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Noise is typically conceived of as being detrimental to cognitive performance. However, given the mechanism of stochastic resonance, a certain amount of noise can benefit performance. We investigate cognitive performance in noisy environments in relation to a neurocomputational model of attention deficit hyperactivity disorder (ADHD) and dopamine. The Moderate Brain Arousal model (MBA; Sikström & Söderlund, 2007) suggests that dopamine levels modulate how much noise is required for optimal cognitive performance. We experimentally examine how ADHD and control children respond to different encoding conditions, providing different levels of environmental stimulation. Participants carried out self-performed mini tasks (SPT), as a high memory performance task, and a verbal task (VT), as a low memory task. These tasks were performed in the presence, or absence, of auditory white noise. Noise exerted a positive effect on cognitive performance for the ADHD group and deteriorated performance for the control group, indicating that ADHD subjects need more noise than controls for optimal cognitive performance. The positive effect of white noise is explained by the phenomenon of stochastic resonance (SR), i.e., the phenomenon that moderate noise facilitates cognitive performance. The MBA model suggests that noise in the environment, introduces internal noise into the neural system through the perceptual system. This noise induces SR in the neurotransmitter systems and makes this noise beneficial for cognitive performance. In particular, the peak of the SR curve depends on the dopamine level, so that participants with low dopamine levels (ADHD) require more noise for optimal cognitive performance compared to controls.
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Listen to the noise: noise is beneficial for
cognitive performance in ADHD
¨ran So
Sverker Sikstro
and Andrew Smart
Department of Psychology, Stockholm University, Sweden;
Lund University Cognitive Science (LUCS), Sweden;
New York University, Department of Psychology, USA
Background: Noise is typically conceived of as being detrimental to cognitive performance. However,
given the mechanism of stochastic resonance, a certain amount of noise can benefit performance. We
investigate cognitive performance in noisy environments in relation to a neurocomputational model of
attention deficit hyperactivity disorder (ADHD) and dopamine. The Moderate Brain Arousal model
(MBA; Sikstro
¨derlund, 2007) suggests that dopamine levels modulate how much noise is
required for optimal cognitive performance. We experimentally examine how ADHD and control children
respond to different encoding conditions, providing different levels of environmental stimula-
tion. Methods: Participants carried out self-performed mini tasks (SPT), as a high memory perform-
ance task, and a verbal task (VT), as a low memory task. These tasks were performed in the presence, or
absence, of auditory white noise. Results: Noise exerted a positive effect on cognitive performance for
the ADHD group and deteriorated performance for the control group, indicating that ADHD subjects
need more noise than controls for optimal cognitive performance. Conclusions: The positive effect of
white noise is explained by the phenomenon of stochastic resonance (SR), i.e., the phenomenon that
moderate noise facilitates cognitive performance. The MBA model suggests that noise in the environ-
ment, introduces internal noise into the neural system through the perceptual system. This noise
induces SR in the neurotransmitter systems and makes this noise beneficial for cognitive performance.
In particular, the peak of the SR curve depends on the dopamine level, so that participants with low
dopamine levels (ADHD) require more noise for optimal cognitive performance compared to con-
trols. Keywords: ADHD, stochastic resonance, dopamine, episodic memory, SPT, noise. Abbrevia-
tions: MBA: moderate brain arousal; SR: stochastic resonance; SPT: subject-performed task; VT:
verbal task (VT).
Stochastic resonance is the counterintuitive phe-
nomenon that an optimal amount of noise may un-
der certain circumstances be beneficial for cognitive
performance. The purpose of this study is to examine
the effects of external auditive noise on performance
in an episodic recall task in children with attention
deficit hyperactivity disorder (ADHD). According to
the Moderate Brain Arousal (MBA) model (Sikstro
¨derlund, 2007), a neurocomputational model of
cognitive performance in ADHD, noise in the en-
vironment introduces internal noise into the neural
system through the perceptual system. This noise is
proposed to compensate for the reduced neural
background activity in ADHD and the hypofunc-
tional dopamine system (Solanto, 2002). The MBA
model predicts that noise enhances memory perfor-
mance for ADHD and attenuates performance for
controls. We will also argue for a link between the
effects of noise, dopamine regulation, and cognitive
ADHD is a developmental disorder characterized
by behavioral impairments in three domains: in-
attention, impulsivity, and hyperactivity. ADHD is
one of the most commonly diagnosed childhood
psychiatric disorders, affecting approximately 3–7%
(Castellanos & Tannock, 2002) of the childhood
population. A vast literature shows that handling
cognitive flexibility and rigidity during maintenance
of goal-directed behavior is difficult to manage for
ADHD children (Martinussen, Hayden, Hogg-Johnson,
& Tannock, 2005).
It has long been known that cognitive processing is
easily disturbed by noise and other distractors
(Broadbent, 1958). The mechanism behind this ef-
fect, in general terms, is that the distractor removes
attention from the target task. Research on this topic
since 1958 has demonstrated this finding to hold
across a wide variety of target tasks, distractors and
participant populations. Consistent with this, ADHD
children are regarded as more vulnerable to dis-
traction compared to normal controls (Corbett &
Stanczak, 1999) and several studies have demon-
strated results supporting this notion (e.g., Geffner,
Lucker, & Koch, 1996; Higginbotham & Bartling,
Two recent studies were, however, able to de-
monstrate the counterintuitive finding that under
certain circumstances participants could benefit
from noise and other task-irrelevant sounds pre-
sented concurrently with the target task. Abikoff,
Courtney, Szeibel, and Koplewicz (1996) showed that
children with ADHD were not distracted by back-
ground music, which can be considered as task-
irrelevant noise. Surprisingly, the results further
Conflict of interest statement: No conflicts declared.
Journal of Child Psychology and Psychiatry 48:8 (2007), pp 840–847 doi:10.1111/j.1469-7610.2007.01749.x
2007 The Authors
Journal compilation 2007 Association for Child and Adolescent Mental Health.
