Transcranial Random Noise Stimulation Does Not Enhance - Am MIT spezialisierte KI-Forschung

Transcranial Random Noise Stimulation Does Not Enhance
the Effects of Working Memory Training

Joni Holmes, Elizabeth M. Byrne, Susan E. Gathercole, and Michael P. Ewbank

Abstrakt

■ Transcranial random noise stimulation (tRNS), a noninvasive
brain stimulation technique, enhances the generalization and
sustainability of gains following mathematical training. Here it
is combined for the first time with working memory training
in a double-blind randomized controlled trial. Adults completed
10 sessions of Cogmed Working Memory Training with either
active tRNS or sham stimulation applied bilaterally to dorso-
lateral pFC. Training was associated with gains on both the

training tasks and on untrained tests of working memory that
shared overlapping processes with the training tasks, but not
with improvements on working memory tasks with distinct pro-
cessing demands or tests of other cognitive abilities (z.B., IQ,
maths). There was no evidence that tRNS increased the magni-
tude or transfer of these gains. Daher, combining tRNS with
Cogmed Working Memory Training provides no additional ther-
apeutic value. ■

EINFÜHRUNG

Intensive training of working memory, the ability to retain
information for short periods of time for ongoing mental
Aktivitäten, generates robust gains on untrained tests of
Arbeitsgedächtnis (von Bastian & Oberauer, 2013; Dahlin,
Neely, Larsson, Backmann, & Nyberg, 2008). In other cogni-
tive domains, the efficacy and generalization of training
benefits has been enhanced by transcranial electrical stim-
ulation (Cappelletti et al., 2013; Snowball et al., 2013; Ditye,
Jacobson, Walsh, & Lavidor, 2012). In this study, we com-
bined the two approaches to investigate whether stimu-
lation could increase the rate and magnitude of training
gains and extend the benefits of training beyond highly
similar untrained tests of working memory. To provide a
rigorous test of the potential added value of stimulation
we used a double-blind randomized controlled design,
with sham stimulation as the control, and tested perfor-
mance on multiple outcome measures. To maximize oppor-
tunities for modulating behavior, a multisession training
program that consistently produces large gains in working
memory was used (Schwaighofer, Fischer, & Bühner, 2015)
in conjunction with stimulation parameters that have been
shown to enhance the effects of maths training (Snowball
et al., 2013).

Working memory training involves practice on working
memory tasks that continually adapt to an individual’s
ability. The benefits of training are greatest for untrained
tests of working memory that draw on the same under-
lying cognitive and neural processes as the training activ-
ities (Sprenger et al., 2013; von Bastian & Oberauer, 2013;

Cambridge University

Dahlin et al., 2008). This has been termed process-specific
transfer, and it is associated with changes in the neural
structures and networks linked with working memory
(Astle, Barnes, Bäcker, Colclough, & Woolrich, 2015;
Kundu, Sutterer, Emrich, & Postle, 2013; Takeuchi et al.,
2010; Dahlin et al., 2008; Olesen, Westerberg, & Klingberg,
2004). Evidence for the transfer of training gains to tests
of working memory with distinct processing demands to
the training tasks is less clear. Some studies report positive
transfer across different categories of working memory
tasks. Zum Beispiel, training on complex span tasks, welche
involve rapidly switching between the storage of memory
items and an interpolated unrelated processing activity,
generates gains on running span tasks that require the
continuous monitoring and updating of a sequence of
Artikel (Harrison et al., 2013). Jedoch, other studies re-
port selective benefits only for transfer tests of working
memory that are the same as the training activities, mit
no transfer across working memory paradigms (z.B.,
Redick et al., 2013; Thompson et al., 2013; von Bastian
& Oberauer, 2013). When the most rigorous random-
ized controlled study designs are used, there is little
to no evidence for the generalization of training-related
effects to complex everyday activities that depend on
Arbeitsgedächtnis, such as academic attainment and
focussed attention (z.B., Cortese et al., 2015; Dunning,
Holmes, & Gathercole, 2013; Rapport, Orban, Kofler, &
Friedman, 2013).

Transcranial electrical stimulation is a noninvasive neuro-
modulatory tool in which a weak electric current is de-
livered to the brain through a pair of electrodes attached
to the scalp. Transcranial electrical stimulation is asso-
ciated with changes in cortical excitability (Nitsche &

© 2016 Massachusetts Institute of Technology. Published under a
Creative Commons Attribution 3.0 Unportiert (CC BY 3.0) Lizenz.

Zeitschrift für kognitive Neurowissenschaften 28:10, S. 1471–1483
doi:10.1162/jocn_a_00993

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Paulus, 2000) and has been proposed to enhance learning
by inducing long-term potentiation (Stagg & Nitsche,
2011). The potential of noninvasive brain stimulation to
modulate and enhance human cognition means that, Wann
combined with a learning task, it has the potential not only
to increase the efficacy of cognitive training but also to
enhance the generalization of training gains.

Previous studies combining stimulation with working
memory training have used transcranial direct current
stimulation (tDCS; Richmond, Wolk, Chein, & Olson,
2014; Martin et al., 2013), a polarity-dependent technique
that generates opposing excitatory and inhibitory activ-
ity under the two electrodes: Anodal stimulation pulls
neurons toward depolarization and is associated with
an increase in cortical excitability, whereas cathodal hyper-
polarizes neurons and is associated with decreased excit-
ability, or inhibition (Nitsche & Paulus, 2000). In one
Studie, tDCS shifted the learning curve of the training tasks
upward relative to sham stimulation, but it did not enhance
the rate of learning on these activities (Richmond et al.,
2014). In the other, stimulation did not increase on-task
training gains (Martin et al., 2013). Active stimulation com-
bined with working memory training was associated with
greater gains on untrained tests than either no inter-
vention (no stimulation and no training; Richmond et al.,
2014) or stimulation alone (no training; Martin et al.,
2013). Both studies concluded that active tDCS enhanced
the transfer of training outcomes. There is a problem with
this conclusion, as critically there were no significant dif-
ferences between groups who received training with active
stimulation and groups who received training with sham
(placebo) stimulation on the transfer tests. Als solche, diese
gains can be attributed to training alone. In both studies,
tDCS anodal stimulation was applied to left dorsolateral
pFC (DLPFC), meaning right DLPFC was either not stimu-
verspätet (Martin et al., 2013) or was under cathodal stimu-
lation (Richmond et al., 2014). Working memory task
performance is associated with bilateral activation of
DLPFC (Rottschy et al., 2012). Failure to stimulate DLPFC
bilaterally may therefore explain why crucial differences
between the active and sham stimulation groups were
not significant.

In other cognitive domains, transcranial random noise
stimulation (tRNS), an alternative method of brain stimu-
lation, has shown more promise. Snowball et al. (2013)
found tRNS applied bilaterally to the DLPFC to be effec-
tive in enhancing the efficacy and generalizability of gains
following arithmetic training. Changes in neural activity
and improvements on untrained mathematical problems
persisted 6 months after training for the tRNS group rel-
ative to the sham group (Snowball et al., 2013). Ähnlich,
Cappelletti et al. (2013) reported significantly steeper
learning curves and long-lasting improvements in magni-
tude judgments following numerosity training combined
with tRNS applied bilaterally to parietal regions compared
with sham stimulation, training combined with tRNS over
motorischer Kortex, or tRNS alone.

