Transcranial direct current stimulation of the anterior cingulate cortex impairs sustained attention
Michael Rojek Giffin Student Number: 10628924 Second Research Project 36 EC
Date of submission: 10 August 2015 Master of Brain and Cognitive Sciences University of Amsterdam
Supervisor: Dr. Ilja Sligte
Abstract
In the present study, we aimed to determine the efficacy of tDCS in enhancing sustained attention. Specifically, with a single-blind, sham-controlled, between-subjects design, we tested whether anodal stimulation of the right dorsolateral prefrontal cortex (DLPFC) or of the anterior cingulate cortex (ACC) could enhance performance on a sustained attention task. To our surprise, we found no significant effect of right DLPFC stimulation on sustained attention, and a significant negative impact on performance in the ACC condition after splitting our sample into high and low decrement groups. We conclude that anodal stimulation of the ACC causes a reduction of sustained attention, but only when the task is relatively taxing on a subject’s attentional resources.
Introduction
Vigilance, the ability to sustain attention over an extended period of time, is a requisite skill for myriad tasks in everyday life. Vigilance is associated with a predominantly right lateralized fronto-parietal network of brain structures comprised of, among other regions, the mid and anterior cingulate cortex (ACC), and the midlateral prefrontal cortex, including the dorsolateral prefrontal cortex (DLPFC) (Langner & Eickhoff, 2013; Lim et al., 2010; Sadaghiani et al., 2010). Performance on vigilance tasks typically declines as a function of time (see e.g., Corbetta et al., 2008; Pattyn et al., 2008), and this performance decline is associated with decreased activation in several nodes of the vigilant attention network (Kim et al., 2006; Langner & Eickhoff, 2013). Importantly, previous research has shown that this decrease in vigilance can be mitigated by exogenously stimulating some of these vigilance network nodes (Nelson et al., 2014; Weiss & Lavidor, 2012). One safe and noninvasive technique for the introduction of exogenous stimulation is transcranial direct current stimulation (tDCS).
tDCS is a method where two electrodes, a positively charged anode and a negatively charged cathode, are attached to the scalp. Electricity is then passed from the anode to the cathode, effectively depolarizing cortical neurons beneath the anode and hyperpolarizing cortical neurons beneath the cathode (Stagg & Nitsche, 2011). tDCS has been shown to enhance selective attention (Gladwin et al., 2012; Moos et al., 2012; Sparing et al., 2009; Weiss & Lavidor, 2012), orienting attention (Stone & Tesche, 2009), and, most importantly for the present study, sustained attention, or vigilance (Coffman et al., 2012; Kang et al., 2009; McIntire et al., 2014; Nelson et al., 2014). However, the results of these studies regarding tDCS for the enhancement of neural activity are somewhat unclear and in some cases inconsistent. For example, Kang et al. (2009) found that stimulation of the left DLPFC improved attention of patients with brain damage, but
that this same stimulation montage had no effect on healthy individuals. McIntire et al. (2009), on the other hand, found that stimulation of the left DLPFC did enhance sustained attention in healthy individuals. The findings of both these studies are particularly striking in light of the fact that sustained attention is associated with a right lateralized network, one node of which is the right DLPFC (Corbetta et al., 2008; Langner & Eickhoff, 2013; Lim et al., 2010; Sadaghiani et al., 2010). Therefore, the mechanisms through which left DLPFC stimulation enhances sustained attention are unclear. Based on the anatomy of the vigilance attention network, we would expect the benefits of tDCS to be most pronounced with a montage stimulating the right, not the left, DLPFC. To our knowledge, the only study attempting to enhance vigilance through stimulation of the right DLPFC comes from Nelson et al. (2014). However, for a number of reasons their findings are extremely difficult to interpret. For example, instead of placing the reference electrode on the contralateral supraorbital area, as is most commonly done when stimulating the DLPFC, they placed the reference electrode on the contralateral DLPFC. This resulted in a simultaneous up-regulation of one hemisphere and down-regulation of the other, making the mechanisms behind their results enigmatic at best. Moreover, in one condition there was a significant difference between active and sham stimulation in the pre-stimulation time-block. Therefore, this study, and all its conclusions, must be taken with caution.
