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Manuscript in press Psychophysiology
fMRI in an oddball task: Effects of target-to-target interval
Michael C. Stevens1,2, Vince D. Calhoun1,2 and Kent A. Kiehl1,2
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Olin Neuropsychiatry Research Center, The Institute of Living, Hartford, CT
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Yale University, New Haven, CT
Corresponding Author:
Kent A. Kiehl, Ph.D
Olin Neuropsychiatry Research Center, Whitehall Building
The Institute of Living / Hartford Hospital
Hartford, CT 06106
(860) 545-7552 Ph
(860) 545-7997 Fax
email: kent.kiehl@yale.edu
Running head: fMRI Oddball target interval
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ABSTRACT
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The amplitude of the P3 event-related potential (ERP) elicited by task-relevant target (“oddball”)
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stimuli has been shown to vary in proportion to the length of time between targets. Here we use
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functional magnetic resonance imaging (fMRI) to identify neural systems modulated by target
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interval in a large sample of healthy adults (n=100) during performance of an auditory oddball
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task that included both target and novel stimuli. A positive relationship was found between
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target interval and hemodynamic activity in the anterior cingulate and in bilateral lateral
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prefrontal cortex, temporal-parietal junction, postcentral gryi, thalamus and cerebellum. This
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modulation likely represents updating of the working memory template for the target stimuli.
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There was no such effect of novel interval, suggesting that neuronal modulation may only occur
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for task-relevant stimuli, possibly in the service of strategic resource allocation processes.
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KEY WORDS: ODDBALL, FMRI, NOVELTY, SEQUENCE, TARGET, P3
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Running head: fMRI Oddball target interval
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fMRI of target-to-target interval
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Oddball tasks often require detection of infrequent target stimuli within the context of
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frequently presented standard stimuli (Polich & Kok, 1995; Sutton, et al., 1965) – for example,
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the detection of a high-pitched tone in a sequence of low-pitched tones. This produces a
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characteristic ERP waveform with a prominent positive peak at approximately 300 msec (i.e., the
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P3). In oddball tasks that require a response to a particular infrequent stimulus type, the P3 is
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thought to reflect cognitive processes necessary for updating working memory representations of
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task-relevant stimuli (Donchin & Coles, 1988). Oddball tasks sometimes also include a low
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probability task-irrelevant stimuli, such as novel, non-repeating random noises, which are
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thought to elicit automatic attentional orienting responses (Friedman, et al., 1993).
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There is great interest in determining what factors modulate the neural response to
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oddball target and various types of nontarget stimuli. Several experiments have demonstrated
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that global target probability (Duncan-Johnson & Donchin, 1977), the inter-stimulus interval
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(Polich, 1990), or the order of nontarget and target stimuli (Polich & Bondurant, 1997) modulate
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the P3. However, these manipulations also change the absolute time between targets (i.e.,
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referred to as target-to-target interval, or target interval). Gonsalvez and colleagues have argued
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that target interval may better explain target-P3 modulation than other factors (Croft, et al., 2003;
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Gonsalvez, et al., 1995; Gonsalvez, et al., 1999; Gonsalvez & Polich, 2002). Because
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intervening novel stimuli do not affect target P3 amplitude (Courchesne, et al., 1977; Johnson &
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Donchin, 1980), this modulation might occur only for task relevant stimuli. However to date, no
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study has explored whether novel-to-novel interval influence neural activity, despite the
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observation that preceding sequence length influences nontarget P3 in a manner analogous to
Running head: fMRI Oddball target interval
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target interval effects on the target P3 (Johnson & Donchin, 1980; Sams, et al., 1983; Verleger &
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Berg, 1991).