In the current study, we investigated, for the first time,
whether tRNS could modulate on-task training gains and
enhance transfer to both untrained working memory
tasks and other cognitive abilities related to working
memory when combined with working memory training.
tRNS offers potential advantages over tDCS, the stimula-
tion technique combined with working memory training
in previous studies (Richmond et al., 2014; Martin et al.,
2013). Most importantly, it is polarity-independent allow-
ing for bilateral stimulation of DLPFC, a region of the
brain associated with working memory function (Owen,
McMillan, Laird, & Bullmore, 2005) and influenced by
working memory training (Takeuchi et al., 2010). It also
has a higher cutaneous perception threshold, making it
particularly suitable for blinding groups to stimulation
condition (Ambrus, Paulus, & Antal, 2010).

Following Snowball et al. (2013), high-frequency (101–
640 Hz) tRNS at a current strength of 1 mA was applied
bilaterally over DLPFC. Cogmed Working Memory Training
(Cogmed, 2005), a program that has been extensively re-
searched and yields larger effect sizes for process-specific
changes than other training packages (Schwaighofer et al.,
2015; Sprenger et al., 2013), was used. Unlike many studies
that have investigated the impact of training on working
memory in a single session (z.B., Fregni et al., 2005), Das
package provided multisession training, allowing us to inves-
tigate the effects of stimulation on learning. A double-blind
randomized controlled trial design was employed. Multiple
outcome measures varied the degrees of overlap with the
trained activities, allowing us to map out the extent to
which gains generalized beyond the trained tasks. Der
primary outcome measures were working memory tests
with processing components that overlapped with the
training tasks. Any enhancement to training via stimulation
should be evident in these measures as well as the trained
tasks. To determine whether any benefits of combining
training with stimulation extend beyond specific trained
processes, participants also completed untrained working
memory tasks with different processing demands to those
in the training tasks. Secondary measures of cognitive pro-
cesses linked with working memory, including tests of in-
hibition (Kane & Engle, 2003) and measures of selective
attention (de Fockert, Rees, Frith, & Lavie, 2001), were in-
cluded alongside tests of information processing and stan-
dardized tests of general cognitive abilities (z.B., Sprache
and nonverbal reasoning) to test whether stimulation en-
hanced transfer beyond working memory paradigms. Ein
emotional recognition task with no memory component
was included as a nonmemory control task. Previous studies
claiming that cognitive training or brain stimulation are
effective have relied on null hypothesis significance testing
(NHST) to imply that the alternative hypothesis is true; Sie
have rarely quantified the degree to which the evidence sup-
ports the null or alternative hypotheses (Sprenger et al.,
2013). Aus diesem Grund, Bayesian methods were employed
to evaluate the strength of the evidence for and against the
null hypothesis in addition to traditional NHST.

1472

Zeitschrift für kognitive Neurowissenschaften

Volumen 28, Nummer 10

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METHODEN

Teilnehmer

Thirty native English-speaking adults aged between 18
Und 35 Jahre (11 men) provided written informed con-
sent to participate in this study, which was approved by
the University of Cambridge’s psychology research ethics
committee. All participants were recruited through the
MRC Cognition and Brain Sciences Unit’s research par-
ticipation system. All participants were stimulation com-
patible (d.h., no metal implants or pacemakers, NEIN
previous history of epilepsy, head injury or neurological
disorders, not currently taking medication affecting the
CNS), had normal or corrected-to-normal hearing and
vision, and were right-handed.

Materials

Process-specific Memory Tasks

Eight tests with processing components that overlapped
with the training tasks were administered. These included
four standardized tests from the Automated Working
Memory Assessment (Alloway, 2007): a test of verbal
STM (digit recall), visuospatial ( VS) STM (dot matrix),
verbal working memory (WM) (backward digit recall)
and VS WM (Mr X). Standard scores (M = 100, SD = 15)
were calculated for each task. Participants also completed
four computerized experimental tests of verbal and VS
storage (STM) and of verbal and VS storage with intrinsic
Verarbeitung (Arbeitsgedächtnis). The storage tasks required
participants to recall either a list of digits (verbal) or spatial
Standorte (VS) in serial order. The working memory tasks
were identical to the storage tasks, except participants
were required to recall the digits (verbal) or spatial loca-
tionen ( VS) in reverse order. Trials were presented in
blocks of four trials. Sequences in the first block started
at a span of two items and increased in length by one item
in each subsequent block if participants scored three or
more trials correct. The tasks discontinued if two or more
errors were made in any block. The maximum span length
reached at this point was scored.

Memory Tasks with Distinct Processes

Participants completed four working memory tasks in-
volving distinct processes to the training activities, zwei
n-back tasks and two complex span tasks. For both
n-back tasks, participants were presented with a sequence
of stimuli one at a time (auditory digits for verbal n-back
and abstract line drawings for VS n-back) and had to in-
dicate by a key press when the current stimulus matched
one presented n items back in the sequence. Sequences
were presented in blocks containing 20 + n items. Dort
were six target items (matches) in each block. Der erste
block started at 1-back and increased in difficulty by 1 In
each subsequent block if less than five errors were made
(z.B., increased from 1-back to 2-back). The tasks dis-