Unanswered questions notwithstanding, there appears to be great potential for tDCS to enhance vigilance. To our knowledge, no previous study has attempted to stimulate the ACC in an attempt to affect sustained attention, and no study other than Nelson et al. (2014) has attempted to stimulate the right DLPFC in an attempt to affect sustained attention. By stimulating these regions, we sought to determine whether or not tDCS is an efficacious tool for enhancing sustained attention, as well as to elucidate more about the role played by the right DLPFC and the ACC in sustained attention.
Methods Subjects
60 right-handed subjects (22 female) with normal or corrected-to-normal vision were recruited from the University of Amsterdam online system. All subjects provided their written informed consent prior to the start of the experiment. Subjects were awarded €20 or 2 research credits for participating in the experiment. Exclusion criteria are presented in Appendix 1. Additionally subjects were asked to refrain from excessive drinking or drug use the day preceding as well as the day of the experiment. The study had been approved by the ethics committee of the Department of Psychology at the University of Amsterdam.
Task
The vigilance task used was a variation of the go/no-go task used in previous studies (Kim et al., 2006; MacLean et al., 2009). The task was designed and presented using Presentation software (www.neurobs.com). Subjects were asked to focus on a centrally located yellow fixation dot overlaid by a grey mask and respond to rarely presented (20%) target stimuli. On every trial, the mask disappeared for 150ms to reveal either the long distractor line or the short target line (see Figure 1). The length of the target line was determined by a variation of the Parameter Estimate by Sequential Testing (PEST) titration protocol (Taylor & Creeman, 1967). This method allowed us to mitigate the between-subject variance in performance by dynamically altering the task difficulty for each subject and resulting in an ~80% target detection accuracy at the start of the testing session. After line length had been established by PEST titration, subjects completed 60 minutes of the actual task, with a 1-minute break every 10 minutes in which they rated their motivation for and aversion to the task. For more information on task specifics, see Maclean et al. (2009).
Figure 1: Image of stimulus. This figure depicts two trials, one presenting the non-target stimulus, and
tDCS administration
Subjects were randomly assigned to one of three stimulation conditions: (1) 20 minutes of 1.0 mA anodal stimulation to the ACC (between Cz and FCz on the 10-20 international EEG system) with the reference electrodes attached to the right cheek bone, (2) 20 minutes of 1.0 mA anodal stimulation to the right DLPFC (position F4 on the 10-20 international EEG system) with the reference electrode attached to the contralateral supraorbital area or (3) 20 minutes of sham stimulation in the DLPFC configuration. Active electrodes were 3 x 3 cm, and reference electrodes were 5 x 7 cm. In the sham condition, stimulation was ramped up to 1.0 mA over 1 minute then turned off in order to induce the transient tingling and/or burning sensation associated with the initial onset of stimulation (Nitsche et al., 2008).
Procedure
Upon arrival participants filled out an informed consent and general health and lifestyle questionnaires that contained questions about their sleeping habits as well as habitual and recent caffeine intake. After all questionnaires had been filled subjects completed the instructions as well as a short (3-4 minutes) practice session. Subjects then completed the PEST titration (see Methods/Task). After completion of the PEST titration, tDCS electrodes were attached in one of two montages: DLPFC or ACC (see Methods/tDCS administration). Following attachment of electrodes, 1 minute of 1.0 mA sample-stimulation was applied (with a 1-minute ramp up) in order to get subjects familiar with the sensation of tDCS. Subjects were asked if they felt any pain, and were informed that if they experienced a strong aversion to the sensations induced by tDCS they were free to leave the experiment. Subjects then completed the actual task. After subjects completed the task, they were questioned about their mood and asked about any adverse effects from the stimulation. They were then asked to remain in the building for at least 30 minutes, after which point they were free to leave.