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Because of the difficulty inferring the location of ERP neural generators in general
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(Baillet & Garnero, 1997; Pascual-Marqui, et al., 1994) and the P3 in particular (Halgren, et al.,
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1995a; Halgren, et al., 1995b; Halgren, et al., 1998), it is not clear which brain structures might
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be modulated by target intervals. The measurement of brain hemodynamics using fMRI
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provides a means to identify which structures are influenced by oddball target interval
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manipulations. One of the largest fMRI auditory oddball studies to date (Kiehl, et al., 2005)
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replicated and extended over a dozen previous fMRI oddball target detection studies, showing
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that hemodynamic activity is elicited in numerous, widespread cortical and subcortical brain
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structures during target detection and novelty processing. This study also showed that activation
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elicited by target and novel stimuli was extremely reliable in the vast majority of these regions.
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Few studies have examined the influence of the interval length between target stimuli on
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hemodynamic activity. Horovitz and colleagues (2002) found that the amplitude of the
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hemodynamic response elicited by target stimuli was positively correlated with amplitude of the
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P3 in left supramarginal gyrus, thalamus, bilateral insulae, and right medial frontal gyrus.
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Similarly, Casey, et al. (2001) reported that activity in dorsolateral prefrontal cortex increased as
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the target stimulus probability decreased. Because lower target probability increases target
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interval, this latter finding may be related to target interval.
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Here we examine the influence of the length of target-to-target intervals on hemodynamic
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activity elicited by target and novel stimuli by re-analysis of a large (n=100) fMRI dataset
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(Kiehl, et al., 2005). Based on previous studies (Casey, et al., 2001; Horovitz, et al., 2002), it
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was hypothesized that target interval length would be positively correlated with the amplitude of
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hemodynamic response in dorsolateral prefrontal cortex, supramarginal gyrus, bilateral inferior
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frontal gyri, and thalamus. Because the response to target stimuli is thought to reflect updating
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of working memory representations, it also was predicted that target interval length would
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modulate right inferior parietal lobule and inferior frontal gyrus activity (Fletcher & Henson,
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2001). A secondary aim was to examine the effect of novel interval length on hemodynamic
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response to novel stimuli. Because intervening task-irrelevant infrequent stimuli do not
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influence target P3 ERP (Courchesne, et al., 1977; Johnson & Donchin, 1980) and novel stimuli
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elicit different cognitive processes from target detection, we did not anticipate novel interval to
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modulate hemodynamic activity in the same manner as target interval. However, previous ERP
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studies have not directly addressed this question. Therefore, specific hypotheses were not made.
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Methods
Participants
One-hundred healthy right-handed volunteers (53 men and 47 women, mean age 29.2
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years (range: 18 – 62; SD 10.03) participated in the study. Further demographic and sampling
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details are presented it Kiehl et al. (2005).
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Task and Procedure
The experimental task was a three-stimulus auditory oddball task previously used in both
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ERP and fMRI studies (Kiehl, et al., 2001a; Kiehl, et al., 2001b; Kiehl, et al., 2005). The
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standard stimulus was a 1000 Hz tone (probability, P ~0.80), the target stimulus was a 1500 Hz
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tone (P ~0.10), and the novel stimuli (P ~0.10) were non-repeating random digital noises (e.g.,
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tone sweeps, whistles). There were 196 standard stimuli, 24 target stimuli, and 24 novels stimuli
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in each of two runs, for a total of 48 target and 48 novel stimuli per subject. Participants were
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instructed to respond as quickly and as accurately as possible with their right index finger when a
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target tone occurred and not to respond to other stimuli. Stimuli were presented for 200 msec
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with a 2000 msec stimulus onset asynchrony (SOA). Target intervals ranged from 8 to 68
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seconds (Session 1 mean=18.7, SD=10.95; Session 2 mean=20.4, SD=14.95). Novel intervals
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ranged from 8 to 62 seconds (Session 1 mean=20.4, SD=13.68; Session 2 mean=19.7,
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SD=12.55). In total, there were 15 separate target intervals and 17 novel intervals. There were
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between 1 to 10 events in each target interval (mean=3.42, SD=2.93) and between 1 to 10 events
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in each novel interval (mean=2.82, SD=2.74). Within each target interval, between 0 to 4 novels
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occurred. In each novel interval, there were between 0 to 5 targets. Target and novel stimuli
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always were preceded by between 3 to 5 standard stimuli (8 to 12 seconds).