continued when five or more errors were made within
a block. False alarms (responding to a nontarget) Und
misses (failing to respond when a match was present)
were counted as errors (missing a target). The maximum
n-back level reached to this point was scored. For both
complex span tasks, participants were presented with a
series of storage items (digits for the verbal task and
spatial locations for the VS task) interpolated with a
same-domain processing task, which was presented for
6 sec in-between the presentation of each storage item.
The processing tasks required participants to judge
whether two letters rhymed (verbal task) or to decide
whether patterns of lines presented inside a pair of hexa-
gons matched ( VS task). Participants were required to
recall the storage items in serial order at the end of the
trial. Trials were presented in blocks of 3. The first block
started at a span of 1 (one storage item and one process-
ing episode) and increased by a span of 1 (zusätzlich
storage item and an additional processing episode) Wenn
two or more trials were correct in any block. Trials were
scored as correct if all storage items were recalled in the
correct serial order and >66% of the processing items
were correct. The tasks discontinued if two of the three
trials in a block were incorrect. A trial was incorrect if the
storage items were recalled incorrectly, accuracy for the
processing tasks was <66%, or if there were no re- sponses for the processing tasks. The maximum span reached was scored. Cognitive Processes Associated with Working Memory Participants completed a set of tasks that included parallel verbal and VS tests of executive function. Two flanker tasks were administered to provide measures of verbal and VS selective attention. Both tasks consisted of 240 trials: 80 baseline, 80 congruent, and 80 incongruent. Trials were presented in a random order. In the baseline condition, participants were required to click on a button on a computer screen showing a letter (verbal) or arrow ( VS) matching the one presented in a box on screen. In the congruent condition, participants were presented with a row of five identical letters (verbal) or a row of five arrows pointing in the same direction ( VS). They were required to click on the letter or arrow corresponding to the middle letter/arrow shown below. In the incon- gruent condition, the central arrow or letter was flanked by incongruent stimuli (e.g., AABAA). Again, participants were asked to respond to the middle stimulus by selecting the appropriate response button shown on screen. RTs for correct trials were recorded for all conditions. The average RT difference between correct congruent and incongruent trials was used to index the Flanker effect. Indices of inhibitory control were provided by two Stroop tasks. Both tasks consisted of 48 baseline, 48 con- gruent, and 48 incongruent trials. These were presented in blocks by condition. On baseline trials in the verbal Stroop task, neutral words (e.g., “when”) were presented Holmes et al. 1473 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 8 / 1 2 0 8 / 1 1 4 0 7 / 1 1 1 4 9 7 5 1 1 / 3 1 2 7 7 8 o 5 c 4 n 3 _ 5 a / _ j 0 o 0 c 9 n 9 3 _ a p _ d 0 0 b 9 y 9 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j f / t . u s e r o n 1 7 M a y 2 0 2 1 on screen printed in yellow, blue, green, or red. Partici- pants were required to click on a color block matching the color the word was printed in. On congruent trials, participants were presented with color words printed in the same color as the word (e.g., “yellow” appeared on screen, printed in yellow ink) and were again asked to click on the color the word was printed in. On in- congruent trials, color words were presented in different colors to the word itself (e.g., “yellow” was printed in red ink). Participants were required to inhibit the over- learned verbal response of reading the color word and instead click on the ink color. On neutral trials in the VS Stroop task, an arrow appeared in the center of a box, pointing either up, down, left, or right. Participants were required to click on the arrow pointing in the same direction from a choice of four presented in a box below. On congruent trials, an arrow appeared touching the edge of the box at a position congruent with the direc- tion it was pointing (e.g., an arrow pointing right ap- peared on screen with the arrowhead touching the right hand side of the box). Participants were asked to select the arrow pointing the same way as the one in the box from a choice of four below. On incongruent trials, participants were presented with an arrow in a position in a box that was incongruent to the direction it was pointing (e.g., an arrow pointing right could appear at the left, top, or bottom of the box). Participants were required to inhibit the prepotent response associated with the position of the arrow and instead respond to the direction of the arrowhead by selecting one of four arrows below. For both tasks, RTs for correct trials were recorded for each condition. The Stroop effect was calculated as the difference between the mean RT for correct trials in the incongruent condition and the mean RT for correct trials in the congruent condition. Information Processing and General Cognitive Abilities Participants completed two information processing tasks. The verbal processing task required participants to judge whether pairs of letters rhymed. Fifty auditory letter pairs were presented, consisting of monosyllabic English alphabet letter names. Pairs were constrained to avoid successive letters in the alphabet (e.g., J, K), highly confusable fricative letter names (e.g., F, S), and familiar acronyms (e.g., PC, IT, US). A parallel VS pro- cessing task required participants to judge whether the line patterns shown on two hexagons presented simultaneously were the same or different. Fifty pairs of hexagons were shown. RTs for correct trials were scored for both tasks. Two subtests of the Wechsler Abbreviated Scaled of Intelligence ( Wechsler, 1999), tests of verbal ( Vocabu- lary) and of nonverbal (Matrix Reasoning) IQ, were also administered. t Scores were derived for each subtest and used to calculate a composite standard score for IQ. The Numerical Operations task of the Wechsler Individual Achievement Test Second Edition ( Wechsler, 2005) was used to measure math ability. The Peabody Picture Vocabulary Test Fourth Edition, a measure of receptive vocabulary (Dunn & Dunn, 2007), was also given. Cognitive Task with No Memory Load The Facial Expressions of Emotion test ( Young, Perrett, Calder, Sprengelmeyer, & Ekman, 2002) is a measure of emotion expression recognition. Participants were pre- sented with 30 morphed faces on an emotional con- tinuum ranging between happiness–surprise, surprise– fear, fear–sadness, sadness–disgust, disgust–anger, and anger–happiness over five blocks. Participants were re- quired to judge which of six emotion labels (happy, sad, anger, fear, disgust, and surprise) best described each facial expression. Only trials with morphed images of 70% or 90% bias toward a particular expression were used to assess performance. Proportion correct across all blocks was scored. Training Participants completed 10 sessions of Cogmed Working Memory Training (Cogmed, 2005). Each session lasted approximately 45 min and