Published by Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA
showed a noise-induced improvement in perfor-
mance in the target (arithmetic) task. To the best of
our knowledge Abikoff’s finding has been replicated
just once, by Gerjets, Graw, Heise, Westermann, and
Rothenberger (2002), where noise was induced by
These studies, however, did not provide a satis-
factory theoretical account for why noise was
beneficial for performance. Here we suggest that the
phenomenon known as stochastic resonance can be
used to account for noise-induced improvement in
cognitive performance. Stochastic resonance (SR) is
the phenomenon that detection of a subthreshold
signal is enhanced by addition of noise in a non-
linear system. SR occurs in any system where
detection requires passing of a threshold, so that
the added noise allows for the combined noise and
signal to pass the threshold, permitting detection of
the signal (Moss, Ward, & Sannita, 2004). This
psychophysical phenomenon is present in biological
sensory systems in animals and humans (Russell,
Wilkens, & Moss, 1999). It has been found in sev-
eral modalities; tactile, hearing, and vision (see
Moss et al., 2004 for a review). The effect is not
restricted to sensory processing. Stochastic reson-
ance has been found in cognitive tasks where
auditory noise improved the speed of arithmetic
computations in a normal population (Usher &
Feingold, 2000). Stochastic resonance is usually
quantified by plotting detection, or cognitive per-
formance, as a function of noise intensity. This re-
lation exhibits an inverted U-curve, where
performance peaks at a moderate noise level. That
is, moderate noise is beneficial for performance
whereas too little, or too much, noise attenuates
performance (see Figure 1). After a review of noise
and cognition studies (e.g., Baker & Holding, 1993)
we suggest that, in order to induce the SR effect,
noise has to be continuous (in order not to be
attention-removing) and at a high energy level at all
frequencies, as in white or pink noise.
Stochastic resonance has been shown to be a
ubiquitous natural phenomenon (Moss et al., 2004).
In the brain, stochastic resonance plays an import-
ant role in dopamine signaling (Li, von Oertzen, &
Lindenberger, 2006). Dopamine modulates neural
responses and function by increasing the signal-
to-noise ratio (SNR) through enhanced differenti-
ation between background or efferent firing and
afferent stimulation. Dopamine thus produces a
suppressive influence on spontaneous activity,
explaining its apparent inhibitory actions, and sim-
ultaneously causes an enhanced excitability in re-
sponse to afferent-driven stimulation (J.D. Cohen,
Braver, & Brown, 2002). It has been suggested that
high activity of catecholamine neuromodulators in
prefrontal neurons is associated with a high SNR of
information processing (Kiefer, Ahlegian, & Spitzer,
2005). Thus, too low or too high neuromodulatory
activity results in a low SNR and worse cognitive
performance in such areas as working memory and
inhibitory control. That is, the relation between
cognitive performance and dopamine transmission
shows an inverted U-shaped curve where either too
high, or too low, levels attenuate performance
(Goldman-Rakic, Muly, & Williams, 2000). Conver-
ging evidence indicates that hypo- or dysfunctioning
catecholamine systems in the prefrontal cortex
(PFC), among other areas, are a central neurobiolo-
gical substrate of the cognitive and behavioral defi-
cits associated with ADHD (Arnsten & Li, 2005).
Based on neurocomputational modeling (Sikstro
¨derlund, 2007), we suggest that dopamine-
deprived neural systems, such as are thought to
occur in ADHD (Solanto, 2002) or in aging (Erixon-
Lindroth et al., 2005), require more noise to induce
SR (see Figure 1).
ADHD is believed to involve a hypofunctional
dopamine system (Solanto, 2002). The MBA model
assumes, consistent with earlier dopamine models
(Li & Sikstro
¨m, 2002; Servan-Schreiber, Printz, &
Cohen, 1990), that the level of dopamine is modu-
lated by the gain parameter in the sigmoid activa-
tion-function. A low dopamine level corresponds to a
low gain, yielding a relatively more linear input–
output relation in neural cells compared to high
dopamine and high gain. The neural system is
influenced by stochastic resonance as the signal
plus noise passes a threshold during generation of
action potentials. Neurocomputational simulations
by Sikstro
¨m and So
¨derlund (2007) showed that low
dopamine levels in ADHD subjects shift performance
on the stochastic resonance curve (inverted U-curve)
to the right, so that ADHD subjects, for a given noise
level, operate on the part of the curve where noise is
beneficial for performance whereas under the same
conditions controls operate on the part of the curve
where performance declines (see Figure 1). Input
with noise
with noise
Figure 1 ADHD needs more noise for optimal per-
formance compared to control. Note. The figure shows
the stochastic resonance phenomena where perform-
ance on cognitive tests (y-axis) is optimal for moderate
noise levels (x-axis), and attenuated for both too low
and too high noise levels. More noise is required for
optimal performance in low dopamine (ADHD) com-
pared to high dopamine (control) neural systems, where
dopamine modulates the gain in the sigmoid activation-
function. SPT has a higher SNR ratio (left side of the
figure) compared to VT (right side)
Listen to the noise 841
2007 The Authors
Journal compilation 2007 Association for Child and Adolescent Mental Health.
parameters to the model are external noise and
signal, which activate internal neural noise and sig-
nal. Through the SR phenomenon these provide an
output measured by cognitive performance. Thus,
these simulations provide a straightforward predic-
tion of noise-induced improvement in cognitive per-
formance for ADHD. The purpose of this paper is to
explicitly set up an experiment to test this novel
Because we were interested in investigating per-
formance for different signal and noise levels (map-
ping to different parts of the stochastic resonance
curve), we used four different encoding conditions.
The conditions were: external auditive noise vs. no
noise and high vs. low memory performance tasks.