Data analysis
We used custom-written Matlab (The Mathworks Inc.) and R (R Core Team, 2013) scripts for the data analysis. In order to compute A’ and ßD” we used a custom-written Matlab function
implementing the mathematical formula presented in Stanislaw and Todorov (1999) for A’ and the mathematical formula presented in See et al. (1997) for ßD”. Additionally, in Matlab we used
the Shape Language Modeling (SLM) package (D’Errico, 2009) for fitting our A’ data to functions in order to eliminate outliers (see below for expansion on this). In R we used the EZ
package (Lawrence, 2013) for type III ANOVAs, and the Cocor package (Diedenhofen, 2015) in order to compare different correlations against one another.
Outliers were identified by the following procedure: we broke each subject’s data into 6 contiguous 10-minute time-blocks and fit a polynomial function to their A’ using the SLM Matlab toolbox (D’Errico, 2009). If the standard error (SE) for a subject’s fit was more than 3 standard deviations (SD’s) from the mean SE of all subjects then that subject was labeled as an outlier and removed from further analysis. This technique revealed one outlier, who was subsequently removed from analysis and replaced with a new subject. Analyses were performed on 3 contiguous time-blocks of 600 trials. As in previous sustained attention research (MacLean et al., 2010; Nelson et al., 2014), our most important dependent variable was the non-parametric measure of perceptual sensitivity A’ (Stanaslaw & Todorov, 1999). Based on our hypotheses, we predicted a significant interaction effect between time and condition. We also examined the following dependent variables: non-parametric measure of response bias ßD” (MacLean et al.,
2010; See et al., 1995), hit-rate, and reaction time (RT). Each dependent variable was baseline corrected by dividing each time-block by time-block 1, and subsequently tested with a 3 x 3 split-plot ANOVA with time (time-blocks 1, 2, and 3) as the within-subject independent variable and condition (ACC, DLPFC, sham) as the between subjects independent variable. Greenhouse-Geisser corrections were performed when assumptions of sphericity were violated. Post-hoc analyses consisted of two-sample Welch t-tests; unless otherwise stated, both uncorrected and Bonferroni corrected p-values are reported. Additionally, we performed an exploratory median split on decline in A’ during the pre-stimulation time-block (the first 20-minute time-block). Specifically, we split each subject’s data into 6 contiguous 10-minute time-blocks, and subtracted their second time-block A’ from their first time-block A’. This provided us with an index of each subject’s pre-stimulation performance decline. We then took the median of this index across all subjects, regardless of condition, in order to create high-decrement and low-decrement groups. We then performed a split-plot ANOVA with A’ entered as the dependent variable, and time, condition, and group (high or low decrement) entered as the independent variables. We subsequently performed 3 x 3 split-plot ANOVA’s in both the high and low decrement groups with A’ entered as the dependent variable and time and condition entered as the independent variables.
Results
Some subjects did report discomfort, tingling, muscle contractions, and headache during stimulation, but these effects faded immediately after cessation of stimulation. There was no significant difference between reports of adverse side effects to stimulation except for muscle contractions, in which subjects in the sham condition reported significantly higher levels of muscle contractions than ACC and DLPFC (F(2,177)=9.91, p<0.0001; mean±SD: ACC=1.10±0.30, DLPFC=1.20±0.51, SHAM=1.55±0.81). Since it is impossible for sham stimulation to cause muscle contractions, we suspect this is simply a false positive.
Our PEST titration procedure resulted in a mean hit-rate of 77% within the first 10-minute time-block. There was no significant difference between groups in the pre-stimulation time-block when looking at A’, hit-rate, or ßD” (all p’s>0.05). Our first split-plot ANOVA
revealed a significant main effect of time on A’ (F(2,114)=33.37, p<0.0001), but no main effect of condition (F(2,57)=1.05, p=0.36) and no time X condition interaction (F(4,114)=1.33, p=0.27, see Figure 2). Therefore, subjects experienced a decline in perceptual sensitivity as a function of time, but there was no difference between conditions, nor was there a difference in the extent to which the different conditions declined over time. The same was true for hit-rate: we found a significant main effect of time (F(2,114)=34.86, p<0.0001), but no main effect of condition (F(2,57)=0.28, p=0.75) and no time X condition interaction (F(4,114)=1.39, p=0.24). Neither time, condition, nor the interaction of the two exerted significant effects on ßD” (time:
F(2,114)=1.33, p=0.27; condition: F(2,57)=0.63, p=0.54; time X condition: F(4,114)=0.71, p=0.52). RT significantly increased as a function of time (F(2,114)=5.54, p=0.009), but there was no main effect of condition (F(2,57)=1.20, p=0.31) nor a time X condition interaction (F(4,114)=1.00, p=0.41).