involved repeated practice on eight training exercises (15 trials on each task totaling 120 trials). Participants completed the same eight tasks in each training session, in one of two counterbalanced task orders. Task order was counterbalanced to ensure all tasks were completed under active stimulation for those in the stimulation group. A mixed ANOVA with order (A or B) and task (gain for each of the eight training tasks) revealed that there were no order effects for either the active stimulation, F(7, 91) = 1.462, p = .191, η p 2 = .101, or sham stimulation, F(7, 91) = .943, p = .478, η p 2 = .068, groups. Three training tasks required the immedi- ate serial recall of verbal or VS items ( Visual Data, Data Room, and Decoder). Five further tasks required mental manipulation (e.g., mental rotation or reversing the se- quence) prior to recall (Input Module, Input Module with Lid, Number Grid, Rotating Data Link, and Rotating Dots). Full details about the training program are pro- vided at www.cogmed.com/rm. All training exercises started at a span of two in the first session. An adaptive algorithm was used to calibrate the difficulty of each task to current performance on a trial-by-trial basis. Task dif- ficulty increased by a span of one following three con- secutive correct responses and decreased by a span of one following two consecutive incorrect answers. The average span was recorded for each task in each session. Data from Session 1 was not included in the analyses as there was no training in this session (the maximum span participants could reach was below the baseline ability of all participants). 1474 Journal of Cognitive Neuroscience Volume 28, Number 10 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 8 / 1 2 0 8 / 1 1 4 0 7 / 1 1 1 4 9 7 5 1 1 / 3 1 2 7 7 8 o 5 c 4 n 3 _ 5 a / _ j 0 o 0 c 9 n 9 3 _ a p _ d 0 0 b 9 y 9 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j f . / t u s e r o n 1 7 M a y 2 0 2 1 Stimulation tRNS was applied bilaterally over the DLPFC. Standard 5 × 5 cm rubber electrodes, covered with saline-soaked sponges, were placed on the scalp on areas correspond- ing to regions F3 and F4 identified using the standard international 10–20 EEG electrode placement procedure. They were fixed by a rubber headband. Stimulation was delivered via a battery-driven electrical stimulator (DC- STIMULATOR-PLUS; NeuroConn). Following Snowball et al. (2013), high-frequency tRNS (101–640 Hz) at a current strength of 1 mA with no DC offset (i.e., varying between −0.5 and +0.5 mA) at a sampling rate of 1280 sample/sec was used. Participants in the active stimulation group re- ceived 20 min of tRNS with 15 sec of increasing and de- creasing ramps at the beginning and end of stimulation. To maximize opportunities for modulating behavior, stimulation began at the onset of training (Pirulli, Fertonani, & Miniussi, 2013). Stimulation faded in for 15 sec and out over 15 sec at the beginning of each session for the sham group to blind participants to their stimula- tion condition (Priori, Hallett, & Rothwell, 2009). The stimulation machine display was identical for both groups ensuring both the experimenter and participants were blind to the type of stimulation being applied. Partici- pants were asked to rate the extent to which they expe- rienced any physical sensations from the stimulation on a scale of 1–10 (1 being not at all). The ratings were similar (stimulation M = 1.000, SD = 1.363, sham M = .9333, SD = 1.580) and did not differ significantly between groups, t(28) = 1.24, p = .902, Cohen’s d = .046, indicating that group blinding was effective. Procedure This was a double-blind randomized controlled study. Participants completed two pretraining sessions, each lasting approximately 2 hr. They were assigned to either an active (9 women) or sham (10 women) stimulation condition (n = 15 per group) after preassessment. Stratified randomization was used to ensure the groups Table 1. Group Characteristics were matched at baseline in terms of age, sex, IQ, and standardized short-term and working memory scores (Table 1). The demand characteristics of the study were identical between the active and sham groups; both completed the same training, were unaware whether they were receiving active or sham stimulation, and were paid for their time. A no-contact control group was not included as they would have been poorly matched in terms of motivation and other demand characteristics (e.g., Shipstead, Redick, & Engle, 2012). Participants then completed 10 sessions of adaptive working memory training with either active or sham stimulation across ∼19 days. Training sessions were run individually with each participant. The time taken to complete training did not differ between groups (Table 1). All pretraining tasks were readministered at the end of training. RESULTS Training Data General linear regression models were conducted for each training task to investigate whether there were any group differences in overall gains. For all models, Session 10 scores were entered as the dependent vari- able, with group (active stimulation or sham) entered as the independent variable. Group did not significantly predict training gains on any task, nor did it predict aver- age gains across the training tasks (Table 2). Previous studies claiming that cognitive training or brain stimulation are effective have relied on NHST to im- ply the alternative hypothesis is true; they have rarely quantified the degree to which the evidence supports the null or alternative hypotheses (Sprenger et al., 2013). For this reason, Bayesian methods were employed to quantify the strength of the evidence for the null hy- pothesis (stimulation does not enhance on-task gains) versus the alternative (stimulation boosts training gains). Bayesian regression analyses conducted in JASP (Love et al., 2015) with default prior scales were conducted for each training task, with group (active stimulation or Age (years) IQ Verbal STM VS STM Verbal WM VS WM Time to complete training (days) Stimulation Sham Group Comparison M 25.270 120.667 101.067 103.733 101.000 103.133 19.330 SD 5.509 8.524 15.696 23.313 20.078 22.427 4.515 M 24.730 119.333 100.600 106.667 101.733 107.867 18.333 SD 4.008 10.834 16.322 22.064 19.282 15.287 3.867 t 0.303 0.375 0.080 −0.354 −0.102 −0.675 0.652 p .764 .711 .937 .726 .919 .505 .520 Cohen’s d 0.113 0.138 0.029 −0.129 −0.037 −0.251 0.238 Holmes et al. 1475 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 8 / 1 2 0 8 / 1 1 4 0 7 / 1 1 1 4 9 7 5 1 1 / 3 1 2 7 7 8 o 5 c 4 n 3 _ 5 a / _ j 0 o 0 c 9 n 9 3 _ a p _ d 0 0 b 9 y 9 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j . f t / u s e r o n 1 7 M a y 2 0 2 1 t s e T t 0 1 F B 5 4 3 . 0 n a i s e y a B n o s i r a p m o C p u o r G m a h S n o i t a u m l i t S ’ d s n e h o C p t D S M N D S M N n a i s e y a B A V O N A l a i t r a P 0 1 F B a t E p F 3 1 7 0 − . 7 5 1 . 8 4 . 1 7 0 0 . 8 3 1 0 . 8 7 8 0 0 . 4 9 1 . 0 1 1 2 0 2 . 4 4 7 1 0 . 0 1 7 8 . 8 7 4 . 0 n a i s e y a B n o i s s e r g e R 0 1 F B 6 3 . 0 n o s i r a p m o C p u o r G m a h S n o i t a u m l i t S p t a t e B D S M D S M 1 2 7 . 1 6 3 . 0 − 8 6 0 . 0 − 9 8 6 . 0 6 4 3 . 1 3 1 5 . 0 6 2 4 . 1 e g a r e v A s k s a t l l a s s o r c a 8 3 . 0 5 1 5 0 . 1 3 3 . 2 0 0 1 − . 9 4 1 0 . 1 7 1 0 . 8 6 8 2 . 0 9 5 0 . 0 0 1 5 8 2 . 4 7 8 0 0 . 