Low memory performance is associated with a high
internal noise level whereas high memory perform-
ance is associated with a low internal noise level. The
external auditive noise activates the internal neural
noise and the internal noise influences performance
through the phenomenon of SR.
For the low noise, or high recall performance, we
used a self-performed task. The self-performed task
(SPT) paradigm is known to help focus attention by
means of enactment. SPT yields an efficient encoding
condition that requires few conscious strategies (R.L.
Cohen, 1981). Participants are presented with verbal
commands, simple verb–noun sentences such as
‘roll the ball’ or ‘break the match’. While these com-
mands are presented, participants are asked to
perform the action indicated by each command. At
the subsequent memory test, participants are
instructed to remember as many of the verbal com-
mands presented as possible. For the high noise, or
low recall performance, we used a verbal task (VT)
that includes the same type of verbal commands,
and the same study time, as in the SPT condition
except that they are presented to the participant
without any instructions to perform any actions.
Results from experiments using this paradigm are
very stable; memory performance after enacted
phrases (SPT) is consistently superior to the ones
without enactment (VT) and is generally referred
to as the SPT effect (see Nilsson, 2000, p. 137 for a
The MBA model predicts that cognitive perform-
ance in ADHD children benefits from noisy environ-
ments because the dopamine system modulates the
SR phenomenon. It suggests that the stochastic
resonance curve is right shifted in ADHD due to
lower gain or lower dopamine. The MBA model pre-
dicts that for a given cognitive task ADHD children
require more external noise or stimulation, com-
pared to control children, in order to reach optimal
(i.e., moderate) brain arousal level. However, in the
high noise condition (VT task) performance will be
near the peak for ADHD children whereas controls
will operate on the part of the SR curve where there is
too much noise for optimal performance. That is,
noise will attenuate performance for controls but not
for ADHD children. In the low noise condition (SPT
task) ADHD children will operate on the part of the
SR curve where noise is beneficial for performance,
whereas controls operate near the peak. That is, in
the SPT condition noise will increase performance for
ADHD children but not for controls. Each participant
is exposed to four conditions: white auditory noise
and a control condition without noise during SPT
and VT encoding.
Forty-two children, aged 9.4–13.7 years, participated in
the study. The ADHD group consisted of 21 boys and no
girls. This group was diagnosed by pediatricians (in
hospitals or local neuro-teams) according to the guide-
lines of DSM-IV (APA, 1994). Fifteen of the children
were diagnosed ADHD-combined type (ADHD-C) and
six as predominantly inattentive (ADHD-I). Diagnoses
were given 1–4 years prior to the experiment and the
children were 6–11 years old at the time of diagnosis
(M ¼8.1 yrs). An interview based on Conner’s rating
scale for teachers confirmed, in all cases, the diagnostic
distinction between ADHD-C and ADHD-I at the time of
the experiment.
Although most of the participants (14) did not use
medication, a smaller group (7) of the ADHD children
used methylphenidate, supplied for one month or lon-
ger (see Table 1). The medicated children comprised the
ADHD-C group in six cases; only one child in the
ADHD-I group was given medication. The medication
was administered in the morning; three of the children
also got an additional dose during the day. For ethical
and practical reasons, the medicated children remained
on medication and the test was conducted in the
morning during a normal school day. The participants
used no other types of medication. To control for poss-
ible confounding effects, the medicated and non-
medicated groups were analyzed separately. We focus
on the non-medicated participants. Further co-dia-
gnoses such as conduct disorder and mental retarda-
tion were used as exclusion criteria. The ADHD children
attended either regular school in small separate groups
(10 children) or schools for children with special needs
(11 children).
The control group was matched to the ADHD group
on the basis of four inclusion criteria; district (controls
were chosen from the same area as the experimental
Table 1 Participant characteristics
School performance
Medicated N Age (SD) (1) (2) (3) (M)
ADHD (no med.) 14 11.2 (1.2) 2 9 3 (2.1)
ADHD (tot) 7 21 11.2 (1.1) 3 13 5 (2.1)
Control 21 11.2 (1.1) 3 12 6 (2.1)
Note. Only boys were tested. School performance was judged
by teachers as: 1 ¼below average, 2 ¼average, or 3 ¼above
average. Medication was Methylphenidate or equivalent.
842 Go
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¨derlund, Sverker Sikstro
¨m, and Andrew Smart
2007 The Authors
Journal compilation 2007 Association for Child and Adolescent Mental Health.
group), gender (boys), age (months), and school per-
formance (teacher ratings). Teachers made a judgment
of school performance on three levels; average, above
average and below average, based on what is expected
for the age according to the curriculum (see Table 1).
Teachers’ school performance ratings corresponded
well with the earlier WISC scores obtained at the time of
the ADHD diagnosis. IQs below 80 were excluded.
Teacher interviews confirmed that all control children
were well within the normal range on the Conner rating
scale and intelligence was within a normal range. The
study was conducted at participants’ schools following
permission from parents, headmasters, and approval of
the local ethics committee at the Department of Psy-
chology, Stockholm University.
The design was a 2 ·2·2, where type of encoding
(subject performed task vs. verbal task) and noise (no
noise versus noise) were the within-subject manipula-
tions and the between-group variable was ADHD versus
The to-be-remembered (TBR) items consisted of 96
sentences divided into 8 separate lists with 12 verb–
noun sentences in each list. Each sentence consisted of
a unique verb and a unique noun (e.g., ‘roll the ball’).
The sentences were placed in random order. All to-be-
remembered sentences were recorded on a CD. In the
no noise conditions the sentences were read in silence
and in the noise conditions they were read in the
presence of white noise. The equivalent continuous
sound level of the white noise and the speech signal was
81 and 80 dB (A), respectively. Thus, the signal-to-
noise ratio was )1 dB. The noise level was set in
accordance with earlier studies where an effect of SR on
cognition (arithmetic) was obtained for a normal popu-
lation (Usher & Feingold, 2000) and on working memory
for Alzheimer patients (Belleville, Rouleau, Van der
Linden, & Collette, 2003). Recordings were made in a
sound studio.
