschke, T., 2010. The dynamics of cognitive control: Evidence for within trial conflict adaptation from frequency
tagged EEG. Psychophysiology, 48(5), 591-600.
4. Chan, J. C. K. (2009). When does retrieval induce forgetting and when does it induce facilitation? Implications for retrieval inhibition, testing effect, and text
processing. Journal of Memory and Language, 61, 153-170.
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