0 5 8 9 . 2 3 2 . 0 8 4 3 . 0 7 7 8 . 6 5 1 . 0 9 2 0 . 0 3 7 6 . 0 7 6 1 . 1 1 3 6 . 0 5 6 1 . 1 a t a d l a u s i V k n i l 7 4 3 . 0 2 5 3 . 1 2 3 3 . 1 1 6 5 0 . 6 7 0 0 . 6 8 0 1 − . 8 4 2 . . 2 1 − 7 8 1 0 . 7 5 1 0 . 8 4 3 1 . 0 7 6 0 . 0 7 8 . 8 0 2 1 . 8 2 1 0 . 3 7 1 . 0 1 1 8 8 1 . 0 1 6 1 . 0 3 2 1 . 9 2 6 . 1 1 8 0 0 . 7 5 2 0 . 6 2 0 3 . 0 5 6 4 . 0 0 1 2 1 2 1 3 1 9 . 8 9 3 0 . 0 4 3 . 6 3 1 . 1 8 5 7 . 0 6 8 0 0 . 0 4 8 9 . 6 3 2 . 0 1 6 1 . 3 1 3 3 0 . 0 4 7 4 . 2 5 9 . 0 9 8 3 . 0 3 6 3 . 0 2 7 3 . 0 5 7 5 . 6 1 7 . 5 5 6 . 7 6 5 . 0 − 7 0 1 . 0 − 8 6 3 . 0 − 9 6 0 . 0 − 1 5 4 . 0 − 5 8 0 . 0 − 7 4 6 . 0 2 7 6 . 0 9 3 7 . 0 8 2 0 . 1 m o o r a t a D 7 4 4 . 0 8 1 8 . 0 1 6 7 . 0 7 6 8 . 0 r e d o c e D 2 1 1 . 2 9 1 7 . 2 8 7 0 . 2 7 3 7 . 2 t u p n I l e u d o m 5 1 7 . 0 1 4 0 1 − . 1 5 0 . 3 2 1 . 2 4 9 1 0 . 3 5 1 0 . 8 7 1 2 . 0 7 6 3 . 0 9 1 1 8 . 8 9 3 0 . 0 9 4 3 . 3 2 1 . 1 7 1 4 . 0 2 8 4 . 2 1 7 . 0 − 3 3 1 . 0 − 1 1 5 . 1 1 5 0 . 2 5 4 3 . 1 1 1 6 . 2 t u p n I l e u d o m d i l h t i w 9 7 3 . 0 6 6 4 0 . 1 3 . 1 4 0 1 − . 6 2 2 0 . 1 2 0 . 1 1 6 5 4 . 0 1 5 0 . 0 2 1 0 5 5 . 0 4 5 1 0 . 0 2 0 9 . 3 4 . 0 7 5 3 . 0 8 5 7 . 1 1 3 . 0 9 5 0 . 0 7 3 8 . 0 1 7 0 . 1 4 0 8 . 0 5 2 0 . 1 r e b m u N d i r g 5 3 1 . 2 8 5 0 . 6 0 3 . 8 8 0 0 . 9 3 1 . 0 5 4 1 . 0 9 3 2 5 . 0 7 4 0 . 0 − 7 0 0 1 . 7 6 8 0 0 . 0 8 8 9 . 6 1 2 . 0 9 5 3 . 0 3 4 7 . 1 3 3 . 0 − 2 6 0 . 0 − 8 4 7 . 0 5 5 9 . 0 6 3 6 . 0 9 5 9 . 0 g n i t a t o R k n i l a t a d 4 3 6 . 0 7 5 0 0 . 2 9 . 1 0 1 0 − . 5 7 0 . 0 7 7 2 . 0 0 1 8 8 4 . 0 1 6 2 . 0 2 1 7 1 7 . 2 2 6 2 0 . 0 6 5 6 . 4 7 . 0 5 4 3 . 0 7 6 9 . 2 4 0 . 0 8 0 0 . 0 7 9 4 . 0 9 6 2 . 1 6 8 6 . 0 0 0 0 . 1 g n i t a t o R s t o d . ) s t n a p i c i t r a p l l a f o y t i l i b a e n i l e s a b e h t w o e b l s a w h c a e r l d u o c s t n a p i c i t r a p n a p s m u m i x a m e h t ( n o i s s e s s i h t n i i g n n i a r t o n s a w e r e h t s a d e z y l a n a t o n e r e w 1 n o i s s e S m o r f a t a D D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 8 / 1 2 0 8 / 1 1 4 0 7 / 1 1 1 4 9 7 5 1 1 / 3 1 2 7 7 8 o 5 c 4 n 3 _ 5 a / _ j 0 o 0 c 9 n 9 3 _ a p _ d 0 0 b 9 y 9 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j f / . t u s e r o n 1 7 M a y 2 0 2 1 e g n a h C f o e t a R n o i s s e S y b p u o r G 0 1 o t 2 s n o i s s e S m o r f s n i a G p u o r G y b e c n a m r o f r e P k s a T i g n n i a r T n i s e g n a h C . 2 e l b a T 1476 Journal of Cognitive Neuroscience Volume 28, Number 10 sham) entered as an independent variable. Inverse BF (BF10) were used to express the odds in favor of the al- ternative hypothesis (group has an effect) compared with the null (no effect of tRNS). As a point of reference: BF10 of 1–3 indicates weak/anecdotal evidence for the alter- native hypothesis; BF10 of 3–10 corresponds to positive/ substantial support for the alternative hypothesis and BF10 > 10 indicates positive/strong evidence for the
alternative hypothesis (Kass & Raftery, 1995). Bayesian
regression analyses, conducted for all training tasks with
group entered as the independent variable, yielded no ev-
idence that stimulation influenced gains on the training
Aktivitäten, BF10 < .5 for all tasks (Table 2). Mixed effects ANOVAs with Session (2–10) as a within- subject factor and Group (stimulation or sham) as a between-subject factor were conducted to investigate whether there were any group differences in training performance across sessions. These analyses revealed a significant main effect of Session for memory span in both groups on each of the training tasks (all ps < .01) and also on span scores averaged across tasks (Figure 1). Neither the main effects of Group or the Group × Session interactions were significant (see Figure 1 for scores aver- aged across tasks and Table 2 for the Group × Session interaction terms for each task). Bayesian ANOVAs re- vealed that a simple main effects model in which Group and Session were entered separately was preferred to a model that included a Group × Time interaction for all tasks and for scores averaged across tasks (BF10 ranging from 8.913 to 74.285 in favor of the main effects model; Table 2). There was therefore strong evidence for similar training performance across sessions for both groups. Figure 1. Training data by group, averaged across all eight training tasks. A main effect of Session, F(8, 224) = 105.114, p < .001, ηp 2 = .790, revealed significant training gains. The absence of a main effect of Group, F(1, 28) = .201, p = .658, ηp F(8, 224) = .478, p = .871, ηp modulated by stimulation. Data from Session 1 are not displayed as there was no training in this session (the maximum span participants could reach was below the baseline ability of all participants). 2 = .007, or Group × Session interaction, 2 = .017, indicates that gains were not Rate of learning on the training activities was estimated by computing a polynomial function that identified the point at which each participant reached asymptotic per- formance on each task. If stimulation enhances learning, the stimulation group should reach this point faster than the sham group. The functions of the polynomials pro- vided the rate of change to asymptote for each partici- pant on each task. These were computed for each individual training task and for average performance across tasks by approximating each participant’s perfor- mance with a function that allowed for two turning points; the second corresponded to the point at which they reached asymptote. The functions of the polyno- mials were then used to calculate how quickly each par- ticipant reached their asymptote for each task. This ROC index was calculated as maximum score at asymptote/ number of sessions to reach asymptote. Group differ- ences in rate of change values were then compared in a series of independent samples t tests (see Table 2). Data were excluded for curves in which the asymptote was outside the observable training window (i.e., if asymptote <2 or>10). There were no significant group
differences in rate of change for any task or for rate of
change in scores averaged across tasks. Bayesian inde-
pendent samples t tests revealed no evidence for group
differences in rates of change (all BF10 < 3), indicating that stimulation did not increase the speed of learning on the training activities (Table 2). Transfer Tasks The influences of training and stimulation on transfer were first assessed on the sample as a whole (Table 3). Significant main effects of Training were observed on all working memory tests sharing processes with the train- ing tasks (all ps < .001). Bayesian analyses indicated that there was strong evidence for these effects. After family- wise correction for multiple comparisons, there were no significant main effects of Training on memory tasks in- volving distinct processes to the training activities. The outcomes of Bayesian t tests concurred with this pattern of effects for all measures except VS n-back, where a BF10 of 3.322 suggested that there was positive evidence for a training effect. Training gains on verbal and VS infor- mation processing tasks and the number operations mea- sure reached significance, with BF10 > 3 in all cases.
There was no evidence for training effects on measures
of selective attention, inhibitory control, Sprache, or non-
verbal reasoning.