Participants were tested individually before lunch. The
experiment lasted for about 45 minutes. First, two
training sentences were presented. There were 4 condi-
tions; SPT, SPT + noise, VT, and VT + noise. SPT/VT
conditions comprised every second list and noise or no
noise was used during every second SPT/VT encoding
condition. The encoding conditions (SPT/VT, no noise/
+noise) were counterbalanced across participants so
that each list was present in every condition equally
many times. List-order (1–8) and condition-order (SPT/
VT and no noise/+noise) were also counterbalanced.
Participants sat at a table screened off from a part of the
table where the to-be-remembered objects were placed.
The items in the SPT conditions required one or two
physical objects. These objects were given to particip-
ants at the time of presentation of the sentence (spoken
as commands to the participants) and were then hidden
behind a screen after the actions had been performed.
The rate of presentation was the same for all conditions
and controlled by the recording on the CD. A new sen-
tence was read every 9th second. Time taken to present
each list of 12 sentences was approximately 1 minute
and 40 seconds. Directly after presentation of the last
item in a list, participants performed a free-recall test in
which they spoke out loud as many sentences as poss-
ible, in any order. Recall time was measured and the
maximum allowed time was 2 minutes.
Recall performance
A2·2·2 mixed ANOVA was conducted with one
between-subject factor, Group (ADHD vs. Control)
and two within-subjects factors, encoding condition
(SPT vs. VT) and noise (no noise vs. +noise). Con-
sistent with earlier SPT studies, strict scoring was
used for the nouns (exact matches were required)
and lenient scoring was used for the verbs (exact
matches not required).
There was a main effect of encoding, where SPT
outperformed VT (F(1,33) ¼45.85, p¼.000, eta
.58). The interaction between group and noise was
also significant (see Figure 2, F(1,33) ¼5.73, p¼
.023, eta
¼.15). No other main effects or inter-
actions were found. When medicated children were
included in the assessment the interaction between
group and noise became stronger (F(1,40) ¼8.41,
p¼.006, eta
Table 2 shows means and standard deviations for
the proportion of correctly recalled items divided into
group, medication, noise level, and encoding condi-
tion. Consistent with our hypothesis, noise
enhanced performance for the ADHD group (M ¼.44
vs. .46) and impaired performance for the control
group (M ¼.47 vs. .43). Paired-sample t-tests were
conducted to test the predictions of SNR within
tasks. In the SPT conditions, consistent with the
prediction ADHD participants performed better with,
compared to without, noise, when all ADHD parti-
No Noise
Free Recall, Percent Correct
Interaction p = .023
Figure 2 Percentage correct answers in free recall as a
function of noise and group
Listen to the noise 843
2007 The Authors
Journal compilation 2007 Association for Child and Adolescent Mental Health.
cipants were included in the analysis (t(20) ¼2.56,
p¼.01, one-tailed); however, when only the
non-medicated children were included the result did
not reach significance but indicated a trend (t(13) ¼
1.59, p¼.07, one tailed). In the control group, noise
did not significantly influence SPT performance.
However, consistent with the prediction, the control
group performed significantly lower in VT + noise
compared to the VT condition (t(20) ¼)2.47, p¼
.01, one-tailed) whereas noise did not influence the
ADHD group in the VT noise condition. In summary,
the tests of our directed hypotheses were significant.
These tests are more precise tests of our predictions
than the three-way interaction between group, noise,
and encoding which was not significant (F(1,33) ¼
.49, p¼.49, eta
The most intriguing result in the present study is the
positive effect of white noise on performance for the
ADHD children. This noise effect was present in both
the non-medicated and medicated children. This
supports the MBA (Moderate Brain Arousal) model
¨derlund, 2007), suggesting that the
endogenous (neural) noise level in children with
ADHD is sub-optimal. MBA accounts for the noise-
enhancing phenomenon by stochastic resonance
(SR). The model suggests that noise in the environ-
ment introduces internal noise into the neural sys-
tem through the perceptual system. Of particular
importance, the MBA model suggests that the peak
of the SR curve depends on the dopamine level, so
that participants with low dopamine levels (ADHD)
require more noise for optimal cognitive performance
compared to controls.
Three ADHD models – cognitive-energetic (Ser-
geant, 2000), delay aversion (Sonuga-Barke, 2002b),
and optimal stimulation (Zentall & Zentall, 1983) –
argue that state factors have to be taken into account
when explaining deficits seen in ADHD. These state
factors could be conceptualized as arousal and
activation regulation and deficiencies that lead to
impairments in allocation of cognitive resources.
However, in contrast to MBA, none of these models
use stochastic resonance modulated by dopamine as
an explanatory framework to account for cognitive
performance in ADHD.
The cognitive-energetic model focuses on energetic
levels. For example, ISIs have been found to alter the
participants’ energetic state, where both over- and
under-arousal could be induced by the applied event
rate (Sergeant, 2000, 2005). As confirmatory evid-
ence, methylphenidate has been found to have the
same effect as an increased event rate, where both
are seen as state-regulating factors (van der Meere,
Gunning, & Stemerdink, 1999). Furthermore, ADHD
children show reduced P300 amplitudes to cues and
distractors (Banaschewski et al., 2003). Energetic
level can also be manipulated through cognitive load,
signal intensity and novelty (Sergeant, 2005). The
MBA model is consistent with this but also points
out the possibility of increasing energetic level
irrespective of task and improving cognitive
performance by the use of noise.
The optimal stimulation model (Zentall & Zentall,
1983) is a homeostatic model, suggesting that there
is an optimal level of stimulation toward which
organisms strive. It is argued that hyperactivity
stems from low levels of arousal and serves to
maintain an optimal arousal level. Hyperactivity,
impulsivity, and a short attention span should be
seen as a form of self-stimulation to achieve an
optimal arousal level. Behaviors supporting this view
are reward-seeking and stimulation-seeking behav-
iors often seen in ADHD (Zentall & Zentall, 1983).
