Transcranial Direct Current Stimulation (tDCS)/Transcranial Alternating Current Stimulation (tACS)Original ArticleQuantitative Review Finds No Evidence of Cognitive Effects in Healthy Populations From Single-session Transcranial Direct Current Stimulation (tDCS)
Introduction
Since its modern resurgence at the turn of the century, transcranial direct current stimulation (tDCS) – a noninvasive neuromodulatory device – has been steadily growing in popularity within both the academic and clinical research sectors. Current theory suggests that tDCS, via time-dependent and polarity specific modulation of neuronal firing patterns, can markedly and predictably enhance a number of higher-order cognitions and behaviors. However, a recent systematic review of the neurophysiologic literature undertaken by this group [1] questions the reliability and significance of tDCS effects on all but one neurophysiologic measure tested. Here, we undertake a quantitative review of the cognition literature to determine if tDCS shows a reliable effect on any cognitive tasks.
tDCS is most commonly delivered via 2 electrodes – 1 anode and 1 cathode – affixed to the scalp overlying cortical regions relevant to the outcome measure of interest [2]. It is believed that passing a weak electric current (typically 0.5–2.0 mA) between these two electrodes modulates neuronal firing patterns in the cortical regions underlying the electrodes via two mechanisms of actions. The first occurs during stimulation and involves ionic concentration shifts within the extracellular fluid which serve to modulate neuronal resting membrane potentials thereby hypo- and hyper-polarizing neurons underlying the anode and cathode, respectively [3]. The second occurs following long duration (>7 min) stimulation and involves long-term potentiation and depression-like mechanisms at the synaptic level thereby effecting hyper- and hypo-communicative activity in neurons underlying the anode and cathode, respectively [3]. To account for these different mechanisms, in this paper we divide studies according to whether the outcome measures were obtained during stimulation (online protocols) or following stimulation (offline protocols).
The poolable cognitive tasks in the literature can be grouped into 4 broad categories: executive functions, language, memory, and miscellaneous. Accordingly, the methods and results sections will be structured around these domains. To be included in this review, the effects of tDCS on a given task must have been explored by at least two different research groups using a comparable tDCS protocol. A full list of studies that assessed the relevant aspects of cognitive function but did not meet these inclusion criteria can be found in Supplemental Material (Fig. S1; Table S3). Each poolable outcome measure that satisfied our inclusion criteria is introduced briefly below.
Executive functions (EFs) are often regarded as a coordinated set of cognitive processes which allow an individual to override more instinctual or automatic responses in order to achieve a specified goal [4]. The following three EF measures met inclusion criteria for this review.
Individuals must determine which target/s amongst a series of targets are “correct” based on an unspecified rule-set via arbitrarily guessing (e.g. – red fruit amongst a series of food-based images). Occasionally, and without warning or explication, the rule-set will change (e.g. – round vegetables amongst a series of food-based images). Improved performance on this task is reflected by a reduction in the time taken to notice this change, abandon the prior rule-set, and learn the new rule-set [5].
Individuals are repeatedly presented with a target (e.g. – a visual circle) and asked to respond as quickly as possible each time it appears. Occasionally, however, the target will be paired with a secondary stimulus (e.g. – an auditory beep); in this instance, the individual should not respond to the target. This task is a measure of automatic response inhibition [6].
Individuals are presented with stimuli which contain multiple, uniquely processed dimensions (e.g. – the word ‘red’ written in a green colored font), of which the individual must respond to only one. The speed which with a person can accurately respond is a measure of selective attention and goal maintenance [7].
Linguistic-based cognitive tasks utilize language production speed and accuracy to explore the psychological and neurobiological factors that enable humans to produce and comprehend speech [8]. The following three language measures met inclusion criteria for this review.
Individuals are presented with paired images and pseudo-words or words from an unfamiliar language and must learn the pairing of the two. The accuracy with which one can respond to correctly- or incorrectly-joined pairs is thought to be a measure of linguistic learning [9].
Individuals are presented with a series of images (either simple line drawings or photos) and asked to name them as quickly as possible. The time taken to accurately name each object is a measure of lexical access, or ‘word-finding ability’ [10].
