The Effects of Transcranial Direct Current
Stimulation of the Dorsolateral Prefrontal Cortex
on Visual Working Memory
Iris de Vries 10367675 Bachelor thesis
Faculty of Social and Behavioral Sciences, Department of Psychology Thesis Advisors: Dr. I. G. Sligte, A. Laufer MSc
Abstract
Even though we experience a rich and continuous image of the world around us, research on visual working memory has taught us that its capacity is limited. Yet, we rely on it everyday. Therefore, it was investigated whether applying tDCS to the right DLPFC would enhance visual working memory capacity by stimulating sixteen participants when they performed a change detection task. It was expected that
performance would increase during tDCS. This study was performed counterbalanced, double blind and placebo controlled by using a sham session. No differences were found between tDCS and sham stimulation. This finding is in contrast with literature on the role of the DLPFC in working memory and the literature on the effects of tDCS. The study did reveal a placebo effect during the sham session, but not during the tDCS session. This finding emphasizes the importance of double blind placebo testing in brain stimulation studies. For now, there seems to be no proof that tDCS enhances visual working memory when stimulating the DLPFC. Replication needs to be done to clarify current findings about the effects of tDCS on visual working memory.
The Effects of Transcranial Direct Current Stimulation of the Dorsolateral Prefrontal Cortex on Visual Working Memory
The environment presents a broad scope of visual information. The visual working memory system is responsible for holding this information active for a short period of time and for the processing of the visually incoming information (Miller, Erickson, & Desimone, 1996; Vogel, & Machizawa, 2004). Visual working memory is helpful in situations in which one quickly want to compare objects in the visual environment, for example to detect changes. Studies have shown that visual working memory predicts fluid intelligence and educational successes (Cowan et al., 2005). Additionally, it is used during highly demanding visual tasks such as military missions (Coffman, Clark, & Parasuraman, 2014).
Even though we experience a rich and continuous image of the world around us, research on visual working memory has taught us that its capacity is limited to about three to four items, and the representation is certainly not flawless (Todd & Marois, 2004; Rensink, 2002; Simons, & Levin, 1997). Research efforts have also been directed at finding the brain areas that underlie these processes.
Indeed, visual working memory is supported by a network of high-level brain regions. This is supported by functional neuroimaging studies in humans (Courtney et al., 1997; Smith and Jonides, 1999). Many areas are found to be part of this network, for example, areas in the dorsolateral and ventrolateral prefrontal cortex (DLPFC, VLPFC), the superior, inferior parietal lobule (SPL, IPL) and the pre-SMA (Linden et al, 2003). On top of that, research has shown that the DLPFC remains active during the delays of visual working memory tasks (Curtis & D’Esposito, 2003) and that lesions in this region impair performance on working memory tasks. These findings make the DLPFC stand out from other regions as regards visual working memory.
Interestingly, transcranial magnetic stimulation (TMS) studies showed that stimulating the right DLPFC during a working memory task negatively influences
working memory capacity (Oliveri et al., 2001; Turatto, Sandrini, & Miniussi, 2004). TMS utilizes an electric coil that uses rapidly changing magnetic fields to induce small
electrical currents in the brain. The use of TMS makes it possible to induce a “virtual lesion”. The negative influence of TMS on visual working memory due to the distortion of the right DLPFC gives rise to the question of whether it is possible to enhance visual working memory by positively stimulating this brain area.
A typical task to measure visual working memory performance is the change detection task (Luck & Vogel, 2013). A set of items is presented for retention. Subjects have to determine whether a probe item belonged to the retention set. Performance on this task indicates visual working memory capacity.
In this paper it is investigated whether applying positive stimulation to the right DLPFC will enhance performance on a change detection task. An often used brain stimulation method is transcranial direct current stimulation (tDCS). Previous tDCS studies already showed effects on regular working memory, making it an excellent candidate (Fregini et al., 2005). It uses constant, low current and it is delivered to the brain via electrodes placed directly on the scalp. Positive polarization (anodal) induces excitation of the underlying cortex area, while negative polarization (cathodal) induces inhibition. Because studies concerning tDCS showed sustained effects of tDCS on the brain after the stimulation itself (Wirth et al., 2011), an exploratory analysis was done on the performance on the change detection task a period after stimulation. By applying anodal stimulation to the right DLPFC it is expected that performance on a change detection task will increase, with possible offline effects after stimulation. We expected
no differences in performance on the change detection task when they were sham stimulated.