More recent research has found that in the presence
of highly appealing toys ADHD children spent half as
much time attending to, and recalled less of, the
content in TV programs (Lorch et al., 2000). The MBA
model is consistent with the proposed need of
external stimulation in ADHD but elaborates on the
conditions when this stimulation will be beneficial.
In the delay aversion model attention is allocated
toward environmental stimulation that speeds up
the perceived passage of time. Intolerance of waiting
is manifested as a tendency to select an immediate
reward rather than a larger delayed reward (Sonuga-
Barke, 2002b). Altered reward processes in ADHD
(Sonuga-Barke, 2003) could be explained as a ceiling
effect due to an excessive phasic DA response to
novel stimuli. Delay aversion is found in over-sensi-
tivity to inter-stimulus intervals (Sonuga-Barke,
2002a), an increase in activity and inattention dur-
ing delay periods (van der Meere et al., 1999), and
avoidance of delay. This over-sensitivity to external
stimulation is suggested to be caused by an over-
Table 2 Proportion of items correctly recalled across encoding conditions and groups (SPT–VT, Noise–No noise, ADHD–Control,
Group N
Type of encoding
SPT (SD) SPT+noise (SD) VT (SD) VT+noise (SD)
ADHD 21 .47 (.12) .52 (.12) .40 (.12) .41 (.10)
ADHD-non-medicated 14 .47 (.11) .50 (.11) .40 (.15) .42 (.11)
ADHD-medicated 7 .49 (.14) .55 (.13) .39 (.06) .39 (.06)
Control 21 .52 (.14) .50 (.13) .42 (14) .35 (.13)
844 Go
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Journal compilation 2007 Association for Child and Adolescent Mental Health.
active alerting system in ADHD that makes behavi-
oral responses maladaptive to external demands
(Nigg & Casey, 2005). This view is complementary to
the MBA model, where prolonged ISIs produce in-
sufficient phasic responses generating too little do-
pamine, and resulting in a dysfunctional arousal
state (Sikstro
¨derlund, 2007).
The beneficial effects of noise in cognitive perfor-
mance for ADHD have not been considered earlier,
nor have these effects been systematically tested, in
the literature. Surprisingly few experiments have
explored the possibilities of stimulating participants
with noise and there are no theories about positive
effects of noise in the literature apart from SR ex-
periments referred to in the introduction. Most ex-
periments since Broadbent’s days deal with the
negative effects of noise and distraction. We know of
only two ADHD studies using noise stimulation;
however, neither of these invoked the concept of
stochastic resonance as an explanatory framework
nor are they theory driven, rather they refer to gen-
eral appeal or arousal. Abikoff et al. (1996) attrib-
uted the enhancing effect to increased level of
general appeal counteracting boredom, and Gerjets
and colleagues (Gerjets et al., 2002) to optimal
stimulation in line with the early optimal stimulation
theory (Zentall & Zentall, 1983).
However, research has shown enhancing effects of
white noise on non-clinical groups (90 dB) on simp-
ler, short-term memory tasks such as anagrams
(Baker & Holding, 1993) whereas speech noise was
detrimental. These noise effects also interacted with
other variables such as gender and time of the day
(Holding & Baker, 1987), which makes these results
equivocal. In simple addition tasks white noise
(80 dB) improved performance, in both elderly and
younger participants, as compared to a no-noise
condition (Harrison & Kelly, 1989). More recent ex-
periments providing white noise found no effect on
cognition in digit-span recall in comparison with
irrelevant speech, which attenuated performance
(Belleville et al., 2003; Rouleau & Belleville, 1996). In
Belleville et al.’s (2003) experiment a small, but non-
significant, increment was seen among older and
Alzheimer patients as compared with young particip-
ants using white noise (75 dB). Furthermore, extra
noise required in old age to induce SR was modeled
by Li and colleagues (2006). White noise also im-
proved performance in monkeys in a delayed task
experiment, whereas Mozart’s piano music was
found detrimental (Carlson, Rama, Artchakov, &
Linnankoski, 1997). In experiments were ecolo-
gically relevant noise was studied, effects on episodic
and semantic memory showed that both road traffic
noise (62 dB followed by 78 dB sequences) and
meaningful irrelevant speech were detrimental for
memory performance. Episodic memory was found
particularly vulnerable to noise and irrelevant
speech was most detrimental for memory perform-
ance. Under some conditions road traffic noise did
not interfere with memory recall at all (Boman, En-
marker, & Hygge, 2005). For example, in Zentall and
Shaw’s (1980) experiment high levels of speech noise
(69 dB) were detrimental for ADHD whereas low
levels (64 dB) were beneficial for cognitive perform-
ance. However, fan noise where the main energy is
below 1000 Hz did not have a positive effect on
ADHD children. Noise and signal levels were also
lower as in the present experiment (50dBHL, SNR
+10 dB) (Geffner et al., 1996). Stimulus levels in the
present experiment were placed according to earlier
studies that have found SR in cognitive tests (Usher
& Feingold, 2000).
In summary, the literature review above suggests
that noise has to be continuous (i.e., not attention-
removing) and at a high energy level at all fre-
quencies, for example white or pink noise, to induce
the SR effect. Furthermore, beneficial noise levels
may vary between groups, i.e., ADHD subjects, the
elderly and people with Alzheimer’s require more
noise to induce SR. In a follow-up experiment we will
manipulate noise levels under the hypothesis that
they have to be estimated on an individual basis, see
arguments below.