To examine the effect of stimulation on transfer, gen-
eral linear regression analyses were performed with post-
training scores as dependent variables and pretraining
scores and group (active or sham stimulation) as indepen-
dent variables. Stimulation group was a significant predictor
of posttraining scores on a verbal n-back task, a memory
test that did not share common processes with the trained
Aktivitäten. Training gains were significantly greater for the

Holmes et al.

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Tisch 3. Training-related Changes in Transfer Tasks

Pretraining

Posttraining

Pre to Post

Cohen’s d

Bayesian t Test BF10

Process-specific Memory Tasks

Digit recall

Dot matrix

100.833

15.735

108.567

15.85 −4.500 <.001 105.2 22.352 120.1 21.865 −6.971 <.001 Backward digit recall 101.367 19.345 115.2 15.338 −5.897 <.001 105.5 19.011 114.733 16.885 −5.541 <.001 Mr X Verbal storage VS storage Verbal backward VS backward Non Process-specific Memory Tasks Verbal n-back VS n-back Verbal complex span VS complex span 7.967 7.267 6.567 6.433 4.933 3.567 6.133 4.667 1.351 1.311 1.612 1.695 1.66 1.547 2.3 1.863 8.967 8.033 8.133 7.367 5.4 4.333 6.9 4.6 1.732 −4.664 <.001 1.752 −3.516 <.001 1.548 −4.683 <.001 1.921 −3.006 .005 2.313 −1.304 1.936 −2.605 2.551 −2.538 .203 .014 .017 2.061 0.220 .827 −0.034 Processes Associated with WM Verbal Flanker effect 82.774 31.099 79.324 66.107 75.165 76.888 74.031 66.553 43.349 130.08 76.764 136.27 −1.004 124.442 68.5 145.107 114.98 −1.043 0.335 0.064 VS Flanker effect Verbal Stroop effect VS Stroop effect General Cognitive Abilities VS processing Matrix reasoning Vocabulary Number operations Verbal processing 2071.47 580.7 1916.78 328.81 2.780 1221.26 435.74 1017.35 308.9 5.166 <.001 60.667 4.95 62.6 61.7 112.4 8.125 63.533 17.047 115.8 4.223 −2.511 8.427 −2.483 15.624 −3.111 18.823 −1.467 .018 .019 .004 .153 Peabody Picture Vocabulary Test 110.467 14.277 112.567 0.490 0.674 0.798 0.514 0.649 0.500 0.991 0.517 0.235 0.440 0.316 −0.071 −0.016 0.251 0.225 −0.340 −0.548 0.421 0.221 0.208 0.127 .740 .949 .324 .306 .009 255.700 131219.000 8818.000 3573.000 385.700 23.720 405.000 7.597 0.419 3.322 2.917 0.199 0.205 0.195 0.308 0.319 4.726 1374.000 2.766 2.624 9.532 0.510 Cognitive Task with No Memory Load Emotion hexagon 89.806 8.704 89.698 8.212 0.088 .930 −0.013 0.195 Bold text indicates significant effect at p < .05 level; bold italics denote significant effects after family-wise correction for multiple comparison. active stimulation group ( p = .046), but this effect did not withstand correction for multiple comparisons (Table 4). Training-related differences between groups on all other measures were nonsignificant (see Figure 2). Bayesian re- gression analyses favored the null hypothesis with BF10 < 1 for all outcome measures, except verbal n-back. For this task BF10 = 1.695, providing equivocal support for the null and alternative hypotheses (Table 4). In summary, these an- alyses provide no strong evidence that stimulation enhances performance beyond training alone on any outcome measure. 1478 Journal of Cognitive Neuroscience Volume 28, Number 10 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 8 / 1 2 0 8 / 1 1 4 0 7 / 1 1 1 4 9 7 5 1 1 / 3 1 2 7 7 8 o 5 c 4 n 3 _ 5 a / _ j 0 o 0 c 9 n 9 3 _ a p _ d 0 0 b 9 y 9 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j f . t / u s e r o n 1 7 M a y 2 0 2 1 n a i s e y a B n o i s s e r g e R 0 1 F B p t n i n o s i r a p m o C p u o r G s n i a G g n n i i a r T a t e B ’ d s n e h o C p t D S M D S M D S M D S M p u o r G e n i l e s a B s n o s i r a p m o C g n i n i a r t t s o P g n i n i a r t e r P g n i n i a r t t s o P g n n i i a r t e r P p u o r G m a h S p u o r G n o i t a u m l i t S 7 2 . 0 3 2 2 . 0 9 4 2 . 0 1 8 3 . 0 1 3 2 . 0 3 4 2 . 0 3 7 4 . 0 3 2 3 . 0 5 9 6 . 1 7 3 3 . 0 6 8 2 . 0 2 2 3 . 0 5 4 3 . 0 4 1 5 . 0 1 8 3 . 0 3 4 . 0 7 1 3 . 9 1 0 . 1 − 0 1 1 . 0 − 9 2 0 . 0 7 3 9 . 0 8 0 . 0 3 2 7 . 6 1 7 6 6 . 6 0 1 2 2 3 . 6 1 0 0 6 . 0 0 1 4 6 2 . 5 1 7 6 4 . 0 1 1 6 9 6 . 5 1 7 6 0 . 1 0 1 3 4 3 . 6 6 9 . 0 − 3 9 0 . 0 − 9 2 1 . 0 − 6 2 7 . 4 5 3 . 0 − 1 0 7 . 0 2 3 3 3 . 9 1 1 4 6 0 . 2 2 7 6 6 . 6 0 1 6 7 6 . 3 2 7 6 8 . 0 2 1 3 1 3 . 3 2 3 3 7 . 3 0 1 l l a c e r t i g i D x i r t a m t o D 4 6 5 . 4 8 5 . 0 4 7 0 . 0 7 3 0 . 0 − 9 1 9 . 2 0 1 . 0 − 7 3 1 . 5 1 3 3 5 . 6 1 1 2 8 2 . 9 1 3 3 7 . 1 0 1 5 9 . 5 1 7 6 8 . 3 1 1 8 7 0 . 0 2 0 0 0 . 1 0 1 l l a c e r t i g i d d r a w k c a B 9 5 7 . 0 1 3 . 0 − 0 4 0 . 0 − 3 7 6 . 6 2 4 . 0 7 5 0 . 0 7 2 6 . 1 9 4 . 0 − 2 9 0 . 0 − 1 5 0 . 0 2 1 4 . 0 0 5 5 . 0 5 9 8 . 3 3 1 . 0 5 9 9 . 1 7 6 8 . 8 1 6 9 . 0 3 3 9 . 7 6 8 4 . 1 7 6 0 . 9 0 9 6 . 1 0 0 0 . 8 3 7 2 . 9 1 1 . 1 6 4 8 . 1 7 6 8 . 7 4 6 4 . 1 0 0 0 . 7 9 9 6 . 1 0 0 2 . 8 5 2 1 . 1 3 3 5 . 7 4 4 1 . 4 0 5 . 1 2 5 5 . 1 7 6 8 . 7 2 4 6 . 1 3 3 1 . 6 9 4 5 . 1 0 0 4 . 8 2 1 5 . 1 0 0 0 . 7 3 5 9 . 9 5 0 . 0 0 1 0 . 0 3 7 2 . 0 − 1 6 4 . 8 4 7 . 0 − 7 6 1 . 2 3 3 5 . 7 8 1 7 . 1 7 6 6 . 6 9 9 6 . 1 0 0 2 . 7 9 9 6 . 1 0 0 2 . 6 9 3 1 . 3 2 5 . 1 6 3 1 . 0 1 5 2 . 0 − 5 0 5 . 5 7 6 . 0 − 4 7 9 . 2 1 0 0 8 . 8 1 1 7 8 2 . 5 1 7 6 8 . 7 0 1 7 6 6 . 9 1 7 6 6 . 0 1 1 7 4 2 . 2 2 3 3 1 . 3 0 1 e g a r o t s l a b r e V e g a r o t s S V d r a w k c a b l a b r e V d r a w k c a b S V X r M s k s a T y r o m e M c i f i c e p s - s s e c o r P 6 4 0 . 8 8 0 . 2 − 1 1 3 . 0 − 9 5 1 . 0 − 8 6 6 . 4 3 4 . 0 − 6 2 4 . 2 3 3 6 . 3 8 4 . 0 − 7 7 0 . 0 − 6 1 5 . 0 − 9 9 1 . 5 1 3 . 1 − 6 1 4 . 2 0 0 8 . 4 7 6 4 . 4 1 5 7 . 1 7 6 0 . 5 4 0 1 . 2 0 0 0 . 6 2 1 6 . 1 0 0 8 . 4 1 8 9 . 1 3 3 9 . 3 3 7 3 . 1 0 0 2 . 4 2 6 8 . 0 0 0 2 . 3 k c a b n - l a b r e V k c a b n - S V 0 9 0 . 7 5 7 . 1 8 0 2 . 0 5 4 5 . 3 1 6 . 0 9 8 0 . 0 3 2 4 . 0 3 7 0 . 0 4 7 2 . 6 1 1 . 1 6 4 6 . 2 0 0 0 . 7 0 2 8 . 2 7 6 6 . 5 1 4 5 . 2 0 0 8 . 6 5 9 5 . 1 0 0 6 . 6 n a p s l x e p m o c l a b r e V 9 4 8 . 3 9 1 . 0 1 5 7 . 1 3 3 7 . 4 4 2 3 . 2 0 0 6 . 4 6 8 3 . 2 7 6 4 . 4 5 3 3 . 1 3 3 7 . 4 n a p s l x e p m o c S V s k s a T y r o m e M c i f i c e p s - s s e c o r p – n o N 6 8 8 . 4 4 1 . 0 4 2 0 . 0 2 2 2 . 0 − 9 7 5 . 1 6 5 . 0 − 2 8 8 . 9 8 2 5 4 . 4 8 0 5 2 . 1 4 8 9 9 . 5 8 8 8 2 . 0 3 6 9 1 . 4 7 8 1 7 . 6 1 1 5 5 . 9 7 t c e f f e r e k n a l F l a b r e V 1 1 3 . 3 3 0 . 1 − 5 0 2 . 0 − 3 8 6 . 0 − 8 8 0 . 6 6 7 . 1 − 3 0 6 . 8 6 3 8 8 . 3 6 4 1 6 . 4 9 1 9 0 . 9 9 5 7 1 . 5 6 8 7 1 . 4 8 7 6 4 . 5 4 9 3 2 . 1 5 t c e f f e r e k n a l F S V 0 7 7 . 6 9 2 . 0 − 9 5 0 . 0 − 4 3 6 . 0 − 6 4 1 . 7 9 4 . 1 − 1 7 9 . 6 6 8 7 7 . 