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Imaging Parameters, Image Processing and fMRI Modeling
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Functional image volumes were collected in axial orientation to the AC-PC line using a
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gradient-echo sequence sensitive to the BOLD signal (TR/TE 3000/40 ms, flip angle 90o, FOV
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24×24 cm, 64×64 matrix, 62.5 kHz bandwidth, 3.75×3.75 mm in plane resolution, 5 mm slice
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thickness, 29 slices) effectively covering the entire brain (145 mm). The two runs consisted of
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167 time points each, prefaced by a rest period of 12 seconds that was discarded prior to
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subsequent processing to remove T1 stabilization effects.
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Functional images were processed using techniques described in greater detail in Kiehl,
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et al. (2005). Briefly, images were reoriented to the anterior commisure/posterior commisure
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plane, corrected for motion using an algorithm unbiased by local signal changes (INRIAlign;
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(Freire & Mangin, 2001; Freire, et al., 2002), spatially normalized to standardized MNI space
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(Friston, et al., 1995), and smoothed with a 12 mm3 FWHM kernel (see Kiehl et al, 2005, for a
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comparison of different smoothing kernels) using Statistical Parametric Mapping 2 software.
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The regressors for each participant’s fMRI model were derived by extracting stimulus onset
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timings for all target, novel, or standard stimuli. The effects of target and novel interval were
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evaluated using 1st order parametric terms, following the analysis framework described in detail
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in (Buchel, et al., 1998). This orthogonalized expansion term models brain activity relative to
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target or to novel stimuli that shows linear increases in the amplitude of hemodynamic response
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over time. For each target (or novel) stimulus, the parametric modulator was the time in seconds
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since the previous target (or novel) stimulus. The first target or novel stimulus in the timeseries
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used the time since session start for the parametric modulator. Each participant’s model included
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terms for 1) standard stimuli relative to implicit baseline, 2) target stimuli relative to implicit
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baseline, 3) novel stimuli relative to implicit baseline, 4) target stimuli × target interval linear
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change, and 5) novel stimuli × novel interval linear change. The implicit baseline represents
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variance in the timeseries that is not explicitly modeled, including error.
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For group analyses, images containing latency variation-corrected (Calhoun, et al., 2004)
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effects of target or novel interval on the amplitude of the hemodynamic response were entered
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into separate one-sample t-test random effects analyses. Statistical significance was evaluated
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using a threshold of p < 0.05, corrected for multiple comparisons using the familywise error rate
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(Worsley, et al., 1996).
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Significant regions were examined further by using a cluster analysis to group regions
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with similar patterns of covariation across target interval lengths. A hierarchical cluster analysis
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(SPSS 12.0) examined the average between-groups linkage based on a Pearson correlation
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similarity measure. This measure was selected because it is less sensitive to size effects that
Running head: fMRI Oddball target interval
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often arise in distance functions. Clustering was performed using extracted mean peak
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amplitudes for each target interval length.
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Mean reaction time for each target interval was compared using repeated-measures
ANOVA (Greenhouse-Geiser corrections) and post hoc tests for linear and quadratic trends.
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Results
Behavioral Performance
Mean target interval reaction time data was available for 99 of 100 subjects. Mean
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reaction time differed across target interval lengths (F(1,98) = 5.426, p = .022) and there was a
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significant linear trend (F(1,98) = 14.225, p = .0003), such that longer target intervals were
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associated with slower reaction times. Reaction time means (SD) for each target interval are
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listed in Table 1.