Clearly, none of our analyses provided evidence in favor of our original hypotheses. In fact, the effect stimulation exerted on performance trended in the opposite direction of our predictions. We decided to perform exploratory analyses in order to see if these trends opposite to our predictions were in fact real effects caused by stimulation. If stimulation was having a detrimental effect on sustained attention, then we reasoned that this effect may be more pronounced in some individuals based on the following rationale: some individuals may not have found the task challenging enough and therefore were not recruiting the vigilance attention network to the extent to which stimulation could interfere with its operation. To explore this possibility further, we performed a median split on the data in order to separately test individuals who, prior to stimulation, experienced a high performance decrement or a low performance decrement (See Methods/Data analysis for more on how these median splits were performed).
Figure 2: Line plots depicting changes in baseline corrected A’ change across the 3 time-blocks.
Stimulation was administered during time-block 2. A, Decline in A’ within entire sample (n=60): no significant time X condition interaction. B, Decline in A’ in group which exhibited low pre-stimulation A’ decrement (n=30): no significant time X condition interaction. C, Decline in A’ in group which exhibited high pre-stimulation A’ decrement (n=30): significant time X condition interaction.
1 2 3 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1
A’ of all three conditions in low decrement group across time−blocks
Time−blocks (20 minute blocks)
A’ ACC DLPFC SHAM 1 2 3 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1
A’ of all three conditions in high decrement group across time−blocks
Time−blocks (20 minute blocks)
A’ ACC DLPFC SHAM
C
AB
1 2 3 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1A’ of all three conditions across time−blocks
Time−blocks (20 minute blocks)
A’
ACC DLPFC SHAM
A
Our median split resulted in 2 groups of 30 participants: high-decrement (ACC: n=11, DLPFC: n=9, sham: n=10) and low-decrement (ACC: n=9, DLPFC: n=11, sham: n=10). A split-plot ANOVA with A’ entered as the dependent variable and time, condition, and group (high or low decrement) entered as the independent variables revealed a significant three-way interaction between time, condition, and group (F(4,108)=2.81, p=0.03). The high-decrement group exhibited a significant time X condition interaction (F(4,54)=2.90, p=0.03), while the low-decrement group did not (F(4,54)=0.95, p=0.43; see Figure 2). This finding provided evidence in favor of our rationale for performing this exploratory test. Post-hoc t-tests revealed that the bulk of this significance in the high-decrement group was driven by a stark difference between the ACC and the sham condition in the last time-block (ACC: mean=0.95±0.03, sham: mean=0.99±0.03, t(18.99)=3.49, p=0.002, uncorrected, p=0.015, Bonferroni-corrected for 6 post-hoc comparisons). There was no significant difference between any other combination of conditions at time-block 2 (ACC vs. DLPFC: t(11.32)=-0.76, p=0.46; DLPFC vs. sham: t(14.45)=-0.05, p=0.96; ACC vs. SHAM: t(15.97)=1.09, p=0.29; all uncorrected) or time-block 3 (ACC vs. DLPFC: t(14.90)=-1.49, p=0.16; DLPFC vs. sham: t(13.97)=-1.27, p=0.22; all uncorrected). We furthermore correlated pre-stimulation A’ decrement with overall A’ decrement (time-block 1 A’ – time-block 3 A’) in each condition and found that pre-stimulation A’ decrement only predicted overall A’ decrement in the ACC condition (r=0.48, p=0.03). Pre-stimulation decrement did not significantly correlate with overall decrement in either the DLPFC (r=-0.07, p=0.77) or the sham (r=-0.25, p=0.28) conditions (see Figure 3). Furthermore, using the Cocor package in R (Diedenhofen, 2015), we compared the extent to which this correlation differed between the different groups. The ACC and sham conditions differed significantly in the extent to which pre-stimulation decline predicted overall decline (z=2.27, p=0.023), however ACC differed only marginally from DLPFC (z=1.73, p=0.08), and DLPFC did not differ significantly from sham (z=0.54, p=0.59). Taken together these results indicate that severity of vigilance decline predicts susceptibility to ACC stimulation, and that these effects are only evident after cessation of stimulation.