1 7 4 5 3 . 4 7 1 4 6 1 . 8 7 2 9 1 . 4 8 1 0 5 7 . 1 8 4 2 3 . 5 4 4 3 5 . 8 t c e f f e p o o r t S l a b r e V 6 3 6 . 9 7 4 . 0 − 5 8 0 . 0 − 8 1 2 . 0 6 7 5 . 6 6 5 . 0 4 8 9 . 1 9 6 2 9 . 0 3 1 3 5 7 . 7 8 5 8 2 . 7 1 1 6 9 9 . 5 3 1 8 8 2 . 9 5 1 7 9 6 . 3 4 0 0 6 . 1 3 1 t c e f f e p o o r t S S V M W h t i w d e t a i c o s s A s e s s e c o r P p u o r G y b s t c e f f E n o i t a l u m i t S d n a i g n n i a r T . 4 e l b a T Holmes et al. 1479 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 8 / 1 2 0 8 / 1 1 4 0 7 / 1 1 1 4 9 7 5 1 1 / 3 1 2 7 7 8 o 5 c 4 n 3 _ 5 a / _ j 0 o 0 c 9 n 9 3 _ a p _ d 0 0 b 9 y 9 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t / f . u s e r o n 1 7 M a y 2 0 2 1 n a i s e y a B n o i s s e r g e R 0 1 F B p t n i n o s i r a p m o C p u o r G s n i a G i g n n i a r T a t e B ’ d s n e h o C p t D S M D S M D S M D S M p u o r G e n i l e s a B s n o s i r a p m o C g n i n i a r t t s o P g n i n i a r t e r P g n i n i a r t t s o P g n n i i a r t e r P p u o r G m a h S p u o r G n o i t a u m l i t S ) d e u n i t n o c ( . 4 e l b a T y t i l i b A e v i t i n g o C l a r e n e G 4 4 2 . 0 4 7 1 . 0 1 4 3 . 0 5 3 1 . 0 7 2 . 0 4 1 1 . 0 1 8 1 . 4 7 3 . 1 1 0 1 . 0 6 1 5 . 0 − 5 6 2 . 7 3 1 . 1 − 9 5 9 . 9 3 4 4 9 5 . 0 1 0 2 6 6 0 . 8 0 8 4 5 4 . 1 9 1 2 4 8 3 . 7 0 1 1 7 9 . 2 2 8 1 4 7 1 . 1 2 1 7 8 4 . 1 5 9 1 g n i s s e c o r p l a b r e V 9 2 6 . 9 8 4 . 0 9 7 0 . 0 0 8 5 . 0 3 2 1 . 9 8 5 . 1 8 7 6 . 4 0 0 2 . 2 6 3 0 8 . 4 7 6 2 . 9 5 6 3 8 . 3 0 0 0 . 3 6 7 4 8 . 4 7 6 0 . 2 6 9 3 8 . 6 0 2 . 0 9 1 0 . 0 4 5 1 . 0 − 7 7 6 . 1 2 4 . 0 − 2 6 2 . 9 7 6 2 . 4 6 9 6 0 . 9 3 3 3 . 2 6 7 5 7 . 7 0 0 8 . 2 6 4 2 3 . 7 7 6 0 . 1 6 8 2 4 . 5 0 8 . 0 2 7 0 . 0 9 9 3 . 0 − 0 3 3 . 2 9 9 . 0 − 0 3 5 . 3 9 3 7 1 1 . 8 8 0 1 5 3 1 . 8 7 5 6 8 1 . 0 0 3 1 4 3 0 . 9 7 1 4 8 5 . 6 4 9 8 8 7 . 3 1 2 6 3 3 . 2 4 1 1 i g n n o s a e r x i r t a M g n i s s e c o r p S V y r a l u b a c o V 7 3 1 . 4 3 5 . 1 − 9 9 0 . 0 − 2 6 0 . 0 − 7 6 8 . 8 6 1 . 0 − 8 8 8 . 6 1 3 3 7 . 4 1 1 5 8 . 5 1 3 3 9 . 2 1 1 4 6 7 . 4 1 7 6 8 . 6 1 1 2 1 7 . 8 1 7 6 8 . 1 1 1 s n o i t a r e p O r e b m u N 3 3 6 . 3 8 4 . 0 − 6 3 0 . 0 − 7 0 3 . 0 − 1 4 . 4 8 . 0 − 0 8 7 . 0 2 0 0 6 . 4 1 1 2 4 3 . 5 1 7 6 6 . 2 1 1 5 2 1 . 7 1 3 3 5 . 0 1 1 5 8 2 . 3 1 7 6 2 . 8 0 1 t s e T y r a l u b a c o V e r u t c i P y d o b a e P 3 7 3 . 0 8 3 3 . 6 7 9 . 0 − 4 3 1 . 0 − 1 2 2 . 0 − 0 5 5 . 5 0 6 . 0 − 0 4 9 . 7 2 6 2 . 9 8 9 8 3 . 8 8 7 7 . 0 9 2 3 7 . 8 5 3 1 . 0 9 3 9 1 . 9 3 3 8 . 8 8 n o g a x e h n o i t o m E d a o L y r o m e M o N h t i w k s a T e v i t i n g o C . l e v e l 5 0 . < p t a t c e f f e t n a c i f i n g i s s e t a c i d n i t x e t d l o B 1480 Journal of Cognitive Neuroscience Volume 28, Number 10 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 8 / 1 2 0 8 / 1 1 4 0 7 / 1 1 1 4 9 7 5 1 1 / 3 1 2 7 7 8 o 5 c 4 n 3 _ 5 a / _ j 0 o 0 c 9 n 9 3 _ a p _ d 0 0 b 9 y 9 g 3 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t f . / u s e r o n 1 7 M a y 2 0 2 1 reversing a sequence of digits or rotating a sequence of spatial items 90°). No training-related enhancements were found on transfer tests of working memory that involved switching between the storage of memory items and an unrelated processing activity (complex span). There was a small training gain on a VS n-back task in- volving the continuous updating and recognition of a set of items. Although this did not survive a correction for multiple comparisons, Bayesian analyses suggested that there was positive but not strong evidence for this effect. There was no evidence for transfer to a verbal n- back task. On balance, this pattern of effects is consistent with previous reports that training induces the learning of task-specific strategies that do not generalize to other categories of working memory task (Dunning & Holmes, 2014; von Bastian & Oberauer, 2013). There was also no evidence for more distant transfer of working memory training without stimulation to tests of nonverbal reasoning and language ability. Small gains were observed on a test of mathematical ability (three standard score points) and short increases in speed of responses on tests of verbal and VS information pro- cessing were also found, but in the absence of a no- intervention test–retest control group, it is impossible to determine whether these reflect genuine training ben- efits or repetition effects. This pattern of far transfer effects is largely consistent with the working memory training literature, which provides no consistent evidence that training alone ameliorates the everyday difficulties associated with working memory such as problems in attentional focus and learning (Holmes et al., 2015; Dunning et al., 2013; Shipstead et al., 2012; see Simons et al., in press, for a review). Crucially, the results of the current experiment dem- onstrate that tRNS does not extend the limited transfer found with working memory training. In line with pre- vious studies that have combined working memory train- ing with a different stimulation technique, tDCS, there were no differences in performance between the active tRNS and sham stimulation groups on any of the transfer tests (Richmond et al., 2014; Martin et al., 2013). Together the results of these studies provide no evidence to sup- port the use of combining training with stimulation as a therapeutic tool to improve working memory function. There was also no evidence that stimulation modu- lated the speed of learning or magnitude of gains on the training tasks. These results provide a challenge to the hypothesis that tRNS provides a global facilitation in brain plasticity when combined with a learning task (e.g., Cohen Kadosh, Levy, O’Shea, Shea, & Savulescu, 2012). They are also inconsistent with findings in another cognitive domain, suggesting that tRNS enhances learn- ing when coupled with mathematics training (Cappelletti et al., 2013; Snowball et al., 2013). This may reflect differ- ences in the impact of tRNS on the different interventions, resulting from the malleability of the neural substrates tar- geted by the working memory and mathematical training Holmes et al. 1481 Figure 2. Changes in process-specific (A) and non–process-specific (B) memory tasks by group. Mean effect sizes are displayed. General linear regression models revealed no significant differences in how the groups responded to training (all ps > .6; Tisch 3), demonstrating that
stimulation did not enhance transfer to untrained tests of memory.