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Hemodynamic Response Modulation by length of Target-to-Target or Novel-to-Novel Interval
Figure 1 illustrates the location of target interval effects in the brain images and Table 1
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lists peak voxel locations, t-scores, and parametric contrast beta coefficients. Target interval
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linear effects were found in numerous brain structures, including bilateral superior/middle and
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inferior frontal gyrus, bilateral insulae, medial frontal gyrus, anterior cingulate, bilateral pre- and
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postcentral gyri, bilateral inferior and superior parietal lobules, left precuneus, posterior
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cingulate, thalamus, bilateral middle temporal gyri, left cuneus/lingual, thalamus, right putamen
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and bilateral cerebellum. All of the above regions showing significant target interval effects
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previously have been observed to be active during target detection (Kiehl, et al., 2005; Stevens,
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et al., in press). There were no brain regions that showed an inverse relationship between target
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interval length and the amplitude of the hemodynamic response.
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At the thresholds appropriate for this large sample (p < .05, corrected for multiple
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comparisons to search the entire brain volume using the familywise error rate), novel interval did
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not modulate the hemodynamic response to novels in any brain region. At liberal thresholds (p <
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.001 uncorrected for multiple comparisons), a linear effect of novel interval was found in
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cingulate gyrus (x,y,z = -4, 4, 44, t99 = 3.95), right inferior parietal lobule (x,y,z = 60, -36, 24, t99
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= 4.45), left superior temporal gyrus (x,y,z = -64, -24, 0, t99 = 4.56), and right middle temporal
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gyrus (x,y,z = 60, -32, 0, t99 = 3.99).
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A cluster analysis on target interval data indicated that there were two patterns of
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hemodynamic change across target intervals. Representative graphs depicting peak
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hemodynamic activity across the 15 target interval time bins are displayed in Figure 2. One
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cluster comprised regions that showed a sharp rise in the amplitude of hemodynamic response
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across target intervals from ~30 to ~50 seconds. The second cluster showed a relatively smooth
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increase of peak hemodynamic activity across all target interval lengths tested. Cluster
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memberships are listed in Table 1.
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Discussion
This study tested the hypothesis that longer intervals between target stimuli would be
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associated with increased hemodynamic activity to subsequent targets. Consistent with
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hypotheses, target interval effects were observed in anterior cingulate, medial frontal gyrus,
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bilateral dorsolateral prefrontal cortex regions, left supramarginal gyrus, bilateral inferior frontal
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gyri, and thalamus. In addition, target interval modulated hemodynamic activity in bilateral
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temporal lobe structures, bilateral postcentral gyri, and bilateral cerebellum. Therefore, the
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present results replicate and extend previous studies. The current study differed from previous
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reports in that it examined the relationship of target interval to hemodynamic activity rather than
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correlating hemodynamic activity to peak ERP amplitude (Horovitz, et al., 2002). The present
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study also employed a wider range of target intervals and a larger sample than used in previous
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studies. At appropriate statistical thresholds, there was no evidence that hemodynamic activity
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elicited by novel stimuli was modulated by novel-to-novel interval.