As the first paper studying the stochastic reson-
ance phenomenon in ADHD, there are limitations in
the current study that should be investigated in fu-
ture studies. For example, our study investigated
only two noise levels and two encoding conditions,
thus it would be interesting to include more levels so
that the entire stochastic resonance curve can be
mapped out. Further studies should also measure
individual dopamine levels, and study how these
levels correlate to symptom severity, intellectual
capacity and the required noise level. Medicated
participants responded as strongly to noise as non-
medicated participants. However, medication is a
confounding variable, and it would be interesting to
look for interaction between noise and medication
during noise exposure.
There are several clinical implications of the MBA
model. For example, it can be used to understand
shortcomings in cognitive functioning for patient
groups where changes in the dopamine system have
been identified. While noise affects children selecti-
vely, it can be used as a complement or as an alter-
native to medication in ADHD. Moreover, reinforced
cognitive processing by noise could have applied
implications for clinical groups, as well as for normal
populations. The MBA model may be used to create
appropriate and adaptive environments for ADHD
children, especially in school settings. White noise
can be replaced with more pleasant auditive stimu-
lation such as music or other pleasant sounds.
Klingberg and colleagues have attained remark-
able results with Robomemo, a computer game that
trains working memory (Klingberg et al., 2005). In
this context, the MBA model can serve as a tool for
tailoring individually adapted treatments for ADHD
children. Computerized training programs are
Listen to the noise 845
2007 The Authors
Journal compilation 2007 Association for Child and Adolescent Mental Health.
particularly interesting because crucial variables
can be manipulated easily and precisely. This pro-
vides us with the hope of creating long-term changes
as an alternative to short-term medications. Further
research will exploit the effect of white noise and
stochastic resonance in the context of learning and
Correspondence to
¨ran So
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Stockholm University, 106 91 Stockholm, Sweden;
Tel: ++46 8 16 38 76; Fax: ++46 8 15 93 42; Email:
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... Electrophysiological studies [4,7] and fMRI meta-analyses [8,9] also support the state of hypoarousal, leading to symptoms of ADHD. Several models have assumed that patients with ADHD benefit in cognitive performance from an increase in arousal, including the cognitive-energetic model [10], the stochastic resonance (SR) effect [11], and the moderate brain arousal (MBA) model [12]. For instance, the MBA model emphasizes that the required level of additional task stimulation depends on the Int. ...
... Public Health 2022, 19, 15391 2 of 14 hypoarousal of the dopamine system so that low arousal individuals (such as children with ADHD) need more noise to achieve optimal cognitive ability than their typically developing peers. There has been a growing volume of empirical research confirming that certain types of task-irrelevant stimulation improve the cognitive performance of children with ADHD, such as background noise during memory performance tasks [12], background music during reading comprehension tasks [13], extra pictures during an auditory continuous performance test (CPT) [14], and external vestibular stimulation during visual CPT tasks [15]. Thus, external stimuli might positively affect cognitive performance, especially for individuals with ADHD. ...
... Stochastic resonance (SR), a phenomenon wherein the response of a nonlinear system to a weak periodic input signal is optimized by the addition of a particular level of noise, has been widely demonstrated across various modalities [21]. The MBA model adopted this phenomenon to explain the importance of external white noise stimuli to the attentional performance of ADHD children; this model states that the SR curve is right-shifted in ADHD children due to lower dopamine and suggests that these children require more external white noise to compensate for reduced neural background activity to reach optimal brain arousal level [12]. White noise is a random mixture of audible frequencies that can improve the detection of simultaneously separated signals with equal power at each frequency. ...
Full-text available
Several models have tentatively associated improving attention-deficit/hyperactivity disorder (ADHD) symptoms with arousal and external environmental stimulation. In order to further clarify the relationships between ADHD symptoms, arousal, and external stimulation, this study focused on exploring the “simultaneous” effects of white noise on intrinsic attentional performance and extrinsic on-task behaviors in preschoolers with and without ADHD. By using the computerized task (K-CPT 2), 104 preschoolers, including 52 ADHD children and 52 typically developing (TD) children, were tested and analyzed for their intrinsic attention (such as detectability, omission errors, commission errors, and reaction time). Simultaneously, these preschoolers’ external on-task behaviors were recorded for analysis through systematic observation. This study showed that white noise could effectively improve attention performance, including enhancing the ability to differentiate non-targets from targets and decreasing omission errors. It could also reduce the extrinsic hyperactive behaviors of preschoolers with ADHD. The findings of this study highlighted that white noise stimulation is a beneficial non-pharmacological treatment for preschoolers with ADHD. In contrast, for TD preschoolers, the results of this study showed that the external white noise stimuli were not only unhelpful but also a burden.
... However, performance in other cognitive domains has failed to replicate these benefits, with outcomes in visual working memory, setshifting, and phonemic fluency tasks unchanged (Bottiroli et al., 2014;Herweg and Bunzeck, 2015), or even impaired (Herweg and Bunzeck, 2015). Moreover, investigations in school children have found improvements only in those diagnosed with attention-deficit/hyperactivity disorder (ADHD) and not healthy comparisons (Söderlund et al., 2007(Söderlund et al., , 2010(Söderlund et al., , 2016. These contrasting findings suggest any cognitive facilitation provided by white noise may be sensitive to both differences between tasks, and study cohorts. ...
... Our present results, where white noise increased response time in incongruent (high conflict/task load), but not congruent (low conflict/task load) trials may also be interpreted in this context. It is important to note that such distinctions may not apply to ADHD-diagnosed individuals, where improvements have been found in prefrontal domains such as working memory and response inhibition (Helps et al., 2014;Söderlund et al., 2016), likely due to physiological/neurochemical differences as outlined in the authors' moderate brain arousal hypothesis (Söderlund et al., 2007(Söderlund et al., , 2010(Söderlund et al., , 2016. ...