Figure 3: Correlations between pre-stimulation A’ decrement and overall A’ decrement in all three conditions. A, Significant correlation between pre-stimulation A’ decrement and overall A’ decrement in
ACC condition. B, No significant correlation between pre-stimulation A’ decrement and overall A’ decrement in DLPFC condition. C, No significant correlation between pre-stimulation A’ decrement and overall A’ decrement in sham condition.
−0.1 −0.05 0 0.05 0.1 0.15 −0.01 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08
Pre−stimulation A’ decrement (first 20 minutes)
Overall A’ decrement
DLPFC pre−stimulation decrement and overall decrement
r=−0.07 p=0.77 0 0.02 0.04 0.06 0.08 0.1 0.12 −0.04 −0.02 0 0.02 0.04 0.06 0.08 0.1
Pre−stimulation A’ decrement (first 20 minutes)
Overall A’ decrement
ACC pre−stimulation decrement and overall decrement
r=0.48 p=0.03 −0.06 −0.04 −0.02 0 0.02 0.04 0.06 0.08 −0.04 −0.02 0 0.02 0.04 0.06 0.08 0.1
Pre−stimulation A’ decrement (first 20 minutes)
Overall A’ decrement
Sham pre−stimulation decrement and overall decrement
r=−0.25 p=0.28
A
B
Discussion
Our study provides evidence that tDCS applied to the ACC has detrimental effects on sustained attention. Using a validated sustained attention paradigm (MacLean et al., 2009) and a sham-controlled, between-subjects design, we showed that individuals who experience an early decline in vigilance, when subjected to anodal stimulation of the ACC, exhibited significantly lower levels of perceptual sensitivity (A’) than individuals receiving sham stimulation (see Figure 2). Importantly, these effects were only present after cessation of stimulation, and were absent in subjects undergoing anodal stimulation of the right DLPFC.
Based on the findings of previous studies (McIntire et al., 2014; Nelson et al., 2014), as well as the anatomy of the sustained attention network, (Corbetta et al., 2008; Helton et al., 2010; Langner & Eickhoff, 2013), we expected a substantial increase in vigilance as a result of anodal stimulation of the right DLPFC as well as the ACC. Surprisingly, we found that, when differentiating subjects into high and low pre-stimulation decrement groups, performance in the right DLPFC condition did not differ significantly from sham, and performance in the ACC condition was significantly worse than performance in sham – but only in the high-decrement group. Therefore, contrary to our predictions, we found no effect in the DLPFC condition, and an effect opposite to that of our prediction in the ACC condition.
Due to differences in cortical folding patterns of our subjects, as well as the position of our reference electrodes, it is possible that we were more consistently able to locate and stimulate the ACC than the DLPFC. There is considerable variety between individuals in terms of cortical convolution patterns as well as skull thickness, and this can lead to difficulties in proper brain region localization as well as differences in responsiveness to tDCS (Kim et al., 2014). It could be the case that our electrodes positioned at F4 and the contralateral supraorbital area did not actually alter cortical activity in the right DLPFC. However, the electrode montage we employed is extremely similar to that used in many previous studies that did show significant results (e.g., Bai et al., 2014; Boggio et al., 2007; Fregni et al., 2005). Therefore, a more likely explanation is simply that sustained attention is not affected by tDCS of the right DLPFC. Further research is certainly needed to explore and explain this finding.