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P3 ERPs elicited by oddball stimuli are commonly interpreted within the theory of
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contextual updating proposed by Donchin and Coles (1988). In this theory, increased neural
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activity with longer target intervals likely reflects the process of updating a working memory
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model as the environmental context is altered by ongoing changes. Alternatively, Gonsalvez and
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colleagues (Croft, et al., 2003; Gonsalvez, et al., 1995; Gonsalvez, et al., 1999; Gonsalvez &
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Polich, 2002) suggest that target interval effects reflect working memory template restoration
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following systematic degradation over time. This account is similar to the contextual updating
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model, but temporal factors are emphasized over subjective or global probability, which are
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important for contextual updating theory. Activity of brain regions within at least one of the two
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clusters may reflect target working memory model updating. This cluster includes regions
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believed to mediate working memory and attentional control, particularly for salient stimuli,
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including bilateral middle frontal gyri, bilateral insulae, right inferior frontal gyrus, bilateral
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inferior parietal lobule, anterior and posterior cingulate (Corbetta & Shulman, 2002). The
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anterior cingulate increases in activation during conditions involving conflict (Carter, et al.,
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1998) or error monitoring (Gehring, 1993; Kiehl, et al., 2000). Therefore, this activity may
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reflect a cumulative process of increasing target expectancy (Donchin & Coles, 1988; Squires, et
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al., 1976). Alternatively, several researchers have suggested that lateral prefrontal and anterior
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cingulate activity might influence norepinephrine modulation of P3 in oddball contexts
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(Nieuwenhuis, et al., 2005). Nieuwenhuis and colleagues have proposed that phasic
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norepinephrine activity driven by the outcome of response decision-making may serve to
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enhance future top-down mediated selective attention for salient stimuli. They predict that
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target-to-target interval would enhance neural response in brain areas active during task-relevant
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target processing, while no modulation would be seen to motivationally insignificant (i.e., task-
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irrelevant novel) stimuli, which is the pattern of results found in this study. This raises the
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possibility that part of the working ‘memory template restoration’ process may be to tune the
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neural network, facilitating the ability to process future target stimuli.
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Gonsalvez and colleagues also propose that target and nontarget stimuli working memory
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templates might be independently represented in the brain, rather than jointly contributing to a
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general “context” for cognitive processing (Croft, et al., 2003). The current results are consistent
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with this proposal. The lack of modulation of the hemodynamic response by novel interval,
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particularly in the presence of modulation by target stimuli, is consistent with the proposed
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independence of working memory templates. The fact that both target and novel stimuli were
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infrequent (i.e., both P ~0.10) strongly suggests task salience, rather than global stimulus class
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probability, was the more influential factor modulating neural response to infrequent stimuli.
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However, it also might reflect an absence of a stimulus-bound memory template for the class of
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continually-changing ‘novel’ stimuli. This could be tested in future studies by contrasting the
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effect of nontarget interval between infrequent stimuli that are novel versus those that are
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repeated.
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The other cluster of brain regions with a target interval effect showed a marked increase
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in activity after approximately 30 seconds. This cluster comprised brain regions known to be
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involved in motor preparation (e.g., premotor, supplementary motor cortex) and execution
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(bilateral cerebellum) and top-down influences on attentional shifting (e.g., bilateral superior
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parietal lobule) (Behrmann, et al., 2004; Cunnington, et al., 2003; Rushworth, et al., 2003).
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These brain regions might show additional activity when the brain must engage additional neural
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resources to prepare a new motor response following sufficient passage of time. Many of these
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brain regions recently have been linked to two motor preparation processes – motor readiness
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potentials (Cunnington, et al., 2003) and contingent negative variation processes (Nagai, et al.,
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2004). However, these latter effects typically are observed following a cue or a decision for
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volitional movement, which might differentiate them from the apparently automatic phenomenon
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captured by the target interval analysis. The relationship of activity in these brain regions and
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reaction time is not yet clear, but both show a significant linear increase over the intervals
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measured in this experiment. Therefore, it is possible there is a relationship between increased
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motor preparation neural activity and reaction time.
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It also is possible that the current findings might be related to well-described contextual
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factors other than target interval that also influence P3 amplitude. Although the current
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paradigm controlled infrequent event global probability (P ~ .10), interstimulus interval (2
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seconds), and preceeding nontarget structure (range 3 to 5 standards), it did not control for other
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sequential structure issues such as local target/novel stimulus probability. Local nontarget
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probability might alter participants’ subjective sense of the likelihood of an upcoming target
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stimulus (Donchin & Coles, 1988; Squires, et al., 1976). Therefore, the current results should be
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interpreted cautiously until such time as data are available that address this possibility. These
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findings also might not reflect the same phenomena observed in published ERP studies because
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the range of target and novel intervals in this experiment was greater than that typically used
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(e.g., <16 seconds). A comparison of how brain activity is modulated by short target intervals
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(i.e., 1-10 seconds) versus long target intervals (i.e., 8–60 second range) would help to clarify the
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relationship between EEG and fMRI target interval-modulation. It also should be noted that the
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reaction time analyses may be limited because several target intervals averaged few
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observations, which raises the possibility that these means were less stable than others. Finally,
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because previous studies focus on target interval effects for P3 ERP amplitude and latency, it is
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not conclusively known if target interval alters other ERP components. Because the
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hemodynamic response to targets reflects neural activity to multiple target-elicited ERPs, it is
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possible that the current findings may be related to other cognitive processes (i.e., not those
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reflected by the P3).