... From our present findings and previous literature, however, only a rudimentary understanding of the parameters by which these factors alter its influence can be proposed. Accordingly, its use in the context of psychiatric care should remain narrowly targetted to particular patient groups where benefit has been clearly described, such as children diagnosed with ADHD (Söderlund et al., 2007(Söderlund et al., , 2010(Söderlund et al., , 2016. Crucial areas for future research include examining how changes in stimulus intensities (outside of signal-to-noise ratios in auditory-based tasks) and cognitive tasks can modulate its influence on behavioural measures, alongside identifying the relevant alterations in underlying physiological processes through functional imaging methods (EEG, fMRI). ...
Full-text available
Auditory stimuli, encompassing a continually expanding collection of musical genres and sonic hues, present a safe and easily administrable therapeutic option for alleviating cognitive deficits associated with neuropsychological disorders, but their effects on executive control are yet to be completely understood. To better understand how the processing of certain acoustic properties can influence conflict processing, we had a large of cohort of undergraduate students complete the Stroop colour and word test in three different background conditions: classical music, white noise, and silence. Because of pandemic guidelines and the necessity to run the experiment remotely, participants also completed the Wisconsin card sorting test (WCST), so that the reliability and consistency of acquired data could be assessed. We found that white noise, but not classical music increased the response time difference between congruent (low conflict) and incongruent (high conflict) trials (conflict cost), hence impairing performance. Results from the WCST indicated that home-based data collection was reliable, replicating a performance bias reported in our previous laboratory-based experiments. Both the auditory stimuli were played at a similar intensity, thus their dissociable effects may have resulted from differing emotional responses within participants, where white noise, but not music elicited a negative response. Integrated with previous literature, our findings indicate that outside of changes in tempo and valence, classical music does not affect cognitive functions associated with conflict processing, whilst white noise impairs these functions in a manner similar to other stressors, and hence requires further research before its implementation into neuropsychiatric care.
... It was also claimed that background sound might release dopamine, which in turn improves cognitive performance . Similarly, Söderlund et al., (2007) explained the effect of music on performance by the stochastic resonance phenomenon, which suggests that signal detection can be improved by adding noise to the system. This is due the fact that signal detection requires passing a threshold, such that the noise together with the signal can pass the threshold. ...
... Not only music has a positive effect on performance among ADHD, but also white noise. For example, in the study conducted by Söderlund et al., (2007), children with ADHD performed a memory task under two conditions: white noise or no noise. The results showed that white noise improved performance in the ADHD group, while among the control group, it interfered. ...
Full-text available
Mind wandering (MW) reflects a situation in which the cognitive system is detached from the main task and involved with inner thoughts. It has been well document that music and other background sounds can have positive effects on number of cognitive functioning. In addition, other body of literature suggests that background sounds might have specifically positive effect on individuals with more attention deficiencies. Hence, the current study examines the effect of background sounds on MW. In two experiments, the effect of background sounds: music (Experiment 1) or an alerting tone (Experiment 2) while performing sustained attention tasks was examined among typical development participants with different severity of attention deficiency. Background sounds were found to reduce MW especially in individuals with more ADHD symptoms. This was further discussed in the context of several theories, and it was suggested that background sound might be used as a tool for MW reduction.
... Brown (2005) suggests the use of headphones that play white noise or soft music to block out distracting sounds. In fact, white noise has found to have positive effects on the memory and verbal task performance of children with ADHD (Söderlund, Sikström & Smart, 2007). Preference towards rock may also be related to its rhythmical clarity and fast tempi, affecting positively on arousal. ...
Conference Paper
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ADHD symptoms increase poor school and academic functioning, risk for dropping out school, social problem such as peer rejection, aggression, and have negative effects on self-esteem. During the last ten years computer-mediated and game-based learning has become a growing area of interest in studying these children's learning. With games or game-like tasks, reduction of off-task, disruptive behavior and improvement has been found in mathematics and reading. In music therapy contexts, music has been shown to have positive effects on executive functions. Moreover, music making may work as a motivating real-life activity especially when it is provided in a game context. The current study describes recent findings and features of cognitive support, computer-mediated and game-based activities, as well as musical features, which are essential in designing a learning environment for children with ADHD. The structure of the musical games (JamMo orientation games 7-12) targeted to children with ADHD of 7 to 12 years of age, is described as well as the pedagogic use of these games in social contexts, to enhance social inclusion. .
... On the one hand, some studies suggest that noise can severely impair children's cognitive abilities as it can cause an attentional burden and interfere with short-term memory 22,28−30 . On the other hand, some studies conducted in laboratory settings suggest that a moderate level of ambient noise is likely to enhance creative performance as it can activate abstract cognition 19,31,32 . Thus, there is no clear understanding of how noise may affect children's academic performance in developed countries. ...
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Many cities across the developing world are witnessing high noise pollution due to infrastructure development and construction works. Despite rising noise pollution, large-scale empirical research on the impact of noise on learning has been sparse. We fill this research gap by investigating whether noise pollution can influence student performance. Leveraging spatial-and-temporal variation in the noise pollution recorded by the monitoring stations within major cities in India and the academic performance in Class 12 examinations across schools located within these cities, we find that a ten percentage-point increase in noisy days in the January-March quarter increases the failure percentage of Class 12 boys by 6.1 percent. This pattern is not gender-neutral, as no association is observed between noise pollution and the academic performance of Class 12 girls. Furthermore, we find no effect of noise pollution recorded in the months away from examination days. Leveraging the variation in schools’ proximity to the nearest noise monitoring station, we find that the association between noise pollution and academic performance is strongest when the schools are located within close proximity of the nearest noise monitoring station. For schools located within 1 km of the nearest noise monitoring station, we find that a ten percentage-point increase in noisy days in the January-March quarter increases the failure percentage of Class 12 boys by 11.3 percent. We explore and discuss three potential mechanisms that can drive the noise-learning relationship. Our findings are consistent with one of them: noise pollution hurts attention when the cognitive burden of students to perform well in examinations is high. Evidence from the data rules out the possibility of poorer quality schools selecting into locations with higher noise as the mechanism driving the observed effect of noise pollution on academic performance. Our findings also rule out the possibility that economic growth by itself can trigger attention depletion that can explain the negative effect of noise pollution on academic performance. Overall, we show that noise pollution has an adverse impact on student performance, and this relationship is driven by the cognitive burden mechanism rather than selection or economic growth mechanisms.