In the ACC condition, only individuals who experienced a relatively pronounced pre-stimulation A’ decline responded to pre-stimulation. In other words, only those subjects who performed worse as a function of time were susceptible to the effects of tDCS. We interpret this finding thusly: individuals who experienced a relatively small performance decline did not find the task difficult and were not recruiting the vigilance attention network to the extent to which tDCS could modulate it’s functioning.
Furthermore, the detrimental effects of ACC stimulation were only present in the post-stimulation time-block, after the electrodes had been removed from each subject in each condition. This means that the differences in performance in this time-block cannot be attributed to the potentially distracting sensation of stimulation, but instead can be attributed to the offline effects of tDCS. Perfusion fMRI studies have shown that cerebral blood flow increases in the right middle frontal gyrus as well as the cingulate cortex in response to sustained attention tasks, and that decreases in blood flow in these regions correlate with performance decline (Kim et al., 2006; Lim et al., 2010). A recent study combining left DLPFC tDCS with perfusion fMRI showed that, after cessation of stimulation, the frontal cortex exhibited a significant decrease in cerebral blood flow (Stagg et al., 2013). It is possible that participants in our ACC condition experienced a significant reduction in blood flow in the cingulate cortex following stimulation which coincided with their reduced performances. Admittedly, although this explanation accounts for the effect observed in the ACC condition, it cannot account for the lack of an effect observed in the DLPFC condition. In order to elucidate the mechanisms behind our results, the present design should be combined with perfusion fMRI in the future.
Another avenue of future research that could help to elucidate the role of the ACC in sustained attention would be to combine our sustained attention task with different stimulation protocols of the ACC. One such protocol should be cathodal stimulation. If anodal stimulation leads to a decrease in performance, it is possible that stimulation with the opposite polarity will lead to an increase in performance. However, previous research has shown that perfusion following both anodal and cathodal stimulation leads to a reduction in perfusion (Stagg et al., 2013). Therefore, if cathodal stimulation does lead to a reduction in sustained attention akin to that which we observed in the anodal ACC condition, then we could reasonably conclude that reduced perfusion is at the root of this decline. On the other hand, if cathodal stimulation leads to an increase in sustained attention, we would be forced to grope for alternative explanations. Theta tACS is another stimulation protocol that could enhance sustained attention. Previous research has shown that theta oscillations in frontomedial regions, including the ACC, are linked to sustained attention (Clayton et al., 2015). If we were to administer alternating current within the theta band, it is possible that we could induce an oscillatory signature that facilitates sustained attention.
Conclusions
Anodal tDCS applied to the ACC (between Cz and FCz on the 10-20 international EEG system) causes a reduction in sustained attention in individuals who exhibit a pronounced early decline in
vigilance. In other words, individuals who struggle to maintain attention are susceptible to detrimental performance modulation via anodal tDCS of the ACC.
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Appendix 1: Exclusion Criteria Questionnaire
1. Do you have epilepsy, or have you ever had an epileptic insult or absence? Yes / No
2. Does epilepsy occur in your family? Yes / No
3. Do you have any other neurological disorder? Yes / No
4. Have you ever had a stroke? Yes / No
5. Do you have brain damage as a result of brain surgery, a severe head injury or a disease?
Yes / No
6. Have you ever had a severe stroke2? Yes / No
7. Have you ever had a disease of the brains, such as meningitis? Yes / No
8. Are you currently using psychotropic drugs (e.g. antidepressants)? Yes / No 9. Do you have a pacemaker or other implanted device? Yes / No 10. Do you have any metal or metal splinters in your head? Yes / No
11. Are you albino? Yes / No
12. Are you pregnant? Yes / No
13. Have you recently fainted or have you had a panic attack? Yes / No
14. Do you have multiple sclerosis? Yes / No
15. Do you often suffer from dizzines or headaches? Yes / No
16. Do you have any skin disorders, e.g. eczema? Yes / No