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Conclusion
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The present experiment demonstrates that longer target intervals are associated with
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increased hemodynamic activity in a large network of brain structures, possibly containing two
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functional subnetworks. Although additional research is needed to more conclusively link fMRI-
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measured target interval-modulations to the target interval modulations of ERP data, the current
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results likely reflect the same neuronal phenomenon previously identified in ERP research. The
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results support the hypothesis that target interval modulates neural activity in diverse brain
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structures by updating of working memory processes.
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Author Note
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All authors are affiliated with the Olin Neuropsychiatry Research Center at the Institute of
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Living in Hartford, CT and with the Department of Psychiatry at Yale University. Dr. Kiehl also
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has an appointment to the Department of Psychology at Yale University. This research was
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supported in part by the National Institutes of Health, under grants by 1 K23 MH070036-01
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(MCS), 1 R01 EB 000840-01 (VDC), 1 R01 MH0705539-01 (KAK) and 1 R01 MH072681-01
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(KAK) and National Alliance for Research on Schizophrenia and Depression (NARSAD) Young
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Investigator awards to KAK and VDC. Address reprint requests to Dr. Kent A. Kiehl at the Olin
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Neuropsychiatry Research Center, 200 Retreat Avenue, Whitehall Building, The Institute of
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Living, Hartford, CT 06106, or by email at kent.kiehl@yale.edu.
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List of Tables
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Table 1. Summary of reaction time means and standard deviations for each target-to-target
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interval.
393
Table 2. Summary of the brain areas showing a significant positive linear relationship between
394
target interval and amplitude of hemodynamic response to target stimuli. Coordinates
395
represent peak t-score for the target interval effect within each region. Cluster membership
396
also is also shown. Statistical significance was evaluated using the family-wise error rate,
397
corrected for searching the whole brain.
398
399
Figure Captions
400
Figure 1. Illustration of brain areas showing increasing amplitude of the hemodynamic response
401
to target stimuli with longer target interval. The legend shows t-score value associated with
402
the color map. The statistical parametric map has a threshold of t99 = 4.55, corresponding to
403
p < .05 (familywise error rate, corrected for searching the whole brain).
404
Figure 2. Representative regions showing target interval effect in each cluster. 2A) The first
405
cluster shows relatively sharp increase in peak hemodynamic activity (x-axis) at
406
approximately 30 seconds by target interval (y-axis). 2B) The second cluster shows
407
relatively smooth linear increases in peak hemodynamic activity (x-axis) with increasing
408
target interval (y-axis). Lines represent mean across participants, bounded by standard error
409
of measurement. Non-depicted regions show similar profiles. All cluster memberships are
410
shown in Table 1.
411
412
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22
413
Table 1. Summary of reaction time
means and standard deviations for each
target-to-target interval.
Target Interval
Mean (SD)
(seconds)
8
429.2 (99.32)
10
406.7 (92.59)
12
394.1 (87.53)
16
423.1 (103.45)
18
419.7 (101.90)
20
406.5 (101.10)
24
416.1 (88.84)
28
423.0 (111.00)
30
461.5 (146.52)
32
426.3 (98.12)
38
449.7 (131.06)
40
431.9 (118.64)
42
414.3 (137.18)
54
423.6 (130.41)
68
439.8 (120.25)
414
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415
Table 2. Summary of the brain areas showing a significant positive linear relationship between target interval
and amplitude of hemodynamic response to target stimuli. Coordinates represent peak t-score for the target
interval effect within each region. Cluster membership also is shown. Statistical significance was evaluated
using the family-wise error rate, corrected for searching the whole brain.