Method Participants
Eighteen subjects participated in the experiment. Two subjects dropped out of the experiment due to planning difficulties. This resulted in 16 participants completing the experiment. Five of which were male and 11 of which were female with the mean age of 20 years (SD = 1.79). The participants were recruited using convenience sampling. Participants were selected based on a list of exclusion criteria. The main criteria were: a personal or family history of epilepsy (because of the risk of an epileptic event caused by tDCS), left-handedness (because of lateralization differences between left-handed and right-handed people), a history of migraine or heavy headaches and dizziness, and neurological disorders (tDCS might worsen the symptoms), and bad vision or color blindness. Participation was not possible if any of the exclusion criteria were met. No financial reward was given and they could be rewarded with a psychology research credit per hour of participation.
Materials
The task in this experiment was based on a classic change detection task. A schematic display of the task is show in figure 1. In this experiment, eight rectangles were placed on the screen in a way that they formed a circle around a fixation cross. The goal was to determine if the orientation of the probe rectangle had changed. The
rectangles (25 x 100 pixels) were black and placed on a background of light grey. Only 15% of the screen size was used for the radius size. The first rectangle was placed at position 0 on the unit circle. They differed in their orientation in a way that it wasn’t possible for one orientation to occur more than three times. The possible angles of the rectangles were: 0◦, 45◦, 90◦, and 135◦. Rectangles were randomly chosen to reappear as probe. There was a 0.5 change the probe changed orientation (i.e. changed 90◦). In total, there were three sessions containing three blocks of 20 minutes. Each block consisted of 160 trials. One trial took 5750 ms in total. At the start of the trial, the black fixation cross (20 x 4 pixels) in the middle of the screen was visible for 1000 ms. Five hundred ms before the memory array appeared, the cross turned green. The memory array was
displayed for 250 ms followed by the probe rectangle. The probe was visible for 3000 ms during which participants had to decide whether they thought the probe had
changed orientation. The z key indicated no change and the m key indicated change. To prevent confusion, the z key was marked with a red sticker and the m key was marked with a green sticker. When not pressing z or m, the trial was saved as a missed trial. Correctly answered trials were indicated by a short sound. This to inform participants of their performance.
Figure 1. The change detection task schematically displayed with the duration of each part
between brackets.
Sham Condition Versus Experimental Condition
In the experimental condition (tDCS), an anode (9 cm2) was placed on area F4 of the right DLPFC. A cathode (25 cm2) was placed on the left part of the forehead. During the second and the third session, direct current of 1 mA was sent through the scalp for 20 minutes during the second block. Conductivity was enhanced by a salt solution. In the sham condition, the anode and the cathode were placed on the head in the same way. After a normal ramp-up period of 60s, the current was turned off until the end of the experiment when it was turned back on again, 60s before the ending of the second block.
Procedure
The selected participants were sent the information brochure to inform them about the experiment beforehand. They were called to make three appointments with at least 72 hours between each session. The first session was a training session of one hour. The next two sessions were experimental sessions. In the training session, participants were first provided with information about the experiment and the
informed consent. The rest of the hour, participants had the chance to get familiar with tDCS and the change detection task itself. If they decided not to continue with the
experiment, they were deleted from the sample and excluded from further participation. The next sessions, participants underwent both tDCS (experimental condition) and sham stimulation (sham condition). In order to control for experimenter effects, the experiment was double blind. The tDCS device had two settings: A and B. The
experimenters did not know which setting was the tDCS condition. During the first experimental session, the tDCS device was randomly set on A or B. The second experimental session the opposite setting was used.
Each experimental session took approximately 1 hour. The experiment consisted of three blocks (20 minutes each) with 160 change detection trials per block with a break of 90s every 5 minutes. Between the three blocks, there was an additional break of 90s. The first block During the second block, tDCS or sham stimulation was delivered. Stimulation was turned off during the third block. After each experimental session, the participant could choose to be brought home by one of the experimenters.
After the last experimental session, participants were provided with the debriefing and they were told that they could ask questions if desired.