Adjunctive strategies that effectively incorporate adolescents’ developmental needs may augment the therapeutic benefits of cognitive behavioral therapy (CBT) for adolescents with attention deficit hyperactivity disorder (ADHD). This preliminary study evaluated a combined CBT and music-based treatment designed to enhance emotion-regulation skills in adolescents with ADHD. Utilizing a single-case experimental design, eight adolescents with ADHD were assigned to a 3-week baseline assessment phase followed by 12 weekly individual sessions of treatment and a 2-month follow-up phase. The intervention was effective in reducing the core symptoms of ADHD, such that, participants showed an increase in adaptive emotion-regulation strategies (cognitive reappraisal) and decrease in maladaptive emotion-regulation strategies (expressive suppression). The intervention was also found to be highly acceptable to participants. The findings provide initial support for combining standard CBT with music-based treatment designed to enhance emotion-regulation skills, and add to the growing body of literature showing that adjunctive strategies can augment the therapeutic benefits of CBT for adolescents with ADHD.
In those moments when focus on creative work overrides input from the outside world, we are in a creative trance. This psychologically significant altered state of consciousness is inherent in everyone. It can take the form of daydreams generating scientific or creative ideas, hyperfocus in sports, visualizations that impact entire civilizations, life-changing audience experiences, or meditations for self-transformation that may access states beyond trance, becoming gateways to transcendence. Artist and psychologist Tobi Zausner shows how creative trance not only operates in scientific inventions and works of art in all media, but is also important in creating and recreating the self. Drawing on insights from cognitive neuroscience, clinical psychology and post-materialist psychology, this book investigates the diversity of the creative trance ranging from non-industrial societies to digital urban life, and its presence in people from all backgrounds and abilities. Finally, Zausner investigates the future of trance in our rapidly changing world.
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Noise is often considered a distractor; however recent studies suggest that sub-attentive individuals or individuals diagnosed with attention deficit hyperactivity disorder can benefit from white noise to enhance their cognitive performance. Research regarding the effect of white noise on neurotypical adults presents mixed results, thus the implications of white noise on the neurotypical population remain unclear. Thus, this study investigates the effect of 2 white noise conditions, white noise level at 45 dB and white noise level at 65 dB, on the cognitive performance, creativity, and stress levels of neurotypical young adults in a private office space. These conditions are compared to a baseline condition where participants are exposed to the office ambient noise. Our findings showed that the white noise level at 45 dB resulted in better cognitive performance in terms of sustained attention, accuracy, and speed of performance as well as enhanced creativity and lower stress levels. On the other hand, the 65 dB white noise condition led to improved working memory but higher stress levels, which leads to the conclusion that different tasks might require different noise levels for optimal performance. These results lay the foundation for the integration of white noise into office workspaces as a tool to enhance office workers’ performance.
Understanding the origins and maintenance of cognitive variation in animal populations is central to the study of the evolution of cognition. However, the brain is itself a complex, hierarchical network of heterogeneous components, from diverse cell types to diverse neuropils, each of which may be of limited use to study in isolation or prohibitively challenging to manipulate in situ. Consequently, highly tractable alternative model systems may be valuable tools. Eusocial-insect colonies display emergent cognitive-like properties from relatively simple social interactions between diverse subunits that can be observed and manipulated while operating collectively. Here, we review the individual-scale mechanisms that cause group-level variation in how colonies solve problems analogous to cognitive challenges faced by brains, like decision-making, attention, and search.
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Sound has enormous influence on human organism. Different types of sound vibrations have both positive and negative effects on peoples health. This review highlights that sound is important factor for health regulation with the emphasis on cognitive functions and mental activity. Also, we describe strategies of using sound in treatment of neurological diseases, anxiety disorders, depressions, and social rehabilitation. Sound influence and its exploit are examined on different levels: ultrasound, infrasound, white noise, music and nature sounds. Finally, our review has shown sound great potential in treatment of neurodegenerative and psychiatric disorders, carpal tunnel syndrome, postoperative rehabilitation, and cognitive functions improvement. We propose the implementation of acoustic monitoring and music therapy as substantial components of rehabilitation medicine.
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There is considerable evidence that organisms can moderate incoming sensory stimulation so as to more closely approach optimal levels of arousal. When normal individuals are exposed to unusually high or low sensory input they tend to show "disordered" behavior similar to that of certain chronically disordered populations, for example, hyperactive and autistic children. It is proposed that at least some of the deviant behavior displayed by such disordered children represents a functional set of homeostatic response to condition of abnormal sensory input. Attempts to correct chronic imbalances in arousal through antecedent manipulations of chemical and sensory stimulation have been relatively successful and may provide not only appropriate treatment but also a better understanding of the mechanisms underlying many kinds of disordered behavior.
Background: In this article an integrative description of hyperkinetic behavior disorders is developed within the theory of action phases. Objective; It is investigated whether this description integrates different explanations of ADHD within a unifying framework. Method: Using the theory of action phases, a motivational explanation for ADHD can be elaborated that postulates ADHD-specific goal intentions as a basis of the hyperkinetic, disorder. These intentions are traced back to a specific need for stimulation. Furthermore, a volitional explanation can be formulated that stresses impairments of action control in protecting the current goal intention. Results: Based on this unifying framework empirical hypotheses can be derived that concern the differential role of possible causes in the etiology of behavioral symptoms that are typical for ADHD children. Conclusions: The action-theoretical framework used in this article is both suitable for the integration of different explanatory approaches and for the derivation of new empirical predictions.