Individuals are presented with a phonemic category (e.g. – the letter ‘p’) or a semantic category (e.g. – animals) and asked to name as many words as possible from said category within a specified time limit. The number of words produced is a measure of semantic access [11].
Memory-based cognitive tasks utilize memorization and recall speed/accuracy to explore the structures and processes involved in the effective storage and retrieval of information [12]. The following five memory measures met inclusion criteria for this review.
Individuals are sequentially presented with verbal strings of numbers which sequentially increase in length and are asked to verbally report the numbers following each presentation. The length of the final number string an individual is able to accurately report back is a measure of digit-span recall WM [13].
Individuals are presented with a list of words several times and asked to memorize it (encoding). Following a delay period (consolidation), during which time the individual is distracted with non-relevant tasks, the individual is presented with ‘target’ words and asked whether or not each was present in the prior memorized list. The accuracy with which an individual responds to the targets is a measure of verbal episodic recognition memory. An identical procedure, though replacing words with visual images, is utilized as a measure of visual episodic recognition memory [14].
Individuals are sequentially presented with a string of visual images. Following each string, a single target is visually presented and the individual must respond whether or not said target was in the prior string. The speed and accuracy with which an individual responds to the target is a measure of visual WM [15].
Individuals are presented with a sequential string of stimuli (e.g. – letters or numbers) and asked to generate a response if a stimulus is identical to the one presented ‘N’ items prior. The accuracy and speed with which an individual responds to targets is a measure of WM according to the modality of the stimuli utilized [16].
An additional four measures met inclusion criteria for this review but could not be grouped into any single cognitive domain.
Individuals are asked to complete simple arithmetic math problems in their head. The speed and accuracy with which an individual can complete these problems is a measure of computational efficiency [17].
Individuals are asked to view and rate a series of images of differing valences (typically negative and neutral). The average rating generated within each valence is a measure of emotional processing [18].
Individuals participate in a ‘gambling-type’ scenario whereby different actions carry varying, yet clearly understood, consequences (e.g. – choose between two boxes, the first of which has a 90% probability of containing $1 whilst the second has a 10% chance of containing $10). The number of low-probability/high-reward choices an individual selects is a measure of risk-taking propensity [19], [20].
Individuals are asked to report about the frequency and intensity of mentally generated self-referential thoughts (typically following a pre-arranged negative valence-type scenario, such as receiving a negative grade on an exam) [21].
Section snippets
Study selection
Papers included in this quantitative review were obtained from a PubMed database search (June 12th, 2014). The search term “transcranial direct current stimulation” generated 1156 papers. The abstract of each of paper was then read to determine which outcome measures were included and what type of population was utilized. This initial review narrowed the study pool to 417 (see Supplemental Material: Fig. S1 for complete study selection flow chart).
Following this, each article was read and the
Set shifting
The directly-replicated anode/offline studies revealed a non-significant SMD effect size for the number of errors generated during task completion (Table 1; Fig. 1a). Only 1 study explored cathodal/offline stimulation [25]and only 1 study explored online tDCS on this task [29]; accordingly, no analysis was undertaken for these measures.
Stop signal task
The directly-replicated anode/offline studies revealed a non-significant SMD effect size for inhibitory reaction time to stop-signal stimuli (Table 1; Fig. 1c).
Discussion
In this paper, we pooled and analyzed every cognitive outcome measure in the literature explored by at least two different research groups utilizing healthy adult populations, the same stimulation-to-task relationship, the same active electrode location, and comparing to a sham (control) condition. Of the 59 analyses undertaken, tDCS was not found to generate a significant effect on any. Taken together, the evidence does not support the assertion that a single-session of tDCS has a reliable
Conclusion
Taken together, we have found no evidence that single-session tDCS has a reliable effect on cognitions in healthy adult populations. When this is combined with our previous work which suggested tDCS does not have a reliable effect on neurophysiologic measures beyond MEP amplitude [1], it becomes difficult avoid questions of device efficacy. It is important to note, however, that these findings may be due to state-dependency effects which, with elucidation, can be controlled for and leveraged.
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