Analysis
The data were loaded and altered in MATLAB 2014. Mean performances were calculated for each participant on each block of each session. For participant 4, the last block of the first session missed because it wasn’t stored properly. The missing block and all other missed trials and responses in de data were replaced by the build-in function Not-a-Number (NaN). In this way, these data were excluded form analysis. The statistical analysis was done in IBM SPSS 23. To test for sphericity, Mauchly’s Test of Sphericity was performed. It indicated that the assumption of sphericity had not been violated, χ2(0) = 0.000, p = ., χ2(2) = 0.065, p = .968, χ2(2) = 1.665, p = .435. Within each session, a check for outliers has been done. If a participants’ performance differed more than three standard deviations from the mean, the participant was excluded from the sample. No participants were deleted.
tDCS or sham was applied on the DLPFC of 16 participants while participants were performing a change detection task. In Table 1, the mean scores and the standard deviation of the change detection tasks for the different blocks and sessions are
displayed. First, it was investigated whether there was an effect of tDCS and time on the performance of the change detection task. Based on the literature, it was expected that participants would perform better when tDCS was applied. No differences should be detected when they were sham stimulated. In order to test this, a repeated measures ANOVA was performed to look for interaction and main effects. The ANOVA was
performed on the mean scores per participant per session per block; with time over one session (three levels) and stimulation (two levels) as within-subject variables. The interaction between time and stimulation was not significant, F(2, 30) = 0.534 , p = .591. This indicated that there was no effect of tDCS and time on the performance of the change detection task. These results are not in line with the hypothesis that stimulation of the DLPFC would improve visual working memory. Figure 2a shows the graph with the expected outcome and Figure 2b shows the graph of the actual data.
Figure 2a. The expected performance Figure 2b. The actual performance on
on the change detection task in the the change detection task in the tDCS tDCS and the sham condition. And the sham condition
To investigate the effect of stimulation compared to baseline, the main effects of the repeated measures ANOVA for stimulation were interpreted. No main effect was found, F(1, 15) = 0.782, p = .390. This result indicates that there are no effects of stimulation on performance.
To investigate the effect of time, the main effects of the repeated measures ANOVA for time were interpreted. There was a significant main effect found for time over one session, F(2, 30) = 5.52, p = .009. This result indicates that there is an effect of time on task performance.
To check whether these results could be attributed to learning effects, two t-tests were performed. When comparing the last block of the first session with the first block of the sham and tDCS trial, no significant difference was found t(14) = -0.28, p = .978 and t(14) = -0.160, p = .875 respectively. These non-significant results indicate that the improvements could not be attributed to learning effects between the sessions.
To find out what these results could be attributed to, t-tests on the first and second block of both tDCS and sham were performed. By comparing the first block, during which the tDCS apparatus was not turned on, and the second block, during which the tDCS apparatus was switched on, it is investigated whether there might have been a placebo effect. Only the sham condition gave a significant result when comparing the first and the second block with a paired samples t-test, t(15) = -2.557, p = .022. There was no significant difference found between the first and the second block in the tDCS condition, t(15) = -1.772, p = .097. This means that the performance during tDCS did not increase significantly. Ironically, the performance in the sham condition increased during the session, indicating a placebo effect.
Also, it was hypothesized that tDCS could cause offline effects after stimulation itself. The effects were to be looked at exploratory, but since it is found that there is no effect of stimulation on the change detection task, it does not seem relevant to look at post-stimulation effects in this article.
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Training session tDCS Sham
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Block 1 .60 (0.055) .64 (0.055) .64(0.079)
Block 2 .61 (0.072) .67 (0.092) .69(0.090)
Block 3 .64 (0.084) .67 (0.096) .67(0.076)
Table 1. The mean scores and the SD (between brackets) of the change detection tasks for the
different blocks and sessions are displayed.
Conclusion and Discussion
The aim of this study was to investigate whether applying tDCS to the right DLPFC would enhance visual working memory capacity. The following two major findings and implications are going to be discussed in this section: (1) in contrast to the expectation that participants would perform better when tDCS was applied, it was found that this was not the case and that tDCS did not enhance visual working memory
capacity, and (2) it was found that participants showed a significant increase in
performance during the sham stimulation compared to the baseline, indicating a placebo effect. Because of the irrelevance, explained in the results section, of the exploratory research on offline effects, it was not further looked at.