Frontal Lobe
L Superior / Middle Frontal Gyrus
L Middle Frontal Gyrus
R Superior / Middle Frontal Gyrus
L Inferior Frontal Gyrus
R Inferior Frontal Gyrus
Medial Frontal Gyrus
Anterior Cingulate Gyrus
L Insula
R Insula
L Precentral Gyrus
L Precentral Gyrus
R Precentral Gyrus
Parietal Lobe
L Postcentral Gyrus
R Postcentral Gyrus
L Superior Parietal Lobule
R Superior Parietal Lobule
L Inferior Parietal / Supramarginal Gyrus
R Inferior Parietal / Supramarginal Gyrus
Posterior Cingulate Gyrus
Precuneus
Occipital Lobe
L Middle Temporal Gyrus
R Middle Temporal Gyrus
Occpital Lobe
L Lingual Gyrus / Cuneus
Other
L Thalamus
R Thalamus
R Putamen / Globus Pallidus
L Cerebellum
R Cerebellum
x
y
z
Target ×
target
interval
t-score
-24
-40
28
-52
56
0
-4
-48
48
-32
-36
28
48
36
48
4
12
8
12
16
20
-20
-28
-4
24
28
28
12
20
48
44
-8
-12
64
60
56
5.21**
5.24**
6.05***
4.91*
5.02**
7.71****
7.80****
7.26****
6.89****
8.30****
7.68****
5.82***
1.71
1.69
2.19
1.62
1.81
4.14
3.62
4.34
4.60
3.31
3.21
1.98
1
2
2
1
2
1
2
2
2
1
1
1
-60
56
-36
24
-64
60
0
-4
-24
-20
-40
-56
-32
-44
-40
-32
16
16
64
64
24
16
28
40
5.45**
6.79****
5.76***
4.85*
6.16***
5.14**
5.02**
5.68***
2.34
2.50
3.13
2.32
1.89
2.08
3.00
2.52
2
1
1
1
2
2
2
2
-56
56
-64
-28
0
-12
5.21**
5.28**
2.25
2.02
2
1
-4
-72
-8
5.05**
3.18
1
-8
0
32
-8
40
-20
-16
12
-84
-72
8
4
0
-20
-24
5.18**
6.31****
4.86*
6.26****
5.87***
2.44
3.03
1.57
5.19
4.38
2
1
2
1
1
*
Target
interval β
Cluster
p < .05, ** p < .01, *** p < .001, **** p < .0001 familywise error rate, corrected for searching the whole brain.
416
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24
417
418
419
420
421
422
423
424
Figure 1. Illustration of brain areas showing increasing amplitude of the hemodynamic response to target stimuli
with longer target interval. The legend shows t-score value associated with the color map. The statistical
parametric map has a low threshold of t99 = 4.55, corresponding to p < .05 (familywise error rate, corrected for
searching the whole brain).
Running head: fMRI Oddball target interval
25
425
426
427
428
429
430
431
432
Figure 2. Representative regions showing target interval effect in each cluster. 2A) The first cluster shows
relatively sharp increase in peak hemodynamic response amplitude (x-axis) at approximately 30 seconds by
target interval in seconds (y-axis). 2B) The second cluster shows relatively smooth linear increases in peak
hemodynamic response amplitude (x-axis) across target interval in seconds (y-axis). Lines represent mean
across participants, bounded by standard error of measurement. Non-depicted regions show similar profiles. All
cluster memberships are shown in Table 1.
Running head: fMRI Oddball target interval