DISKUSSION

This randomized controlled trial provides the first test of
the potential additive benefits of combining tRNS with
working memory training. An effective training program
(Schwaighofer et al., 2015) was employed in conjunction
with stimulation parameters that have been used to en-
hance training gains in another cognitive domain (Snowball
et al., 2013). tRNS did not enhance the rate, magnitude, oder
degree of transfer of working memory training in an active
stimulation group relative to a sham group. Strong train-
ing gains were found on trained activities in participants
irrespective of stimulation condition, and as in previous
Forschung, these effects extended to transfer tests with pro-
cessing and storage demands in common with the train-
ing activities (Melby-Lervåg & Hulme, 2013; von Bastian &
Oberauer, 2013; Dahlin et al., 2008).

Im Gegensatz, on memory tests with minimal overlap
with the training activities there was little evidence for
the benefits of training alone. The training tasks involved
practice on serial memory paradigms that required either
the reproduction of a sequence of verbal or VS items, oder
mental manipulation of the items prior to recall (z.B.,

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Programme, and the complexity of the training programs and
their doses. Future research needs to develop a greater
understanding of the neurophysiological underpinnings
of stimulation and the impact of different stimulation pro-
tocols when applied to different scalp regions and com-
bined with different training regimes. Candidate factors
for further investigation include the type, duration and in-
tensity of stimulation (Batsikadze, Moliadze, Paulus, Kuo, &
Nitsche, 2013; Monte-Silva, Kuo, Liebetanz, Paulus, &
Nitsche, 2010), the timing of stimulation relative to the
Aufgabe (Pirulli et al., 2013), individual differences in brain
anatomy (Opitz, Paulus, Will, Antunes, & Thielscher, 2015),
and the functional state of the brain during stimulation (Ein-
tal, Terney, Poreisz, & Paulus, 2007).

New interventions that promise cognitive enhancement
such as working memory training and brain stimulation are
appealing to the scientific community, practitioners, Und
the general public alike, generating high levels of interest
and intense research activity. Their history also shows that
they are marked by high levels of early positive results that
are typically not sustained over longer periods, probably
because of publication bias (Dwan, Gamble, Williamson,
& Kirkham, 2013; Scherer, Langenberg, & von Elm,
2007). At this relatively early point in the brain stimulation
research field, the clear conclusion from this study is that,
when using the most rigorous intervention design and
combining training and stimulation protocols that have
been shown to be effective in other domains, es gibt kein
evidence that tRNS targeting bilateral DLPFC enhances the
benefits of Cogmed Working Memory Training.

Reprint requests should be sent to Dr. Joni Holmes, Cognition
& Brain Sciences Unit, MRC, 15 Chaucer Road, Cambridge,
United Kingdom of Great Britain and Northern Ireland, CB2
7EF, oder per E-Mail: joni.holmes@mrc-cbu.cam.ac.uk.

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Holmes et al.

1483 Transcranial Random Noise Stimulation Does Not Enhance image

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