In contrast to the expectation that participants would perform better when tDCS was applied, it was found that this was not the case and that tDCS did not enhance visual working memory capacity. The choice of using tDCS on the DLPFC was mainly based on research concerning TMS. In these studies, creating a ‘virtual lesion’ by applying TMS to the DLPFC induced a decrease in visual working memory performance (Oliveri et al., 2001; Turatto, Sandrini, & Miniussi, 2004). It was expected that the capacity would increase when trying to achieve the opposite of a ‘virtual lesion’ by using tDCS. These contradicting findings might be due to a couple of possible factors. First, there might be an unchangeable limit of visual working memory that cannot be exceeded in any way. The fact that the capacity can be decreased does not necessarily mean that it can also be increased. Another issue that needs to be considered is the fact that the task was quite monotonous, long-winded and difficult and required constant fast reactions. Much attention was needed to answer trials correctly. It may be that the task did not measure visual working memory, but did in fact measure attention. In that case, stimulating the DLPFC might not enhance the task performance because the DLPFC is not involved in attention processes in the brain. Lastly, even though the choice of stimulating the DLPFC is supported by a large body of research, the DLPFC might just not be the right location to stimulate. These are only speculations and further research needs to be done on the location that corresponds with visual working memory. Also, even if the DLPFC is the right area to stimulate, in this experiment, the localization of f4 on the DLPFC was
somewhat arbitrarily done. If the localization were done perfectly, the stimulation might have ‘hit’ the DLPFC better.
Interestingly, it was found that participants showed a significant increase in performance during the sham stimulation compared to the baseline, indicating a placebo effect. This placebo effect might be due to the mere presence of the tDCS apparatus. The idea of the stimulation and the expected effects of such a thing might have increased the performance. This effect only appeared at the sham condition, but it is possible that with a bigger sample size the effect would have been significant for the tDCS condition too. The sample size was not quite large. We aimed for about 25 participants, ending up with only 16. Another reason for this result could be that the stimulation caused distraction at the highly demanding task. Many participants complained about mild pain or
itchiness. These issues continued for the full 20 minutes of stimulation. Even though it is usual to accommodate a little to it, it is very different from the feelings that are caused by the sham stimulation. It needs to be kept in mind that a significant effect of tDCS would not indicate that tDCS is better than sham stimulation. It would suggest that it doesn’t matter for the performance on a change detection task whether you apply tDCS or sham.
An important lesson that can be learned from this study is that it is necessary to control for placebo effects in brain stimulation studies too. Because of the seemingly ‘hard’ method of the brain stimulation, it is often neglected, forgotten or simply thought of as redundant to use a placebo condition in brain stimulation research. The article of Horvath, Forte, & Carter (2015) includes a huge body of brain stimulation research. Throughout the whole article, it becomes clear how many of the included research lacks a proper design. Often, sham conditions are not included and the experiment is not set up double blind. For example, the authors stated that “the lack of sham controlled, double-blind (…) TMS studies are somewhat alarming”. In their study they tested a large body of brain stimulation research and came to the conclusion that only 18 of the 106 TMS studies included in the analysis used a sham condition. Additionally, only 7 of the 106 studies used a double blind design. In addition to the previous article, another study revealed that only 87.5% of the tDCS studies examining foundational claims on which the modern tDCS field is built*, used a proper control condition (Horvath, Carter, & Forte, 2014). In the future, stricter guidelines should available on the use of sham
set-up contribute to the framework of literature, possibly causing a distorted view of reality. This might result in hypotheses based on that view. To prevent the confusion of placebo effects with actual effects, it is critical to set up experiments that are focused purely on the placebo effects in brain stimulation studies. In an experiment like this, participants sign up for a brain stimulation study. In fact, they are not stimulated at all. Preferably, the experimenters are not aware of this, so the study is performed double blind.
This study showed that the use of tDCS to enhance visual working memory isn’t straightforward. Further research on the effects of tDCS of the right DLPFC on visual working memory should at least focus on a bigger sample size and accurately
determining F4 on the DLPFC. Most importantly, it should be double blind and placebo controlled. No matter how straightforward the instrument and literature seems, never underestimate the power of suggestion. For now, there seems to be no proof that tDCS enhances visual working memory when stimulating the DLPFC. Replication needs to be done to clarify current findings about the effects of tDCS on visual working memory.
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